Schriften zu Genetischen Ressourcen - Genres

U. FREYTAG, G.H. BUCK-S ORLIN and B. SCHMIDT
image analysis allows the determination of geometrical and greyscale values from
digital images of arbitrary sources. Each of 100 seeds, pods and pod transverse sections
as well as the curvature of the pod tips were measured with distances of 10
pixels horizontally and 5 pixels vertically.
Analysed per accession and year were: area (mm 2 ), length (mm), diameter (mm),
circumference (mm) and roundness (roundness is a factor which for a circle adopts
its smallest value of 1. It corresponds to the square of an object’s circumference, divided
by its area).
Statistical analysis
Phenological as well as biometrical data (the latter gathered automatically through
digital image analysis) were stored in MS Excel files and analysed statistically as appropriate
using the software MINITAB (version 12.1 for Windows). Here, the functions
Describe, Oneway, Twoway, GLM, Regress, % Fitline, and Correlation of
MINITAB were employed to compute means and standard deviations for the parameters
measured and to carry out analyses of variance, correlations and regressions.
Results and discussion
Phenological traits and image analysis
Of all phenological traits, the time to flowering (TTF), the time to maturity (TTM) and
the net growth time (NGT) significantly depended upon the genotype (accession),
whereas the germinability (GERM), the duration of cultivation (TV), and the time to
seed emergence (EMERG) were all independent of the genotype but exhibited heavy
fluctuations among the different years (especially EMERG where the complete variability
was annual: Figure 5). The data that were gained by image analysis (area,
length, diameter, circumference, roundness of seeds, pods, and pod transverse sections)
conveyed a different picture: Whereas the seed characters were all strongly
genotype-specific (only about 5% annual variability), the annual variability of the pod
transverse section parameters amounted to about 35%. The situation was unclear as
regards the pod characters: although the percentage of the annual variability lay between
19 and 69% according to the nested analysis of variance, all pod characters
differed significantly only among the accessions. This shows that the choice of accessions
can have a strong influence upon the analysability of climate data: morphologically
strongly deviating genotypes are masking a relatively weaker but actually
clear climatically related variability.
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