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
Abstract. Wheat is a crop with a very long growing season, during which it is subjected to prolonged exposure to many environmental factors. For this reason, the interaction of genotype with conditions is very common for any character of wheat. This study aims to determine whether the grain yield is affected by the change of the ear emergence date (EED) in various environments. In a four-year period, 30 current for national real grain production winter wheat varieties were studied. The EED and grain yield (GY) were studied as quantitative traits within five locations of the country having various soil and climatic conditions. Using several statistical programs, genotype x environment interaction of two traits was analyzed. The emphasis on data analysis was whether changes of traits due to the conditions were related and that the optimization of the ear emergence date could serve as a breeding tool for increasing grain yield. The date of ear emergence and grain yield are traits that are reliably influenced by growing conditions. The change in the date of emergence is mainly of the linear type, while the grain yield shows linear and nonlinear type changes in the same environmental conditions. It was found that the key roles in the change of characteristics are the conditions of the year, with the relatively weakest impact of the genotype on them. There is a positive relationship between the two traits, although their change depends on environmental factors. Although they change to different degrees and in relation to each other, there is a positive correlation between them. The more favorable the environmental conditions, the weaker the relationship between these two traits and vice versa. Under changing climatic conditions, the change in the relationship between the two traits is a signal of the need to create different varieties by date of ear emergence in order to obtain higher yields in the future.
Data from the Multi Environmental Field Trail (MET), which examined 24 varieties of common wheat, were divided into three "datasets" related to three of the five study locations. Using meta-analysis, these three data sets were compared with those from the whole experiment. The aim of the study is to determine whether a 4-year growing period in three country-specific locations, it is possible to establish a significant impact of the environment on the stability of a group of varieties. The analysis of the genotype x environment interaction (GEI) was performed in parallel in the three groups of data, which were compared with the entire MET database. A direct comparison was made on them regarding the possibilities of non-parametric methods to assess the stability of the variety. The analysis of the results of the four "datasets" is done through a number of statistical approaches, allowing them to be correctly compared at different levels. Genotype x environment interaction was found in each of the studied locations. The variation in yield in them is a result of the direct effect of the "year" and the combined effect of the genotype x year. At all three locations, the GEI is broken down into four main components, which is evidence of the strong linear and non-linear nature of the dispersion of grain yield. These results are a prerequisite for an objective assessment of genotype stability. All applied parameters give completely similar stability information for each of them, regardless of the test location. Data from one location are sufficient to assess the stability of each variety in a group. This may be the case if significant differences between the seasons of the trial, are found. The applied non-parametric methods for stability assessment give correct information about the varieties, in the presence of GEI, regardless of the conditions from which the data for analysis are selected.
The study was conducted to evaluate the stability of common wheat varieties in four locations with proven different environmental conditions. Three indexes of grain quality were studied: wet gluten content, (WGC); gluten index of grain (GI) and grain sedimentation value (Zeleny). The stability of varieties has been evaluated by many parameters that reflect different aspects of the complete picture for it. The indexes studied are strongly influenced by environmental conditions. The most genetically stable among them is the gluten index (GI), where the genotype has a decisive role of about 70% of the variation, and the most unstable is the wet gluten content (WGC), with only 17% of the effect. As a result of reliable GE, the ranking of the varieties according to the performance of each of the indexes is different in the individual locations. The ranking of varieties in terms of stability according to the ranks of each of the parameters is very different. Even a visual representation of the results, which clears the picture to the maximum extent, shows a different set of stable varieties in each of the quality indexes. Only a few of the varieties (G2, G6, G9, G13, G18, G20, G22) have a good balance between the size and stability of all quality parameters, with a moderate compromise with the grain yield level. The assessment of the stability of the variety in terms of quality can be made according to any of the indexes used. The stability of the variety depends to a large extent on the effect of the environment, which must be considered when selecting a specific index for assessment. The most suitable for this purpose is the gluten index (GI), where the influence of genotype is the strongest, with a significant GE interaction accounting for 25% of all variation. The stability of the variety does not depend on the magnitude of the quality indexes. Stable can be both quality (G2, G6) and varieties with very low grain quality (G18, G20, G22). Stability of quality, at high levels of indexes, is associated with low grain yield and vice versa. From this point of view, combining high yield stability and grain quality at the highest possible levels is a very rare exception (G2, G9).
Abstract. In ecological field experiment involving common wheat varieties, several quality parameters were analyzed, which express different aspects of grain quality. Objective of the study was to establish in detail the main relations about the influence of the conditions (location and year) and their interaction with the genotype on each of the parameters, separately. The accepted hypothesis was that the growing conditions have a different strength and direction of effect on each parameter, which should ultimately be reflected in a unique way on the performance of each variety of the studied group. In four locations, which represent a sample of the main grain-producing regions of the country, twenty-four varieties of common winter wheat were investigated. Five indexes of grain quality were analyzed as follows: Sedimentation index (Zeleny); Deformation energy (W); P/L alveograph configuration ratio (P/L); Swelling index (G); Dough stability time (Dstab). All possible aspects of the interaction of genotype (GEN), environment (ENV) as well as the interaction between them (GEN*ENV) were investigated. Statistical approaches and methods that are specialized for this purpose were used. Each of the three main factors – “location”, “year” and “genotype” influenced the variation of the group of varieties through the changes of the conditions, independently and in combination with each other. In this combination of effects expressed as (GEN*ENV) the most essential role was the “location”. The established significant interaction caused an adequate (linear) and inadequate (non-linear) change of the varieties, relative to those of the conditions. For the majority of parameters, this change was mostly linear (PC1=70%), with the exception of the P/L (alveograph configuration ratio), where both effects had parity (PC1≈PC2-4). The environments in the locations during individual seasons had high degree of repeatability (H2=0.75 – 0.94), which allows a high degree of prediction of the values of each single parameter. All parameters were affected to varying degrees by the studied factors and the interaction between them. The influence of the conditions was relatively the strongest on the Dough stability time index (Dstab), and the Swelling index (G) was most closely related to the genetic predisposition of the variety. The effects of the interaction of the genotype with the environments (GEN*ENV) made up about 20-30% of the total variation of three of the parameters, for Deformation energy index (W) the effect reached 40%, and for the Dough stability time index (Dstab) it was only about 13%. The environments during the seasons were the cause of a dynamic change of the correlations between the yield and some of the parameters, in some of the locations studied. Probably, this was directly dependent on the specific combination between the levels of extraction and the level of a given parameter.
Abstract. Information on the relationships between quantitative traits affecting yields is extremely important for winter wheat. For it, the annual genotype*environment interaction is palpable and often masks the influence of individual traits on grain yield. The aim of the study is to determine the traits through the selection of which the grain yield could be significantly increased in the future. The data from three field multifactorial experiments were used (FERT, PGR, ABC), in which a significant influence of various factors (year, point, density, fertilization) on the size and variation of all studied traits was established. In the database thus formed the observed strong variance in the values of the traits is a great prerequisite for the established correlations to be accepted with a high degree of reliability. The mutual influence in the formation of each of the traits is a good basis for their grouping, according to the type of their effect on yield. 1) The characteristics, number of grains per m2 (NGm), grain weight per spike (WGS) and number of productive tillers per m2 (NPT) have a significantly positive effect on grain yield, 2) the weight per 1000 grains (TGW) and number of grains in spike (NGS) are traits that have a direct effect, but it is unstable in manifestation and 3) the traits, as height of stem (HOS), total plant biomass (TBM), and harvest index (HI) do not show a direct effect on grain yields. A significant increase in yield in the breeding of winter wheat can be achieved by increasing the number of grains per unit area (NGm). This is possible while maintaining the achieved level of number of grains in spike (NGS) with a parallel increase of tillering productive ability (NPT). The increase of this trait by selection should be taken into account when reducing the grain size (TGW). This will increase the chance of increasing the number of grains in the spike (NGS), will reduce the weight of the grain per spike (WGS), which in turn will be a prerequisite for optimizing the stability of lodging
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