Abstract
The statistical analysis of the results of studies on the effect of sowing time on the yield and quality of winter wheat grains, from the perspective of multivariate variance analysis and multiple comparison of averages, is carried out in the article. It was found that the application of the procedure of a multivariate generalized linear model allows comparing the variants of experiments for all indicators in the aggregate. An important advantage of multiple comparisons over paired Student comparisons is also the ability to isolate homogeneous subgroups of experiments. In this study, post hoc comparisons according to the Tukey criterion were applied, the results of which are presented in tables of homogeneous experiment subgroups and multiple comparisons of indicators’ differences. The distribution of experiment variants by zones of desirability of Harrington functions of yield and generalized indicator of grain quality, depending on shift of sowing time is also presented. It is justified that the maxima of yield and quality of winter wheat grains provide a sowing period of 10 days later than previously recommended for the region. The use of multivariate dispersion analysis and multiple comparison of average increases the reliability of statistical conclusions, allows you to distinguish homogeneous versions of experiments in agricultural production.
Highlights
The choice of winter wheat sowing time under the conditions of climate aridization in the Oryol region is very important
Post hoc comparisons according to the Tukey criterion were applied, the results of which are presented in tables of homogeneous experiment subgroups and multiple comparisons of indicators’ differences
Based on the results of our simulation of triplicate replication, we have five options of the experiments and data on the yield, and on four indicators of wheat grain quality, and a valid method for detecting the impact on these indicators of the shift in the sowing time is a dispersion analysis according to the multidimensional generalized linear model scheme.In this case, multivariate analysis of variance should be preferred to one-dimensional one, since dependent variables correlate with each other: according to correlation data analysis, it was revealed that most Pearson correlation coefficients are statistically significant at a level at least 0.05, and considering the correlation of dependent variables with each other will allow taking into account all the connections hidden in the numerical data
Summary
The choice of winter wheat sowing time under the conditions of climate aridization in the Oryol region is very important This is due to the increase of the warm autumn period by 23 weeks with an average daily temperature of 10-120С and often with a lack of moisture in the soil, in comparison with the previously recommended winter wheat harvest dates for the zone. A.A. Lyubishchev pointed out the importance of using dispersion analysis to make informed conclusions based on the results of the biological studies. Taking into account the above mentioned, statistical analysis of the results of the studies on the effect of sowing time on quality indicators of the grains of winter wheat variety Moskovskaya 39 given in the work [6] is performed from the point of view of multiple comparison of average
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