microsatellite-based phylogenetic tree analysis of …...microsatellite-based phylogenetic tree...
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Microsatellite-based phylogenetic tree analysis of Australian Prunus fruit varieties
Cheryl Chan (MScForSci)
Centre for Forensic Science
University of Western Australia
This thesis is presented in partial fulfilment of the requirements for the
Master of Forensic Science
2010
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I declare that the research presented in this thesis, for the Master of Forensic Science at the University of Western Australia, is my own work. The results of the work have not been submitted for assessment, in full or part, within any other tertiary institute, except where due acknowledgement has been made in the text.
Cheryl Chan
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ACKNOWLEDGEMENTS
First, I would like to thank my supervisors A/P Guan Tay and Prof. Ian Dadour. Guan for
providing guidance, support and knowledge for the duration of this project. Ian for
providing the facilities and support for the completion of this project.
To the members of the lab who provided their friendship, support and reviews of my
written work. Stephen Iaschi who helped me on a daily basis by dispensing much of his
knowledge relating to DNA based research and statistic analysis. Catherine Rinaldi and
Haifa Khoory for their knowledge in DNA based research. The other members of Guan’s
research group Aishah Kadher, Habiba Al Safar, and James Meagher who provided
knowledge, support and friendship.
I would like to thank Alexandra Knight and the other members of staff at the Centre for
Forensic Science who keep the Masters course running smoothly.
Special thanks to my parents and Jonathan, who may be miles away but I would not have
made it to the end of this project without their constant support, understanding, and love.
Last but not least, He who made everything possible.
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PREFACE
The main objective of the research undertaken here was to make use of DNA and
chemical profiling to differentiate a newly patent premium hybrid of stone fruit, Nadia™
(Prunus salicina), from the rest of the Prunus family members.
This thesis contains 3 chapters. The first chapter reviews the current literature associated
with fraudulence in the food and beverage industry and its forensic significance. It also
introduces some common forensic DNA markers and their applications, including
microsatellite analysis.
Chapter 2 describes the DNA profiling of Nadia™ and a range of different Prunus
varieties based on 3 microsatellite markers. PCR and Gene Scan Analysis (ABI) was
based on using genetic distances of the combined microsatellites for differentiation. The
phylogenetic tree that was constructed effectively showed a distinction between Nadia
and the rest of the 13 other Prunus varieties tested.
Chapter 3 describes the chemical assessment of Nadia™ and other closely related stone
fruits. It is the first attempt to report the chemical assessment of Nadia™, revealing its
premium quality in terms of physical appearance, desirable post-harvest traits and high
nutritional values. The chapter also attempts to introduce β-carotene as one of the
potential chemical profiles used to effectively differentiate Nadia™ from the rest of the
stone fruits. Chapter 2 is presented as a manuscript submitted to Journal of Agricultural
and Food Chemistry, and is written in the format required by the journal.
The entire thesis is tied together with the obligatory abstract and bibliography section.
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TABLE OF CONTENTS TABLE OF CONTENTS……………………….………………………………….……………....iv
ABSTRACT………………………………………………..………………….……...ix
CHAPTER 1 .................................................................................................................... 1
LITERATURE REVIEW .............................................................................................. 1 1.1 FRAUDS IN FOOD AND BEVERAGE INDUSTRY ............................................... 2 1.2 PROTECTING NEW VARIETIES WITH PLANT BREEDER’S RIGHTS (PBR)
UNDER THE UPOV 1991 ACT .................................................................................. 4 1.3 METHODS OF APPLYING FOR PLANT PATENT UNDER THE RULES AND
REGULATION OF IP AUSTRALIA ......................................................................... 9 1.4 CASE STUDY ON DICKSONIA ANTARTICA ....................................................... 10 1.5 THE PRUNUS FAMILY AND THE MOTIVATION BEHIND BREEDING NEW
VARIETIES ................................................................................................................ 11 1.6 MARKET OF PRUNUS SPECIES IN AUSTRALIA/WORLDWIDE ................. 12 1.7 CASE STUDY: PINK LADY™ APPLES AND ITS SUCCESS ........................... 17 1.8 METHODS OF TESTING AUTHENTICITY OF FRUITS .................................. 18 1.8.1 TAXONOMIC CLASSIFICATION ..................................................................... 19 1.8.2 CHEMICAL TESTING ......................................................................................... 20 1.8.3 BIOLOGICAL TESTING ..................................................................................... 22 1.9 DNA IN FORENSIC ANALYSIS ............................................................................. 22 1.10 WHAT IS DNA? ......................................................................................................... 24 1.11 FORENSIC GENETICS ............................................................................................ 26 1.12 POLYMERASE CHAIN REACTION (PCR) IN FORENSIC ANALYSIS ......... 29 1.13 FORENSIC DNA MARKERS FOR PLANT GENOME ANALYSIS .................. 31 1.13.1 RESTRICTION FRAGMENT LENGTH POLYMOPHISM (RFLP) .............. 33 1.13.2 RANDOMLY- AMPLIFIED POLYMORPHIC DNA MARKERS (RAPD) .... 33 1.13.3 AMPLIFIED FRAGMENT LENGTH POLYMORPHSIM (AFLP) ................ 34 1.13.4 MICROSATELLITES ........................................................................................... 34 1.14 CURRENT PLANT/ FRUIT DATABASES ............................................................ 35 1.15 AIMS OF STUDY ...................................................................................................... 38 CHAPTER 2 (PART 1) ................................................................................................ 41
MATERIALS AND METHODS ................................................................................. 41 2.1.1 LEAF SAMPLE COLLECTION .............................................................................. 42 2.1.2 DNA EXTRACTION FROM PRUNUS LEAVES .................................................. 43 2.1.3 DNA PURIFICATION ............................................................................................... 43 2.1.4 GENOMIC PCR AMPLIFICATION OF MICROSATELLITE MARKERS ..... 44 2.1.5 VISUALISATION OF PCR PRODUCTS BY GEL ELECTROPHORESIS ....... 45 2.1.6 DETERMINATION OF MICROSATELLITE ALLELE SIZE BY GENE SCAN ............................................................................................................... 45 2.1.7 PHYLOGENETIC TREE ANALYSIS .................................................................... 45 CHAPTER 2 (PART 2) ................................................................................................ 47
RESULTS AND DISCUSSION ................................................................................... 47 2.2.1 AMPLIFICATION OF MICROSATELLITE REGIONS BY PCR ..................... 48 2.2.2 POLYMORPHISM IN DNA BAND PROFILES .................................................... 54
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2.2.3 GENE SCANNING .................................................................................................... 56 2.2.4 POLYMORPHISM INFORMATION CONTENT (PIC) ...................................... 64 2.2.5 PHYLOGENETIC TREE ANALYSIS .................................................................... 65 2.2.6 CONCLUSION ........................................................................................................... 69 CHAPTER 3 .................................................................................................................. 71 Abstract .............................................................................................................................. 74 Introduction ............................................................................................................................. 75 Results .............................................................................................................................. 82 Discussion and Conclusion ..................................................................................................... 84 Safety .............................................................................................................................. 87 Acknowledgement ................................................................................................................... 87 Literature Cited ....................................................................................................................... 87 BIBLIOGRAPHY ......................................................................................................... 98
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LIST OF FIGURES Figure 1: Development of Plant Variety Protection from 1973 to 2003 showing the
increasing number of titles being enforced each year since 1981. (Adapted from: Jordens, 2005) ...................................................................................... 7
Figure 2: Production of various stonefruits in millions of megatonnes (MT) by the respective top 6 producing countries from year 2000 to 2007 showing increasing trend in the total number of the respective Prunus fruit production. (Data obtained from FAOSTAT, 2007) ...................................................... 14
Figure 3: Volume of Australian produced fresh stone fruits that are exported between 1990- 2000. There is an increasing trend in amount of fresh stone fruits production each year especially for peaches, nectarines and plums. (Adapted from: Food and Agriculture Organisation 2002, Market overview- the Australian stone fruit industry, Independent Assessment May 2002). ........ 15
Figure 4: The Structure of DNA (reproduce from Sherwood, 1997) consisting of nucleotide bases attached to a sugar-phosphate backbone, forming a double helix structure. ............................................................................................. 25
Figure 5: Developments in forensic genetics. The timeline that summarises the important developments that have occurred since the discovery of the 1st genetic polymorphism that was applicable to solving crimes. .................... 28
Figure 6: Basic Polymerase Chain Reaction showing three basic steps of denaturation, annealing and extension............................................................................... 30
Figure 7: Examples of Prunus leaf samples collected from Joseph Rullo Orchards and are carefully labelled. .................................................................................. 42
Figure 8: Gel electrophoresis on positive control samples 17T(B), 187D(A), 260T(A) using unlabelled pchgms 20F1/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002. ............................................................................................................ 49
Figure 9: Gel electrophoresis on positive control samples 73J(B), 203X(A), 217Z(A) using unlabelled pchgms20F1/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002. ............................................................................................................ 50
Figure 10: Gel electrophoresis on positive control samples 17T(B), 187D(A), 260T(A) using unlabelled pchgms20F2/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002 ............................................................................................................. 51
Figure 11: Gel electrophoresis on positive control samples 73J(B), 203X(A), 217Z(A) using unlabelled pchgms20F2/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002. ............................................................................................................ 52
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Figure 12: Gel electrophoresis on positive control samples 187D(A), 17T(B), 73J(B) using unlabelled pchgms12 F/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002. ............................................................................................................ 53
Figure 13: Gel electrophoresis on samples using labelled Pchgms 20F2/R primers set.55
Figure 14: Gene scan signal graph that shows a single signal at allele size of 248kb, indicating the homozygosity of the microsatellite allele in this particular sample, 260T(A) (Flavour Fall plum) using Pchgms 20F1/R primer pairs. 57
Figure 15: Gene scan signal graph that shows signals at allele size of 248kb and 255kb, which indicates the heterozygosity of the microsatellite allele in this particular sample, 16R(B) (Fortune plum) using Pchgms 20F1/R primer pairs. 58
Figure 16: Gene scan signal graph that shows a single signal at allele size of 564kb, indicating the homozygosity of the microsatellite allele in this particular sample, 261U (Nadia™) using Pchgms 20F2/R primer pairs. .................... 59
Figure 17: Gene scan signal graph that shows signals at allele size of 556kb and 572kb, which indicates the heterozygosity of the microsatellite allele in this particular sample, 227J(B) (RubySun plum) using Pchgms 20F2/R primer pairs. ............................................................................................................ 60
Figure 18: Gene scan signal graph that shows a single signal at allele size of 427kb, indicating the homozygosity of the microsatellite allele in this particular sample, 248M (T5R3 03-10RN peach) using Pchgms 12 primer pairs. ..... 61
Figure 19: Phylogenetic tree reconstruction for 14 Prunus fruit varieties based on 3 microsatellite markers using NJ method. .................................................... 68
Figure 20: ORAC values and β-carotene levels in Nadia relative to other Prunus related fruits. (*ORAC values of were obtained from the USDA.) ....................... 97
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LIST OF TABLES Table 1: Exports and Market value of various fruits in Western Australia reaching
millions of dollars in the recent years. ........................................................... 16
Table 2: Comparison of different types of DNA polymorphic analyses in forensic investigation .................................................................................................. 32
Table 3: Table summarising the common fruit and plant DNA databases available ...... ....................................................................................................................... 37
Table 4: Three primers selected to amplify microsatellites in Prunus leaf DNA ....... 46
Table 5: Tabulation of allelic size of 3 microsatellite markers and genotypes across a variety of Prunus samples. ............................................................................ 62
Table 6: PIC values of the 3 microsatellite markers on 14 different varieties of Prunus. ....................................................................................................................... 65
Table 7: Differences in production attributes between “Nadia” and a generic cherry .... ....................................................................................................................... 93
Table 8: Nutrition panel of Nadia showing similarities shared with a generic cherry (shaded) and the Black Amber plum (bold) ................................................ 94
Table 9: Ratio of ORAC to β-carotene of the various common fruits including Nadia™ from mother and 2 year old trees. Fruits in the green shaded region have high ORAC values but low β-carotene; fruits in the pink shaded region have low ORAC values but high β-carotene, while fruits in the blue shaded region have moderately high values of both ORAC and β-carotene values. Nadia from both mother and 2 year old trees (in bold) falls in the blue region. ...................... 96
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ABSTRACT
This thesis contains three discrete chapters to address the objectives of this study. Chapter
1 presents the state of knowledge on the subject matter related to profiling plant material,
specifically Prunus species. Stone fruit species are important food crops. With new
varieties being developed constantly, there is a need to protect new breeds and strains.
The food and beverage industry faces significant losses in income due to illegal
propagation of new varieties to avoid royalty payments. Together with its high
nutritional values, characteristic physical properties and desirable post harvest traits, the
newly bred variety, Nadia™, is one of a series of novel hybrids of the Prunus family,
which could possibly attract premium prices. The authentication of new fruit varieties is
now part of doing business in the lucrative horticultural industry. Taxonomic description,
chemical composition and DNA profiling have all been used for this purpose.
The main objective of this study was to make use of DNA profiling and analysis of
biochemical composition to differentiate Nadia™ from other fruits of the Prunus family.
Various plant and fruit databases were reviewed for this chapter of the thesis. While the
information from these databases is extensive, microsatellite DNA profiling for Prunus
species are not readily available. Hence, the possibility of generating a concise database
for microsatellite markers of a variety of Prunus varieties is to be assessed in the second
chapter of this thesis.
Chapter 2 describes the use of DNA- based profiling on fruit collected from several
varieties of Prunus species. At the time when work commenced, Nadia™ was a novel
variety and its DNA characteristics were unknown. This study specifically used
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previously described DNA microsatellite markers to show that Nadia™ is a unique
Prunus variety, more closely related to plums than peaches or apricots.
Samples were screened for variation by using the Polymerase Chain Reaction (PCR) to
separate microsatellite alleles from Prunus leaf genome, which were then sent for Gene
Scanning at Royal Perth Hospital, WA. Three microsatellite loci of fourteen different
Prunus varieties were analysed to quantify differentiation between the varieties. A
phylogenetic tree based on the polymorphic microsatellite allelic sizes of the fourteen
Prunus varieties was constructed.
Phylogenetic analysis revealed the genetic relationship among the Prunus varieties based
on the genetic distances generated from their microsatellite allelic sizes. Successful
segregation between the plums, peaches and apricots was observed and the tree showed
that Nadia™ is a unique Prunus variety, more closely related to plums than peaches or
apricots.
Chapter 3 describes the study of biochemical profiling used to authenticate Nadia™. The
nutritional values and chemical composition between Nadia™ and its closely related
Prunus family members were compared. This part of the study specifically aimed to
describe the chemical profile towards providing methods for the authentication of
Nadia™ and differentiating it from other Prunus varieties.
Initial observation of Nadia™ revealed its desirable quality, better post harvest traits and
higher yield than a generic cherry has. Chemical analysis of Nadia™ showed that it not
only contains high levels of antioxidant properties, it also has relatively high levels of β-
carotene in the fruit. Typically, dark red fruits, including cranberries, are associated with
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high antioxidant levels and orange- fleshed fruits, such as apricots, are associated with
high β-carotene levels. Nadia™ is unique in that it has relatively high levels of both
compounds. When combined, the ratios of antioxidant levels, β-carotene and relative
sugar content could be a potential chemical profile for the identification of Nadia™ from
other fruits in the Prunus family. Work in chapter 3 is presented as a manuscript
prepared for the Journal of Agriculture and Food Chemistry and it is presented in the
format required by the Journal.
This study successfully made used of chemical composition analysis and DNA profiling
to differentiate Nadia™, the new patented hybrid, from fruits from the same Prunus
family. At the same time, information obtained from DNA profiling can be extrapolated
using a larger sample pool with more microsatellite markers in order to construct a DNA
database containing information on different allelic sizes of various Prunus varieties,
including Nadia™.
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CHAPTER 1
LITERATURE REVIEW:
The application of chemical and DNA profiling to novel fruit varieties:
A case study using the newly developed cherry X plum interspecific hybrid,
Nadia™.
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1.1 FRAUDS IN THE FOOD AND BEVERAGE INDUSTRY
Forensic science, in its broadest definition, is the application of the knowledge and
technology of major scientific disciplines to criminal and civil law. With the hype
generated in the media, forensic science is widely known to the public for its application
in criminalistic cases such as murder, rape and arson. Examples include forensic serology
on bloodstain and blood pattern analysis, fingerprint and footprint analyses, organic and
inorganic analyses of soil and glass, forensic anthropology, psychology, pathology, and
not forgetting forensic DNA analysis on hair and fluids. Other than its application in
criminal cases, forensic science is also applicable in civil cases, such as investigating
document counterfeiting in computer forensics to combat hacking of the Internet, child
pornography or in the establishment of paternity. There are, however, other areas of the
forensic science that are equally important but mostly unknown to the public. The project
outlined here is one such example; the use of forensic science to authenticate the origin of
commercial plants and fruits in the food and beverage industry.
Crimes in the food and beverage industry include counterfeiting brand names of premium
quality products or illegally propagating new varieties of fruits or plants to avoid royalty
payments. When brand names are counterfeited, food products are fraudulently labeled
and sub-standard quality products are sold as premium products, the food and beverage
industry for a long time suffered significant losses in revenue. In all cases, the retailers
and consumers do not get value for their money.
Fraud has become more sophisticated and increasingly difficult to detect. Consequently,
it is necessary to use advanced analytical techniques to detect frauds and evaluate
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authenticity of products. There are some companies that provide such testing and support
services for food, environment, pharmaceutical and consumer products. They often
specialise in specific techniques to detect adulteration of food products (Eurofins
Scientific, 2005). Some of the food products that can be tested include fruit juices,
honey, wine, cider, spirits, caffeine, meat products, fish, diary products, cereals and
basmati rice (Eurofins Scientific, 2005).
Civil crimes can also be committed by the agricultural or horticultural industry when
farmers illegally propagate patent hybrids to avoid royalty payments. There are two
different types of royalties. The first type is charged at sale for each patented plant sold,
and the second is a crop improvement royalty made to the owner of a plant variety for the
right to breed that variety. Royalties charged at sale for each patented plant sold, which
usually cost a few cents per plant, goes to the plant breeder. Extra costs are also added for
marketing efforts that advertise the variety. The crop improvement royalty is paid on
production rather than on seed sales. An example of this form of royalty is the grain
delivered for all future varieties bred by Agriculture Western Australia and its crop-
breeding partners. It ensures that those who pay are those who benefit directly from
adopting the new varieties. The introduction of production royalties in other parts of
Australia and the world has encouraged greater investment in crop breeding (Carr, 2001),
and has led to improved varieties with desirable and superior attributes.
It is a common practice for owners of the new hybrid to first register the plant to be
protected. This is achieved under plant variety protection laws and subsequently royalty
payments are collected from farmers who want to breed or sell this new plant hybrid.
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1.2 PROTECTING NEW VARIETIES WITH PLANT BREEDER’S RIGHTS
(PBR) UNDER THE UPOV 1991 ACT
Plant Breeder’s Right is a sui generis form of intellectual property protection, specifically
tailored for the purpose of protecting particular breeding, cultivation methods and the use
of new plant varieties. Examples of other such rights include patents, copyrights,
trademarks, and industrial designs. It also enables the reproduction of protected plant
varieties to be constrained by the owner of the protected variety.
PBR is a protection scheme terminology used in Australia, which is the same as Plant
variety Protection (PVP), a terminology used in Japan. They conform to the 1991 Act of
the International Convention on Protection of New Varieties of Plants, and they share
similarities in the scope of protection offered; the type of plants that can be protected; and
the standard criteria for new varieties (IP Australia).
With the growing population, there is a need to increase agricultural productivity to meet
demands. New variety of plants with improved yield, resistance to plant pests or high
quality, are necessary to increase productivity and product quality in the agriculture and
horticulture industries. In order to breed new varieties of plants, substantial investment in
skill, labour, material, resources and money are required, and some breeding programmes
involve years of research. In granting the breeder the exclusive right to exploit new
varieties, it encourages investment and research to plant breeding, which contributes to
the development of the agriculture, horticulture and forestry industries.
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In order to promote an effective system of plant variety protection, the International
Union for the Protection of New Varieties of Plants (UPOV) system was released in 1961
and has seen considerable expansion throughout the years. It aims to encourage the
development of new varieties of plants for the benefit of the society (UPOV, 2009).
The adoption of the UPOV convention and its revision in 1972, 1987 and 1991 reaped
great benefits for agriculture. In the United States of America (USA) for example, maize
yield has increased from 1.8 metric tons per hectare in 1940 to 8.5 tons per hectare in
200l. Similarly in South Africa, the average maize yield has increased from 1 ton per
hectare in 1950 to 2.7 tons per hectare in 2001 (Silvey, 1981). It is generally recognised
that 30% to 60% of the increase, according to the crop and the location, is due to genetic
improvements (Rademaker, 2000).
The last revision to UPOV was made in 1991, known as the “The 1991 Act” or the “Last
Act”. The changes made were to deal with challenges identified through the arising of
scientific discovery and the technological developments that took place between 1961
and 1991.
Today, the Acts of the UPOV Convention have established the standard criteria for
protection that includes novelty, variety denomination, distinctness, uniformity and
stability. It means that a variety is deemed to be novel only if it has not been sold with the
consent of the breeder before the date of the application for a breeder’s right. The variety
also has to be clearly distinguishable from any other variety at the time of application.
Uniformity and stability of the variety have to be ensured. In other words, the new variety
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could be expected to exhibit the described features of its propagation, and the relevant
characteristics of the variety have to remain unchanged after repeated propagation
(UPOV, 2009).
Further clarifications were made with regard to the scope of protection of the varieties.
The Essentially Derived Varieties (EDV) concept was developed to protect varieties that
are deemed to be derived from a protected variety but are subjected to the authorisation of
the breeder of the initial protected variety (Jordens, 2005). At the same time, the 1991
Act also extended the minimum duration of protection to 25 years for varieties of trees
and vines, and to 20 years for other varieties (Jordens, 2005). This means that new
varieties are only protected under the scheme for the indicated number of years, thereafter
the varieties will no longer be protected and can be propagated by any breeders without
being charged for royalty payments.
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Figure 1: Development of Plant Variety Protection from 1973 to 2003 showing the increasing number of titles being enforced each year since 1981. (Adapted from: Jordens, 2005)
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In United States of America (US), the UPOV Convention is implemented by the Plant
Variety Protection Act (1970). It complied with the 1991 UPOV Convention and extended
protection to the first generation hybrids and tuber propagated plants (BiOS website).
Figure 1 illustrates the growth of the Plant Variety Protection Union in terms of
membership and titles of protection. It indirectly depicts the growing trend in the number
of plant variety rights issued from 1973 to 2003, reflecting the increasing number of
research programmes undertaken to produce new plant hybrids. Since legislation was
enacted to grant protection to new products in the field, the number of patents has rapidly
increased. Until Title 35 was enforced, there has been a three-fold increase in the number
of Intellectual Property (IP) titles granted.
Similarly to the US, Australia is both a World Trade Organisation (WTO) and UPOV
member and has implemented the UPOV protection system plant varieties are protected in
Australia by a Plant Breeder's Right (PBR) under the Plant Breeder's Rights Act (1994)
(BiOS website). Plant breeders, under the PBR Act, can exploit their exclusive right by
producing and selling all the reproductive or propagating materials of their new varieties
that are needed by the market. Alternatively, the proprietor can grant licenses to others to
commercially exploit the variety in exchange for a royalty. Intellectual-property law is an
integral part of the biotechnology industry and responds to the enormous changes that this
sector is contributing to plant breeding. This will ensure that breeders are rewarded for
their efforts and encouraged further investment in new techniques (Jordens, 2005).
Consequently, it is important to protect the breeding rights of the newly patented Nadia™,
to prevent illegal propagation and avoidance of royalty payments. Hence, in this project,
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chemical and DNA profiling techniques are used to generate novel markers of a newly
developed cherry X plum hybrid known as Nadia™.
1.3 METHODS OF APPLYING FOR PLANT PATENT UNDER THE RULES
AND REGULATION OF INTELLECTUAL PROPERTY (IP) AUSTRALIA
In order to register a variety for PBR, the variety has to be new or newly exploited. By
definition, a new variety is one that has not been put on sale with the breeder’s consent
while a newly exploited variety is one that has been sold with the breeder’s consent for up
to 12 months in Australia.
There are at least four criteria that the variety must meet to be eligible for protection.
Applicants have to show the distinct morphological characteristics of the new variety from
existing varieties, together with comparative DNA or protein profiles at time of
application. At the same time, these characteristics have to be uniform for all the plants of
the new variety, allowing only a maximum of 2 or 3 deviations from 140 of the plant parts
measured. Moreover, breeders of the new variety have to repeat propagation over two
generations in separate or comparative trial from seeds and demonstrate stability (IP
Australia).
Thereafter, the breeder of the new variety will have to compile detailed description of the
variety based on the universal Interactive Variety Description System with the relevant
photos in order for the application to be successful. Examinations may take up to six
months for any objection or comments. Only with the successful completion of all the
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requirements and any resolution of objections, the applicant will receive a Certificate of
Pant Breeder’s Rights upon payment of the Certificate fee (IP Australia).
At the same time, it is important to note that it is not all illegal to breed fruits varieties
protected under PBR. If the breeding of these PBR protected plant varieties are done for
private, experimental or breeding purposes of other plant varieties, they do not infringe the
PBR.
1.4 CASE STUDY ON DICKSONIA ANTARTICA: UNPAID ROYALTY
DISCOURAGES INNOVATION AND HURTS THE INDUSTRY
In a report to the Australian Parliamentary Senate on the commercial use of Australian
native flora, the harvest of the tree fern, Dicksonia antartica (D. antartica) was tabled. A
royalty was imposed on the 80,000 plant harvested in Tasmania for commercial sale in
Victoria. Owing to the lack of information on the market for D. antartica, there is concern
on what the impact of illegal harvesting will have on the industry. The funds generated are
for conservation purposes and for research towards developing methods for nursery-grown
sporlings. It is estimated that the commercial industry around D. antartica could be valued
at $30 million per annum just on exports alone. The quoted figure of 80,000 plants is less
than the number of plants available in nurseries in 1991. It was reported that additional
20,000 to 240,000 plants were available for sale illegally by means of price-cutting,
poaching or unpaid royalties (Parliament of Australia). This could possibly lead to a loss in
more than $ 2 million from the illegal sale.
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1.5 THE PRUNUS FAMILY AND THE MOTIVATION BEHIND BREEDING
NEW VARIETIES
There are hundreds of peach, nectarine (Prunus persica (L.) Batsch), plum (Prunus
salicina Lindl. and hybrids), apricot (Prunus armeniaca.), and cherry (Prunus avium L. and
Prunus cerasus L.) cultivars throughout the world. However, there is a continuing need to
develop new stone fruit cultivars as the requirements of the industry change. The
motivation behind the development of new varieties includes the increased interest in the
health benefits of fruits. As nutritionists uncover the health benefits of specific compounds
particularly antioxidants, there has been a focus on selecting cultivars that contain
augmented levels of these compounds. The increasing demand for fruit quality increases
sales of cultivars, and satisfies the need of having multiple choices for the consumers.
Breeders, when propagating new varieties, also look to develop varieties with better
retention and post harvest traits. Desirable retention traits include fruit resistance to
common plant diseases that often plague the cultivars, and higher yield of fruit production,
both minimise any potential loss of revenue. Post harvest traits incorporating ease of
picking, reduced cracking from environmental conditions and careful packing attributes
minimise bruising of the fruits are examples of important and highly sought after
characteristics.
New improved varieties continue to be registered. By ways of providing some numbers,
the nurseries in the southeastern U.S. has listed between 50 to 150 new peach and nectarine
cultivars and the California Tree Fruit Agreement lists 80 to 85 major cultivars of peach
and nectarine each (CTFA, 2003). Throughout the world, breeders have been releasing on
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average, approximately 100 peaches and nectarines, 20 apricots, 30 plums, and 20 cherry
cultivars every year between 1988 and 1998 (Della et al., 1996; Fideghelli et al., 1998).
1.6 MARKET OF PRUNUS SPECIES IN AUSTRALIA/WORLDWIDE
Global market of Prunus species easily exceeds hundreds of millions of USD dollars each
year. In 2000, world export market for peaches and nectarines was worth almost $US 850
million. The dominant players of the peach and nectarine market were Italy and Spain,
contributing US$ 244 million and US$ 219 million worth of world exports respectively
(FAO, 2002). France and Spain, on the other hand, are the dominant players in the world
export market for apricots, contributing a total of US$ 85 million to the world export
market worth US$ 180 million (FAO, 2002). In 2007, Turkey contributed more than
500,000 megatonnes of apricot production. World plum market itself is worth around US$
321 million (FAO, 2002). Figure 2 shows the combined apricots, peaches, nectarines and
cherries production from the respective top 6 countries and reveals a growing trend in the
production of these fruits, albeit small between 2000 and 2007 (FAOSTAT, 2007).
In Australia, the stone fruit crop includes peaches, nectarines, apricots, cherries and plums.
The global market for stone fruit is so large that Australia only contributes less than 1% of
the world production of peaches and nectarines, plums, cherries and apricots (FAO, 2002).
Victoria is the major state for the Australian production of stone fruit, producing
approximately 45% of the total national crop. This is followed by South Australia, New
South Wales and Western Australia. Figure 3 shows that the volume of Australian
produced fresh apricots and cherries remained almost unchanged from 1990 to 2000, while
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there is a general increasing trend in the volume of peaches, nectarines and plums being
exported between 1990 and 2000. There was also an increase in the amount of peach and
nectarine exports between 1997 and 1998, rising from less than 2,000 tonnes to more than
4,000 tonnes in one year (see Figure 3) (FAOSTAT, 2007).
Comparison of the exports and market values of various important fruits in Western
Australia were made in Table 1. Stone fruit market brings high revenue in the horticultural
industry in Western Australia. In the financial year 1998 to 1999, the export value of stone
fruit reached AUD 10 million, and is possibly much higher now 10 years later.
These increasing trends in the market of Prunus cultivars in Australia inevitably lead to the
need of propagating new varieties. Nadia™ is a newly developed interspecific hybrid
resulting from a controlled cross between two Prunus fruit varieties: the “Black Amber
plum (P. salicina) and “Supreme” cherry (P. avium). It was bred at a commercial orchard
at Shepparton, Victoria, Australia. The development of this newly patented variety,
Nadia™, has the potential to increase the revenue produced from the Prunus industry both
in Australia and worldwide.
14
Figure 2: Production of various stonefruits in millions of megatonnes (MT) by the respective top 6 producing countries from year 2000 to 2007, showing increasing trend in the total number of respective Prunus fruit production. (Data obtained from FAOSTAT, 2007)
15
Figure 3: Volume of Australian produced fresh stone fruits that were exported between 1990- 2000. There is an increasing trend in
amount of fresh stone fruits production each year especially for peaches, nectarines and plums. (Adapted from: Food and Agriculture Organisation 2002, Market overview- the Australian stone fruit industry, Independent Assessment May 2002).
16
Table 1: Exports and Market value of various fruits in Western Australia, reaching millions of dollars in the recent years.
Type of fruits Market percentage
Exports Value of Market
Strawberries The export was increased by
15% in 2008
85% of Australia strawberries were exported from WA
The Australian strawberry market was worth $7.5 million in 2008
Stone fruits WA contributed 10% of the national plum, nectarine production
Out of the 30% of total stone fruit export, 60% total plum export in Australia
Export value of stone fruits was valued at $10 million between 1998 and 1999
Table grapes WA contributed 5% of Australian grape production
Exports were expected to increase to $5 million by 2008
Value of table grapes in WA was worth $3.5 million between 2002 and 2003
Citrus industry Eg: lemons, limes, mandarins, oranges and grapefruit
_ WA exported $1.5 million worth of citrus fruits between 2000 and 2001
In 1999, market of the citrus fruits was estimated at $8.2 million
17
1.7 CASE STUDY: PINK LADY™ APPLES AND ITS SUCCESS AS A
PREMIUM FRUIT
One of Australia’s successes in the horticultural industry was the creation of the apple
hybrid, Pink Lady™ by John Cripps in Western Australia in the 1970s. It is a cross
between Golden Delicious and Lady Williams apple, and was only introduced in the late
20th century. Pink Lady™ proved to be the epitome of a trend towards product marketing
and branding in the sale of apples. It was one of the first apple varieties to be marketed as
a “club”, with “members” with newsletters being emailed to all participating countries It
covers topics of demand and supply, marketing campaigns, retail performances,
production and trade issues, industry developments, milestones, etc. Today, The Pink
Lady™ business has reached out to countries like the USA, Europe and UK (Pink Lady®
Newsletter, 2008). With Plant Variety Protection, this variety has been grown under a
strictly controlled license, then marketed through a limited number of resellers to
supermarkets. A master license must be granted by Apple and Pear Australia Ltd before a
company can produce, pack and market Pink Lady™ apples both domestically or
internationally (IPLA, 2009). Pink Lady™ apples that are packaged for sale have to be
delivered in special cartons printed with their signature heart-shaped logo, and each apple
has to be tagged with their logo stickers (IPLA, 2009). Through this tight control, it
ensures that the quality and prices of Pink Lady™ apples remain high and being
portrayed as a premium product.
In order to preserve its premium appeal, physical appearance of Pink Lady™ apples
undergo stringent quality control. When the standards required for Pink Lady™ are not
18
met, they are sold instead as Cripps Pink apples. The distinction is primarily made on the
colour intensity and its sugar/acid balance. This ensures that the variability of Pink
Lady™ quality is lesser than most other varieties seen in the market.
With successful marketing and increasng popularity of Pink Lady™ apples, it is
inevitable that there will be apple growers who illegally attempt to sell sub-quality apples
as Pink Lady™. Just recently, The Age Business article reported a fraudulent case
committed by a Brazilian exporter who shipped 100-tonnes of Brazilian apples under the
name of Pink Lady™ (http://www.theage.com.au/). It is important that apple growers
who subscribed to the Pink Lady scheme are permitted to use the trademark if the fruit
meets the quality standards, otherwise they are constrained to sell them as ordinary
Cripps Pink.
It is estimated that the annual Pink Lady wholesale trade in Europe is worth
approximately AU$306 to AU$340 million, with sales of between 150,000 and 160,000
tonnes of fruit. Global Pink Lady trade has yielded $1.6 billion in the last 15 years
(Durham, 2006). The success of the Pink Lady™ as a premium fruit is a result of its
ingenious marketing, stringent quality control as well as its protection as a patented
variety by PVP and PBR.
1.8 METHODS OF TESTING AUTHENTICITY OF FRUITS AND THEIR
PRODUCTS
Similar to how forensic science uses cross disciplines between biology, chemistry and
19
physics. Similarly, the analysis of food samples also makes use of these three major
disciplines to determine fruit authenticity and fruit content, a pre-requisite for quality
control and consumer’s protection.
1.8.1 TAXONOMIC CLASSIFICATION
Taxonomic classification based on physical morphological features of new varieties has
been one of the easiest and most upfront methods in varietal identification and
differentiation. It has been used extensively in the study of different fern species (Pal and
Pal, 1970), fungi differentiation (Humphrey, 1891) as well as in fruit differentiation
(Akcin, 2008). As an example, a study conducted by Akcin (2008) using
micromorphology analysis on Cynoglossum L. (Boraginaceae) species, successfully
separate the species into different sub-types based on the differences found on the seed
coat and fruit surface.
Unlike chemical and biological analysis, comparative morphology does not require any
expensive chemical reagents or elaborate equipments for analysis. Comparative
morphology is cost effective and easy to perform. Basic observations can be done easily
with dissecting or light microscope, and the keen observation skills of a taxonomist or
researcher.
As technology advances, more stringent observations of micromorphological
characteristics have been done with biometrics or high magnification microscopy. They
have been used extensively in both animals and plants. Some examples of using these
techniques in animals are the differentiation of female leaf beetles based on the
20
morphological differences in the genitalia and abdominal structures (Chamorro-Lacayo et
al., 2006), and comparing physical attributes in nematodes using Scanning Electron
Microscope (SEM) (Naem, 2007). TEM was also used in the differentiation of mussels
from the characteristic shape of their spermatozoa (Walker et al., 1996). These robust
techniques have extended to the analysis in plants. The examples include the
characterisation of fruit surfaces (Ackin, 2008), petals of the Turkish Onosma species
(Ackin, 2009), and pollens (Moon and Hong, 2003).
1.8.2 CHEMICAL TESTING
With the development of highly sensitive analytical tools that are both rapid and
inexpensive, researchers today are able to quantify different types of chemical
components in fruits and their products. This has led to a new approach in determining
fruit authenticity and product content and is based on the assumption that fruits may have
unique chemical markers that are unique to individual species and varieties. Furthermore,
breeding location can contribute to the unique profile of a crop. Based on the soil type,
environment, climatic conditions (Aprotosoaie et al., 2010), and farming method
(Khushk et al., 2009), the chemical profile of plants and fruits can be different. As a
result, chemistry can be used to determine the breeding location, however, it can be
unreliable since growing environment are subjected to variables beyond the growers’
control.
There are many analytical techniques that are widely used in the food industry for
analysing ingredients. For example, Near Infrared spectroscopy (NIR) has been used to
analyse ingredients in foodstuff (Downey and Kelly, 2006), specifically to evaluate fruit
21
authenticity from cell wall components analysis (Kurz et al., 2009). Other technologies
include High Performance Liquid Chromatography (HPLC), Gas Chromatograph coupled
Flame Ionisation Detector (GC-FID) (Kosmala et al., 2009), pyrolysis mass spectrometry
coupled with Gas Chromatography coupled Mass Spectrometry (GC-MS) (Garcia-wass,
2000; Baltes, 1978; Donelly, 1982). Specifically in the study performed by Garcia-Wass
et al. (2000), pyrolysis mass spectrometry was used to detect authenticity in orange juice
and successfully discriminate the juices from seven different countries including Israel,
Brazil, Florida and Cuba.
With these techniques, researchers are able to analyse cell wall polysaccharides to
characterise fruits and their products (Kosmala et al., 2009). Differentiation of mango
cultivars performed by Berardini was based on their contents of flavonol and xanthone C-
Glycosides, anthocyannins and pectin. (Berardini et al., 2005). Other chemical
components that have been used to differentiate fruit authenticity include carbohydrates
(Baltes and Schmahl, 1978), sugar contents (Kurz et al., 2009), soy proteins (Raghavan et
al., 1986), antioxidant (Prior et al., 2005) and phenolic compounds (Campo et al., 2005).
As an example, Campo et al. (2005) used physiochemical parameters, sugars, acid and
phenolic compounds, to differentiate Basque cider apple juices from five other varieties.
By applying multivariate analysis on the data, they were able to separate the apple juices
into groups that correspond to different cultivars.
To date, there is no one single assay that can accurately authenticate a wide variety of
fruits and their products. The process of chemical differentiation usually requires a list of
assays to be performed. Furthermore, different fruits may require their own unique
22
chemical profiles for identification. Hence, this form of analysis is usually expensive and
labour intensive.
1.8.3 BIOLOGICAL TESTING
DNA analysis has previously been used to profile many plant species including, celery
(Dovicovicova et al., 2004), cannabis (Hsieh et al., 2005; Linacre and Thorpe, 1998),
potatoes (Hyo et al., 2001) and rice (Rahman, et al., 2009). It is a very powerful
technique that requires only a small amount of DNA sample. It is now one of the major
tools in forensic analysis to help solve legal cases.
1.9 DNA IN FORENSIC ANALYSIS
Forensic science is a tool that aids the judiciary solves legal issues by presenting
objective evidence in both criminal and civil cases. This field crosses boundaries between
biology, chemistry, physics and mathematics, and includes disciplines as varied as
botany, physical ballistics, and pattern analysis for the assessment of fingerprints, ear-
prints, sound analysis, handwriting and documents anaylses.
For the past 25 years, one powerful biological tool has revolutionised forensic
investigations- the application of DNA to match persons of interest to biological evidence
at a crime scene. As all living things contain DNA, and all DNA exhibits variability both
among and within species, any biological material associated with a legal case will carry
in it this small and robust information about its source. It was the discovery of
hypervariable regions in human DNA in 1985 that led to the development of DNA
fingerprinting as the first molecular genetic forensic technique (Jeffreys et al., 1985).
23
Human DNA analysis has played a major role in criminal investigation, from the ability
to link suspects to crime scenes, link one crime scene to another, to match relatives and
identify victims of mass disasters. However, non-human DNA is beginning to find a
place in the prosecution of individuals in both criminal and civil cases. There are
extensive forensic investigations based on animal DNA analysis by using short tandem
repeats (STRs) for the identification of animals (Cassidy and Gonzales, 2005), microbial
DNA as a response to bioterrorism (Pattnaik and Jana, 2005), as well as the application in
plant DNA.
Plant DNA has the same basic structure across all phyla, therefore methods currently
used to analyse humans and animals can be applied to plants. The difference between
human and plant DNA, besides hypervariability of the sequence, is that plant cells may
be polyploidy and contain more than 48 chromosomes normally found in human cells
(Blair, 1975; Yi et al., 2004). Polyploidy is common in plants, that is, there can be up to
double or triple the number of chromosomes in each cell, for example Symplocarpus
foetidus contains 60 chromosomes (Blair, 1975). Polyploidy occurs naturally in plants,
fungi, invertebrates and lower vertebrates during evolution (Otto and Whitton, 2000). The
reason for gene duplications is largely unknown but it was hypothesised that gene
duplications form the basis for evolutionary diversity (Ohno et al., 1968). Regardless of
the genotype of plants, it does not affect the protocols involved in DNA profiling or any
results obtained from DNA analysis. Protocols that are used in this study work effectively
for the DNA extracted from the leaves of Prunus species.
Forensic botany using molecular biology has assisted in criminal and civil investigations.
24
The first criminal case that used plant DNA typing to gain legal acceptance was a
homicide that occurred in 1992 in Arizona’s Maricopa County (Yoon, 1993). RAPD
analysis was used to generate DNA band patterns to match the seed pods found at the
back of the truck to the pods of the tree where the body was discovered. RAPD analysis
of plant DNA was also used to settle a lawsuit involving the unauthorized
commercialization of a patented strawberry variety “Marmolada” in Italy (Congiu et al.,
2000).
1.10 WHAT IS DNA?
DNA is a polymer that consists of units known as nucleotides, composed of a sugar
molecule, a phosphorus-containing group and a base. There are four different bases
found in DNA, adenine, cytosine, guanine and thymine. These bases are complementary
to each other and they interact with each other with either two or three hydrogen bonds:
adenine is complementary to thymine; guanine to cytosine. The sugar component is
joined with a phosphate group to form the backbone of the DNA strand while the bases
are projected from the backbone. The interaction of the sugar-phosphate backbone in a
double stranded DNA gives the molecule a unique double helix structure, as shown in
Figure 4.
25
Figure 4: The structure of DNA (reproduce from Sherwood, 1997), consisting of nucleotide bases attached to a sugar-phosphate backbone, forming a double helix structure.
26
1.11 FORENSIC GENETICS
Forensic genetics has been driven by human genetic variation. The application of DNA
used in genetics began more than a century ago with Karl Lansteiner’s discovery of the
human ABO blood group polymorphism (Jeffreys et al., 1985). Although the extent of
variation cannot definitively be used to identify individuals, it can show conclusively that
the sample did not come from a specific person by a method of exclusion. It was not
until the 1980s that the DNA revolution began with the discovery of hypervariable loci
by Alec Jeffreys, also known as minisatellites (Jeffreys et al., 1985). Shortly after, DNA
fingerprinting method was developed to describe DNA fragment patterns generated by
multilocus probes after electrophoretic separation of genomic DNA. The probability of
two unrelated people sharing the same combination dropped from 0.001 in serological
ABO blood markers to less than 5 x 10-19 (Jobling and Gill, 2004) (See Figure 5 for
historical timeline).
In the late 1980s, methods based on the Polymerase Chain Reaction (PCR) were
developed. They provided an enormous increase in sensitivity that allowed minute
amounts of degraded DNA to be analysed (Saiki et al., 1985). Thus, it now forms the
basis of most forensic DNA typing. Initially, the power of DNA typing was low with
sample mixtures difficult to interpret. It was the discovery of short tandem repeats
(STR’s), together with automated sequencing technology that led to the current systems
for individual identification. As a result, the advantages of high discriminating power,
high sensitivity and the ability to resolve sample mixtures were fully utilised.
Furthermore, STR’s allowed unambiguous assignment of alleles, making the method
27
suitable for the development of databases. The US FBI CODIS (Combined DNA Index
System) contains 13 STRs plus the amelogenin sex test. Other examples of DNA
databases include the European DNA Profiling group (EDNAP) and the National Institue
of Standards and Technology (NIST) supported website for Forensic STRs and SNPs.
Other than STR multiplexes, markers on the Y-chromosomes and mitochondrial DNA
(mtDNA) have also been developed for more specialised uses. The first time mtDNA was
admitted as evidence in a US court was in 1996 in the case of the State of Tennessee vs.
Paul Ware. In this case mtDNA was used to link two hairs recovered from the crime
scene to the defendant (State v. Ware, 1999), which resulted in the conviction of Paul
Ware for a crime that involved rape and murder of a four-year-old girl.
Other than an emphasis on the development of DNA-based markers in humans for
forensic science, these versatile molecular markers have also been useful in livestock and
plant genome analysis. Applications such as genome fingerprinting, population genetics,
plant breeding, taxonomy, and characterization of genetic variability (Joshi et al., 1999)
have been exploited for generating DNA databases for plant genomes (Blenda, 2006).
28
Figure 5: Developments in forensic genetics. The timeline that summarises the important developments that have occurred since the discovery of the 1st genetic polymorphism that was applicable to solving crimes.
29
1.12 POLYMERASE CHAIN REACTION (PCR) IN FORENSIC ANALYSIS
In this study, basic Polymerase Chain Reaction (PCR) is used to amplify microsatellite
regions of the Prunus DNA. PCR is a revolutionary technique emerged in the mid 1990s
to replace the Restriction Fragment Length Polymorphism (RFLP) technique that
dominated the DNA typing procedure since 1985. PCR is a simple technique that is
designed to replicate DNA strands. However, in the forensic context, PCR is a powerful
technique as minute quantities of materials are often presented to the criminal lab
analysts. The steps involved in PCR are shown in Figure 6.
PCR involves three steps: denaturing, annealing and extending. The first step in PCR
process is to denature the DNA strands at a temperature of approximately 94℃. At high
temperature, the hydrogen bonds between the complementary bases are broken and
separate the DNA into two single strands. The second step is to anneal the primers to the
separated stands by lowering the temperature suitable for the annealing process. Finally,
DNA polymerase and a mixture of free nucleotides are incorporated to the separated
strands, known as the extension step. This results in the production of two complete pairs
of double stranded DNA segments. The outcome of PCR is the exponential increase in
the number of DNA strands after a series of cycles.
PCR provides a distinct advantage to forensic scientist in that it can amplify minute
amount of DNA, overcoming the limited sample-size problem that is often associated
with crime scene evidence. Its high sensitivity is also another reason that RFLP is
eventually being replaced.
30
Figure 6: Basic Polymerase Chain Reaction showing three basic steps of
denaturation, annealing and extension.
31
1.13 FORENSIC DNA MARKERS FOR PLANT GENOME ANALYSIS
Juridical cases have become more frequent with derivation of new varieties in the
horticultural industry. As a result, it is essential to analyse the complex genetic diversity
of varieties in the same family, using DNA markers. Ideal DNA markers for estimating
variation should meet certain criteria. They include, high polymorphism, co-dominant
inheritance and the direct involvement in the genetic control of the adaptive trait (Joshi,
1999). DNA markers that are polymorphic in nature indicate that the region where the
marker is found undergoes frequent genetic evolution, thus allowing differentiation based
on the differences in the DNA sequence. Furthermore, DNA markers that follow
Mendelian’s co-dominance or dominance trait model ensure that the DNA region is
always phenotypically expressed. At times it is essential for the ideal DNA marker to
have high reproducibility and high genome frequency in order to facilitate the assessment
of genomic variation in related varieties.
It is extremely difficult to find a molecular marker that would meet all three criteria of
high polymorphism, co-dominance and phenotypic expression. Depending on the type of
study to be undertaken, a marker system can be identified that would fulfill a minimum of
the above criteria (Weising et al., 1995). Some examples of molecular markers that are
widely used in forensic analyses are Restriction fragment length polymorphism (RFLP),
Randomly- amplified polymorphic DNA markers (RAPD), Amplified fragment length
polymorphism (AFLP) and microsatellite analysis which is reviewed in the next section.
32
Table 2: Comparison of different types of DNA polymorphic analyses in forensic investigation
DNA techniques Description Advantages Disadvantages
Restriction fragment length polymorphism (RFLP)
Distinguish samples based on the different sizes of DNA fragments produced by restriction enzymes One of the first techniques used in forensic science
Ability to detect DNA fragments from all homologous chromosomes Reliable markers in linkage analysis
Require large amount of DNA Time consuming Labour intensive Inability to detect single base changes.
Randomly- amplified polymorphic DNA markers (RAPD)
Detects nucleotide sequence polymorphism by using a single primer of arbitrary nucleotide sequence
Ability to direct amplification of several discrete loci in the genome
Poor reproducibility Faint or fuzzy products Difficulty in scoring bands
Amplified fragment length polymorphism (AFLP)
Detection of genomic restriction fragments by PCR amplification
Fingerprints can be produced without any prior knowledge of sequence Useful in detecting polymorphism between closely related genotypes
Stringent reaction conditions are required, especially for primer annealing
Microsatellites Detects different numbers of short DNA repeats
Ability to simultaneously detect multiple DNA loci Ideal marker to distinguish individuals
Time consuming
33
1.13.1 RESTRICTION FRAGMENT LENGTH POLYMOPHISM (RFLP)
RFLP markers were used for the first time in the construction of genetic maps in man
(Botstein et al., 1980). Subsequently, RFLP analysis has expanded to include other
purposes such as identification. In RFLP analysis, genomic DNA is digested by a
restriction enzyme before it is resolved by gel electrophoresis (Southern, 1975) and blotted
on a nitrocellulose membrane. Specific banding patterns on the membrane are visualised
by hybridisation with labelled probes. As codominant markers, RFLPs can detect the
coupling phase of DNA molecules. They are also very reliable markers that can
differentiate linked traits (Winter et al., 1995). However, the disadvantages of RFLPs
include the large amount of DNA required for restriction digestion and Southern blotting.
The need for radioactive isotope also makes the analysis relatively expensive and
hazardous. On top of that, the assay is time-consuming and labour- intensive and only one
out of several markers may be polymorphic, which may cause inconvenience in the
analysis of crosses between closely-related species (Enjalbert et al., 1999).
1.13.2 RANDOMLY- AMPLIFIED POLYMORPHIC DNA MARKERS (RAPD)
Randomly- amplified polymorphic DNA marker (RAPD), a PCR-based genetic assay, was
developed in 1991 by Welsh and McClelland (Welsh, 1990). It detects nucleotide sequence
polymorphisms in DNA by using a single primer of an arbitrary nucleotide sequence. It
allows the amplification of several discrete loci in the genome, making it useful for
efficient screening of nucleotide sequence polymorphism between individuals (Tingey,
1993). As RAPD uses random sequence primers, it is important to optimise and follow
stringent and consistent reaction conditions for reproducible DNA amplification. Being
34
dominant markers, they are limited in their use as markers for mapping, but it can be
overcome by markers linked in coupling (Williams et al., 1993).
1.13.3 AMPLIFIED FRAGMENT LENGTH POLYMORPHSIM (AFLP)
Amplified Fragment Length Polymorphism (AFLP) is a technique based on the detection
of genomic restriction fragments by PCR amplification. With a limited set of generic
primers, the assay can be performed on any DNA of any origin or complexity without any
prior knowledge of sequence. Stringent reaction conditions are required for primer
annealing, making the AFLP technique reliable. This combination of RFLP and PCR
techniques is useful in the detection of polymorphism between closely related genotypes
(Ehrlich et al., 1991).
1.13.4 MICROSATELLITES
Microsatellites, introduced by Litt and Lutty in 1989 (Litt and Lutty, 1989), consists of 1 to
6bp long monomer sequences that are repeated in the genome. These loci will vary in the
number of repeat units between the genotypes. Thus, microsatellites form an ideal marker
system to differentiate individuals even in the same species. The multilocus probes create
complex banding patterns and they generate oligonucleotide fingerprints that can be
visualised by the hybridisation of a labelled microsatellite probe. As microsatellites can be
easily identified from the genome, they make ideal markers for plant genetic linkage,
physical mapping, population studies and varietal identification (Morgante and Olivieri,
1993).
35
1.14 CURRENT PLANT/ FRUIT DATABASES
To the best of our knowledge, databases on microsatellite DNA profiling for Prunus
species are not readily available. This is because commercial companies have restricted
access for DNA profiling services and the information will only be available for a price.
Major databases that are easily accessible from the Internet are reviewed in this section.
Table 3 summaries the differences and usage of the various major databases available.
Comparative genomics is the study of the genomic relationships between different species
by explaining observed similarities and differences within a molecular evolutionary
context. It can be done through categorising species’ gene contents and chromosomal
arrangements. It is also the principle method to analyse and compare whole genome
sequences in order to identify genes of interest (Irish et al., 2004). There are several
prominent public databases that provide access to plant genome data. They include
GenBank (Benson, 2003), The Arabidopsis Information Resource (TAIR) (Rhee et al.,
2003), PlantGDB (Dong et al., 2004), GreenPhylDB (Conte, 2007) and the larger database
providers such as National Center for Biotechnology Information (NCBI) and The Institute
for Genomic Research (TIGR).
GenBank is a database containing all known nucleotide and protein sequences with
supporting bibliographic and biological annotations. It is built and distributed by NCBI and
contains over 3.4 billion nucleotide bases from 4.6 million different sequences with
information on Sequence-based taxonomy, Expressed sequence tag (EST) data, Sequence-
tagged site (STS) data, Genome Survey Sequence (GSS) data, High throughput genomic
(HTG) data, etc (Dong Q, 2004).
36
PlantGDB is a database of molecular sequence data specifically for important plant
species. It contains EST clusters and assemblies for all major plant species and employs an
user-friendly interface (Dong Q, 2004).
GreenPhylDB is one of the most recent comprehensive databases designed to facilitate
comparative functional genomics in plants (Conte et al., 2008). However, it focuses on the
comparison of Oryza sativa and Arabidopsis thaliana genomes with using a semi-
automatic clustering procedure or a phylogenomic approach. Their limitation is that it only
focuses on Oryza sativa and Arabidopsis thaliana genomes.
The United States Department of America (USDA) also has an extensive plant database.
Instead of genomic data, The USDA plant database contains information on plant
taxonomy, classification, nutrients properties and the physiological properties. It contains
no genomic information.
Many of the databases integrate information with several other databases. For example,
GreenPhylDB shares information with UniPro, KEGG, TAIR and TIGR, while raw
sequence data in PlantGDB can be obtained from GenBank, NCBI (Conte et al., 2008).
Therefore, different databases provide different information to suit varying research
purposes. As much as these databases are extensive and well documented for thousands of
species and varieties of plants, information based on the microsatellite makers for Prunus
varieties have not been developed. In this study we assessed the possibility of generating a
concise database based on the DNA profiling of microsatellite markers on a variety of
Prunus species.
37
Table 3: Table summarising the common fruit and plant DNA databases available.
Plant Database Description
Plant GDB - Resources for Plant Comparative Genomics • Has special datasets, e.g. SRGD for the study of pre-mRNA splicing in plants
• Has complete genome for certain plant species • Makes use of BLAST tools • Allows annotation of gene structure, alignment, and sequence
downloads. • Website: http://www.plantgdb.org/
GenBank (NCBI) • Provides a wide variety of genome mapping and sequencing
data • Insufficient data on Prunus species in the genomic BLAST
database • Website: http://www.ncbi.nlm.nih.gov/
BAZ fruit database • Federal Centre for Breeding Research on Cultivated Plants
• No DNA sequences available • Database consists of fruit crop collections in Germany • Website: http://www.genres.de/bosr/
Plant database by USDA • United States Department of Agriculture (USDA)
• No DNA sequences available • Extensive information on taxonomy, classification, properties
and images • Website: http://www.usda.gov/wps/portal/usda/usdahome
38
1.15 AIMS OF STUDY
Nadia™ is a newly patented interspecific hybrid resulting from a controlled cross
between two Prunus fruit varieties: ‘Black Amber’ plum (not patented) and ‘Supreme’
cherry (not patented).
Variety protection is of high importance for the horticultural industry and judicial cases
have become more frequent with the increasing number of essential derivation of
varieties in the market. Illegally propagating of new varieties and fraudulent labeling of
sub- standard quality products have led to severe financial losses to farmers in the
horticultural industry.
In order to prevent illegal breeding of Nadia™, it is important to accurately differentiate
Nadia™ from the rest of the related stone fruit crops to determine authenticity and to
protect against counterfeits. There are two ways of differentiating Nadia from the rest of
the Prunus family. One method is to make use of DNA profiling using suitable DNA
markers, and the other is the analysis of the chemical composition of the Nadia™ fruit
to reflect differences among the Prunus family.
Taking these into consideration, the main objective of this study is to use DNA and
chemical profiling to successfully authenticate Nadia™. The flowchart below
summaries the aims of the project and details of the experimental design.
39
A few prominent public databases that provide access to plant genome data are
Nadia™
Generate phylogenetic tree based on the length variation of each microsatellite
locus
Create DNA database on Prunus varieties based on microsatellite markers
Obtain accurate allelic sizes from Gene scanning
PCR to amplify 3 sets of microsatellite alleles
DNA profiling
DNA extraction from leaves of 20 different Prunus varieties
Assess the relationship between Nadia™ and the rest of the Prunus varieties from DNA profiling and chemical analyses
40
reviewed in the previous section. They include GenBank, GreenPhylDB, and the
USDA. While they contain different information to suit varying research purposes,
these databases readily integrate their information in order to facilitate the exploitation
of the resources. As much as these prominent databases contain data of hundreds of
different plant species, they lack sufficient information on the Prunus species.
This study aims to generate a concise database containing genomic information on
various Prunus varieties, including Nadia™, based on a few of their microsatellite
markers. In this way, by comparing genetic data obtained from the leaves of a suspect
Nadia™ plant to the database, it will authenticate Nadia™ and halt any illegal
propagation of this new variety.
41
CHAPTER 2
PART 1:
MATERIALS AND METHODS
For DNA profiling of Prunus varieties
42
2.1.1 LEAF SAMPLE COLLECTION
Prunus leaves were personally collected from Kirup Orchard, WA. Ethanol-
swabbed scalpels were used to cut the leave samples at the stalk with the whole
lamia still intact, and each leaf sample is placed in one zip-lock bag and carefully
labeled (See Figure 7). 30 samples were delivered from Joseph Rullo Orchard,
Shepperton, VIC and 50 samples were delivered from Gavin Porter’s orchard,
Bathurst, NSW. Prior to DNA extraction, all leaves were stored in -70℃ fridge.
Figure 7: Examples of Prunus leaf samples collected from Joseph Rullo Orchards and are carefully labelled.
43
2.1.2 DNA EXTRACTION FROM PRUNUS LEAVES Prunus leaves were ground with a small sterile pestle and approximately 0.10g of
finely powdered leaves were transferred to an eppendoff tube before 300ul of Plant
DNAZOL® regent (Invitrogen, USA, Cat # 10978-021) was added. The solution
was mixed by gentle inversion and incubated with shaking at room temperature for
5 min. 300μl of chloroform (Sigma, UK, Cat # C2432-500ml) was added, after
which the solution was vortexed and further incubated with shaking at room
temperature for another 5 min. The extracts were centrifuged at 12,000 x g for 10
min and 0.225ml of 100% ethanol was added to the supernatant in a fresh tube. The
tubes were inverted 8-10 times and store at room temperature for 5 min. The DNA
was precipitated at 7,000 x g for 4 min at room temperature and the resulting pellet
vortexed in 300μl of Plant DNAZOL-ethanol wash (1 volume Plant DNAZOL®
regent and 0.75 volume 100% ethanol). The samples were stored again for 5 min at
room temperature and centrifuged at 7,000 x g for 4 min. Further washing was done
with 300μl of 75% ethanol, followed by centrifugation at 5,000 x g for 4 min. The
supernatant was decanted and the DNA pellet was air-dried for 3 min. DNA was
then resuspended in 70ul TE buffer.
2.1.3 DNA PURIFICATION
300μl of Plant DNAZOL® regent (Invitrogen, USA, Cat # 10978-021) was added to
the previously extracted DNA and the mixture was mixed by gentle inversion at
room temperature for 2 min. 300μl of chloroform (Sigma, UK, Cat # C2432-500ml)
was then added and mixed by gentle inversion at room temperature for another 2
min. The extracts were centrifuged at 12,000 x g for 10 min and 0.225ml of 100%
44
ethanol was added to the supernatant in a fresh tube. The tubes were inverted 8-10
times and store at room temperature for 5 min. The DNA was precipitated by
centrifugation at 7,000 x g for 4 min at room temperature and the resulting pellet
vortexed in 120μl of TE buffer before it was transferred to the Microcon filter tube
with attached eppendoff tube. Additional 200μl of TE buffer was added to the
Microcon filter tube before it was centrifuged at 8,000 x g for 10 min at room
temperature. Rewashing of DNA was done by adding another 200μl of TE buffer
and centrifuged at 5,000 x g for 10 min at room temperature. DNA was then eluted
by inverting the spun Microcon filter tube into fresh eppendoff tube, followed by
centrifuging at 5,000 x g for 10 min and reconstituted in 70ul TE buffer. DNA
quantification was performed with computerised Nano-drop software.
2.1.4 GENOMIC PCR AMPLIFICATION OF MICROSATELLITE
MARKERS
Three sets of primers were chosen to amplify three different microsatellite regions
from DNA extracted from the leaf samples (See Table 5). Microsatellites were
amplified with the following conditions: 1x PCR buffer (10mM Tris-HCl, 1.5mM
MgCl2), 0.2mM of each dNTP, 0.5uM of each primer, 0.5U of DNA polymerase
(Fisher Biotech), 80ng of genomic DNA in a 20μl final volume. PCR reactions
were performed in an Bio-rad iCycler with “hot-start” of 95℃ for 8 min, followed
by initial denaturation for 4 min at 95℃, 35 cycles of 45 s at 94℃, 45 s at 54℃, 1
min at 72℃; and a final extension of 8 min at 72℃.
45
2.1.5 VISUALISATION OF PCR PRODUCTS BY GEL
ELECTROPHORESIS
PCR products were visualised by electrophorosis at 120V for 4 min, followed by
100V for 40 min on 1% agarose with ethidium briomide in 0.5x TBE buffer (45mM
tris, 45mM boric acid, 1mM EDTA). After electrophoresis, the DNA bands on the
gel were visualised under UV light. Promega (Madison, WI, USA) 100bp DNA
ladder was used.
2.1.6 DETERMINATION OF MICROSATELLITE ALLELE SIZE BY
GENE SCAN
As agarose gels do not provide adequate power to resolve small base pair
differences, the fluorescently labeled PCR products were sent to Royal Perth
Hospital, Department of Immunology for Applied Biosystems (ABI) Genescan
technology. It uses polyacrylamide matrix to separate DNA base pairs at a much
higher resolution than agarose gel can provide. Details on the three microsatellites
markers with their fluorescent tags were tabulated in Table 4.
2.1.7 PHYLOGENETIC TREE ANALYSIS
Microsatellite allele size from the Gene Scan results were then tabulated. The allele
frequencies of the three microsatellite markers were calculated directly by the
number of observed occurrence of that allele. Genetic distance were determined
using PHYLIP™ before the phylogenetic tree was constructed with the MEGA 4.1
software.
46
Table 4: Three primers selected to amplify microsatellites in Prunus leaf DNA
Primer Name
Primer sequence Fluorescence Repeat Product Size (bp)
Size range Phenotypic characteristics
Pchgms 20 F1/R
AAT TGC ATC ACA GCA AGA GC GGG GGT TTG GTT AAG ATC G
TET - Green
(TA)15(TC)11
252
249-267
Peach developing fruit mesocarp Prunus persica cDNA
Pchgms 20 F2/R
CCC TTA CCC CCT TAC CAC TT GGG GGT TTG GTT AAG ATC G
TET - Green (TA)15(TC)11 560 540-580 Peach shoot Prunus persica cDNA
Pchgms 12 F/R
CGA CAC TTA GCT AGA AGT TGC CTT A TCA AGC TCA AGG TAC CAG CA
6-FAM – Blue (CT)9(TC)20(CA)9 433 448-490 Plum Pox Virus infected Prunus persica cDNA
47
CHAPTER 2
PART 2:
RESULTS AND DISCUSSION:
For DNA profiling of Prunus varieties
48
2.2.1 AMPLIFICATION OF MICROSATELLITE REGIONS BY PCR
Three sets of primers were used to amplify microsatellite regions in the cellular DNA of
Prunus leaves. They were Pchgms 20F1/R, Pchgms 20F2/R and Pchgms 12 primers that
were identified in peach (Prunus persica (L.) Batsch) by Wang et al. (Wang et al., 2002).
Figure 8 to 12 show gel photos of leaf samples (n=3) that were amplified by PCR using
these three sets of unlabelled primers. Microsatellite regions of each leaf sample were
successfully amplified based on the distinct DNA bands visualised with the aid of
ethidium bromide on 1% agarose gel after gel electrophoresis. DNA ladders from
Promega (Madison, WI, USA) used in the gel electrophoreses are in 100bp increments.
Fortune plum, Cherry Royale, Nadia™, Flavour Fall and Suplum11 plums were chosen
as the positive controls for the gel diagrams as they give the most distinct DNA banding
on the gel for all three primer sets, Pchgms 20F1/R primers (Figure 8 and Figure 9),
Pchgms 20F2/R (Figure 10 and Figure 11) and Pchgms 12 (Figure 12). The bands were
distinct and the sizes of the amplified microsatellite regions for each marker coincide
with the allele size reported in previous study (Wang et al., 2002). This shows that the
markers used in this project are suitable for successful amplification of the required
microsatellite regions from the Prunus genome.
As agarose gels do not provide the adequate power to resolve small base pairs
differences, the PCR amplified products were subsequently analysed using a
polyacrylamide matrix with the aid of ABI’s Genescan technology.
49
Figure 8: Gel electrophoresis on positive control samples 17T(B), 187D(A), 260T(A) using unlabelled pchgms 20F1/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002.
Fortune plums Cherry Royale Flavour Fall
50
Figure 9: Gel electrophoresis on positive control samples 73J(B), 203X(A), 217Z(A) using unlabelled pchgms20F1/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002.
Fortune plums Nadia™ Suplum11
51
Figure 10: Gel electrophoresis on positive control samples 17T(B), 187D(A), 260T(A) using unlabelled pchgms20F2/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002
Fortune plums Cherry Royale Flavour Fall
52
Figure 11: Gel electrophoresis on positive control samples 73J(B), 203X(A), 217Z(A) using unlabelled pchgms20F2/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002.
Fortune plums Nadia™ Suplum11
53
Figure 12: Gel electrophoresis on positive control samples 187D(A), 17T(B), 73J(B) using unlabelled pchgms12 F/R primer pairs. Amplified DNA bands fall within the microsatellite size range reported in the article by Wang et al., 2002.
Cherry Royale Fortune Plum Fortune Plum
54
2.2.2 POLYMORPHISM IN DNA BAND PROFILES
Hints of polymorphism between different varieties can be detected at the preliminary
stage of experiment. Despite the low power of resolution offered by a 1% agarose gel,
there were distinct banding patterns generated from the four varieties in the agarose gel
photo in Figure 13. It clearly showed that differentiation of varieties is possible from the
intensity and patterns of DNA bands. Lane 2 to 7 has similar banding profiles, indicating
that they are of the same DNA sample, which in fact, are DNA samples from the Settler’s
Gold peach. Lane 8 and 9 have 2 distinct bands in each lane, while lane 10 and 11 have
only 1 distinct band in each lane thus showing two very different varieties; they are the
Angelino plum and Nadia™ plum samples respectively.
Gel from Figure 13 also shows the reproducibility of data. Lanes 2 and 3 (Sample
52Y(B)), and Lanes 4 and 5 (Sample 51X(A)) are samples from 2 independent leaf
samples while Lane 4 and 5 (Sample 51X(A)), and Lanes 6 and 7 (Sample 51X(B)) are
samples obtained from the same leaf, but had independent DNA extractions performed on
separate occasions. Hence, regardless of the independent leaf samples and DNA
extractions, leaves from the same type of variety share similar DNA banding profile
when they are amplified with Pchgms 20F2/R primer pair.
55
Figure 13: Gel electrophoresis on samples using labelled Pchgms 20F2/R primers set.
Settler’s Gold Peach Angelina Nadia™
56
2.2.3 GENE SCANNING
The Prunus leaf DNA samples were then subjected to PCR amplification with labelled
primers and sent to Department of Immunology, Royal Perth Hospital, Western Australia
for Gene Scanning. Figure 14 to 18 show examples of the electrophoretograms of each
pre-labelled microsatellite amplified by the 3 primer pairs, containing information on
their allele sizes and genotype of the sample.
Electrophretograms reveal information on the genotype of the sample from the number of
peaks present in the profile. Figure 14 and 15 show the eletrophoretograms from two
selected samples amplified by labelled Pchgms 20F1/R primers. Specifically from Figure
14, amplification of microsatellite from Flavour fall plum by Pchgms 20 F1/R resulted in
a single signal peak being detected at the allelic size of 248kb indicating homozygous
allele. On the other hand, amplification of microsatellite from Fortune plum by Pchgms
20 F1/R primers resulted in two signal peaks at size 248kb and 255kb (shown in Figure
15), indicating heterozygous nature of the allele in this variety. Genotypes and allelic size
of the microsatellite markers for the rest of the Prunus samples are tabulated in Table 5.
In order to exhibit reproducibility and reliability of the methods used in this study,
numerous samples have been used on each of the varieties, such as the Fortune plums,
Flavour Falls plums and Settler’s Gold Peaches (See Table 5). The allelic sizes of the
microsatellite markers for these varieties were very similar showing reproducibility of the
gene scanning method. Having multiple samples for each variety also aid in increasing
accuracy in data analysis.
57
Figure 14: Gene scan signal graph that shows a single signal at allele size of 248kb, indicating the homozygosity of the microsatellite allele in this particular sample, 260T(A) (Flavour Fall plum) using Pchgms 20F1/R primer pairs.
Size (Base pairs)
58
Figure 15: Gene scan signal graph that shows signals at allele size of 248kb and 255kb, which indicates the heterozygosity of the microsatellite allele in this particular sample, 16R(B) (Fortune plum) using Pchgms 20F1/R primer pairs.
Size (Base pairs)
59
Figure 16: Gene scan signal graph that shows a single signal at allele size of 564kb, indicating the homozygosity of the microsatellite allele in this particular sample, 261U (Nadia™) using Pchgms 20F2/R primer pairs.
Size (Base pairs)
60
Figure 17: Gene scan signal graph that shows signals at allele size of 556kb and 572kb, which indicates the heterozygosity of the microsatellite allele in this particular sample, 227J(B) (RubySun plum) using Pchgms 20F2/R primer pairs.
Size (Base pairs)
61
Figure 18: Gene scan signal graph that shows a single signal at allele size of 427kb, indicating the homozygosity of the microsatellite allele in this particular sample, 248M (T5R3 03-10RN peach) using Pchgms 12 primer pairs.
Size (Base pairs)
62
Table 5: Tabulation of allelic size of 3 microsatellite markers and genotypes across a variety of Prunus samples.
Pchgms 20 F 1 Pchgms 20 F2 Pchgms 12 Sample Number Common Name Species Allele Size Allele size Allele Size 203X(A) Nadia™ P. salicina
245 245 593 593 451 458 245 245 - - 451 458
202W(A) 245 245 593 593 450 458 245 245 593 593 450 458
16R(B) Fortune P. salicina
248 255 566 573 450 462 248 255 566 573 450 462 17T(B) 252 259 566 573 451 462 252 259 - - - - 18U(B) 248 255 566 573 451 462 248 255 - - 451 462 73J(B) 252 259 566 573 450 462 - - - - 451 462 79W(A) Angelino P. salicina 242 248 564 564 450 462 - - - - 450 462 175P(A) Teagen blue P. salicina 252 252 566 566 450 458 252 252 566 566 450 458 32W(A) 248 248 566 566 450 458 248 248 566 566 451 458 187D(A) Cherry Royale P. salicina 245 245 564 564 450 459 245 245 593 593 450 459 260T(A) Flavour Falls
P. salicina
248 248 566 566 452 452 252 252 564 564 450 458 252 252 566 566 450 459 - - - - 450 458 261U(A) 252 252 564 564 450 459 - - 564 564 452 459
63
Table 5b: Tabulation of allelic size of 3 microsatellite markers and genotypes across a variety of Prunus samples.
Pchgms 20 F 1 Pchgms 20 F2 Pchgms 12 Sample Number Common Name Species Allele Size Allele size Allele Size 226H(B) Avner plum P. salicina 248 248 564 564 - - 248 248 564 564 - - 227J(B) RubySun plum P. salicina 248 255 566 573 458 468 248 255 566 573 - - 271Z(A) Suplum11 P. salicina 252 252 - - 451 458
252 252 - - 451 459 262W(B) Suplum 24 P. salicina 248 248 564 564 451 458 - - 564 564 - - 51X(A) Settler’s Gold peach P. persica 240 246 - - 427 428 240 246 - - 427 428 51X(B) 240 246 - - 427 428 240 246 - - 427 428 52Y(B) 240 246 - - 427 428 240 246 - - 427 428 248M(A) R5T3 03-10RN
Peach P. persica - - 551 551 427 427
- - 551 551 427 427 219A(A) Alex apricot P. armeniaca 254 254 - - 469 469 254 254 - - - - 218Z(A) Mascot apricot P. armeniaca - - - - 469 469
64
2.2.4 POLYMORPHISM INFORMATION CONTENT (PIC)
We used the Polymorphism Information Content (PIC) value to determine degree of
polymorphisms for each microsatellite in each Prunus variety. The term polymorphism
information content was coined by Bostein et al. (Bostein et al., 1980) to measure
polymorphism for a marker locus used in linkage analysis. In this study, we used the
algorithm described by Anderson et al. (Anderson et al., 1993) to calculate PIC values
for Pchgms 20F1/R, Pchgms 20F2/R and Pchgms 12 microsatellite markers for each
Prunus variety (See Table 6) from the allelic sizes tabulated in Table 5.
PIC values range from 0.00 to 1.00. The higher the value, the more polymorphic the
marker for the particular variety. From Table 6, degree of polymorphism is the highest
for the Pchgms 12 marker for Flavour Falls plum with a PIC value of 0.77. This is
followed by Pchgms 20F1/R and Pchgms 12 for Fortune plum, with PIC values of 0.75
and 0.62 respectively. PIC values of microsatellite markers for several varieties were
null values. While this may indicate null polymorphisms in the markers, the lack of
sample replicates could possibly lead to the inaccuracy in PIC value calculation.
65
Table 6: PIC values of the 3 microsatellite markers on 14 different varieties of Prunus.
PIC values
Pchgms 20 F1/R
Pchgms 20 F2/R
Pchgms 12 Variety Nadia™
0.00 0.00 0.63
Fortune plum
0.75 0.5 0.62
Angelino plum
0.50 0.00 0.50
Teagan Blue plum
0.50 0.00 0.59
Cherry Royale
0.00 0.50 0.50
Flavour Falls plum
0.38 0.48 0.77
Avner plum
0.00 0.00 -
Ruby Sun plum
0.50 0.50 0.50
Suplum 11
0.00 - 0.61
Suplum 24
0.00 0.00 0.50
Settler’s gold peach
0.50 - 0.50
R5T3 03-10RN peach
- 0.00 0.00
Alex Apricot
0.00 - 0.00
Mascot Apricot
- - 0.00
2.2.5 PHYLOGENETIC TREE ANALYSIS
The analysis of DNA sequence variation is important in genetic studies and these
molecular markers have become important tools for assaying genetic variation. A
variety of molecular markers include RFLPs, RAPDs, AFLPs and microsatellites have
been developed in different plants (Philips et al., 2001). Due to their reproducibility,
codominant inheritance, multi-allelic nature and relative abundance, microsatellite
66
markers have been useful in their application in genetics studies (Powell et al., 1996)
and they are effective in linking phenotypic and genotypic variation (Gupta et al.,
2000).
In the recent years, microsatellite DNA loci have been used for phylogenetic analysis to
study inter-population, allowing phylogenetic trees of human individuals to be
constructed to reflect geographic origin (Bowcock et al., 1994). It has also been used to
differentiate species and interpreting evolutionary and biogeographic histories (Petren et
al., 1999). Similarly, phylogenetic tree analyses based on microsatellites alleles have
been done in plants and fruits, for example in egg-plants (Stagel et al., 2008) and oats
(Li et al., 2000).
In this study, we extrapolated the research idea and construct a phylogenetic tree based
on 3 microsatellite markers of 14 diffferent Prunus varieties. There are two methods of
phylogenetic reconstruction that are suitable for microsatellite DNA loci: the neighbour-
joining (NJ) method and the unweighted pair group method with arithmetic mean
(UPGMA). While UPGMA can be used for allele frequency data when the evolutionary
rate is nearly the same for all populations (Nei, 1987), NJ method is reported to be
applicable for a variety of situations (Nei, 1991). Hence, we make use of NJ method to
produce an unrooted phylogenetic tree of Prunus varieties based on 3 microsatellite
markers (See Figure 12). Genetic distances were calculated from allele frequencies
using the Cavalli-Sforza chord measurement.
Other than Nadia™ and Cherry Royale (in bold), there are three main Prunus varieties
in the phylogenetic tree (Figure 19), the plums (italised), the peaches (underlined) and
the apricots (regular).
67
From the phylogenetic tree in Figure 19, it clearly shows that there are two main
branches, separating the plums from the apricots and peaches. Nadia™, being a cross
hybrid of Black Amber plum and Sweet Cherry, was expected Nadia™ to have closer
relationship to the plum varieties than to the apricots and peaches as shown in the tree.
Interestingly, it is observed that Nadia™ and Cherry Royale were branched off
exclusively from the rest of the plum varieties. Nadia™ and Cherry Royale carry
different names but they are of the same hybrid. In other words, this Prunus variety is
unique in the way that separates them from the rest of the plum varieties. This
observation emphasize Nadia™ as a whole new variety, segregating from its parental
plum or cherry varieties in the Prunus family. This indicates that it is possible to
differentiate Nadia™/ Cherry Royale from the rest of the plum varieties, and even more
so from the apricots and peaches.
In this study, Nadia™ and Cherry Royale are treated separately as individual varieties
even though they are of the same hybrid. This ensures that our experimental methods
are reproducible and also reduces biasness in the collection of results. While Nadia™
and Cherry Royale are the same variety; it produced slightly different results from the
amplification of Pchgms 20 F2 microsatellite markers alleles shown in Table 5 (See
Table 5). The differences in the results could be due to inaccurate binding of
microsatellite primers to the DNA region of interest. As there is a lack in repeated tests,
it is difficult to verify the discrepancy.
This study can be improved greatly by including the Black Amber plums and Supreme
cherries in the phylogenetic tree analysis. More interesting observations can be made by
68
comparing the relationship between Nadia™ and its parents with respect to their genetic
distances on the phylogenetic tree.
Due to the time and funding constrains, this study made use of only 3 microsatellite
markers with 14 Prunus varieties out of 50 different varieties provided by the suppliers
were used to analyse genetic variation of the stone fruit family. By using more
microsatellite markers and testing on bigger sample pool, it would drastically improve
the accuracy and the reliability of this study. In spite of the insufficiency of data, we are
still able to show the possibility in differentiating Nadia™ from the rest of the Prunus
family members by using polymorphic microsatellite markers.
Figure 19: Phylogenetic tree reconstruction for 14 Prunus fruit varieties based on 3 microsatellite markers using NJ method.
69
2.2.6 CONCLUSION
Close to 100 primer pairs of microsatellite have been developed in Prunus genome
(Testolin et al., 2000; Dirlewanger et al., 2002; Zhebentyayeva et al., 2003). Most of
them were isolated and sequenced from peach cultivars. Even though the microsatellite
markers were developed in peach (Prunus persica (L.) Batsch), their use in genetic
diversity analysis in peaches, sweet cherry, and apricots have been established
(Dirlewanger et al., 2002; Zhebentyayeva et al., 2003). In view of this, this study
successfully used three microsatellite markers developed from peach Simple Sequence
Repeats (SSR)-enriched genomic libraries (Wang et al., 2002), Pchgms 20 F1/R,
Pchgms 20 F2/R and Pchgms 12 markers to assess the diversity of genetic variation
across a range of varieties including plum, apricot and peach cultivars from the Prunus
family.
Scientists or researchers usually use more than 10 microsatellite markers to assess
genetic diversity of various populations (Rout et al., 2008; Ayub et al., 2003). Due to
the time and funding constraints, only three microsatellite markers were used in this
project and only 14 out of 50 Prunus varieties were chosen. The 14 Prunus varieties
were chosen to make sure that the selection covers a wide variety of Prunus family
members, such as plums, peaches and apricots. The reason for omitting cherry variety in
the results is the difficulty in extracting good quality DNA from the cherry leaves using
DNAzol® technique from Invitrogen. This can be resolved by using other DNA
extraction techniques, such as CTAB. However, it could not be done in this study with
the lack of funds.
70
As much as it is deemed insufficient for an accurate and reliable analysis, interesting
observations could still be made from the microsatellite- based phylogenetic tree
constructed from 14 varieties of Prunus fruits. It allows Nadia™ to be differentiated
from the rest of the plums, peaches and apricots as a unique hybrid of the Prunus
family. It could also provide information on the relationship of hybrids and their parents
based on their genetic distances, and shows that new hybrids could be unique on its own
but at the same time share very close genetic relationship with their parents.
The next possible step to this research could be the optimising of a multiplex PCR to
amplify multiple microsatellite alleles on the same strand of DNA. Although there could
be difficulty in setting up the essential primers and optimal conditions, it is a very useful
technique if multiple markers can be amplified from the same DNA strand and is
essential when the amount of sample is small. Together with a concise microsatellite
DNA database for the Prunus family, this technique can be developed into a more
sophisticated authenticity validation for this newly patent Nadia™ hybrid.
71
CHAPTER 3
The characteristics of a novel inter-specific Japanese Plum X Sweet
Cherry hybrid
Cheryl Chan, Aishah Kadher, Stephen Iaschi and Guan Tay
This section was submitted to Journal of Agriculture and Food Chemistry and is
presented in the form required by the journal.
72
Preface
The research efforts resulted in the description of the chemical profiling of a fruit for the
first time. The novelty of the information is presented as a manuscript to the Journal of
Agriculture and Food Chemistry.
It includes an introduction that supplements the Chapter 1: Literature Review of this
thesis. It stresses on the importance of authenticating fruits and their products in the
food and beverage industry. A quick review of the current chemical techniques that
were established to study chemical profiling of various commercially available fruits
was also included. Nadia™ as a newly patent Prunus hybrid was described, and its
chemical profiling was reported for the first time.
This is followed by the material and methods used to generate the chemical profile of
Nadia. A variety of nutritional compositions were analysed. They include the fat
contents, simple sugar contents, acidity, sodium/ potassium levels, Vitamin C, α- and β-
carotene, tocopherol, and antioxidant properties. All of the chemical analyses were done
in collaboration with DTS (Dairy Technical Services Ltd) and NMI (National
Measurement Institute). The first observations for Nadia™ were provided by Dr Gavin
Porter.
Results and discussion section included some physical observations of Nadia™ as a
fruit at time of harvest, tables of its nutritional profiles. With its high content of β-
carotene and antioxidant properties, Nadia™ is considered to be a premium Prunus
hybrid. A chemical profile was also suggested to enable differentiation of Nadia™ from
the rest of the Prunus family members based on the chemical properties.
This section was submitted to Journal of Agriculture and Food Chemistry on 28 April
2010 and is presented in the form required by the journal. However it was rejected by
73
the journal on 20 May 2010 as they do not publish articles concerning characteristics
and analyses of newly patent fruit products. In view of this, this section will be
submitted to Acta Horticulturae for their review.
74
Abstract The food and beverage industry faces significant losses in income due to illegal
propagation of new varieties to avoid royalty payments. Together with its high
nutritional values, characteristic physical properties and desirable post harvest traits, the
newly bred variety, Nadia™, is one of a series of novel hybrids of the Prunus family,
which could possibly attract premium prices. The authentication of new fruit varieties is
now part of doing business in the lucrative horticultural industry. Taxonomic
description, chemical composition and DNA profiling have all been used for this
purpose. By assessing characteristic chemical properties of Nadia™, and comparing the
nutritional values and chemical composition between Nadia™ and its closely related
Prunus family members, this study specifically aims to describe the chemical profile
towards providing methods for the authentication of Nadia™ and differentiating from
other Prunus varieties. The study showed that Nadia™ not only contains high levels of
antioxidant properties, it also has relatively high levels of β-carotene in the fruit.
Typically, dark red fruits are associated with high antioxidant levels and orange fleshed
fruits, such as apricots, are associated with high β-carotene levels. Nadia™ is unique in
that it has relatively high levels of both compounds. When combined, the unique ratios
of antioxidant levels, β-carotene and relative sugar content could be a potential
chemical profile for the authentication of Nadia™ among other fruits in the Prunus
family.
Keywords: Prunus, Authenticity, Nadia™, Antioxidants, ORAC values, β-carotene,
Sugar profile.
75
Introduction Fraud in the food and beverage industry has been a major factor that contributes to
substantial loss of income. It affects producers who lose a revenue stream and
consumers, who do not get value for their money. Fraudulent cases include
counterfeiting the brand names of premium quality products, such as illegally altered
rainbow trout being passed off as the more expensive Atlantic Salmon (1), or illegally
breeding new varieties of fruits or plants to avoid royalty payments (2). With an
increasing demand for quality of fruit products, and the increasing interest in the health
benefits of fruits, there is a continuing need to develop new fruit varieties. The cost
associated with developing new fruit varieties can be substantial. Since the economic
gain can be significant, there is increased likelihood in having more counterfeits in the
market. When the economic incentive is great, fraudsters will adulterate food products
with their less expensive counterparts or sugar solutions.
The Prunus fruit industry is one of the more significant horticultural industries in
Australia. This sector of the industry produces crops including peaches, nectarines,
apricots, cherries and plums. Nadia™ is a newly developed interspecific hybrid
resulting from a controlled cross between two Prunus fruit varieties: the ‘Black Amber’
plum (P. salicina) and ‘Supreme’ cherry (P. avium). It was bred at a commercial
orchard at Shepparton, Victoria, Australia. As with all fruit varieties protected by
patents and plant breeder’s rights (PVR and PBR), it is of the utmost importance to
accurately differentiate Nadia™ from the rest of the stone fruit crops in order to
determine authenticity, to protect against counterfeits and to allow prosecution of
unlicensed growers. It is also important to assess the eating quality and the nutritional
value of Nadia™ and to meet the demands for better post harvest traits, fruit quality and
enhanced health benefits.
76
With the development of highly sensitive analytical tools that are both rapid and
inexpensive, researchers are able to quantify different types of chemical components in
fruits and their products. This has led to a new approach in determining fruit
authenticity and product content based on the assumption that fruits may have unique
chemical markers that allow differentiation among species, varieties and breeding
location.
There are many analytical techniques that have been widely implemented in the food
industry for analyzing food products. Near infrared spectroscopy (NIR) has been used
to analyze various ingredients in food (3), specifically to evaluate fruit authenticity from
cell wall component analysis (4). Other technologies also include High Performance
Liquid Chromatography (HPLC) and Gas Chromatography coupled with flame
ionization detector (GC-FID) to characterize fruits and their products from cell wall
polysaccharides (5). In addition, pyrolysis Mass Spectrometry coupled with Gas
Chromatography (GC-MS) based on testing carbohydrates (6), soy proteins (7) and
oligossacharrides (8) can be used to autenticate fruit, as well as being used to detect
fruit juice (9) in processed products.
With these powerful analytical techniques, many different chemical components have
now been readily used as markers for differentiating fruits and their products. For
example, differentiation of mango cultivars have been reported by Berardini N. (2005)
based on their contents of flavonol and xanthone C-Glycosides, anthocyannins and
pectin (10). Sugar content (4) and antioxidant (11) properties have also been used in
fruit differentiation.
77
To date, there is no specific chemical marker that can accurately authenticate a wide
range of fruits and their products. The process of chemical differentiation usually
requires a list of assays to be performed. The juice authenticity testing program at
HiTech Analytical and Diagnostic Solutions (HADS), founded by the late Dr Allen
Brause, had produced a set of standards and guidelines for authenticity testing. It
includes a matrix of laboratory tests for thirteen different chemical components, which
include organic acids, sugars, flavonoids, anthocyanins, benzoic and sorbic acids,
polyphehols, amino acids, etc. (12)
The objective of this study is to assess the chemical composition and compare the
nutritional content of Nadia™ with other closely related Prunus fruits to develop a
chemical marker or a profile that can possibly aid in differentiating Nadia™ from the
rest of the Prunus family members.
Materials and Methods
Oxygen Radical Absorbance Capacity-fluorescein (ORAC-FL) Assay
The method is adapted and modified on the previous procedure described by Ou et al
(13). 75mM phosphate buffer (pH 7.4) making up to 200μl was used in the reaction.
20μl of antioxidant solution and 120μl of fluorescein solution (70nM, final
concentration) were placed in the well of the microplate, which was then preincubated
for 15min at 37℃. 60μl of 12mM 2,2’-azobis(2-methylpropionamidine) dihydrochloride
(AAPH) solution was added rapidly before the microplate was immediately placed in
the reader. Fluorescence was recorded at every minute for 80min. A blank, consisting of
FL and AAPH with phosphate buffer was used including eight calibration solutions of
Vitamin E at a range of 1μM to 8μM. All reaction mixtures were prepared in duplicate,
and at least three independent assays were performed for each sample. Raw data were
78
exported from the Fluostar Galaxy software to an Excel macro program (Microsoft,
Roselle, IL) for further calculations. Antioxidant curves (fluorescence Vs time) were
first normalized to the curve of the blank of the same assay. Thereafter, the area under
the fluorescence decay curve (AUC) was calculated. Regression equations between net
AUC and antioxidant concentration were calculated for all the samples. ORAC-FL
values were expressed as Vitamin E equivalents by using the standard curve calculated
for each assay. ORAC-FL assay was further extended to lipophilic antioxidants by
using methylated β-cyclodextrin as water solubility enhancer (14).
Total Tocopherol determination by HPLC
Sample Preparation
This method was adapted from previous procedure by Indyk, H. E. (1988) (15): flesh of
the fruits were accurately weighed and 10 ml of 100% ethanol containing pyrogallol
(1%m/V) was added and agitated to avoid agglomeration. A known aliquot of the α-
tocopherol standard (200μl) was used as a parallel assay external standard and to
provide recovery data. 2ml of Potassium hydroxide solution (50% m/V) was added
immediately and the reactions were incubated for 7min at 70℃. Periodic agitation was
ensured for efficient digestion of lipid. Reaction mixture was cooled before extraction
solvent: 20ml mixture of 3 part light petroleum to 1 part diisopropyl ether was added
and the tubes were stoppered securely and agitated for 5min. 30ml of distilled water was
added and the tubes were re-stoppered and inverted 10 times and centrifuged at 180 x g
for 10 min.
Quantification
10μl of the supernatant layer was injected directly into the isocratic HPLC system.
Routine determinations were performed with a 5μm C-18 Rad-PAK cartridge and 100%
79
methanol as the mobile phase. Flow-rate of 1ml/min and fluorescence detection (λex =
295nm; λem = 33nm) were used. Calculations were based on comparison of the peak
areas of tocopherol congeners and with recovered α-tocopherol.
Carotenoid extraction
Carotenoid substances extraction method is adapted from previous paper described by
Wilberg and Rodriguez-Amaya in 1995 (16). Fruits were weighed and transferred to test
tube with 20 ml of ethanol:hexane (1:1) solvent mixture, and homogenized in a blender.
The pulp is then filtered with 0.45 micra pore diameter PTFE (polytetrafluoroethylene)
membranes. Homogenization process was repeated with residue retained on the
membrane filter. All filtrate was transferred to a separator funnel in a mixture of 20ml
of hexane and 25ul of distilled water, and shook for 60sec before phase separation. The
aqueous phases collected was transferred to a second separator funnel for a second re-
extraction process. Any remaining aqueous residue in the hexane phases was removed
by adding 1.0g of sodium sulphate anhydride (Na2SO4) and then inverted gently for
30sec. All hexane carotenoid extract content were transferred to volumeric flask and
concentrated by vacuum rotary evaporator at 40℃ for 25 min. After concentration,
samples were recovered and hexane was added to make up the exact volume.
Determination of Carotenoid content
Carotenoid content was determined by reverse phase-HPLC analysis (17). HPLC
separation was done using an ODS C18 column and a mobile phase of
methanol:acetonitrile:chloroform (47:47:6) (17). The flow rate was set at 2ml/min and
all readings were taken at 461nm. Retention time comparison was made with
commercially available standards to identify α- and β-carotene. Extinction coefficients
for β-carotene was 2396 in chloroform at 465 nm; α- carotene, 2800 in light petroleum
80
ether at 444 nm.
Carbohydrates analysis
Carbohydrate analysis was performed using High Performance anion-exchange
chromatography (HPAEC) coupled with PAD (Pulsed Amperometric Detection) on a
Dionex DX-500 chromatograph (Sunnyvale, USA). The column was a Dionex
Carbopac PA-10 (4mm x 250mm) with a PA-10 guard column (4mm x 50mm).
Deionized water and 300mM MaOH were used as eluents. Percentages of both eluents
were calculated to obtain the desired hydroxide concentration of 12mM during 25 min,
12-150mM in 1 min, 150mM at 5 min, 150-12mM in 1 min and column equilibration at
12mM for 8 min. Flow rate was fixed at 1ml/min and the column was kept at 30℃. PAD
detection was performed with a gold working electrode and an Ag/AgCl reference
electrode, with a data collection rate of 2Hz. Potential was set at 0.10V for 0.41s, -2.0V
for 20ms, 0.6V for 10ms and -0.10V for 60ms. 5-points calibration curves ranging from
1 to 100μmol/L, was used to quantify the carbohydrates.
Sample preparation for proximate analysis
Moisture, ash, fat, protein content in the sample were determined using methods by The
Scientific Association Dedicated to Analytical Excellence® International (AOAC) (18).
Moisture content: Crucible was first placed in drying oven at 105℃ for 2hr before being
placed in the desiccators for cooling. The sample was then dried at 105℃ for 3 hr.
Percentage of dry weight and percentage of moisture content in sample was calculated.
Ash: Preparation of ash was similar to the preparation of crucible in the measurement of
moisture content. 2.0g of sample was placed in crucible and weigh was recorded before
81
being placed in muffle oven at 550℃ for 8hr.
Fat: Fat content was extracted from the dried ground fruits with petroleum ether in an
intermittent Soxhlet extractor (Soxhlet Extractor Darmstadt, Germany) for 4hr. Residue
at the bottom of the flask was weighed and its reflective index was determined.
Crude protein: 2g of dried samples was digested in Kjeldahl digester (Tecator Kjeltec
System, Germany) for 30mins with 2 tablets of catalyst and 20ml of sulphuric acid at
400℃. 50ml of distilled water was added for distillation. Sample was then titrated with
hydrochloric acid (0.2 M) to calculate amount of HCl present in 40% NaOH solution.
4% boric acid solution was used for the catalyst reagent. Amount of proteins can be
calculated by multiplying 6.25 to the percentage of nitrogen present.
Sugar/Acid Ratio
Sugar analysis: Refractometer analyses were performed on a “Schmidt + Haensch -
DUR’ digital refractometer at 20℃. The amount of soluble components in the fruits was
expressed as the Brix-value.
Acidity: Acidity of fruit was measured using a pH meter. 0.1M NaOH was titrated into
10 ml of juice solution until pH meter reads pH 8.1 and the amount of NaOH used was
recorded. Calculation for sugar/acid ratio is described below:
Percentage acid = titre x acid factor x 100 / 10 ml of juice
Sugar acid ratio = Brix value/ Percentage acid
Potassium- Sodium ratio
Dried samples were first digested with a mixture of 5 parts HNO3 and 2 parts H2O2. The
82
sample was then diluted to 25 ml before subjected to 3 independent measurements by a
sequential Inductive coupled plasma atomic emission spectrometer (ICP-AES)
instrument, type Atom Scan 25 ICP (19).
Results Table 7 summarizes the production attributes between Nadia™ and a generic cherry. It
includes the physical appearance, size, yield and fruit’s susceptibility to brown rot and
splits. Nadia™ fruit is physically distinguishable from a generic cherry from its size as
it is almost 4 times larger than a normal sized cherry. Nadia™ fruit has a 5 to 1 flesh to
pip volume ratio, compared to a 2 to 1 flesh to pip ratio of a generic cherry. It has at
least 25% more sugar (20 to 24 Brix) than what a generic cherry (17 to 18 Brix) has at
time of harvest. More importantly, it has been observed that Nadia™ is highly resistant
to brown rot and splits that are commonly plague many cherry varieties, and has a much
higher product yield than a generic cherry. These initial observations were collated by
Dr Gavin Porter of the Australian Nurserymen’s Fruit Improvement Company
(ANFIC).
In this study, we attempted to compare nutritional qualities of Nadia™ and its closely
related Prunus varieties. Nadia™ fruits were collected from the mother tree and two
year old trees grown out for commercial production. The nutritional qualities of
Nadia™ were compared with Black Amber plums, Sweetheart cherries, Prime Time
plums and another non-Prunus fruit, blueberries. All fruit varieties were in 20
duplicates and the average value of each nutritional quality was tabulated (See Table 8a
and 8b). Nadia™, being a cross hybrid of “Black Amber plum” and “Supreme” cherry,
appears to contain qualities that are a reflection of the two parents: Nadia™ fruit from 2
year old trees has an average weight of 44.8g, that is almost as heavy as the black amber
83
plum (47.5g), and its protein level at 1.0g/100g was higher than the “Supreme” cherry,
measured at 0.9g/100g.
Another noteworthy nutritional quality is the carbohydrate component of Nadia™ fruit.
Total carbohydrate present in Nadia™ exceeds that of Black Amber plum and
Sweetheart cherry. Sodium/ Potassium levels in Nadia™ (1.00mg and 230mg
respectively in 100g) are on the higher end, more similar to Sweetheart cherry (1.40mg
and 200mg respectively in 100g) than Black Amber plums (0.65mg and 140mg per
100g). Total ORAC values of Nadia™ are comparable to that of Sweetheart cherries
and Black Amber plums, recorded at 41,743umol/100g for Nadia™ and
39,596μmol/100g for Sweetheart cherry and 42,346μmol/100g for Black Amber plum.
The other important observation is the higher amount of β-carotene present in Nadia™.
It is higher at 183.3μg/100g for Nadia™ from 2 years old plants, while β-carotene in
Sweetheart cherries, plums and blueberries range from 29μg to 81μg per 100g.
ORAC values and β-carotene values of Nadia™ were then compared across a whole
range of Prunus fruits, including apricots, cherries, nectarines, peaches and a few
different varieties of plums (See Figure 20). From Figure 20, antioxidant levels of
Nadia™ from 2-year old plants is the fourth highest among the various Prunus fruits,
falling shortly behind Black Amber plum, Prime Time Plum and a generic plum of
unknown variety. Apricots have the most β-carotene in its fruit. Nadia™ from the
mother plant contains the second most β-carotene at more than 200μg per 100g, which
is followed by generic plums and Nadia™ from 2-year old plants.
We also compared ORAC and β-carotene values of Nadia™ as a ratio with a vast
84
variety of fruits including cranberries, apples, mangoes, bananas, melons, etc. The
ORAC: β-carotene ratios were tabulated in Table 9 in descending order. Green shaded
region of the table indicates fruits with high ratio values, i.e. fruits with very high
ORAC but low β-carotene levels. Blue shaded region of the table indicates fruits with
mid ratio values, while pink shaded region indicates fruits with low ORAC: β-carotene
ratios. Fruits with very low ORAC: β-carotene ratios are those with low ORAC but
high β-carotene levels. On the other hand, mid ratio values indicate that both ORAC and
β-carotene levels are moderately high in the fruits. Nadia™ harvested from both mother
and 2 year old trees, together with grapes, banana, orange and some plum varieties,
have ORAC: β-carotene ratios falling within the mid region.
Discussion and Conclusion Nadia™ is a newly bred hybrid that has satisfied the demands for new fruit varieties. As
a cross hybrid between ‘Black amber’ plum and ‘Supreme’ cherry, Nadia™ fruit has
acquired traits that are of premium quality. Not only is the fruit of Nadia™ bigger than
a normal sized cherry, it also has an average 5 to 1 flesh to pip volume ratio indicating
that Nadia™ has more edible flesh than a 2 to 1 flesh to pip volume ratio of a generic
cherry. Furthermore, it is generally sweeter than a generic cherry for its 25% increase in
sugar content than what a generic cherry has at time of harvest.
Nadia™ also has better post harvest traits than a generic cherry. It is highly resistant to
two of the most common undesirable post-harvesting traits faced by common stone
fruits: brown rot and splits. Brown rot is a major disease caused by the fungus,
Monilinia fructicola, affecting most commercially grown stone fruits. It is one of the
main factors causing major crop losses, as it can infect the flowers and the fruit bearing
twigs that can eventually lead to fruit infections causing entire crop loss on the tree or in
85
storage (20). Rain cracking, on the other hand, is most noticeable when cherries split in
the rain as rainwater is absorbed through the cuticle. It is a problem that affects cherry
growers throughout the world. With splits in the cherry, it makes the fruit more
susceptible to brown rot infections (21). Deterioration of the quality of commercial
fruits is inevitably the main concern for cherry growers as it affects sales and profit.
Nutrition analysis of Nadia™ in Table 8 shows similarities in the nutritional values
shared between a generic cherry and the Black Amber plum. “Nadia” harvested from 2
year old trees have similar moisture content, total carbohydrates, amount of total sugar
content and sodium-potassium content as the Sweetheart cherry. On the other hand, like
Black Amber plums, Nadia™ contains large amounts of antioxidant and its acid levels
falls between the cherry and the plum.
It is known that dietary supplementation with fruits or vegetable extracts high in
antioxidants plays a role by decreasing the enhanced vulnerability to oxidative stress
that occurs in aging and reduce deleterious effects of behavior and brain aging (22,23).
All aerobic organisms are susceptible to oxidative stress because reduced oxygen
species, superoxide and hydrogen peroxide are produced by mitochondria during
respiration (24). Reactive oxygen species have been implicated in the etiology of a host
of degenerative diseases including cardiovascular disease, diabetes (25), cancer (26),
Parkinson’s disease (27), Alzheimer's disease (28,29) and other neuro-degeneration in
motor neurone diseases (30). It also contributes to the aging process (31). However,
evidence have shown that the antioxidant compounds provided by fruits and vegetables,
and possibly Nadia™, are able to reduce effects of aging in animals (32,33) and protect
against cancer and cardio- and cerebrovascular diseases (34,35,36).
86
Another notable observation from Table 8b is the distinct difference in the amount of β-
carotene present in Nadia™ fruit and its two parents. Nadia™ fruits that are harvested
from both the mother and the 2-year old trees contain two times more β-carotene than
Sweetheart cherry and Black Amber plum.
A further comparison of both antioxidant properties to β-carotene ratio among a wide
variety of common fruits in Table 9 was made. The ratios obtained from each fruit
revealed the relative levels of the two chemical properties. Nadia™ harvested from the
mother and 2 year old trees have ORAC: β-carotene ratios that fall in mid region,
indicating that Nadia™ has moderately high levels of both the antioxidants and β-
carotene, unlike strawberries which has extremely high levels of antioxidants but low β-
carotene level (large ORAC: β-carotene ratio), and apricot which has low levels of
antioxidants but high β-carotene content (small ORAC: β-carotene ratio).
Sufficient β-carotene in dietary supplements is known to be beneficial for basic human
health. β-carotene, together with α-carotene and β-cryptoxanthin are provitamin A
carotenoids. As a result, its deficiency may indirectly correlates with that of Vitamin A
deficiency. Research has shown that β-carotene aids in cancer prevention, protecting
eye and vision by reducing the effects of retinal degeneration caused by Vitamin A
deficiency (37). β-carotene also serves as an antioxidant and reduces the effects of
oxidative stress in aging (38). Carotenoids can facilitate communication between
neighboring cells grown in culture by stimulating the synthesis of connexin proteins
(39). While vitamin A is essential for normal immune system function, it is difficult to
determine whether the effects of provitamin A carotenoids are related to their vitamin A
activity. However, some clinical trials have found that β-carotene supplementation
improves several biomarkers of immune function (40,41). Potrykus and Beyer have
87
been successful in the development of genetically engineered “Golden rice” that
concentrates β-carotene in the grain to reduce incidence of blindness, disease
susceptibility and premature death of small children (42). In the same way, Nadia™
fruit could possibly be the next alternative dietary food for its high content of naturally
occurring β-carotene.
Nadia™ not only contains high levels of β-carotene, the level of β-carotene also far
exceeds Black Amber plum and Sweetheart cherry β-carotene levels. This indicates that
β-carotene could be a potential chemical marker to differentiate Nadia™ fruit from its
parents. However, it being the only marker for authenticity testing may result in the lack
of accuracy in the differentiation. In view of this, more nutritional analyses on the other
chemical components on Nadia™ should be performed to seek for more potential
markers, such as polyphenols, flavonoids, amino acids, etc. in order to generate a
chemical profile that can be used to authenticate Nadia™ from the other fruits of the
Prunus family.
Safety Combustible reagents used in this study were methanol and ethanol; Toxic reagents
were chloroform and acetonitrile.
Acknowledgement We would like to thank DTS (Dairy Technical Services Ltd) and NMI (National
Measurement Institute), for assisting in analyzing chemical properties of the fruits
tested in this article. We also thank Dr Gavin Porter for the first observations made for
Nadia™.
Literature Cited
(1) Hu, C. J.; Zhang, M. H.; Gao, Q.; Li, Y. W. Varieties of colorants and
88
functions affecting coloration of rainbow trout. J. Chinese Forage. 2005, 1, 22-
23 (in Chinese)
(2) Jones, K. J.; Whitham, M. E.; Handler, P. S. Problems with royalty rates,
royalty stacking, and royalty packing issues. In Handbook of Best Practices.
2007, Vol. 11 no. 9, pp. 1121.
(3) Downey, G; Kelly, J.D.; Petisco R. C. Food authentication - Has near infrared
spectroscopy a role? Spectroscopy Europe. 2006, 18, 12-13.
(4) Kurz, C.; Martin, L.; Carle, R.; Schieber, A. Evaluation of fruit authenticity
and determination of the fruit content of fruit products using Ft-NIR
spectroscopy of cell wall components. Food Chem. 2010, 119, 806-812
(5) Kosmala, M.; Milala, J.; Kolodziejczyk, K.; Markowski, J.; Mieszezakowska,
M.; Cinies, C.; Renard, C. M. G. C. Characterisation of cell wall
polysaccharides of cherry (Prunus cerasus var. Schattenmorelle) fruit and
pomace. Plant Food Hum. Nutr. 2009, 64, 279-285
(6) Baltes, W.; Schmahl, H. (1978) High frquency Py-GC-MS of selected
carbohydrates. Z Lebensm Unters For. 1978, 167, 69-77
(7) Raghaven, S.K.; Ho, C.T.; Daun, H. (1986) Identification of soy protein in
meat by pyrolysis-high resolution gas chromatography. J. Chromatogr. 1986,
351, 195-202
(8) Donelly, B.J.; Voigt, J.E.; Scallet, B.L. (1982). Reaction of oligosaccharides
from pyrolysis-gas chromatography. Cereal Chem. 1982, 57, 388-390
(9) Garcia-Wass, F.; Hammond, D.; Mottram, D.S.; Cutteridge, C.S. Detection of
fruit juice authenticity using pyrolysis mass spectroscopy. Food Chem. 2000,
69, 215-220
(10) Berardini, N.; Fezer, R.; Conrad, J.; Beifuss, U.; Carle, R.; Schieber, A.
Screening of Mango (Mangifera indica L.) cultivars for their contents of
89
flavonol O- and xanthone C-glycosides, anthocyanins and pectin. J. Agr. Food
Chem. 2005, 53, 1563-1570
(11) Prior, R. L.; Wu, X.; Schaich, K. Standardised methods for the determination
of antioxiant capacity and phenolics in foods and dietary supplements. J. Agr.
Food Chem. 2005, 53, 4290-4302
(12) Fruit juice authenticity. HiTech Analytical and Diagnostic Solutions. Retrieved
30 Jan, 2010, from http://www.hadsolutions.com/index.php
(13) Ou, B.; Hampsch-Woodill, M.; Prior, R. L. Development and validation of an
improved oxygen radical absorbance capacity assay using fluorescein as the
fluorescent probe. J Agr. Food Chem. 2001, 49, 4619-4626
(14) Indyk, H. E. Simplified saponification procedure for the routine determination
of total vitamin E in diary products, foods and tissues by High-performance
Liquid Chromatography. Analyst. 1988, 113, 1217-1221
(15) Huang, D.; Ou, B.; Hampsch-Woodill, M.; Flanagan, J. A.; Deemer, E. K.
Development and validation of oxygen radical absorbance capactiy assay for
lipophilic antioxidants using randomly methlated β-cyclodextrin as the
solubility enhancer. J. Agr. Food Chem. 2002, 50, 1815-1821
(16) Willberg, V. C.; Rodriguez-Amaya, D. B. (1995) HPLC: Quantitation of major
carotenoids of fresh and processed guave, mango and papaya. Lenbensmittel-
Wissenschaft and Technologie. 1995, 28, 474-480
(17) Broich, C. R.; Gerber, L. E.; Erdman, J. W. Jr. Determination of lycopene, α-
and β- carotene and retinyl esters in human serum by reverse-phase high
performance liquid chromatography. Lipids. 1983, 18, 253-257
(18) AOAC. International. (1995). Official methods of analysis. Trends in Food
Science Technology.
(19) Szentmihalyi, K.; Kery, A.; Then, M.; Lakatos, B.; Sador, Z.; Vinkler, P.
90
Potassium- Sodium Ratio for the Characterisation of Medicinal Plant Extracts
with Diuretic Activity. Phytother. Res. 1998, 12, 163-166
(20) Boehm, E. W. A.; Ma, Z.; Michailides, T. J. Species-specific detection of
Moniliniaa fructicola from California stone fruits and flowers. Phytopathology.
2001, 91, 428-439
(21) Simon, G. Review on rain induced fruit cracking of sweet cherries (Prunus
avium L.), its causes and the possibilities of prevention. Int. J. Hor. Sci. 2006,
16, 27-35
(22) Youdim, K. A.; Joseph, J. A. A possible emerging role of phytochemicals in
improving age-related neurological dysfunction: a multiplicity of effects. Free
Radical Bio. Med. 2001, 30, 583-594
(23) Cantuti-Castelvetri, I.; Shukitt-Hale, B.; Joseph, J. A. Neurobehavioral aspects
of antioxidants in aging. Int. J. Dev. Neurosci. 2000, 18, 383-399
(24) Chance, B.; Sies, H.; Boveris, A. Hydroperoxide metabolism in mammalian
organs. Physiol. Rev. 1979, 59, 527–605
(25) Davì, G.; Falco, A.; Patrono, C. Lipid peroxidation in diabetes mellitus.
Antioxid. Redox Signal 2005, 7, 256–268
(26) Neumann, C.; Krause, D.; Carman, C.; Das, S.; Dubey, D.; Abraham, J.;
Bronson, R.; Fujiwara, Y.; Orkin, S.; Van Etten, R. (2003). Essential role for
the peroxiredoxin Prdx1 in erythrocyte antioxidant defence and tumour
suppression. Nature 2003, 424, 561–565
(27) Wood-Kaczmar, A.; Gandhi, S.; Wood, N. Understanding the molecular causes
of Parkinson's disease. Trends Mol. Med. 2006, 12, 521–528
(28) Christen, Y. (2000). Oxidative stress and Alzheimer disease. Am. J. Clin. Nutr.
2000, 71, 621S–629S.
(29) Nunomura, A.; Castellani, R.; Zhu, X.; Moreira, P.; Perry, G.; Smith, M.
91
Involvement of oxidative stress in Alzheimer disease". J. Neuropathol. Exp.
Neurol. 2006, 65, 631–641
(30) Cookson, M.; Shaw, P. Oxidative stress and motor neurone disease. Brain
Pathol. 1999, 9, 165–86.
(31) Sohal, R. Role of oxidative stress and protein oxidation in the aging process.
Free Radic. Biol. Med. 2002, 33, 37–44
(32) Joseph, J.A.; Shukitt-Hale, B.; Casadesus, G. Reversing the deleterious effects
of aging on neuronal communication and behaviour:beneficial properties of
fruit polyphenolic compounds. Am. J. Clin. Nutr. 2005, 81(Suppl), 313S-316S
(33) Cotman, C.W.; Head, E.; Muggenburg, B.A.; Zicker, S.; Milgram, N. W. Brain
aging in the canine: A diet enriched in antioxidants reduces cognitive
dysfunction. Nuerobiol. Aging. 2005, 23, 809-818
(34) Ames, B. M. Dietary carcinogens and anticarcinogens: oxygen radicals and
degenerative diseases. Science 1983, 211, 1256-1263
(35) Gey, K. F. The antioxidant hypothesis of cardiovascular disease: epidemiology
and mechanisms. Biochem. Soc. T. 1990, 18, 1041-1045
(36) Gey, K. F.; Puska, P.; Jordan, P.; Moser, U. K. Inverse correlation between
plasma vitamin E and mortality from ischemic heart disease in cross-cultural
epidemiology. Am. J. Clin. Nutr. 1991, 53, 326S-334S
(37) Tam, B. M.; Qazaibash, A.; Lee, H. C.; Moritz, O. L. (2009) The dependence
of retinal degeneration caused by the rhodopsin P23H mutation on light
exposure and vitamin A deprivation. Invest. Ophth. Vis. Sci. 2009, 47, 3234-
3241.
(38) Yong, A. J.; Lowe, G. M. Antioxidant and pro-oxidant properties of
carotenoids. Arch. Biochem. Biophys. 2001, 385, 20-27
(39) Bertram, J. S. Carotenoids and gene regulation. Nutr. Rev. 1999, 57, 182-191
92
(40) van Poppel, G.; Spanhaak, S.; Ockhuizen, T. Effect of β-carotene
immunological indexes in healthy male smokers. Am. J. Clin. Nutr. 1993, 57,
402-407
(41) Hughes, D. A.; Wright, A. J.; Finglas, P. M. The effect of β-carotene
supplementation on the immune function of blood monocytes from healthy
male nonsmokers. J. Lab. Clinc. Med. 1997, 129, 309-317
(42) Golden Rice Project. Retrieved 30 Jan, 2010, from http://www.goldenrice.org/
93
Table 7: Differences in production attributes between “Nadia” and a generic cherry.
Trait Generic Cherry Nadia
Size 15 - 18mm up to 42 - 48mm
Flesh to pip volume ratio 2 to 1 5 to 1
Flavour - sugar at harvest 17 to 18 Brix 20 to 24 Brix
Texture Cherry – true to type Cherry – true to type
Appearance
Flesh Cherry – true to type Cherry – true to type
Skin Cherry – true to type Cherry/Plum
Shape Cherry – true to type Cherry – true to type
Stone Cherry – true to type Cherry – true to type
Stem Yes No and Yes (treated1)
Yield Moderate High
Brown Rot Highly susceptible Highly resistant
Splits Highly susceptible Resistant
Production system Free standing/Trellis Trellis
1 Stem elongation can be induced by treatment with gibberellins.
94
Table 8a: Nutrition panel of Nadia showing similarities shared with a generic cherry (shaded) and the Black Amber plum (bold)
Ave
rage
wei
ght
moi
stur
e
Prot
ein
(TN
X 6
.38)
Ash
@ 5
50o C
Ener
gy V
alue
Fat
Satu
rate
d Fa
t
Tran
s Fat
Tota
l Car
bohy
drat
e
Sucr
ose
Lact
ose
Glu
cose
Gal
acto
se
Fruc
tose
Mal
tose
Tota
l sug
ars
SAMPLE grams g/100g g/100g g/100g kJ/100g g/100g % m/m g/100g g/100g g/100g g/100g g/100g g/100g g/100g g/100g g/100g
Cherry Sweetheart 10.2 80.9 0.9 0.5 318 0.1 < 0.1 < 0.1 17.6 < 0.1 < 0.1 6.7 < 0.1 6.0 < 0.1 12.7
Cherry X Plum Nadia (2) 44.8 80.2 1.0 0.4 332 0.1 < 0.1 < 0.1 18.3 0.3 < 0.1 6.4 < 0.1 5.7 < 0.1 12.4
Cherry X Plum Nadia (m) 37.8 83.4 0.6 0.6 274 0.1 < 0.1 < 0.1 15.3 0.4 < 0.1 5.2 < 0.1 4.9 < 0.1 10.5
Plum Black Amber 47.5 87.2 0.5 0.3 214 0.1 < 0.1 < 0.1 11.9 1.0 < 0.1 2.8 < 0.1 2.8 < 0.1 6.6
Plum Prime Time 82.9 82.0 0.6 0.5 298 < 0.1 < 0.1 < 0.1 16.9 3.2 < 0.1 3.4 < 0.1 3.4 < 0.1 10.0
Blueberry Oz berries 1.7 83.5 0.4 0.2 281 0.2 < 0.1 < 0.1 15.7 < 0.1 < 0.1 5.4 < 0.1 5.8 < 0.1 11.2
95
Table 8b: Nutrition panel of Nadia showing similarities shared with a generic cherry (shaded) and the Black Amber plum (bold).
Tota
l sug
ars
Titra
tabl
e A
cidi
cty
(as
anhy
citr
ic a
cid)
AC
ID:S
UG
AR
ratio
Sodi
um
Pota
ssiu
m
Vita
min
C
α-ca
rote
ne
β-ca
rote
ne (p
ro-v
it A
)
α-to
coph
erol
β-to
coph
erol
δ-to
coph
erol
γ-to
coph
erol
OR
AC
_Vit
E Eq
uiv
(hyd
ro)
OR
AC
_Vit
E Eq
uiv
(lipo
)
OR
AC
_Vit
E Eq
uiv
(Tot
al)
SAMPLE g/100g % m/m mg/100g mg/100g mg/100g
Cherry Sweetheart 12.7 0.38 0.03 1.40 200 < 2 < 5 81 0.2 < 0.1 < 0.1 < 0.1 39,200 396 39,596
Cherry X Plum Nadia (2) 12.4 1.40 0.11 1.00 230 < 2 < 5 183.3 0.3 < 0.1 < 0.1 < 0.1 40,900 843 41,743
Cherry X Plum Nadia (m) 10.5 1.50 0.14 1.10 200 < 2 < 5 210 0.2 < 0.1 < 0.1 < 0.1 35,400 5 35,405
Plum Black Amber 6.6 1.90 0.29 0.65 140 < 2 < 5 77.5 0.2 < 0.1 < 0.1 < 0.1 41,700 646 42,346
Plum Prime Time 10.0 1.80 0.18 0.69 190 < 2 < 5 29.8 0.4 < 0.1 < 0.1 < 0.1 48,100 900 49,000
Blueberry Oz berries 11.2 0.45 0.04 2.10 79 < 2 < 5 37.5 1.4 < 0.1 < 0.1 0.8 70,300 664 70,964
µmol/100gµg/100g mg/100g
96
Table 9: Ratio of ORAC to β-carotene of the various common fruits including Nadia™ from mother and 2 year old trees. Fruits in the green shaded region have high ORAC values but low β-carotene; fruits in the pink shaded region have low ORAC values but high β-carotene, while fruits in the blue shaded region have moderately high values of both ORAC and β-carotene values. Nadia from both mother and 2 year old trees (in bold) falls in the blue region.
OR
AC
_Vit
E
Equ
iv(to
tal)
β-ca
rote
ne
Rat
io o
f O
RA
C:β
-car
oten
e va
lues
Common fruits μmol/100g μg/100g Strawberries 3577 7 511.0 Raspberry 4882 12 406.8 blueberries 6552 32 204.8 Plum (PT) 4900 30 163.3 Pears 1911 13 147.0 Apple 2589 27 95.9 Cherry 3365 38 88.6 Plum (BA) 4235 78 54.3 Cherry (SH) 3960 81 48.9 Blackberries 5347 128 41.8 Banana 879 26 33.8 Grapes (red) 1260 39 32.3 Grapes (white) 1118 40 28.0 Orange 1819 72 25.3 NADIA (2) 4174 183 22.8 Plum 6259 289 21.7 NADIA (m) 3541 210 16.9 Kiwifruit 882 53 16.6 Peach 1814 162 11.2 Pineapple 385 35 11.0 Melons, Honeydew 241 30 8.0 Nectarine 750 150 5.0 Grapefruit, red & pink 1548 686 2.3 Mangoes 1002 445 2.3 Apricot 1115 1094 1.0 Watermelon 142 303 0.5 Melons, Cantaloupe 315 2020 0.2
97
Figure 20: ORAC values and β-carotene levels in Nadia relative to other Prunus related fruits. (*ORAC values of were obtained from the USDA.)
0
1000
2000
3000
4000
5000
6000
7000
OR
AC
Vit_
E E
quiv
(tot
al) i
n μm
ol/1
00g
0
50
100
150
200
250
β-ca
rote
ne in
μg
per
100g
1,094
98
BIBLIOGRAPHY Akcin, O. E. (2008). Seed coat and fruit surface micromorphology of some Cynoglossum
L. (Boraginaceae) species. Bangladesh J. Bot. 37, 115-119 Akcin, O. E. (2009). Micromorphological and anatomical studies on petals of 11 Turkish
Onosma L. (Borginaceae) taxa. Bangladesh Journal of Plant Taxonomy. 16, 157-164
Anderson, J. A., Churchill, G. A., Autrique, J. E., Tanksley, S. D., and Sorrells, M. E.
(1993). Optimizing parental selection for genetic linkage maps. Genome. 36, 181-186
Aprotosoaie, A. C., Spac, A., Hancianu, M., Miron, A., Tanasescu, V. F., Dorneanu, V., Stanescu, U. (2010). The chemical profile of essential oils obtained from fennel fruits (Foeniculum vulgare Mill.) Farmacia. 58, 46-53
Ayub, Q., Mansoor, A., Ismail, M., Khaliq, S., Mohyuddin, A., Hameed, A., Mazhar, K., Rehman, S., Siddiqi, S., Papaioannou, M., Piazza, A., Cavalli-Sforza, L. L., Mehdi, S. Q. (2003). Reconstruction of human evolutionary tree using polymorphic autosomal microsatellites. American Journal of Physical anthropology. 122, 259-268
Baltes, W., and Schmahl, H. (1978). High frquency Py-GC-MS of selected carbohydrates. Zeischrift fur Lbensmittel Untersuchung und Forschung. 167, 69-77
Benson, D. A., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., and Wheeler, D. L. (2003).
GenBank. Nucleic Acids Research. 31, 23-27 Berardini, N., Fezer, R., Conrad, J., Beifuss, U., Carle, R., and Schieber, A. (2005).
Screening of Mango (Mangifera indica L.) cultivars for their contents of flavonol O- and xanthone C-glycosides, anthocyanins and pectin. Journal of agricultural and food chemistry. 53, 1563-1570
Blair, A. (1975). Karyotypes of Five Plant Species with Disjunct Distributions in Virginia
and the Carolinas. American Journal of Botany. 62, 833-837. Blenda, A., Scheffler, J., Scheffler, B., Palmer, M., Lacape J. M., Yu, J. Z., Jesudurai, C.,
Jung, S., Muthukumar, S., Yellambalase, P., Ficklin, S., Staton, M., Eshelman, R., Ulloa, M., Saha, S., Burr, B., Liu, S., Zhang, T., Fang, D., Pepper, A., Kumpatia, S., Jacobs, J., Tomkins, J., Cantrell, R., and Main, D. (2006) CMD: a Cotton microsatellite database resource for Gossypium genomics. BMC Genomics. 7, 132
BiOS, Biology Innovation for Open Society. Can IP rights protect plants? Retrieved on
20 July 2010, from http://www.patentlens.net/daisy/bios/1234#sample_countries. Botstein, B., White, R. L., Skolnick, M., and Davis, R. W. (1980). Construction of a
genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics. 32, 314-331
99
Botstein, D., White , R. L., Skolnick, M., and Davis, R.W. (1980). Contruction of a
genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet. 32, 314-331
Bowcock, A. M., Rulz-Linares, A., Tomfohrde, J., Minch, E., Kidd, J. R., and Caalli-
Sforza, L. L. (1994). High resolution of human evolutionary trees with polymorphic microsatellites. Nature. 368, 455-457
Carr H. (2001) The crop improvement royalty. Department of Agricultural and Food.
Retrieved on 13 Jan, 2010, from http://www.agric.wa.gov.au/PC_90771.html Cassidy, B. G. and Gonzales, R. A. (2005). DNA testing in animal forensics. Journal of
Wildlife Management. 69, 1454-1462 Charmorro-Lacayo, M. L., Konstantinov, A. S., Moseyky, A. G. (2006). Comparative
morphology of the female genitalia and some abdominal structures of neotropical Cryptocephalini (Coleoptera: Chrysomelidae: Cryptocephalinae). The Coleopterists Bulletin. 60, 113-134
Congiu, L., Chicca, M., Cella, R., Rossi, R., Bernacchia, G. (2000). The use of random
amplified polymorphic DNA (RAPD) markers to identify strawberry varieties: a forensic application. Molecular Ecology. 9, 229-232
Conte, M. G., Gaillard, S., Lanau, N., Rouard, M., and Perin, C. (2008). GreenPhylDB: a
database for plat comparative genomics. Nucleic Acids Research. Database issue, D991-D998
CTFA. (2003). 2003 Annual report. California Tree Fruit Agreement. Reedley, Ca. Della, S. G., Fideghelli, C., and Grassi, F. (1996). Peach and nectarine cultivars
introduced in the world from 1980 to 1992. Acta Hort. 374, 43-51. Department of Agriculture and Food, Gov of WA, Australia. Retrieved on 9 Jan, 2010,
from http://www.agric.wa.gov.au/PC_91273.html?s=1001 Dirlewanger, E., Cosson, P., Tavaud, M., Aranzana, M. J., Poizat, C., Zanetto, A., Arus,
P., Laigret, F. (2002). Development of microsatellite markers in peach [Prunus persica (L.) Batsch] and their use in genetic diversity analysis in peach and sweet cherry (Prunus avium L.). Theor Appl Genet. 105, 127-138
Donelly, B. J., Voigt, J. E., and Scallet, B. L. (1982). Reaction of oligosaccharides from
pyrolysis-gas chromatography. Cereal Chemistry 57, 388-390 Dong, Q., Schleuter, S. D., and Brendel, V. (2004). PlantGDB, plant genome database
and analysis tools. Nucleic Acids Research. 32, 354-359
100
Dovicovicova, L., Olexova, L., Pangallo, D., Siekel, P., and Kuchta, T. (2004) Polymerase chain reaction (PCR) for the detection of celery (Apium graveolens) in food. European Food Research Technology. 218, 493-495.
Downey, G., Kelly, J. D., and Rodriguez, P. C. (2006). Food authentication - Has near
infrared spectroscopy a role? Spectroscopy Europe 18, 12-13 Durham, J. (2006). Pink Lady™ on the move in the UK Apples and Pear World News.
Pub. Apple & Pear Australia Limited. 9, 8 Ehrlich, H. A., Gelfand, D. H., and Sninsky, J. J. (1991). Recent advances in the
polymerase chain reaction. Science 252, 1643-1651 Enjalbert, J., Goldringer, I., Paillard, S., and Brabant, P. (1999). Molecular markers to
study genetic drift and selection in wheat populations. J. Expl Bot. 50, 283-290. Eurofins Scientific. Retrieved on 9 Jan, 2010, from http://www.eurofins.com/en.aspx FAOSTAT. Food and Agriculture Organisation of the United Nations. Retrieved 6 Mar,
2010, from http://faostat.fao.org/default.aspx Fideghelli, C., Della, S. G., Grassi, F., and Morico, G. (1998). The peach industry in the
world: Present situation and trend. Acta Hort. 465, 29-39. Garcia-Wass, F., Hammond, D., Mottram, D. S., Cutteridge, C. S. (2000). Detection of
fruit juice authenticity using pyrolysis mass spectroscopy. Food Chemistry 69, 215-220
Gupta, P. K., and Varsheny, R. K. (2000). The development and use of microsatellite
markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphytica. 113, 163-185
Hsieh, H.-M., Liu, C.-L., Tsai, L.-C., Hou, R.-J., Liu, K.-L., Linacre, A., and Lee, J. C.-L.
(2005). Characterization of the polymorphic repeat sequence within the rDNA IGS of Cannabis sativa. Forensic Science International. 152, 23-28.
Humphrey, J. E. (1891). The comparative morphology of the fungi. The American
Naturalist. 25, 1055-1069 Hyo W. S., Jung, Y.Y., Hyun, M. C., Young, E. P., and Seung, E. O. (2001).
Discrimination of potato varieties by random amplified polymorphic DNA analysis. Korean Journal Horticultural Science and Technology. 19, 29-33
Irish, V. F., and Benfey, P. N. (2004). Beyong Arabidopsis. Translational biology meets
evolutionary developmental biology. Plant Physiology. 135, 611-614 IP Australia. Plants Breeder’s Rights. Retrieved on 30 Jan, 2010, from
http://www.ipaustralia.gov.au/pbr/about.shtml
101
IPLA. (2009). Trade Mark Guidelines. International Pink Lady® Alliance Limited. Retrieved on 24 Jan, 2010, from
http://www.pinkladyapples.com/about/TM%20guidelines.html Jefferys, A. J., Wilson, V., and Thein, S. L. (1985). Hypervariable “minisatellite” regions
in human DNA. Nature. 314, 67-73 Jobling, M. A., and Gill, P. (2004). Encoded evidence: DNA in forensic analysis.
Genetics Nature Reviews. 5, 739- 751 Jordens, R. (2005). Progress of plant variety protection based on the International
Convention for the Protection of New Varieties of Plants (UPOV Convention). World Patent Information. 27, 232- 243
Joshi, S. P., Ranjekar, P. K., and Gupta V. S. (1999). Molecular markers in plant genome
analysis. Current Science. 77, 230-240 Khushk, A. M., Memon, A., Lashari, M. I. (2009). Factors affecting guava production in
Pakistan. J. Agric. Res. 47, 201-210 Kosmala, M., Milala, J., Kolodziejczyk, K., Markowski, J., Mieszezakowska, M., Cinies,
C., and Renard, C. M. G. C. (2009). Characterisation of cell wall polysaccharides of cherry (Prunus cerasus var. Schattenmorelle) fruit and pomace. Plant foods and human nutrients. 64, 279-285
Li, C. D., Rossnagel, B. G., and Scoles, G. J. (2000). The development of oat
microsatellite markers and their use in identifying relationships among Avena species and oat cultivars. Theoretical and Applied Genetics. 101, 1259-1268
Linacre, A., and Thorpe, J. (1998). Detection and identifcation of cannabis by DNA.
Forensic Science International. 91, 71-76. Litt, M., and Luty, J. A. (1989). A hypervariable microsatellite revealed by in vitro
amplification of a dinucleotide repeat within the cardiac muscle actin gene. American Journal of Human Genetics. 44, 397-401
Moon, H. K., and Hong, S. P. (2003). Pollen morphology on genus Lycopus (Lamiaceae).
Ann. Bot. Fennici. 40, 191-198 Morgante, M., and Olivieri, A. M. (1993). PCR-amplified microsatellites as markers in
plant genetics. Plant Journal. 3, 175-182 Mulcaster, G. (2009). Apple fraud no way to treat Pink Lady. The Age Business News
article.Retrieved on 13 Jan, 2010, from http://www.theage.com.au/business/apple-fraud-no-way-to-treat-pink-lady-20090830-f3z5.html
Naem, S. (2007). The comparative morphology of three equine habronematid nematodes:
102
SEM observations. Parasitology Research. 101, 1432-1955 Nei, M. (1987). Molecular Evolutionary Genetics. (New York: Columbia University
Press).
Nei, M. (1991). Relative efficiencies of different tree-making methods for molecular data. In Phylogenetic Analysis of DNA Sequence, M. M. Miyamoto and J. Cracraft, ed. (New York: Oxford University Press), pp. 90-128
Ohno, S., Wolf, U., and Atkin, N. B. (1968). Evolution from fish to mammals by gene duplication. Hereditas. 59, 169-187
Otto, S. P., and Whitton, J. (2000) Polyploidy incidence and evolution. Annu. Rev. Genet. 34, 401-437
Pal, S. and Pal, N. (1970). Spore morphology and taxonomy of Polypodiaceae. Grana 10, 141-148
Parliament of Australia, Senate. Commercial Utilisation of Australian Native Wildlife. Chapter 16. Native trees and shrubs, Plants. Retrieved on 30 Jan, 2010, from http://www.aph.gov.au/Senate/committee/rrat_ctte/completed_inquiries/1996-99/wild/report/contents.htm
Pattnaik, P. and Jana, A. M. (2005). Microbial forensics: applications in bioterrorism. Environmental Forensics. 6, 197-204
Petren, K., Grant, B. R., and Grant, P. R. (1999). A phylogeny of Darwin’s finches based on microsatellite DNA length variation. Proc. R. Soc. Lond. B. 266, 321-329
Philips, R. L., and Vasil, I. K. eds (2001). DNA- Based Markers in Plants (Kluwer Academic Publishers)
Powell, W., Machray, G. C., and Provan, J. (1996). Polymorphism revealed by simple sequence repeats. Trends Plant Sci. 1, 215-222
Prior, R. L., Wu, X., and Schaich, K. (2005). Standardised methods for the determination of antioxiant capacity and phenolics in foods and dietary supplements. Journal of agricultural and food chemistry 53, 4290-4302
Rademaker, C. A. (2000). The classification of plants in the United States classification system. World Patent Information 22, 301-308
Raghaven, S. K., Ho, C. T., and Daun, H. (1986). Identification of soy protein in meat
pyrolysis-high resolution gas chromatography. Journal of chromatography. 351, 195-202
Rahman, M. S., Molla, R., Alam, S., and Rahman, L. (2009). DNA fingerprinting of rice
(Oryza sativa L.) cultivars using microsatellite markers. Australian Journal of Crop Science. 3, 122-128
Rhee, S. Y., Beavis, W., Berardini, T. Z., Chen, G., Dixon, D., Doyle, A., Carcia-
103
Hernandez, M., Huala, E., Lander, G., and Montoya, M. (2003). The Arabidopsis Information Resource (TAIR): a model organism database providing a centralised, curated gateway to Arabidopsis biology, research materials and community. Nucleic Acids Research. 31, 224-228
Rout, P. K., Joshi, M. B., Mandal, A., Laloe, D., Singh, L., Thangaraj, K. (2008).
Microsatellite- based phylogeny of Indian domestic goats. BioMed Central Genetics. 9, 11
Saiki, R. K., Scharf, S., Faloona, F., Mullis, K. B., Horn, G. T., Erlich, H. A., and
Arnheim, N. (1985). Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science 230, 1350-1354
Silvey, V. (1981) The contribution of new wheat, barley and oat varieties to increasing
yield in England and Wales. J. Nat. Inst. Agric. Bot. 15, 399-412 Southern, E. M. (1975). Detection of specific sequences among DNA fragments
separated by gel electrophoresis. Journal of Molecular Biology 98, 503-517 Stagel, A., Portis, E., Toppino, L., Rotino, G. L., and Lanteri, S. (2008). Gene-based
microsatellite development for mapping and phylogeny studies in eggplant. BMC Genomics. 9, 357- 370
State v. Ware, 1999 WL 233592 (Tenn.Crim.App., Apr 20, 1999) (NO. 03C01-
9705CR00164) Testolin, R., Marrazza, T., Cipriani, G., Quarta, R., Verde, I., Dettori, M. T., Pancaldi,
M., Sansavini, S. (2000). Microsatellite DNA in peach (Prunus persica L. Batsch) and its use in fingerprinting and testing the genetic origin of cultivars. Genome. 43, 512-520
Tingey, S. V., Rafalski, J. A., and Williams, J. G. K. (1993). Application of RAPD
technology to Plant Breeding (ed. Neff, M). (ASHS Publishers, Minnesota). pp. 3-8 UPOV. (2009). International Union for the Protection of New Varieties of Plants. UPOV
Publication No. 437 (E). 2009 edition. Walker, G. K., Black, M. G., Edwards, C. A. (1996). Comparative morphology of zebra
(Dreissena polymorpha) and quagga ( Dreissena bugensis) mussel sperm: light and electron microscopy. Can J Zool. 74, 809-825
Wang, Y., Georgi, L. L., Zhebentyayeva, T. N., Reighard, G. L., Scorza, R., and Abbott,
A. G. (2002). High-throughput targeted SSR marker development in peach (Prunus persica). Genome 45, 319-328
Weising, K., Nybron, H., Wolff, K., and Meyer, W. (1995). DNA fingerprinting in Plants
and Fungi (ed. Arbor, A). (CRC Press, Boca Raton.) pp. 1- 3
104
Welsh, J. and McCelland, M. (1990). Fingerprinting genomes using PCR with arbitrary
primers. Nucleic Acids Research. 18, 7213-7218 Williams, J. G. K., Hanafey, M. K., Rafalski, J. A. and Tingey, S. V. (1993). Genetic
analysis using random amplified polymorphic DNA markers. Methods in Enzymology. 218, 704-740
Winter, P., and Kahl, G. (1995). Molecular marker technologies for plant improvement.
World Journal of Microbiology and Biotechnology. 11, 438-448 Yi, T., Lowry, P. P., II, Plunkett, G. M., and Wen, J. (2004). Chromosomal evolution in
Araliaceae and close relatives. Taxon. 53, 987-1005. Yoon, C. K. (1993). Botanical witness for the prosecution. Science. 260, 894-895 Zhebentyayeva, T. N., Reighard, G. L., Gorina, V. M., Abbott, A.G. (2003). Simple
sequence repeat (SSR) analysis for assessment of genetic variability in apricot germplasm. Theor Appl Genet. 106, 435-444