Genotype by year interaction for selected quantitative traits in hybrid lines of Triticum aestivum L. with Aegilops kotschyi Boiss. and Ae. variabilis Eig. using the additive main effects and multiplicative interaction model

This study estimated the genotype × environment interactions for ten yield associated traits in advanced generation hybrids of several cultivars of common wheat (Triticum aestivum L.) with Aegilops kotschyi Boiss. and A. variabilis Eig. using the additive main effects and multiplicative interaction (AMMI) models. Tests were ran over five years at one location in replicated field trials. The AMMI model showed significant genotypic and environmental effects for all analysed traits. A majority of the hybrid lines were less stable in the analysed traits than their parental wheats. The older wheat cultivars, with lower environmental sensitivity, were the most stable. The best total genotype selection index, for all ten traits combined, was observed for the oldest cvs. Gama and Rusałka, and among the hybrid lines, for Ae. kotschyi/Rusałka//Smuga and Ae. kotschyi/Rusałka//Muza. The lines Ae. kotschyi/Rusałka//Smuga, Ae. kotschyi/Rusałka//Muza, Ae. kotschyi/Rusałka//Korweta, Ae. kotschyi/Rusałka//Begra///Smuga, and Ae. kotschyi/Rusałka//Begra///Turnia are recommended for inclusion in breeding programmes due to their greater stability and the good average values for the observed traits.

Genotype by Trait Interaction (GT) in Maize Hybrids on Complete Fertilizer

We investigated the interaction between genotype by trait, and an experiment was conducted at the University of Debrecen. Two maize cultivars, FAO340 and FAO410, were studied in a randomized complete block design with four replications. This experiment was applied to the six fertilization treatments. Fertilizer levels were NPK0 (control) (N:0, P2O5:0, K2O:0), NPK1 (N:30, P2O5:23, K2O:27), NPK2 (N:60, P2O5:46, K2O:54), NPK3 (N:90, P2O5:69, K2O:81), NPK4 (N:120, P2O5:92, K2O:108), and NPK5 (N:150, P2O5:115, K2O:135). The first principal component showed 54.24%, and the second principal component showed 20.75%, which explained the total squares interaction using the AMMI model in the case of the FAO410 hybrid. As regards the FAO340 hybrid, the first principal component showed 58.18%, and the second principal component showed 18.04%, explaining the total squares interaction using the AMMI model in the FAO410 hybrid. In the GGE biplot on FAO410, the first and the second principal components covered 91.20% of the total data in this analysis. Accordingly, the desirable treatment was NPK5, followed by NPK4, NPK2, NPK3, NPK1, and NPK0. NPK4 and NPK5 had the most desirable treatments for the number of seeds per row, chlorophyll, weight of 1000 seeds, and stem diameter in the case of the FAO410 hybrid.

Identification of spring barley genetic sources of increased and stable 1000 kernel weight performance (Hordeum vulgare L.)

The trials were conducted in 2018–2020 at the V.M. Remeslo Myronivka Institute of Wheat of NAAS. The aim of the research was to identify new spring barley genetic sources with combination of increased and stable 1000 kernel weight performance for creation initial breeding material under ecological conditions of the central part of Ukrainian Forest-steppe. There were studied 96 spring barley collection accessions originated in different ecological conditions. To identify peculiarities among genotypes within different subspecies (two-rowed and sixrowed), groups of varieties (covered and naked), as well as among two-rowed covered accessions of different ecological origin the genotypes under study were divided into six groups. Within four groups of accessions there were selected genotypes combining the maximum 1000 kernel weight performance and high homeostatic (Hom) and selection value (Sc) indexes. The other two groups of accessions were characterized with the fact that genotypes with high1000 kernel weight through three years did not have high Hom and Sc indexes due to higher variability. The analysis of variance of the AMMI model revealed almost the equal contribution to the total variance for growing season conditions (34.02%), genotype (34.67%) and their interaction (31.32%). The identified features indicate both the significant genetic diversity presented in this panel of spring barley accessions and the significant influence of weather conditions on the formation of 1000 kernel weight, as well as the different reaction of genotypes on the conditions of individual years of the research. When using statistical parameters and visualizations of the GGE biplot, new spring barley genetic sources with the optimal combination of increased and stable the trait performance were identified. In particular, to improve 1000 kernel weight the accessions Sviatovit (UKR), Dar Nosivshchyny (UKR), Smaragd (UKR), Sunshine (DEU), Lilly (DEU), and Vladlen (KGZ) are recommended to use as parental components for two-rowed covered barley varieties, the accession NSGJ-1 (SRB) is for naked barley varieties, and Yerong (AUS) is for six-rowed barley varieties.

Understanding the Effects of Growing Seasons, Genotypes, and Their Interactions on the Anthesis Date of Wheat Sown in North China

Quantitative studies on the effects of growing season, genotype (including photoperiod genes and vernalization genes), and their interaction (GGI) on the anthesis date of winter wheat (Triticum aestivum L.) are helpful to provide a scientific reference for selecting or developing adaptive varieties in target environments. In this study, we collected 100 winter wheat varieties with ecological adaptability in North China and identified the anthesis date under field conditions for three consecutive years from 2016 to 2019 with mapped photoperiod and vernalization alleles. Our results showed that the number of the photoperiod-insensitive Ppd-D1a allele increased with variety replacement, while the haplotype Ppd-A1b + Ppd-D1b + vrn-D1 (A4B2) decreased from the 1940s to 2000s. The anthesis date of A4B2 was significantly delayed due to the photoperiod-insensitive alleles Ppd-A1b and Ppd-D1b. The additive main effect and multiplicative interaction (AMMI) model and GGI biplot analysis were used for data analysis. A large portion of the total variation was explained by growing seasons (66.3%), while genotypes and GGIs explained 21.9% and 10.1% of the anthesis dates, respectively. The varieties from the 1940s and before had a great influence on the anthesis date, suggesting these germplasms tend to avoid premature anthesis and could facilitate the development of phenological resilient varieties.

ADAPTABILITY AND STABILITY FOR IRON AND ZINC IN COWPEA BY AMMI ANALYSIS

ABSTRACT Iron and zinc deficiency is one of the main problems affecting vulnerable populations in the Colombian Caribbean, thereby generating malnutrition from the consumption of foods with low content of essential minerals. The objective of this study was to evaluate the genotype-environment interaction for iron and zinc accumulation in grains in 10 cowpea bean genotypes by additive main effects and multiplicative interaction (AMMI) model and to select the most stable ones to stimulate their planting or as parents in the genetic improvement program. Nine promising lines and a commercial control were evaluated using the randomized complete block design with 10 treatments and four replications in 10 environments of the northern Colombia in the second semester of 2017 and first of 2018. The adaptability and stability analysis was done using AMMI model. The results showed highly significant differences at the level of environments, genotypes, and genotype-environment interaction for iron and zinc, demostrating a differential adaptability of genotypes in the test environments. Genotypes 2 and 3 expressed greater adaptability and stability for iron contents in the seed; while genotype 1, recorded it for zinc contents. These three genotypes outperformed the commercial control and, therefore, can be recommended for planting or be used as parents in the genetic improvement program.

Genotype × environment analysis of cowpea grain production in the forest and derived savannah cultivation ecologies

Differential performance of genotypes in different cultivation environments has remained a challenge to farmers and plant breeders, the emphasis being the selection of high yielding and stable genotypes, across similar ecologies. A set of nine cowpea genotypes were cultivated in Ago-Iwoye and Ayetoro, two locations representing high and moderate moisture zones. Plantings were done with the early and late season rains in Ago-Iwoye and mid-late season rains of Ayetoro. Statistical analysis was done to understand genotype reaction to the different environments and the plant and environment factors mediating the performance. The Additive Main Effect and Multiplicative Interaction (AMMI) model captured 61.30% of the total sum of squares (TSS). The main effects: genotype (G) environment (E) and their interaction (GxE) were significant with the largest contribution of 28.70% by the environment while the interaction and genotype fractionscaptured 20.20% and 12.40%, respectively. The percentage contribution of the main effects and GxE to total sum of squares (TSS) for traits was not consistent. The Genotype plus Genotype-by-Environment (GGE) analysis summarized 91.30% of the variation in genotype performance across environment. The cultivation environments were separated into two, with IT 95M 118 as the vertex genotype in the Ayetoro while TVU 8905 was the topmost genotype in Ago-Iwoye. The two genotypes recorded the highest grain weight per plant (GWPP) but were also the most unstable The stable genotypes IT 95M 120 and IT 86 D 716 flowered relatively late compared to others, are taller, had higher vegetative score and are low grain producers. Key words: AMMI, drought, GGE, stability, Vigna unguiculata

Stability Analysis of Agronomic Traits for Maize (Zea Mays L.) Genotypes Based on Ammi Model

Stability and adaptability of promising maize hybrids in terms of three agronomic traits (grain yield, ear weight and 100-kernel weight) in multi-environments trials were evaluated. The analysis of AMMI model indicated that the all three agronomic traits showed highly significant differences (p < 0.01) on genotype, environment and genotype by environment interaction. Results showed that genotypes Hengyu321 (G9), Yufeng303 (G10) and Huanong138 (G3) were of higher stability on grain yield, ear weight and 100-kernel weight, respectively. Genotypes Hengyu1587 (G8) and Hengyu321 (G9) showed good performance in terms of grain yield, whereas Longping208 (G2) and Weike966 (G12) showed broad adaptability for ear weight. It was also found that the genotypes with better adaptability in terms of 100-kernel weight were Zhengdan958 (G5) and Weike966 (G12). The genotype and environment interaction model based on AMMI analysis indicated that Hengyu1587 and Hengyu321 were the ideal genotypes, due to extensive adaptability and high grain yield under both testing sites. Bangladesh J. Bot. 50(2): 343-350, 2021 (June)