ASPECTS OF PRODUCT QUALITY IN PLANT PRODUCTION

1. Glucosinolates

2. NIRS for oil / protein / carbohydrate … content

Practical experiments / Oil/protein crops

Analytical methods for crop

quality determination

• large sample numbers to be managed in a short

period of time (plant breeding, silo ...)

• small sample size (e.g. single plant harvest)

• whole seed measurement (non-destructive

measurement) in plant breeding

• sufficient accuracy (depending on goal of

measurement)

• adequate sampling (problems of sample

disintegration, single plant samples etc.)

Pre-requisites

Analytical methods for crop

quality determination

• Kjeldahl nitrogen determination (protein)

• Soxhlet extraction (oil)

• GC (gas chromatography), HPLC (high performance liquid

chromatography) e.g. for fatty acids, amino acids and many other separable constituents such as agrochemical residues, toxins etc.

• NIRS (near-infrared reflectance spectroscopy) for different organic constituents

• Element analyzer (e.g. CN analyzer)

Universal methods

Analytical methods for crop

quality determination

• sedimentation

• farinogram

• extensiogram

• amylogram

• falling number

• vitrousness

• carotinoid content

• polarisation

• glucosinolate tests

Specific methods (a few examples)

• image analysis

• iodine value

• paper chromatography for erucic acid

• thiobarbituric test for linolenic acid

• electrophoresis (SDS-PAGE) for specific protein patterns

• DNA markers

Determination of glucosinolate content

Glucosinolates: Present in all Brassicaceae plants

S-D-thioglucose, sulfate ester, R = organic side chain.116 different glucosinolates according to side chain.

Some glucosinolates are toxic or mutagenic and used as biocides to sterilize soils, other glucosinolates are known to have health benefits in human nutrition.

Determination of glucosinolate content

DIRECT DETERMINATION METHODS USING DEGRADATION PRODUCTS

1. determination of glucose

2. formation of coloured complexes

3. determination of sulphate

METHODS BASED ON DETERMINATION AND SUMMATION OF INDIVIDUAL

GLUCOSINOLATES

1. Gas chromatography of trimethylsilylated desulphoglucosinolates

2. HPLC methods of desulphoglucosinolates or intact glucosinolates

3. Capillary electrophoresis

INDIRECT METHODS (NON-DESTRUCTIVE)

1. X-ray fluorescence

2. Near IR spectroscopy

Determination of glucosinolate content

Method 1: determination of sulphate

Method 2: determination of glucose

glucosinolate is hydrolized by the enzyme myrosinase

(present in cells, active when cells are destroyed), glucose

is determined using a glucose testing strip with o-tolidine

1 mole glucose = 1 mole of glucosinolate

high glucosinolate

low glucosinolate

Determination of glucosinolate content

Image analysis

Analysis of digital images:

Numerical information on color, intensity, distance, area,

perimeter, shape and other characteristics can be

obtained from digital images.

Sample applications:

Medicine, remote sensing, quality control, agriculture,

biometrics etc.

Image analysis applications in agriculture

Quality control: seed coloration, sample purity etc.

Quality determination: yellow pigmentation of durum wheat, cotton grades (color), fibre content of flax from stem cross-section micrographs

Microscopic image analysis of quality features in cereal grains and flours (wheat, barley , oat)

Agronomy: Nitrogen fertilization control (leaf color), irrigation control, plant density measurement, leaf area, weed density etc.

Yield: yield estimation from satellite images or aerial pictures

Image analysis (color)

Image analysis (color)original

overlay

Overlay area measurement

Image analysis (intensity)

Image analysis (intensity)

Image analysis (pore size of bread samples)

Image analysis (pore size of bread samples)

Pores in bw-mode

Image analysis (pore size of bread samples)

Pore analysis results

Image analysis (leaf size, chlorophyll

content, nitrogen fixation)

F6-lines in the field

nod-nod+

Image analysis (leaf size, chlorophyll

content, nitrogen fixation)

Image analysis (nitrogen fixation)

saturation (HSB leaf image analysis)

0,50 0,55 0,60 0,65 0,70 0,75 0,80 0,85

se

ed p

rote

in c

onte

nt

(g/k

g)

300

350

400

450

Col 2 vs Col 3

Col 6 vs Col 7

Plot 1 Regr

r = -0.83

Thiobarbituric acid test for linolenic acid

Testing principle:

linolenic acid from seed is oxidized using

UV and / or acids,

thiobarbituric acid (TBA) + oxidized

linolenic acid forms a complex of intense

red color.

Applications: Selection for low or high

linolenic acid in oilseeds, control of lipid

oxidation in food control

TBA test during selection for linolenic acid

near-infrared: 800-2500 nm

mid-infrared

far-infrared

micro-waves

NIRS as an example of

a physical analytical method

• Principle: NIRS uses reflections/absorption of light in the range of 800-2500 nm wavelength to determine the content of organic components of a sample

• Calibration of NIRS machine with known reference samples / Validation

• Routine measurement (scanning) of samples

• Prediction of chemical content

• Advantages / problems over other methods

NIRS: Near infrared reflectance spectroscoopy

Reference

samples

Chemical

analysis

NIRS calibration

development

NIRS

spectra

Calibration model development Routine analysis

Samples

NIRS

spectra

Prediction of

results

NIRS principles / procedures

Analytical methods for crop

quality determination

NIRS (near-infrared reflectance spectroscopy) machines

NIRS spectra

wave number (cm-1)

absorbance

Chemical wavelength (nm)

-CH3 1195

water 1450

C=O 1450

urea 1490

-NH 1500

protein 1520

starch 1540

cellulose 1780

water 1790

protein 2055

oil 2070

starch 2100

protein 2180

oil 2310

Examples of NIRS absorbance areas

NIRS principles

Spectroscopic absorbance peaks

at different wavelengths are due to

different constituents, e.g. water

peak at 1450 nm.

Vis-NIR spectra for zeaxanthin (black), lutein (blue), and

lutein mixtures (maize; Brenner & Berardo, 2004)

NIRS principles

Spectroscopic absorbance peaks

at different wavelengths are due to

different constituents, e.g. water

peak at 1450 nm.

The Beer-Lambert law describes

the linear relationship between

absorbance and concentration of

an absorber of electromagnetic

radiation.

NIRS spectra

wave number (cm-1)

absorbance

NIRS applications in plant breeding

Quantitative predictions (examples):

oil, protein, starch, fibre, sugars, moisture

fatty acids, amino acids, glucosinolates

carotinoides, isoflavones, beta-glucane

breadmaking parameters, brewing parameters

grain hardiness, particel size, digestibility,

botanical composition (hay) etc.

Qualitative applications

Diversity analysis, sample/genotype discrimination,

metabolic analysis ... (mutant identification ?)

Prediction of seed protein content in soybean(Bruker Matrix I / OPUS Quant validation)

Prediction of malt extract content in brewing barley

NIRS developments:

GenotypingCultivar identificationReal time measurement

Analytical methods for crop

quality determination

Examples of molecular genetic techniques

PCR-based DNA-

markers

(microsatellites)

SDS-PAGE type

electrophoresis

of proteins (wheat)

Kunitz trypsin inhibitor of soybean

Soybean Kunitz - trypsin inhibitor in

SDS PAGE type of electrophoresis

(absence of 21.5 kDa-protein in lanes

4, 6 and 8)

Kunitz trypsin inhibitor of soybean

Genetic markers

48 soybean genotypes differing in an SSR (simple sequence

repeat = microsatellite) marker

Genetic markers

48 soybean genotypes differing in an SSR (simple sequence

repeat = microsatellite) marker

SSR marker SacK149 associated with low (lo) or high

(hi) cadmium (Cd) accumulation in soybean seed

Genetic markers

Seed cadmium content in four soybean

genotypes at three Cd rates in the soil

Merlin, Gallec:

Allele for high Cd

OAC Erin, ES Mentor:

Allele for low Cd