ABSTRACT
The dataset focuses on evaluating the performance of 17 sweet potato varieties (G) released by the Bangladesh Agricultural Research Institute (BARI) in terms of storage root yield and stability across five locations (E) in Bangladesh-Gazipur, Bogura, Jamalpur, Jashore, and Chattogram. The result revealed that BARI Mistialu-12 exhibited the highest average storage root yield at 45.35 t/ha, closely followed by BARI Mistialu-16 at 44.64 t/ha. Conversely, BARI Mistialu-1 had the lowest mean yield of 25.99 t/ha. Among the locations, Bogura recorded the highest mean root yield at 37.05 t/ha, while Chattogram exhibited the lowest at 31.27 t/ha. A combined analysis of variance revealed the presence of variability in storage root yield attributed to the genotype-location (environment) interaction (GEI). To delve deeper into this interaction, additive and multiplicative interaction effect models (AMMI) along with a linear mixed model (LMM) were employed for further investigations to confirm the significant contribution of GEI variance to root yield. The LMM results showed genetic variance (%), heritability (%), selection accuracy (%), and GEI correlation coefficients of 52.27, 54, 94, and 30, respectively. The AMMI analysis indicated that the first two principal components accounted for 74.60 % of GEI, with 20.16 % attributed to it. Assessing significant Interaction Principal Component Analyses (IPCAs) through the Weighted Average of Absolute Scores (WAAS) indicated that BARI Mistialu-12 is the most stable genotype, followed by BARI Mistialu-16 and BARI Mistialu-8, all displaying above-average root yield. The mega-environment analysis associated the highest root production of BARI Mistialu-11 and BARI Mistialu-2 with the Jamalpur location, while Gazipur, Bogura, and Jashore were linked with the superior performance of BARI Mistialu-12 and BARI Mistialu-16 genotypes. These findings are crucial for future breeding programs and the rapidly growing sweet potato industry, given the stable high-yield potential across diverse agro-ecological conditions. However, it is imperative to repeat the study to ensure reliable outcomes.
ABSTRACT
The dataset primarily focused on selecting genotypes of sweet oranges based on their phenotypic performances. The dataset resulted significant variations in the best linear unbiased predictions (BLUPs) of 20 out of 21 traits, including leaves, flowers, fruits, and seeds. A strong positive correlation (r= 0.73 to 0.95) was observed among the majority of morphological traits. The sweet orange genotypes demonstrated considerable genetic variance, surpassing 65% for almost all traits, with a selection accuracy exceeding 92%. Using the multi-trait genotype-ideotype distance index (MGIDI), CS Jain-001 emerged as the top-ranked genotype, followed by BAU Malta-3 and CS Jain-002 in order of desirability. The broad sense heritability of selected traits was above 75.60%, and the selection gain reached a maximum of 12.60. These identified genotypes show promise as potential parent donors in breeding programs, leveraging their strengths and weaknesses to develop promising varieties in Bangladesh.
ABSTRACT
The dataset explores the impact of waterlogging stress on sesame plants during the pre-flowering stage, recognizing its global impact on crop yield and the identification of tolerant genotypes using the MGIDI index. Carried out in Bangladesh, the research assesses the survival status, grain yield, and stress tolerance indices of 40 sesame genotypes, revealing that twelve of them demonstrated resilience under 72 h of waterlogging stress at the pre-flowering stage. There were variations in genotypic grain yield, and G15 exhibited the highest yields, recording 5.22 g/plant under normal conditions and 4.10 g/plant under waterlogging stress. The MGIDI index, evaluating waterlogging tolerance, identified G4 as the most favorable genotype, followed by G5 and G12. Factor analysis within the MGIDI index uncovered distinct tolerance and susceptibility indices, highlighting strengths and weaknesses in the selected genotypes. The selection gain percentages of these genotypes ranged from 12.9 to 37.4, indicating high broad-sense heritability (≥0.97). These results underscore the potential of genotype selection based on waterlogging stress indices, providing valuable insights for breeders addressing stress-related crop challenges in the face of changing climatic conditions.
