Resumo em Inglês:

Abstract In wax gourd breeding, mature fruit cuticular wax is an important trait that contributes to preservation ability and commercial value. A previous study has shown that this trait is determined by a dominant allele linked to SNP markers on the BhWAX gene. Notably, a critical SNP at position #902 (relative to the start codon) features a T allele in waxy lines and a C allele in non-waxy lines. This study focuses on establishing a tetra-primer ARMS-PCR system to genotype this trait in various Vietnamese wax gourd landraces (4 varieties × 3 individuals, n = 12). The assay successfully identified homozygous T/T and heterozygous T/C genotypes in all 12 samples, consistent with sequencing results; however, the C/C genotype was absent due to the unavailability of corresponding landraces. The study provides an effective, low-cost molecular screening tool, offering strong support for wax gourd breeding programs, especially in laboratories with limited equipment.

Resumo em Inglês:

Abstract Accurate classification of wheat genotypes for adaptability and stability across diverse environments remains challenging in multi-environment trials. This study integrated mixed models, genotype plus genotype × environment interaction (GGE) biplot analysis, the Eberhart-Russell (ER) stability approach, and supervised machine learning to evaluate wheat genotype performance and improve ER-based classification. Seventy wheat genotypes were tested across 23 environments in Pakistan under the National Uniform Wheat Yield Trials (2023-2024). Genotype and environment effects were highly significant (p < 0.01), while genotype × environment interaction was significant (p < 0.05), confirming differential genotype responses. GGE biplot analysis identified interaction patterns, specific adaptation, and stable entries, whereas ER parameters classified genotypes into six stability classes. After SMOTE, PCA, and hyperparameter tuning, the optimized support vector machine achieved the best performance, with 94.4% accuracy and strong agreement with ER classes. This integrated framework supports the selection of stable, high-yielding wheat genotypes.

Resumo em Inglês:

Abstract Recurrent selection methods are most suitable for improving quantitative traits in plant breeding. This study estimated genetic parameters and assessed the genetic diversity of black common bean progenies from the fourth cycle of recurrent selection. Thirty-five S0:4 progenies and four cultivars were evaluated in a randomized complete block design with three replications across four environments. Grain yield (YIELD), 100-seed weight (100SW), and sieve yield (SY) were evaluated. Molecular characterization was performed using microsatellite markers. Statistical analyses included analysis of variance, genetic parameters, genetic divergence, and population structure. Different strategies were used to select progenies. The analysis of variance showed significant effects for genotypes and the genotype × environment interaction. Expected gains within the program’s potential were 6.01% for YIELD, 3.47% for 100SW, and 2.77% for SY. Molecular analysis indicated inconsistent clustering and lack of genetic structure. For progeny selection, the Mulamba and Mock index with economic weights achieved better gain.

Resumo em Inglês:

Abstract This study aimed to evaluate the General Combining Ability (GCA) and Specific Combining Ability (SCA) of soybean germplasm adapted to tropical regions. Ten soybean crosses from six tropical-adapted varieties were performed which revealed substantial genetic variability in seven agronomic traits. Genetic variance, heritability, and correlations for growth and yield-related traits were evaluated. In the F1 generation, high genetic variance was observed for plant height (PH) and number of pods per plant (NPPP), whereas broad-sense heritability was highest for PH (0.82) and 50-seed weight (50SW; 0.72). Number of seeds per plant (NSPP) was strongly influenced by environmental effects. Genetic correlations identified key yield predictors, especially between NPPP and NSPP (r = 0.93), and positive associations of PH with yield components. In F2, Semsa-107 and Huasteca-100 showed superior performance, while Cedrela × Semsa-107 and Cedrela × Huasteca-100 were the best hybrids. Combining ability analysis indicated additive effects in Cedrela, NK-12, and Semsa-107.

Resumo em Inglês:

Abstract GenomicLand is a free, open-source platform for genomic prediction and genome-wide association studies. Developed in R software using Shiny, it supports diploid and polyploid datasets and integrates statistical learning, Bayesian, machine learning, and neural network methods. GenomicLand provides an accessible environment for researchers, breeders, and students.