Grain Yield In Environments Research Articles

Genotype by environment interactions and stability for grain yield and other agronomic traits in selected sorghum genotypes in Ethiopia

AbstractEnvironmental changes pose major impacts on the performance of crop genotypes with important implications for crop improvement strategies. Hence, breeders pay attention to the effects of genotype by environment interaction (GEI) to mine genetic resources and select adapted genotypes. Twenty sorghum genotypes selected from a large collection of Ethiopian sorghum landraces and two improved varieties were evaluated using a randomized complete block design with three replications at eight locations representing different environmental conditions in Ethiopia. The study aimed at assessing GEI and identifying stable and high‐yielding genotypes of sorghum for grain yield and major agronomic traits. Analysis of variance and additive main effect and multiplicative interaction (AMMI) revealed highly significant (p ≤ 0.001) variance due to genotypes, environments, and GEI among all traits except for days to maturity. Plant height, days to maturity, panicle width, panicle weight, and grain yield were highly affected by environment and GEI, while days to flowering, panicle length, and 1000‐grain weight were mainly affected by genotypic variations. The data also suggest the importance of considering GEI in screening for high‐yielding and stable sorghum genotypes across environments. Among testing sites, Chawaka, Gute, and Uke were ideal environments for grain yield and Asosa was the most discriminative environment. Three genotypes (ETSL100808, Merera, and ETSL100474) were superior and stable across test environments for grain yield and related traits. Overall, based on mean grain yield and disease reaction, AMMI, GGE (genotype and genotype by environment interaction) biplot, and regression models, ETSL100808 was the most stable, high‐yielding, and disease‐tolerant sorghum genotype, suggesting its potential both in breeding program, as donor of traits, and for direct release as a variety.

Assessment of Genotype × Environment Interaction and Phenotypic Stability in Single Cross Hybrids Subjected to Drought Stress in Maize (Zea mays L.)

Maize production and productivity are hampered by global climate change. The primary concern of crop breeders always have been about high and stable yields. The genotype × environment interaction alters the relative grain yield of genotypes in different environments and makes it difficult to select superior genotypes. Therefore the Eberhart and Russell model for genotype × environment interaction analysis was taken up in the present study for the prediction of performances and phenotypic stability of the single cross hybrids synthesized by crossing 15 inbreds with 3 testers in Line × Tester mating design. All the 18 parents, 45 F1s and 3 checks were evaluated for fifteen quantitative and qualitative traits over three different environments viz., optimal environment, drought stress environment at tasseling stage, and drought stress environment at grain filling stage, during spring 2021, in a Randomized Complete Block Design with three replications. The ANOVA on the basis of pooled data unraveled significance of mean sum of squares due to genotypes and due to genotype × environment interaction which affirms existence of variability and interplay between genotypes and their environments. Out of 45, 39 hybrids expressed non-significant deviation from regression (S2 di) unveiling their higher predictability over changing environments for grain yield per plant. The hybrid L15×T2 had higher mean value than population mean along with regression coefficient equivalent to unity (bi=1) hence was recognized as highly stable and superior for grain yield per plant, and suitable for cultivation in different kinds of environments. Among other hybrids, L6×T2, L14×T2, L1×T3, L8×T1, L10×T1, L14×T1, L15×T1, L12×T2, L4×T3, L15×T3 were noted stable in performance over the environments for flowering traits. While L10×T2, L2×T2, L15×T2, L11×T1, L3×T2 and L5×T2 were recognized stable in performance for higher yield and its component traits over the environments.

Yield performance and adaptation of advanced large-seeded common bean (Phaseolus vulgaris L.) genotypes in Ethiopia

To ensure the food demand of the rapidly growing population along with changing climate and limiting resources, development and adoption of high-yielding crop cultivars adapting to the adverse effects of climate is crucial for enhancing food production and productivity. The objective of this study was to evaluate the performance and adaptability of 23 advanced bean lines generated by single-seed descent and two commercial varieties (Batu and SAB-736), using additive main effects and multiplicative interaction (AMMI) and genotype plus G x E interaction (GGE) models. Field experiments were conducted in 2019 wet season (from July to October) at five diverse growing environments of Ethiopia. Wide variations were observed across the genotypes and environments for grain yield and other related traits. Mean performance of genotypes for yield ranged from 1.20 to 1.67 t ha −1 across environments, with a grand mean of 1.50 t ha −1 thereby favors genetic enhancement of the trait through selection. Environmental and interaction impacts were greater for all measured traits including yield. Except for number of pod plant −1 and 100 seed weight where interaction effect was more important, the percent variation due to environment was the highest for all traits expression, from 14.76 to 91.09%, to the total variation. Three advanced genotypes showed better yield than SAB-736 (the recent c. variety) and general adaptation across the environments. But, their consistency should be checked across seasons to suggest them for cultivation on these and other similar environments.

Genotype × Environment Interaction and Stability Analysis for Grain Yield and Yield Related Traits in Little Millet (Panicum sumatrense L.)

The present study was conducted to evaluate Genotype × Environment interaction and stability analysis for grain yield, its components in 50 little millet genotypes under three environments i.e. Waghai, Vanarasi and Navsari locations (Gujarat, India) in year Kharif-2020. Stability analysis revealed that G x E interaction was significantly differed for all the characters except calcium content (mg/100g) and ash content (mg/100g) indicated that different genotypes reacted differently to different environmental conditions. Estimates of environmental indices indicated that Waghai location was favourable for most of the yield contributing characters along with quality parameters followed by Navsari and Vanarasi. The results of present study revealed that none of the genotypes exhibited average stability for all the characters. Among the genotypes, WV 262, WV 258, WV 256, WV 293 and WV 273 were found average stable over environments for grain yield per plant with one or more yield contributing characters and quality parameters. So, these genotypes may be used in further breeding programme in little millet.

Performance of Different Varieties of Spring Field Pea (Pisum sativum L.) under Irrigated and Rainfed Environments in North China

Field pea (Pisum sativum L.) is one of the most important pulse crops, and is widely grown in North China. To exploit potential pea varieties suitable for growing in spring planting areas, a set National Regional Trials of Spring Pea Genotype was carried out under irrigated and rainfed environments across seven locations. Grain yield and agronomic traits of fourteen pea cultivars were evaluated. Analysis of variance indicated that the effect of genotype, environments and genotypes × environments interaction was significant (p < 0.01). Results of GGE biplot analysis showed that the first and second principal components accounted for 77.5% and 14.5%, respectively. Genotypes accounted for just 14.7% of the variation in seed yield, while environments accounted for 39.9%, and genotypes × environments interaction accounted for 45.5% of the variation. Investigating the polygon view led to the identification of five superior genotypes and five productivity environments. Superior genotypes and key environments for grain yield were determined using a general linear model. The significant genotypes × environments interaction effects indicated the inconsistent performance of genotypes across the tested environments. Among the tested genotypes, significant differences were observed for grain yield and yield-related traits. The semi-leafless pea variety Longwan 10 was observed the highest yield (3308 kg/ha) over seven locations. Dingwan 12, Dingwan 13, Tongwan 5, Kewan 7 showed higher, stable grain yield than the overall mean of genotypes and check variety Zhongwan 6. The most representative and productivity regions for grain yield of field pea were Yondeng, Qitai, Liaoyang, Dingxi and Tangshan. These findings represent a comprehensive analysis of yield and stability of spring pea varieties and growing locations, which may be useful for national and international pea improvement programs.

Combining ability analysis in bread wheat (Triticum aestivum L.) under different environmental conditions

A Pooled analysis was carried out to evaluate the general and specific combining ability effects in 9 diverse genotypes of bread wheat of diverse origin of cultivation, their 36 F1’s and 2 checks during Rabi 2020-21 at RCA, Udaipur in three different environments for grain yield and its component traits. Analysis of variance revealed the differences between parents and crosses for GCA and SCA, respectively due to GCA and SCA effects were significant for all the characters except days to 50 % flowering in E3 (GCA) on pooled basis. Similarly, mean squares due to GCA x E and SCA x E were significant for all characters revealed influence of environment on GCA and SCA, respectively. The variance due to GCA was higher than their respective SCA for all characters except spike length, awn length and harvest index indicated that additive type of gene action played role in the expression of all the traits. Among parents, DBW 173, HD 2967, GJW 463 and RAJ 4120 were exhibited significant GCA effects for grain yield and its component traits. Maximum significant positive GCA effects were exhibited by parent DBW 173 (1.80) over the environments. Among crosses, thirteen crosses recorded showed significant SCA effects for grain yield and its related traits. Cross, HD 2967 x DBW 173 was exhibited maximum positive significant SCA effects for grain yield and harvest index in the environments as well as on pooled basis. Cross, HD 2967 x DBW 173 depicted maximum SCA effects (4.00) followed by RAJ 3777 x RAJ 4120 (2.92) for grain yield over environments. Attempting cross combinations involving different parents with high GCA for desirable yield and other traits could be useful.

Combining ability analysis in bread wheat (Triticum aestivum L.) under different environmental conditions

A Pooled analysis was carried out to evaluate the general and specific combining ability effects in 9 diverse genotypes of bread wheat of diverse origin of cultivation, their 36 F1’s and 2 checks during Rabi 2020-21 at RCA, Udaipur in three different environments for grain yield and its component traits. Analysis of variance revealed the differences between parents and crosses for GCA and SCA, respectively due to GCA and SCA effects were significant for all the characters except days to 50 % flowering in E3 (GCA) on pooled basis. Similarly, mean squares due to GCA x E and SCA x E were significant for all characters revealed influence of environment on GCA and SCA, respectively. The variance due to GCA was higher than their respective SCA for all characters except spike length, awn length and harvest index indicated that additive type of gene action played role in the expression of all the traits. Among parents, DBW 173, HD 2967, GJW 463 and RAJ 4120 were exhibited significant GCA effects for grain yield and its component traits. Maximum significant positive GCA effects were exhibited by parent DBW 173 (1.80) over the environments. Among crosses, thirteen crosses recorded showed significant SCA effects for grain yield and its related traits. Cross, HD 2967 x DBW 173 was exhibited maximum positive significant SCA effects for grain yield and harvest index in the environments as well as on pooled basis. Cross, HD 2967 x DBW 173 depicted maximum SCA effects (4.00) followed by RAJ 3777 x RAJ 4120 (2.92) for grain yield over environments. Attempting cross combinations involving different parents with high GCA for desirable yield and other traits could be useful.

GGE Biplot Analysis for Stability in Diverse Maturity Groups of Rice (Oryza sativa L.) Advanced Lines

The experiment was carried out under three seasons with 15 genotypes at Agricultural Research Station, Kunaram, Telangana state, India during rabi season (December to April) 2014–15 (E1), kharif season (July to November) 2015 (E2) and rabi season (December to April) 2015–16 (E3). The objective of the study was to assess the stability and adaptability of 15 rice genotypes of the various maturity groups over three seasons. The GGE biplot tool of these 15 rice genotypes of various maturity durations expressed a significant genotype, environment and G×E interaction for yield and days to 50% flowering. Genotype and environment interaction effect was responsible for the greatest part of the variation, followed by genotypes and environment effects for grain yield. Days to 50% flowering of genotypes was highly affected by environments followed by genotypes, and genotype and environment interaction. It also detected that rabi season 2014–15 (E1) was identified as the best suited season for the potential expression of the grain yield, while kharif season 2015 (E2) was the right season for the expression of reduced days to 50% flowering. Further, the what–won–where model indicated that short duration rice genotype G14 (KNM 1690) and medium duration genotype G9 (KNM 1632) in the environments rabi season 2014–15 (E1) and kharif season 2015 (E2), respectively and the early line G11 (KNM 1684) in the environment rabi season 2015–16 (E3) were the winning genotypes and suitable for their respective environments for grain yield. G7 (KNM 1616) was the vertex early genotype and closer to the ideal genotype expressed high yield and stability for all the environments. G13 (KNM 1689) and G14 (KNM 1690) were found to be stable for earliness across all the seasons and could be utilized for the development of early duration varieties. The rice genotype, G15 (BPT 5204) was found to be stable for lateness for all the seasons.

Identification of QTLs affecting post-anthesis heat stress responses in European bread wheat

Key messageThe response of a large panel of European elite wheat varieties to post-anthesis heat stress is influenced by 17 QTL linked to grain weight or the stay-green phenotype.Heat stress is a critical abiotic stress for winter bread wheat (Triticum aestivum L.) especially at the flowering and grain filling stages, limiting its growth and productivity in Europe and elsewhere. The breeding of new high-yield and stress-tolerant wheat varieties requires improved understanding of the physiological and genetic bases of heat tolerance. To identify genomic areas associated with plant and grain characteristics under heat stress, a panel of elite European wheat varieties (N = 199) was evaluated under controlled conditions in 2016 and 2017. A split-plot design was used to test the effects of high temperature for ten days after flowering. Flowering time, leaf chlorophyll content, the number of productive spikes, grain number, grain weight and grain size were measured, and the senescence process was modeled. Using genotyping data from a 280 K SNP chip, a genome-wide association study was carried out to test the main effect of each SNP and the effect of SNP × treatment interaction. Genotype × treatment interactions were mainly observed for grain traits measured on the main shoots and tillers. We identified 10 QTLs associated with the main effect of at least one trait and seven QTLs associated with the response to post-anthesis heat stress. Of these, two main QTLs associated with the heat tolerance of thousand-kernel weight were identified on chromosomes 4B and 6B. These QTLs will be useful for breeders to improve grain yield in environments where terminal heat stress is likely to occur.

Straw mulch-based no-tillage improves tillering capability of dryland wheat by reducing asymmetric competition between main stem and tillers

The moisture-conserving effect of straw mulch-based no-tillage (SMNT) is expected to increase fertile spikes and grain yield in environments with rainfall less than 200 mm. However, the mechanisms underlying the positive effect of SMNT on wheat tillering are not fully elucidated. A split-plot experiment was designed to investigate the combined effects of SMNT and cultivars on tillering of dryland wheat grown under both dry and favorable climates. Application of SMNT to a cultivar with 1–2 tillers exploited both tillering and kernel-number plasticity, increasing the mean grain yield by 20.5%. This increase was attributed primarily to an increased first-tiller emergence rate resulting from increased N uptake, leaf N content, and N remobilization from tillers to their grain. The second and third tillers, as transient sinks, contributed to the tiller survival rate, which depends on tiller leaf number. The increased total N uptake by SMNT also increased the dry mass yield of tillers and the C:N ratio, reducing the asymmetric competition between main stem and tillers. Owing to these beneficial effects, reduced mitogen-activated protein kinase (MAPK) and abscisic acid signals were observed under SMNT, whereas indole-3-acetic acid (IAA) signals and genes involved in DNA replication and mismatch repair were increased. These signals activated three critical transcription factors (the calmodulin-binding transcription activator, GRAS domain, and cysteine-2/histidine-2 family) and further increased rapid drought response and tiller maintenance after stem extension. Phenylpropanoid biosynthesis, sphingolipid biosynthesis, and galactose metabolism were most relevant to increased tillering under SMNT because of their critical role in drought response and lignin biosynthesis. Our results suggest that straw mulch-based no-tillage activates rapid drought response and improved wheat tillering by coordinating root N uptake, N remobilization, and asymmetric competition between main stem and tillers.

Genotype by environment interaction, correlation, AMMI, GGE biplot and cluster analysis for grain yield and other agronomic traits in sorghum (Sorghum bicolor L. Moench).

Genotype by environment (G×E) interaction is a major factor limiting the success of germplasm selection and identification of superior genotypes for use in plant breeding programs. Similar to the case in other crops, G×E complicates the improvement of sorghum, and hence it should be determined and used in decision-making programs. The present study aimed at assessing the G×E interaction, and the correlation between traits for superior sorghum genotypes. Three hundred twenty sorghum landraces and four improved varieties were used in alpha lattice experimental design-based field trial across three environments (Melkassa, Mieso and Mehoni) in Ethiopia. Phenotypic data were collected for days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT) and grain yield (GY). The results revealed that the variance due to genotype, environment and G×E interaction were highly significant (P < 0.001) for all traits. GY and PAWT were highly affected by environments and G×E whereas DTF, PALH, PAWD and PH were mainly affected by genotypic variation. Therefore, multi-environment testing is needed for taking care of G × E interaction to identify high yielding and stable sorghum landraces. GY and PAWT revealed highly significant positive correlations indicating the possibility of effective selection of the two traits simultaneously. Among the studied populations, South Wello, West Hararghe and Shewa zones had highly diverse genotypes that were distributed across all clusters. Hence, these areas can be considered as hotspots for identifying divergent sorghum landraces that could be used in breeding programs. Melkassa was the most representative environment whereas Mieso was the most discriminating. Five genotypes (G148, G123, G110, G203 and G73) were identified as superior across the test environments for grain yield with farmer-preferred trait, such as plant height. The identified stable and high yielding genotypes are valuable genetic resources that should be used in sorghum breeding programs.

Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature

Recent predictions on climate change indicate that high temperature episodes are expected to impact rice production and productivity worldwide. The present investigation was undertaken to assess the yield stability of 72 rice hybrids and their parental lines across three temperature regimes over two consecutive dry seasons using the additive main effect and multiplicative interaction (AMMI), genotype and genotype × environment interaction (GGE) stability model analysis. The combined ANOVA revealed that genotype × environment interaction (GEI) were significant due to the linear component for most of the traits studied. The AMMI and GGE biplot explained 57.2% and 69% of the observed genotypic variation for grain yield, respectively. Spikelet fertility was the most affected yield contributing trait and in contrast, plant height and tiller numbers were the least affected traits. In case of spikelet fertility, grain yield and other yield contributing traits, male parent contributed towards heat tolerance of the hybrids compared to the female parent. The parental lines G74 (IR58025B), G83 (IR40750R), G85 (C20R) and hybrids [G21 (IR58025A × KMR3); G3 (APMS6A × KMR3); G57 (IR68897A × KMR3) and G41 (IR79156A × RPHR1005)] were the most stable across the environments for grain yield. They can be considered as potential genotypes for cultivation under high temperature stress after evaluating under multi location trials.

Performance and Stability of some bread wheat genotypes under heat stress conditions in new land at middle and upper Egypt

This study aimed to assess the heat tolerance of twelve bread wheat genotypes under eight different environments. Wheat genotypes were sown in two locations (Tomas, Luxor governorate, representing Upper Egypt and Alfashn in Bani Suef governorate, representing Middle Egypt) at two planting dates 25th November (recommended) and 25th December (late) during two seasons of 2018/2019 and 2019/2020. The experiment was grown in a randomized complete block design with three replications in each environment. The combined analysis of variance showed that number of spikes/m2, number of kernels/spike, 1000-kernel weight and grain yield were significantly affected by locations, and planting dates. Parameters of phenotypic stability indicated that wheat genotypes Misr2 and Giza171 were highly adapted to recommended environments for grain yield (ton/ha) in Luxor and Bani-Suef governorates, respectively. Whereas, Misr2 and Giza168 could be grown under heat stress environments for grain yield (ton/ha) in Luxor and Bani-Suef governorates, respectively. According to GE biplot and ASV, the most desired and stable genotypes were Shandaweel 1, Line#2, Sids 14 for number of spikes/m²; Misr 2, Sids 14 ,Giza 171 for number of kernels/spike; Line#2, Shandaweel1, Misr 2, Giza 168, Giza 171 for 1000-kernel weight and Line#1, Giza168, Sids12 and Misr2 for grain yield (ton/ha).

Combining Genetic and Multidimensional Analyses to Identify Interpretive Traits Related to Water Shortage Tolerance as an Indirect Selection Tool for Detecting Genotypes of Drought Tolerance in Wheat Breeding.

Water shortages have direct adverse effects on wheat productivity and growth worldwide, vertically and horizontally. Productivity may be promoted using water shortage-tolerant wheat genotypes. High-throughput tools have supported plant breeders in increasing the rate of stability of the genetic gain of interpretive traits for wheat productivity through multidimensional technical methods. We used 27 agrophysiological interpretive traits for grain yield (GY) of 25 bread wheat genotypes under water shortage stress conditions for two seasons. Genetic parameters and multidimensional analyses were used to identify genetic and phenotypic variations of the wheat genotypes used, combining these strategies effectively to achieve a balance. Considerable high genotypic variations were observed for 27 traits. Eleven interpretive traits related to GY had combined high heritability (h2 > 60%) and genetic gain (>20%), compared to GY, which showed moderate values both for heritability (57.60%) and genetic gain (16.89%). It was determined that six out of eleven traits (dry leaf weight (DLW), canopy temperature (CT), relative water content (RWC), flag leaf area (FLA), green leaves area (GLA) and leaf area index (LAI)) loaded the highest onto PC1 and PC2 (with scores of >0.27), and five of them had a positive trend with GY, while the CT trait had a negative correlation determined by principal component analysis (PCA). Genetic parameters and multidimensional analyses (PCA, stepwise regression, and path coefficient) showed that CT, RWC, GLA, and LAI were the most important interpretive traits for GY. Selection based on these four interpretive traits might improve genetic gain for GY in environments that are vulnerable to water shortages. The membership index and clustering analysis based on these four traits were significantly correlated, with some deviation, and classified genotypes into five groups. Highly tolerant, tolerant, intermediate, sensitive and highly sensitive clusters represented six, eight, two, three and six genotypes, respectively. The conclusions drawn from the membership index and clustering analysis, signifying that there were clear separations between the water shortage tolerance groups, were confirmed through discriminant analysis. MANOVA indicated that there were considerable variations between the five water shortage tolerance groups. The tolerated genotypes (DHL02, DHL30, DHL26, Misr1, Pavone-76 and DHL08) can be recommended as interesting new genetic sources for water shortage-tolerant wheat breeding programs.

Elucidation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield of Rice (Oryza sativa L.) Varieties in Bangladesh Rainfed Condition

The research was evaluated in seven ecological zones throughout the country following randomized complete block design with three replications in each location. The combined analysis of variance for grain yield indicated that the differences among all sources of variation were highly significant (P&lt;0.01). Environment (E), Genotype (G) and G × E interaction effects explained by 25.54%, 17.02% and 48.97% for inbred and 35.26%, 17.03%, 31.23% for hybrid of the total sum of square, respectively. Locations E2 (Chattogram); E3 (Dhaka) for inbred and E2 (Chattogram); E4 (Khulna); E5 (Rajshahi); E7 (Sylhet) for hybrid varieties were found most discriminating and more informative among all. Ideal environment was found in E6 (Rangpur) for inbred and E4 (Khulna) for hybrid varieties. According to GGE mean and stability biplot, the most stable genotypes were G18 (BRRI dhan34); G26 (BRRI dhan52); G28 (BRRI dhan57); G19 (BRRI dhan37); G13 (BR25); G27 (BRRI dhan56); G21 (BRRI dhan39) for inbred and G2 (BADC hybrid dhan-2); G4 (BADC hybrid dhan-6); G5 (Bayer hybrid dhan-4) for hybrid compared to the other genotypes. The ideal genotypes were found G18 (BRRI dhan34) for inbred and G26 (BRRI hybrid dhan6) for hybrid varieties. In summary, we identified stable genotypes adapted across the environments for grain yield. These genotypes can be used as commercial cultivation with sustainable production as well as a parent/pre-breeding material in future rice breeding program.&#x0D; Bangladesh Rice J. 24 (1): 59-71, 2020

Characterization of Agronomical and Quality Traits of Winter Wheat (Triticum aestivum L.) for Fusarium Head Blight Pressure in Different Environments

For food security, it is essential to identify stable, high-yielding wheat varieties with lower disease severity. This is particularly important due to climate change, which results in pressure due to the increasing occurrence of Fusarium head blight (FHB). The objective of this study was to evaluate the stability of winter wheat (Triticum aestivum L.) grain yield under different environmental conditions. Twenty-five winter wheat varieties were evaluated under two treatments (naturally-disease infected (T1) and FHB artificial stress (T2)) during two growing seasons (2018–2019 to 2019–2020) in Osijek and in 2019–2020 in Tovarnik. The interaction between varieties and different environments for grain yield was described using the additive main-effects and multiplicative interaction (AMMI) effects model. The Kraljica and Fifi varieties were located near the origin of the biplot, thus indicating non-sensitivity to different environmental conditions. Principal component analysis (PCA) was used to understand the trait and environmental relationships. PC1 alone contributed 42.5% of the total variation, which was mainly due to grain yield, 1000 kernel weight and test weight in that respective order. PC2 contributed 21.1% of the total variation mainly through the total sedimentation value, test weight, wet gluten and protein content ratio (VG/P) and wet gluten content, in descending order.

Exploration of Grain Yield Stability of Advanced Chickpea Strains Across Environments

| Exploration of yield stability and defining the adaptation domains of advance strains is highly imperative for crop genetic improvement programs. The research aimed to determine the yield stability of sixteen advance chickpea strains was carried out at eleven diversified locations across the Punjab province of Pakistan during cropping season 2019-20. GGE biplot and mega environment analysis were employed to identify the most stable and high yielding chickpea advance strains. GGE biplot among PC1 and PC2 illustrated that G-10 (K-15019) was ideal genotype performing best across the environments. Higher yield potential coupled with more yield stability across all test environments was recorded in G-10 (K-15019) followed by G-2 (CH47/12), G-12 (K-15001), G-15(CH66/10) and G-16(CH53/12). Mega environment analysis revealed that E8 (Adaptive Research Farm, Karor) and E2 (Nuclear Institute for Agriculture and Biology, Faisalabad) were most discriminating environments for grain yield and most useful for screening of genotypes. Result for yield stability indicated that G-10 (K-15019), G-2 (CH47/12), G-12 (K-15001), G-15 (CH66/10) and G-16 (CH53/12) were higher yielding and more stable across environments, therefore these genotypes may be utilized in chickpea breeding program for development of widely adapted chickpea cultivars. Moreover, G-10 (K-15019) identified as ideal genotype in terms of stability and yield potential may be released as commercial variety for general cultivation in future.

Agronomic Performance and Genotype × Moisture Conditions Interaction for Morpho-Physiological Traits in Durum Wheat

Fourteen promising durum wheat lines, representing the elite durum germplasm for rainfed conditions, along with three check cultivars were assessed under drought and irrigated conditions for three growing seasons. The main objectives were to (i) evaluate the agronomic performance of durum wheat genotypes under different moisture stress conditions (mild, moderate, severe) and (ii) investigate the traits significantly contributing to drought tolerance. Combined ANOVA across environments for grain yield and the traits studied showed significant differences (P < 0.01) for genotype, year, moisture condition, year × moisture condition, genotype × year, and genotype × moisture condition interactions. There were differences in trait associations across the years and moisture conditions showing that the traits were significantly affected by the year and moisture conditions effects. Heading date, plant height, spike length and SPAD-reading with low ratio of σ2ge/σ2g showed a high value for heritability. Genotypes showed specific adaptation to different environmental condition as supported by significant (P < 0.01) for genotype × moisture condition interaction. Heading date, peduncle extrusion, plant height, days to maturity and 1000-kernel weight with lower genotype × moisture interaction than grain yield, were the traits contributing the most to drought tolerance. It is concluded that these traits could aid in the selection of durum wheat subject to moderate and severe stress, particularly in early generations. Under severe water stress condition, earliness to heading was an important drought escape mechanism, but inherent drought tolerance could be inferred from responses of a few genotypes. To determine effects of GE interaction on grain yield, data were subjected to GGE biplot analysis, which identified breeding lines G16, G12, G15 and G10 as the most stable and high yielding genotypes across different moisture stress conditions that can be used in convergent durum breeding program to develop drought tolerant varieties. The breeding lines which out-yielded the check cultivars are the stand out as the best promising germplasm but present different sets of favorable traits under stressed or favorable conditions.

Mean performance and stability parameters for comparing bread wheat cultivars under different environmental conditions

The present study was conducted to selecting wheat stable cultivars with high productivity across various environments using the models of Eberhart & Russell (1966) and Tai (1971). Fife wheat cultivars viz, Shandwell 1, Sids 1, Sids 12, Giza 168 and Misr 2 were grown in a randomized complete block design with four replications under sixteen environmental conditions (2 years x 2 locations x 4 sowing dates) on yield and yield components during two successive seasons of 2017/2018 and 2018/2019. Pooled analysis of variance for grain yield and its components revealed significant variance due to genotypes, environments, and their interactions, indicating that they varied in their responses to diverse environments. Highest significant grain yield across varied environments was found by Sids 12 (14.60 ardab/feddan) followed by Shandwell 1 (13.61 ardab/feddan). The results indicated that according to Eberhart & Russell and Tai, the cultivar Shandwell 1 was genetically stable across various environments because it showed high mean performance for grain yield over these environments when compared with grand mean beside acceptable stability parameters (bi near to one, S2di non-significant, α stability value not significantly differed from zero and the λ statistic was not significantly differed from one, also it appeared stable over environments for other traits according to both previous methods. Meanwhile, cultivar Sids 12 were stable over all the studied environments for grain yield, but only according to Eberhart & Russell method.

Delineation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield in Mungbean

In the present study, fifty-two mungbean (Vigna radiata) genotypes were evaluated for seven morphological traits at three different environments in South Indian state Tamil Nadu, namely Virinjipuram (E1), Eachangkottai (E2), and Bhavanisagar (E3) during Kharif 2017, 2018, and 2019, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variablility was observed among the genotypes for the following traits viz., plant height, days to fifty per cent flowering, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and grain yield. Correlation analysis showed that the trait number of pods per plant was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (61.07%). GGE biplot showed E3 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., EC 396111 for E1, EC 396125 for E2 and EC 396101 for E3 environments. The genotypes with minimum genotype stability index (GSI) viz., V2802BG (7), HG 22 (13), and EC 396098 (13) were observed with wide adaptation and high yields across all the three environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/pre-breeding materials in future mungbean breeding programs.