Experimental designs suitable for testing many factors with limited

number of explants in tissue culture

Mehmet Nuri Nas1,*, Kent M. Eskridge2 & Paul E. Read31Department of Horticulture, Faculty of Agriculture, Kahramanmaras Sutcu Imam University, 46060Kahramanmaras, Turkey; 2Department of Statistics, University of Nebraska-Lincoln, 103 Miller Hall,Lincoln, NE 68583-0712; 3Department of Agronomy and Horticulture, Institute of Agriculture and NaturalResources, University of Nebraska-Lincoln, 377 Plant Sciences, Lincoln, NE 68583-0724 (*requests foroffprints: Fax: +90-344-223-0048; E-mail: mnurinas@ksu.edu.tr)

Received 15 September 2004; accepted in revised form 19 October 2004

Key words: factor screening, factorial treatments, fractional factorial design, Plackett–Burman design,prioritizing factors, screening designs

Abstract

The majority of plant tissue culture experiments are set up as factorial experiments in completely ran-domized designs (CRD), randomized complete block designs (RCBD) or split-plot designs (SPD) thatrequire a great number of stabilized cultures. For various reasons, an insufficient number of explants mayprevent the employment of CRD, RCBD or SPD with factorial treatments and hinder the optimization offactors affecting culture response. To prioritize the optimization of ‘‘the most important’’ factors affectingculture response, we explored the applicability of Plackett–Burman Design (PBD) and Fractional FactorialDesign (FFD) with a limited number of explants. To test the effects of 8 factors (genotype, 6-benzyladenine(BA), CuSO4� 5H2O, Fe source, agar, pH, myo-inositol and cold treatment following inoculation of ex-plants) at 2 levels on response of single-node grape vine cultures, 12 treatment combinations were generatedaccording to the PBD and 16 treatment combinations were generated according to the FFD. These designsrequire many fewer explants since a typical experiment with eight factors, each at two levels of will require256 (28) treatment combinations. However, the costs of the PBD and FFD are that there is limited, if anyinformation, on interactions and if available may be more difficult to interpret. Of the factors tested,cultivar, BA and agar concentrations were found to be the most important factors affecting culture re-sponse. The types of culture response were in agreement with previous reports indicating that PBD andFFD can effectively be employed with limited number of explants to test effects of several factors andprioritize the ‘‘most important’’ factors.

Abbreviations: BA – 6-benzyladenines CRD - completely randomized designs; IBA - indole - 3 butyric acid;FFD - Fractional Factorial Design PBD - Plackett - Burman designs; NMR - nas and Read (2004) mediumRCBD - randomized complete block designs; SPD - split-plot designs

Introduction

The use of appropriate experimental designs andstatistical analyses in plant cell and tissue culturestudies is necessary to ensure unbiased and preciseestimates of treatment effects and to provideproper interpretation of results. The design and

analysis of tissue culture research with a relativelysmall number of factors has been addressed in theliterature (Mize and Chun, 1988; Compton, 1994;Mize et al., 1999; Ibanez et al., 2003). The major-ity of plant cell and tissue culture studies areconducted under controlled light, temperature andhumidity conditions with uniform culture vessels

Plant Cell, Tissue and Organ Culture (2005) 81:213–220 � Springer 2005

and are set up as factorial experiments in com-pletely randomized designs (CRD), randomizedcomplete block designs (RCBD) or split-plot de-signs (SPD) (Compton, 1994; Compton and Mize,1999). These types of experimental designs areuseful when the researcher has previously identi-fied a few factors to study and there is a sufficientamount of explant material to properly replicate.However, in some tissue culture research, thesetypes of experimental designs may not be appro-priate, or even feasible. In the initial stages of aresearch program, typically there are a largenumber of factors of interest and a limited numberof available explants. Therefore, the objectivesshould be prioritized and experimental compo-nents should be selected according to budget andtime available (Compton and Mize, 1999). Duringthe establishment of aseptic cultures (Stage I),where for various reasons many explants are lost,using a factorial experiment with a CRD, RCBDor SPD may not be possible since these designswould require too many explants. For instance, anexperiment with eight factors, each with only twolevels will result in 256 (28) treatment combina-tions and will require 512 explants when two rep-licates are used per treatment. In these situations,there is a need for special types of designs thatrequire a minimal number of explants and can aidwith screening a large number of factors for thosewith major effects which will be further studied inmore detail using classical types of experimentaldesigns.

Fractional factorial designs can be used inplant cell and tissue culture research to effectivelyidentify important factors and interactions whileusing a minimal number of explants. These designshave been used for many years in industrial re-search where it is critical to minimize the amountof needed experimental material (Box et al., 1978).A very simple example is an experiment that hasfour factors called A, B, C and D where eachfactor has two levels. The full factorial will have atotal of 24 ¼ 16 treatment combinations, while a½ fraction would have ½ 24 ¼ 8 treatment com-binations. The obvious advantage of these types ofexperiments is that they reduce the requirednumber of experimental units while providinginformation on all factors, however, informationon one or more effects is lost and information onthe remaining effects maybe more difficult tointerpret. In the ½ fraction example, the particular

set of treatment combinations are chosen to pro-vide the maximum amount of information on themain effects of the four factors, while foregoingany information on the four way interaction(ABCD). In addition, information on each two-way interaction is confounded (or aliased) withanother two-way interaction. More specifically,the AB interaction is aliased with CD, AC is ali-ased with BD, and AD is aliased with BC. Thismeans that based on the data analysis, it is notpossible to separate the AB interaction effectsfrom the CD effects etc.

Aliasing and loss of information on some ef-fects are important considerations with FFD intissue culture research, but may not be veryimportant depending on the particular objectivesof the research. Often with tissue culture experi-ments, higher order interactions are small or neg-ligible and the researcher knows which factors arelikely to interact. In such cases, fractional facto-rials may be constructed to obtain information oneffects that are likely to be present and foregoinformation on those that are not. For example,with the ½ 24 fraction described above, if themajor objective of the research is to obtain infor-mation on the main effects of the factors (A, B, Cand D), with less interest on the interactions, and ifit is likely that the interactions CD, BD, BC andABCD will be small, then this design could bequite useful. However, if the focus of the researchis on interactions, then a full factorial design asdescribed above should be used.

FFD are generally characterized by the numberof factors being evaluated and the size of thefraction. These two features will generally deter-mine which effects will be aliased and which effectswill be lost. Large fractions, such as ½ or ¼fractions with six or more factors, will providesound information on all main effects and some ofthe lower order interactions since main effects andlower order interactions are aliased with higherorder interactions, which are assumed to be neg-ligible. As the size of the fraction becomes smaller,main effects become aliased with lower orderinteractions and information on more effects islost. Plackett–Burman designs (PBD) are a specialtype of fractional factorial where up to n)1 factorscan be evaluated in n runs and when n is a multipleof four (Box et al., 1978). PBD have some maineffects aliased with two-way interactions andinformation on a number of effects is totally lost.

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Yet if the primary objective is to determine theimportant factors to study in further experiments,small fractions such as PBD can be quite effectivein plant cell and tissue culture research.

To the best of our knowledge, PBD and Frac-tional Factorial Design (FFD) have not been re-ported for the plant cell and tissue culture literature.The objectives of this study are to demonstrate theapplicability of the PBD and FFD in identifying themost important medium and treatment factorsaffecting culture response in vitrowith axillary budsof two grape cultivars and to compare results fromthese two different designs.

Materials and methods

Eight factors (A–H) were applied in combinationsat two levels:

A (genotypes): ‘Chancellor’ – ‘MN1047’B [6-benzyladenine (BA)]: 0.2–0.4 mg l)1

C (CuSO4 � 5H2O): 0.025–2.5 mg l)1

D (Fe source, 6 mg Fe l)1): 100 mg Sequestrene138 Fe l)1 – 50 mg Sequestrene 330 Fe l)1

E (agar): 6–8 g l)1

F (pH): 5–6 ± 0.02G (myo-inositol): 100–300 mg l)1

H (cold treatment following inoculation of ex-plants): 48 h cold at 4 �C – no cold treatment

Plant materials and culture conditions

Axillary buds of two grape cultivars, ‘Chancellor’and ‘MN 1047’ (Frontenac), grown on Nas and

Read Medium (NMR (Nas and Read, 2004))containing 0.01 mg indole-3 butyric acid(IBA) l)1 and 0.2 mg BA l)1 were used as theexplants. For the current study NMR supple-mented with 0.01 mg IBA l)1 + 30 g l)1 sucrosewas used as the culture medium. The amounts ofCu, Fe, myo-inositol in the culture medium andthe pH were adjusted to the levels describedabove, then 6 or 8 g agar l)1 (Sigma, A-1296) wasadded to the medium, and was autoclaved at121 �C and 1.4 kg cm)2 for 15 min. Seventymilliliter of medium was distributed into dispos-able clear plastic sundae cups [bowl: DSD8X –lid: LD8-58 (Sweetheart Cup Company, MD,USA)]. Two axillary buds were cultured in onecup, and each treatment had two replicates(cups). When subjected to cold treatment, fol-lowing the inoculation of explants the cultureswere placed in a cold storage room at 4 �C for48 h then shifted to the culture room (23 ± 2 �Cunder cool-white fluorescent light(28 lmol m)2 s)1) for 16 h per day).

Experimental designs

Two different experiments were conducted, eachwith a different design. One experiment was set upas a PBD where twelve treatment combinationswere generated to examine the effects of the eightfactors according to a PBD (Table 1; Box et al.,1978). Since the design allows up to eleven factorsto be included with twelve treatment combina-tions, we did not use the last three factors given in

Table 1. Schematic illustration of PBD for 12 combinations of 8 factors at 2 levels

Run Cultivar BA

(mg l)1)

CuSO4 � 5H2O

(mg l)1)

Sequestrene

Fe source

Agar

(g l)1)

pH Myo-inositol

(mg l)1)

Cold (h)

1 MN 1047 0.2 2.5 138 Fe 6 5 300 48

2 MN 1047 0.4 0.025 330 Fe 6 5 100 48

3 Chancellor 0.4 2.5 138 Fe 8 5 100 0

4 MN 1047 0.2 2.5 330 Fe 6 6 100 0

5 MN 1047 0.4 0.025 330 Fe 8 5 300 0

6 MN 1047 0.4 2.5 138 Fe 8 6 100 48

7 Chancellor 0.4 2.5 330 Fe 6 6 300 0

8 Chancellor 0.2 2.5 330 Fe 8 5 300 48

9 Chancellor 0.2 0.025 330 Fe 8 6 100 48

10 MN 1047 0.2 0.025 138 Fe 8 6 300 0

11 Chancellor 0.4 0.025 138 Fe 6 6 300 48

12 Chancellor 0.2 0.025 138 Fe 6 5 100 0

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the design on p. 398 in Box et al. (1978). We alsoused a 1/16 28 FFD to evaluate the 8 factors using16 treatment combinations (Table 2). The treat-ment combinations were generated using SASPROC FACTEX (SAS, 1995) where the aliasstructure can be found on p. 403 of Box et al.(1978). Since the PBD and FFD required 12 and16 treatment combinations, respectively, bothdesigns showed a considerable reduction over thetotal 28 ¼ 256 treatment combinations needed forthe full factorial.

The PBD was based on the assumption thatall interactions among the factors are insignificantor quite small relative to the main effects of thefactors. The assumptions of the FFD was thatonly the main effects and possibly the two-wayinteractions of cultivar with the other factorswere important, while all other interactions wereeither nonexistent or small relative to the maineffects. In tissue culture studies, the interactionsof experimental components (i.e., medium,growth regulators and genotype) often have asignificant influence on the type and level ofculture responses, however, at the early stages oftissue culture program, such interactions betweenenvironmental factors are less important (Hansenet al., 1999) because explants are still largely un-der the influence of donor plants (McCown and

McCown, 1987). In this study, assuming culturedevelopment was at Stage I, primary interest wason identifying the most important factors with alimited number of explants. Thus we assumedthat if a main effect of a factor was large, that themain effect was much more pronounced thaninteraction effects on the explant response.

Collection and statistical analysis of data

At the end of a 35-day culture period, number ofshoots developed per cultured explant, number ofnodes (leaf) per cultured explant and callus freshweight per explant were recorded. Data for ex-plants in a culture vessel were divided by thenumber of explants and the means were used forstatistical analysis. The analysis of variance wasperformed for both the PBD experiment and theFFD experiment using SAS PROC GLM (SASInstitute Inc., 1996). Error variance was computedas the variance among cups within a treatmentcombination. For the PBD experiment, the modelcontained only the main effects of the factors. Forthe FFD experiment, the model included all maineffects and two-way interactions of the factorstested. All statistical tests were conducted ata ¼ 0.05. Separation of treatment means was doneby Fisher’s least significant difference (LSD) test.

Table 2. Schematic illustration of fractional factorial design for 16 combinations of 8 factors (1/16 of 28 factorial combinations) at 2levels

Run Cultivar BA

(mg l)1)

CuSO4 � 5H2O

(mg l)1)

Sequestrene

Fe source

Agar

(g l)1)

pH Myo-inositol

(mg l)1)

Cold

(h)

1 Chancellor 0.2 0.025 138 Fe 6 5 100 0

2 Chancellor 0.2 0.025 330 Fe 8 6 300 0

3 Chancellor 0.2 2.5 138 Fe 8 6 100 48

4 Chancellor 0.2 2.5 330 Fe 6 5 300 48

5 Chancellor 0.4 0.025 138 Fe 8 5 300 48

6 Chancellor 0.4 0.025 330 Fe 6 6 100 48

7 Chancellor 0.4 2.5 138 Fe 6 6 300 0

8 Chancellor 0.4 2.5 330 Fe 8 5 100 0

9 MN 104 0.2 0.025 138 Fe 6 6 300 48

10 MN 104 0.2 0.025 330 Fe 8 5 100 48

11 MN 104 0.2 2.5 138 Fe 8 5 300 0

12 MN 104 0.2 2.5 330 Fe 6 6 100 0

13 MN 104 0.4 0.025 138 Fe 8 6 100 0

14 MN 104 0.4 0.025 330 Fe 6 5 300 0

15 MN 104 0.4 2.5 138 Fe 6 5 100 48

16 MN 104 0.4 2.5 330 Fe 8 6 300 48

216

Results and discussion

The results obtained from the PBD and FFD weresimilar. Genotype, BA and agar were found to bethe most important factors affecting cultureresponse (Tables 3 and 4). In general, with respectto proliferation rates (number of shoots producedper cultured explant), potential multiplicationrates (number of nodes produced per cultured ex-plant) and the amount of callus produced percultured explant, cultivar Chancellor was superiorto cultivar MN104. The use of 0.4 mg BA l)1 or6 g agar l)1 in the culture medium resulted inhigher number of shoot and/or nodes per culturedexplant compared to the use of 0.2 mg BA l)1 or8 g agar l)1 (Tables 5 and 6), respectively.

The amenability of many plants to in vitro cul-ture is reported to be genotype dependent (Henryet al., 1994) and the effect of genotype on in vitroculture response has been realized to the extent thatmany researchers have focused on understandingthe inheritance of genes responsible for culture re-sponse (Carputo et al., 1995; Machii et al., 1998;McLean and Nowak 1998; Hansen et al., 1999;Ozgen et al., 2001) and selection for more respon-sive or even breeding donor plants for an improvedculture response (Rosati et al., 1994). Reportsindicate that the culture response may be controlledby nuclear (McLean and Nowak 1998) and/orcytoplasmic genes (Ozgen et al., 2001) and reorga-nization of nuclear and cytoplasmic genomes mayoccur during the culture period (Rani et al., 2000).

The effect of cytokinins on shoot morphogen-esis is a long known phenomenon (Skoog andMiller, 1957). Cytokinins (BA) are commonly usedto promote shoot regeneration and shoot prolif-eration via axillary budbreak. BA in the multipli-cation medium increased the total number ofshoots produced per three-node explants ofstrawberry tree (Mereti et al., 2002) and single-shoot explants of Cryptocoryne wendtii (Kaneet al., 1999). The balance of auxin and cytokininsin the culture medium plays an important role inthe morphogenic fate of cultures. A relatively highlevel of auxin to cytokinin favors rooting, alow level leads to shoot formation and an inter-mediate level stimulate callus proliferation (Skoogand Miller, 1957). In the current study,0.4 mg BA l)1 resulted in higher number of shootscompared to 0.2 mg BA l)1. Although not signif-icant, a high ratio of IBA (0.01 mg l)1) to BA(0.2 mg l)1) produced more amount of calluscompared to the lower ratio of IBA (0.01 mg l)1)to BA (0.4 mg l)1) (Tables 3 and 4).

Agar is the most commonly used medium gel-ling agent. To determine the influence of agarconcentration on the in vitro growth and devel-opment of Maranta leuconeura, Ebrahim andIbrahim (2000) added Difco-Bacto agar into theculture medium at 0, 3, 5, 7 and 9 g l)1. With re-spect to growth and development at pH of 5.7,liquid medium (control) was superior to solidifiedmedia and, although statistically not significant, adecrease in explant response was observed as the

Table 3. Analysis of variance for the PBD for dependent variables: number of shoots produced per cultured explant, number of nodesper cultured explant and callus fresh weight per cultured explant (Callus W.)

Source DF Shoot/explant Node/explant Callus W. explant

SS F value SS F value SS F value

Cult. 1 140 21.7** 773 30** 16.4 21**

BA 1 485 74.9** 2530 97** 0.2 0.3

Cu 1 2.0 0.3 41 1.6 0.0 0.0

Seq. 1 2.1 0.3 40 1.5 0.2 0.2

Agar 1 16.4 2.5 215 8.3* 1.8 2.3

pH 1 1.0 0.1 12 0.5 0.9 1.2

Myo. 1 17.4 2.7 10 0.4 0.3 0.4

Cold 1 30 4.6* 95 3.7* 0.2 0.3

Error 15 97.0 6.5+ 390 26+ 11.8 0.8+

Cult., cultivar; BA, 6-benzyldenine; Cu, CuSO4 Æ 5H2O; Seq., Sequestrene Fe source; Myo., Myo-inositol; **, *: Significant at 0.005,

0.05; +: Mean square error, respectively.

217

concentration of agar was increased (Ebrahim andIbrahim, 2000). The superiority of liquid or loose-solidified medium over firm-solidified mediumcould be ascribed to– a better contact between explants and liquid/

loose-solidified medium leading to increasedavailability of cytokinin and nutrient uptake(Debergh, 1983),

– dilution of exudates from explants (Ziv andHalevy, 1983) and/or

– more aeration of the medium, which enhancesgrowth and multiplication (Ibrahim, 1994).There were also some differences between PBD

and FFD. Regarding main effects, PBD detectedsignificant cultivar and cold treatment effects fornodes/explant but FFD did not. For shoots/ex-plant, FFD found agar to be significant while PBD

did not, while PBD found cold to be slightly sig-nificant (p ¼ 0.049) while FFD did not. The rea-sons for these differences in results are likely due tolarge error variances of the experiments. Coeffi-cients of variation ranged from approximately 30for nodes with FFD to approximately 102 forcallus with PBD.

Due to the nature of these designs, FFD pro-vided tests for some two-way interaction whilePBD did not. Based on FFD, Cultivar · BA wassignificant for shoots/explant and callus weight;Cultivar · pH was significant for shoots per ex-plant and nodes/explant while Cultivar · Cu wassignificant for shoots/explant. However, theseinteractions should be interpreted with care sincethey are aliased with other interactions (Table 4).For example, Cultivar · BA was aliased with

Table 4. Analysis of variance of the fractional factorial design for dependent variables: number of shoots produced per culturedexplant, number of nodes per cultured explant and callus fresh weight per cultured explant (Callus W.)

Source DF Shoot/explant Node/explant Callus W. explant

SS F value SS F value SS F value

Cult. 1 71.4 10.7** 28.4 1.8 18.7 28.5**

BA 1 572.3 85.8** 1912.2 122.5** 1.5 2.3

Cu 1 15.3 2.3 32.6 2.0 0.1 0.1

Seq. 1 27.5 4.1 3.1 0.2 0.1 0.1

Agar 1 78.5 11.8** 186.4 11.9** 0.1 0.4

PH 1 2.9 0.4 20.8 1.3 0.4 0.8

Myo. 1 0.5 0.0 2.8 0.1 0.0 0.0

Cold 1 25.7 3.9 2.8 0.1 0.0 0.0

Cult. · BA 1 32.1 4.8* 12.1 0.7 5.0 7.7*

Cult. · Cu 1 34.1 5.1* 0.6 0.0 1.2 1.8

Cult. · Seq. 1 0.8 0.1 1.7 0.1 0.0 0.0

Cult. · Agar 1 1.3 0.2 12.0 0.7 1.2 1.9

Cult. · pH 1 38.0 5.7* 117.8 7.5* 1.0 1.7

Cult. · Myo. 1 22.8 3.4 5.0 0.3 1.3 1.9

Cult. · Cold 1 6.8 1.0 61.3 3.9 0.0 0.0

Error 16 106.8 6.7+ 249.7 15.6+ 10.5 0.6+

Alias structure of two-way interactions (assume 3-way interactions and higher zero)

Cult. · BA = Cu · Cold = Seq. · Myo. = Agar · pH

Cult. · Cu = BA · Cold = Seq. · pH = Agar · Myo.

Cult. · Seq. = BA · Myo. = Cu · pH = Agar · Cold

Cult. · Agar = BA · pH = Cu · Myo. = Seq. · Cold

Cult. · pH = BA · Agar = Cu · Seq. = Myo. · Cold

Cult. · Myo. = BA · Seq. = Cu · Agar = pH · Cold

Cult. · Myo. = BA · Cu = Seq. · Agar = pH · Myo.

Cult, cultivar; BA, 6-benzyldenine; Cu, CuSO4 � 5H2O; Seq., sequestrene Fe source; Myo., Myo-inositol; **, *: Significant at 0.005,

0.05; +, Mean square error, respectively.

218

Cu · Cold, Seq · Myo and Agar · pH meaningthat these interactions could also be contributingto the Cultivar · BA significance. Both the maineffects of Cultivar and BA are large which verylikely could lead to their interaction and sinceAgar is significant, Agar · pH may also beimportant. In addition, since the main effects forCu, Cold, Seq, pH and Myo are small and non-significant, it is reasonable to assume interactionswith these effects are negligible. Thus, we consid-ered Cultivar · BA (and possibly Agar · pH) assignificant. Similar reasoning leads to the conclu-sion that Cultivar · Cu and possibly BA · Coldand/or Agar · Myo could be important forshoots/explant and that BA · Agar (and possibly

Cultivar · pH) affects shoots and nodes per ex-plants. Overall, since pH, Myo and Cold maineffects are insignificant the three factors Cultivar,BA and Agar would appear to be the mostimportant factors to study further.

In the current study, that the effects of cultivar,BA and agar concentration on the culture re-sponses were significant and the type of cultureresponses were in agreement with previous reportsindicate that PBD and FFD can effectively beemployed to test effects of several factors with alimited number of explants and prioritize the ‘mostimportant’ factors. The next logical step would bethe optimization of the prioritized factors followedby that of less significant ones when sufficientnumbers of explants become available for largerexperiments.

Table 5. The effects of eight factors on culture responsesobtained using PBD

Factor level Shoot

/explant

Node

/explant

Callus weight (g)

/explant

Genotype

‘Chancellor’ 6.9a 19.7a 1.5a

‘MN1047’ 3.4b 11.5b 0.3b

BA (mg l)1)

0.2 2.0b 8.4b 0.9a

0.4 8.3a 22.9a 0.8a

CuSO4 � 5H2O

(mg l)1)

0.025 5.4a 16.7a 0.9a

2.5 4.8a 14.3a 0.9a

Fe source

(6 mg Fe l)1)

Sequestrene 138 5.4a 14.8a 0.8a

Sequestrene 330 4.8a 16.2a 0.9a

Agar (mg l)1)

6 5.6a 17.4a 0.7a

8 4.6a 13.7b 1.0a

pH

5 ± 0.02 5.0a 16.3a 1.0a

6 ± 0.02 5.1a 14.7a 0.7a

Myo-inositol

(mg l)1)

100 4.6a 15.3a 1.0a

300 5.6a 16.0a 0.8a

Storage of ex-

plants at 4 �C for

48 h

48 h 5.8a 16.7a 0.8a

0 h 4.4b 14.4b 0.9a

Means in the same column within a factor followed by the same

letter are not significantly different.

Table 6. The effects of eight factors on culture responsesobtained using FFD

Factor level Shoot

/explant

Node

/shoot

Callus weight

(g)/explant

Genotype

‘Chancellor’ 6.2a 14.a 1.5a

‘MN1047’ 4.0b 12.7a 0.5b

BA (mg l)1)

0.2 2.0b 7.8b 1.1a

0.4 8.1a 18.8a 0.8a

CuSO4 � 5H2O (mg l)1)

0.025 5.6a 14.1a 0.9a

2.5 4.6a 12.5a 1.0a

Fe source (6 mg Fe l)1)

Sequestrene 138 5.8a 13.6a 1.0a

Sequestrene 330 4.4a 13.0a 1.0a

Agar (mg l)1)

6 6.2a 15.1a 1.0a

8 4.0b 11.6b 1.1a

pH

5 ± 0.02 5.3a 14.0a 0.9a

6 ± 0.02 4.9a 12.7a 1.1a

Myo-inossitol (mg l)1)

100 5.2a 13.1a 1.0a

300 5.0a 13.5a 1.0a

Storage of explants at

4 �C for 48 h

48 h 4.4a 13.1a 1.0a

0 h 5.7a 13.5a 1.0a

Means in the same column within a factor followed by the same

letter are not significantly different.

219

References

Box GEP, Hunter WG & Hunter JS (1978) Statistics for

Experimenters. Wiley. New York.

Carputo D, Cardi T, Chiari T, Ferraiolo G & Frusciante L

(1995) Tissue culture response in various wild and cultivated

Solanum germplasm accessions for exploitation in potato

breeding. Plant Cell Tiss. Org. Cult. 41: 151–158

Compton ME (1994) Statistical methods suitable for the

analysis of plant tissue culture data. Plant Cell Tiss. Org.

Cult. 37: 217–242

Compton ME & Mize CW (1999) Statistical consideration for

in vitro research: I–Birth of an idea to collecting data. In Vitro

Cell Dev. Biol. Plant 35: 115–121

Debergh PC (1983) Effects of agar brand and concentration on

the tissue culture medium. Physiol. Plant 59: 270–276

Ebrahim MKH & Ibrahim IA (2000) Influence of medium

solidification and pH value on in vitro propagation ofMaranta

leuconeura cv. Kerchoviana. Sci. Hortic. 86: 211–221

Hansen LN, Ortiz R & Anderson SB (1999) Genetic analysis of

protoplast regeneration ability in Brassica oleracea. Plant

Cell Tiss. Org. Cult. 58: 127–132

Henry Y, Vain P & De Buyser J (1994) Genetic analysis of in

vitro plant tissue culture responses and regeneration capac-

ities. Euphytica 79: 45–58

Ibanez MA, Martin C & Perez C (2003) Alternative statistical

analyses for micropropagation: a practical case of prolifer-

ation and rooting phase in Viburnum opulus. In Vitro Cell

Dev. Biol. Plant 39: 429–436

Ibrahim AI (1994) Effect of gelling agent and activated charcoal

on the growth and development of Cordyline terminalis

cultured in vitro. Proc. First Conf. Ornamental Hortic. 1: 55–

67

Kane ME, Davis LG, McConnell DB & Gargiulo JA (1999) In

vitro propagation of Cryptocoryne wendtii. Aquat. Bota. 63:

197–202

Machii H, Mizuno H, Hirabayashi T, Li H & Hagio T (1998)

Screening wheat genotypes for high callus induction and

regeneration capability from anther and immature embryo

cultures. Plant Cell Tiss. Org. Cult. 53: 67–74

McCown DD & McCown BH (1987) North American hard-

woods. In: Bonga JM & Durzan DJ (eds) Cell and Tissue

Culture in Forestry, Vol. 3, Case Histories: Gymnosperms,

Angiosperms and Palms. (pp. 247–260). Martinus Nijhoff,

Dordrecht, Boston, Lancaster

McLean NL & Nowak J (1998) Inheritance of somatic

embryogenesis in red clover (Trifolium pratense L.). Theor.

Appl. Genet. 97: 557–562

Mereti M, Grigoriadou K & Nanos GD (2002) Micropropa-

gation of the strawberry tree, Arbutus unedo L. Sci. Hortic.

93: 143–148

Mize CW & Chun YW (1988) Analyzing treatment means in

plant tissue culture research. Plant Cell Tiss. Org. Cult. 13:

201–217

Mize CW, Koehler KJ & Compton ME (1999) Statistical

consideration for in vitro research: II – Data to presentation.

In Vitro Cell Dev. Biol. Plant 35: 122–126

Nas MN & Read PE (2004) A hypothesis for the development

of a defined tissue culture medium of higher plants and

micropropagation of hazelnuts. Sci. Hortic. 101: 189–200

Ozgen M, Turet M & Avci M ( 2001) Cytoplasmic effects on

tissue culture response of callus from winter wheat mature

embryos. Plant Cell Tiss. Org. Cult. 64: 81–84

Rani V, Singh KP, Shiran B, Nandy S, Goel S, Devarumath

RM, Sreenath HL & Raina SN (2000) Evidence for new

nuclear and mitochondrial genome organizations among

high-frequency somatic embryogenesis-derived plants of

allotetraploid Coffea arabica L. (Rubiaceae). Plant Cell

Rep. 19: 1013–1020

Rosati C, Landi P & Tuberosa R (1994) Recurrent selection for

regeneration capacity from immature embryo-derived calli in

maize. Crop Sci. 34: 343–347

SAS (1995) SAS/QC Software: Usage and Reference, Version 6,

1st ed., Vol. 1. SAS Institute, Cary, NC

SAS (1996) SAS/STAT Software: Usage and Reference, Ver-

sion 6, 1st ed., Vol. 2. SAS Institute, Cary, NC

Skoog F & Miller CO (1957) Chemical regulation of growth

and organ formation in plant tissue cultures in vitro.

Symposium Soc. Exp. Biol. 11: 118–131

Ziv M & Halevy AH (1983) Control of oxidative browning and

in vitro propagation of Strelitzia reginae. Hort. Sci. 18: 434–

436

220