Aug 2026· Agricultural Science Digest - A Research Journal· 0 citations· 24 references
Abstract
Background: To increase area and production of greengram, breeders must develop high yielding, stable and adaptable varieties. This study aims to identify such superior greengram genotypes that perform consistently well across different locations. Methods: The experiment was carried out during Kharif, 2023 in six locations at different Agricultural Research Stations of Telangana state. A total of 15 genotypes were evaluated in RBD with three replications. The data on seed yield was subjected to statistical analysis. The G×E interaction was studied as per Eberhart and Russel model, AMMI, GGE biplot and WAAS model analysis. Result: Regression analysis revealed that genotypes MGG-385 and MGG-573 considered as stable. AMMI analysis of variance indicated that genotypes contributed 13.1% followed by environment (55.4%) and G×E interaction (20.48%). With further examination of GGE using AMMI analysis, two significant principal components were separated explaining 69.7% of variance interaction (PCI-42% and PC2-27.7%). The results of AMMI 1 and 2 biplot analysis, the genotypes MGG-385 and MGG-295 were considered as stable with high mean seed yield and recorded nearly zero IPCA1 score. The environments of Madhira and Tandur had recorded the lowest IPCA1 scores had less interaction effects. AMMI stability value and stability indexes were indicated MGG-385 was more stable. Y×WAAS graph revealed the genotypes VBN-4, MGG-570, MGG-571 were unstable had high seed yield, while the environments Palem, Tornala and Warangal provided high seed yield and presented good discrimination ability as had recorded high WAAS values. The genotypes MGG-573, MGG-556, MGG-385 and MGG-564 were broadly adopted. Based on all the stability models, the genotype MGG-385 was considered as stable with high mean seed yield across locations.
The experimental study was conducted using 83 greengram genotypes during the rabi season (November, 2023 to February, 2024) at the Regional Agricultural Research Station (RARS), Lam, Guntur, Andhra Pradesh, India to study the yield-related traits and employed an integrated analytical framework comprising path coefficient analysis, principal component analysis (PCA), and hierarchical cluster analysis with heatmap visualization. Path coefficient analysis revealed that pods plant-1 and days to maturity exerted a direct effect on the yield trait, indicating that these traits played a crucial role in influencing seed yield. In total, seven principal components were extracted, of which the first three PCs exhibited greater than 1 and collectively accounted for approximately 82.37% of total variability, suggesting that a substantial proportion of genetic diversity was captured within these components. The 83 genotypes were classified into 4 groups through hierarchical clustering. Group III comprised the largest number of genotypes (35), followed by Group I (25 genotypes) and Group II (21 genotypes), while Group IV contained only 2 genotypes. Additionally, a two-way clustered heatmap further elaborated on genotype-trait interactions and facilitated the identification of high-performing subsets for specific attributes. Genotypes belonging to group III demonstrated superior performance for pods plant-1 and seed yield plant-1 (g), while group I genotypes excelled in early maturity traits, making both groups promising candidates for targeted selection in future greengram improvement programmes.
V. V. Mokshith, V. Roja, N. Satyanarayana et al.· International Journal of Bio...· 0 citations
Black cumin is an annual spice crop valued for its nutritional, medicinal and economical importance. Although the Amhara Region of Ethiopia possesses suitable agroecological conditions for black cumin production, seed yield remains below the national average, largely due to the limited availability of improved varieties. This study was conducted to evaluate the agronomic performance, genotype x environment interaction (GEI) and seed yield stability of promising black cumin genotypes. Multi-environment trials were carried out at three locations during the 2021 and 2022 main cropping using a randomized complete block design with three replications. Eighteen advanced genotypes and two standard check varieties were evaluated. Combined analysis of variance revealed significant differences among genotypes, environments, and genotype x environment interactions for all measured traits. Genotypes Moyale-230777 (G12), Achefer-9068 (G2), and Gofazuria-90517 (G7) exhibited the highest mean seed yields of 647.6 kg ha-1, 647.1 kg ha-1, and 623.9 kg ha-1, respectively. However, Achefer-9068 had lower oleoresin content. Moyale-230777(G12) and Gofazuria-90517 (G7) showed yield advantages of 17.8% and 26.8%, respectively, over the standard check varieties Dershaye and Aden. The genotype with environment interaction in the seed yield data of six environments (location and year combinations) was analyzed using AMMI and GGE biplot models. The result showed that environment had the greatest effect (53.0%) followed by GEI (32.2%) and genotype (14.9%). Based on AMMI, AMMI stability value (ASV), yield stability index, oleoresin content, and GGE biplot analysis G12 and G7 ranked the 1st and 2nd the genotypes for their yield performance, quality, identifying top performing genotypes with wide adaptability across the testing environments. Consequently, these genotypes were selected for on-farm verification, and accession number Moyale-230777 (G 12) has been released for commercial production in 2024 under the name “Tena”. Therefore, variety Tena is recommended for demonstration, scaling-up and commercial cultivation in the spice growing of Amhara Region and other similar agroecological zones.
BACKGROUND
The purpose of this study was to examine how year, genotype, and their interaction affect agromorpho/phenological and quality variables in a population of 15 newly created doubled-haploid winter camelina lines. The study was conducted in the field using a split-plot design with three replications over the course of three consecutive years (2022-2024). Moreover, the research unveils two novel stability indices, namely: ASP1 and ASP2, marking a significant advancement in the field of agronomy and plant breeding.
RESULTS
The findings showed that genotype (all factors except plant height and seeds per pod) and years (all traits) had a substantial impact on phenological, thousand-seed weight, and seed yield. The first three genotypes with the greatest concentrations of glucosinolate were line 15, Soheil variety and line 2 (in 2023 and 2024). In three years, line 7 demonstrated an early flowering genotype, while lines e.g. 8 and 14 demonstrated early ripening in every year. Days to ripening, seed yield, days to flowering and oil content, showed a gradual first IPCA score explained in a range of 79.3 to 98.3% of the variation in the interaction effect, respectively, according to the AMMI analysis. According to the ASI stability index, the best genotypes were lines 10 (for days to flowering), 9 (for days to ripening ), 5 (for seed yield), and 12 (for oil). Additionally, lines 4 and 11 were demonstrated to be the stable and high-yielding genotypes based on the two new AMMI-based indices that are currently available: ASP (AMMI Stability Parameter)1 and ASP2.
CONCLUSIONS
This research successfully identified the most effective and stable camelina lines applying the AMMI procedure, highlighting their potential for breeding advancement. The findings showed also that the ASP1 and ASP2 indices were proactive in evaluating genotype stability and that there was enough genetic variation in the current population to be used in camelina genetic mapping or hybrid breeding projects.
Fariborz Noormohammadi, A. Arminian, Hossein Rostami Ahmadvandi et al.· BMC Plant Biology· 0 citations
Genotype × environment interaction is an important consideration in groundnut improvement because yield and related traits are strongly influenced by environmental conditions. The present study evaluated the stability and adaptability of 74 groundnut genotypes, including four standard checks, across six environments during the Kharif seasons of 2023 and 2024. The environments represented three locations: CTAE Instructional Farm, Udaipur; KVK, Rajsamand; and KVK, Chittorgarh. The experiment was conducted in an augmented block design, and observations were recorded for days to 50 per cent flowering, number of branches per plant, dry pod yield per plant, kernel yield per plant, and 100-seed weight. Stability analysis was performed using the Eberhart and Russell model based on mean performance, regression coefficient, and deviation from regression. Pooled analysis of variance showed significant effects of genotype, environment, and genotype × environment interaction for all studied traits, indicating differential responses of genotypes across environments. Several genotypes showed desirable mean performance and adaptation for yield-related traits. Based on dry pod yield, kernel yield, and associated stability parameters, PI-614, PI-1362, PI-1660, PI-1989, PI-2124, PI-2311, PI-2452, PI-2506, PI-2571, PI-2749, PI-1473, PI-1530, PI-1918, PI-2344, PI-2544, and PI-3132 were identified as promising genotypes. These genotypes may be useful in breeding programmes aimed at improving yield performance and adaptability in groundnut, subject to further validation across additional environments.
Sarita Choudhary, P. Singh, R. B. Dubey et al.· Journal of Advances in Biolo...· 0 citations
This study was designed to analyze the stability of thirty genotypes of Taramira (Eruca sativa Mill.) and was evaluated over four environments during Rabi 2022–23 at Experimental Farm, Sri Karan Narendra College of Agriculture, Jobner, Rajasthan for various yield and yield attributing traits. Yield stability was analysed employing Eberhart and Russell’s model, which revealed significant differences among genotypes x environments (linear) for most of the characters except siliqua length and 1000-seed weight. Environment + (G x E) was significant for most of the characters except siliqua length and pooled deviation was also significant for all the traits except for maturity, primary branches per plant, siliqua length and seeds per siliqua. Stability parameters for seed yield revealed that the genotypes viz., RTM-1351, RTM-1591 and RTM-1829 were identified as the most acceptable and consistent performers for seed yield per plant. Whereas RTM-314, RTM-1613 and RTM-1822 were showed non-significant deviations coupled with bi values higher than unity (bi>1), indicating that they were specifically suited for a better environment with good management. The identified stable and superior genotypes may serve as valuable genetic resources for selection and hybridization. Further, these genotypes can be tested in multi-location trials for wider adaptability and potential varietal release.
Sukhjot Singh, Manohar Ram, M. K. Meena et al.· Electronic Journal of Plant...· 0 citations
Vetch, a highly valued herbaceous legume for livestock, was studied in Northern Ethiopia from 2021 to 2023 to analyze genotype by environment interaction (GEI) in multi-environment trials (MET) and identify adaptable vetch genotypes. Combined analysis of variance (ANOVA), AMMI ANOVA and Eberhart and Russell regression for forage yield were analyzed. GGE, AMMI1 and AMMI2 bi-plots for forage yield of vetch genotypes were created. Principal Component Analysis (PCA) and correlation network plots were created, along with the analysis of multi-trait stability index (MTSI) for agronomic traits. AMMI stability measures, Best Linear Unbiased Prediction (BLUP) based indexes; parametric and non-parametric statistics were computed using R-statistical software. AMMI ANOVA revealed significant effects of genotype (G) (28.35% SS), environment (E) (30.29% SS), and GEI (17.48% SS) for the dry matter yield. The likelihood ratio test (LRT) revealed significant genotypic effects for all agronomic traits except days to emergence and survival rate, while the LRT for GEI was significant for all traits except the number of branches. AMMI and GGE bi-plots selected G3 and G4 as the most adaptable genotypes. Stability parameters: ASTAB, ASI, ASV, AVAMGE, DA, FA, Shukla, Ecovalence, Wi_u, Pi_u, S2 N3, and MASI identified G4 and G1 as the most stability genotypes. SIPC, DZ, EV, MASV, Wi_g, HMGV, S3, S6, R2 and ZA ranked G4 and G3 as most stable genotypes. HMRPGV, HPGV, WAAS, WAASB, Wi_f, Pi_a, Pi_f and GAI also ranked G3 and G4 most stable genotypes. The average rank sum (ARS) of the stability statistics groups was considered. AMMI-based stability statistics identified G4 and G1 as the top two stable. The WAAS index, BLUP-based, and non-parametric statistics identified G3 and G4 as the most stable genotypes. In contrast, parametric statistics ranked G4 first and both G1 and G3 second in stability. Overall, G4 and G3 were identified as the most stable genotypes. The MTSI also selected G4 (MTSI = 1.65) and G3 (MTSI = 1.79), are recommended for further verification and demonstration before being recommended for wider forage production in Tigray.
S. Markos, K. Gebremeskel, S. Gebreyowhans et al.· Discover Agriculture· 0 citations
