Comparison of statistical parameters for estimating the yield and stability of winter common wheat

Abstract

Abstract. Data from different multi-environmental trails (MET) were analysed, including different number of varieties, number of locations and different research periods. The first experiment (24 PhD) included 24 wheat varieties that were studied in five locations of the country over a period of four years (2009-2012). The second field experiment (40 ABC) consists of 40 new advanced wheat lines and cultivars, which were studied in three locations over a three-year period (2017-2019). The grain yield datasets from the two experiments were used to make a direct comparison of various statistical parameters to assess the genotype stability against the background of significant growing conditions. The study involves the use of several statistical packages that are specialized for this purpose. Based on the ranking assessment of the values of each statistical parameter, a critical analysis was made of its relationship with the yield, for each dataset separately. For this purpose, the possibilities of correlation, principal component and cluster analyses were used. Parameters for which information differs between datasets or between statistical packages are removed from the analysis list. The final set of 31 parameters was analysed according to the set goal, after a statistically justified possibility to merge the two datasets. Most of the rank parameters do not show correlation with grain yield. The units are the parameters, the correlation of which is either positive (Pi, Ysi, TOP, λ) or, respectively, negative (DJi, NP(1), CVi]). The analysis of the data through different statistical approaches shows that the parameters correspond to the dynamic concept of stability assessment. Only one of the parameters (θi) is related to static stability assessment. In the presence of many more effective than it, it should not be applied because it is an exception from the analysed group. The groups of parameters of the regression coefficient (bi), the deviation from the regression line (s2di), ecovalence (W2i) and the stability variance (σ²i), give objective information about the behaviour of the variety in environmental conditions and it is not influenced by software. Some of the non-parametric [S(i) NP(i)] assessment methods provide diametrically opposed information for stability because of differences arising from either the dataset or the software used. Suitable for stability assessment are non-parametric approaches - [S(1) and S(2)], which is fully confirmed by the three software packages. Each of the used software packages contains a set of parameters, the application of which as a set gives correct information about all aspects of the wheat stability

Analysis of genotype by environmental interaction of common wheat (Triticum Aestivum L.) by non-parametric stability methods

“…The main reason for its application is that it provides significantly more objective information about the sources of variation, in cases where there is a significant difference between the locations in the manifestation of the sign. Such a difference was found and proven experimentally (Tsenov et al, 2022a), because there are at least four principal components of variation (PC1-PC4), and even five (PC5, for "all locations"). In addition, the value of the first component (linear variation) is approximately as large as the sum of the other components, which represent the part of the nonlinear type of variation.…”

“…In this study, an attempt was made to determine whether the conditions of several consecutive seasons in the regions characteristic of the country's grain production (Dobrich, Ruse and Yambol) would provoke GEI. For comparison, an experiment was used in which there is a proven strong and multi-layered interaction of the genotype with the environmental conditions (Tsenov et al, 2022a;Tsenov et al, 2022b). Comparisons made using different statistical approaches show unequivocally that there are real possibilities for assessing the impact of conditions at one point.…”

“…In a multi environment field experiment, 24 varieties of winter common wheat were studied in five regions of the country (Dobrich, Trastenik, Veliko Tarnovo, Plovdiv and Yambol) over a period of four years (2009)(2010)(2011)(2012). Some of the data collected by them, in connection with the possibilities for evaluation of varieties in grain yield and stability, have already been published (Tsenov et al, 2022a(Tsenov et al, , 2022b. In this study, data from three (Dobrich, Trastenik and Yambol) out of a total of five locations were analysed separately to establish the interaction of genotype x environment in them.…”

Impact of Genotype × Environment Interaction on Seed Yield and Pod Shattering of Soybean Genotypes in Nigeria

“…Yield stability is always considered as an important topic in plant breeding, especially with continuous variation in climatic conditions. Crop varieties may not show uniform performance across different environments due to G×E interactions [13]. A stable soybean cultivar usually possesses a relatively small seed yield fluctuations across locations.…”

“…As a result, this is not of interest to plant breeders to evaluate the phenotypic stability of the genotype performance, or other related random variables. Although, it is helpful to evaluate the phenotypic stability of the traits that should retain their levels such as stress characters like drought resistance, qualitative traits, or disease resistance [13].…”