Response of tropical maize inbred lines to maize streak virus and major agronomic traits

Integrating Multiple Disease-Related Traits Improves Phenotypic Stratification of Corn Stunt Tolerance in Tropical Maize

Corn stunt is one of the most important diseases affecting maize (Zea mays L.) production in tropical regions of the Americas. The disease is caused by a complex of pathogens transmitted by the corn leafhopper (Dalbulus maidis), and its predominantly quantitative inheritance complicates the identification of tolerant genotypes under field conditions. In this context, we aimed to perform a comprehensive phenotypic stratification of corn stunt tolerance in a tropical public maize diversity panel and to identify contrasting inbred lines for breeding and genetic studies. A total of 360 inbred lines were evaluated under natural infection using three complementary disease-response traits: survivor plant health score (SPHS), proportion of survivor plants (PSP), and whole-plant health score (WPHS). Multi-trait mixed-model analyses revealed significant genotypic variation, moderate to high broad-sense heritability, and significant genotype × environment interactions for all evaluated traits. A multi-trait index (MSI), calculated from standardized best linear unbiased predictions (BLUPs), successfully integrated the three phenotypic components and enabled robust stratification of the diversity panel, identifying 60 highly tolerant and 60 highly susceptible inbred lines. Further, a genomic principal component analysis demonstrated that these phenotypic extremes were distributed across both tropical and subtropical germplasm, indicating that tolerance is not restricted to a single genetic background. The proposed phenotypic framework provides a robust and reproducible strategy for characterizing quantitative disease tolerance, identifying valuable parental germplasm, and establishing well-defined phenotypic extremes for future investigations of the genetic architecture of corn stunt tolerance.

The genetic architecture of maize yellow mosaic virus resistance in corn

The results indicate that the genetic architecture of corn in response to MaYMV is complex, and that developing immune cultivars may not be achievable using natural sources of genetic variation, but this study provides a foundation for breeding maize with improved tolerance and advances the understanding of host response to MaYMV infection.

Evaluation of Rice yellow mottle virus Resistance and its Impact on Agronomic Performance in Aromatic Rice Lines

Rice yellow mottle virus (RYMV) is one of the most destructive viral diseases limiting rice production in Africa. Identifying genotypes that combine resistance with superior agronomic performance is essential for developing improved cultivars. This study evaluated 61 aromatic rice lines and three reference genotypes differing in RYMV resistance under greenhouse conditions using healthy and mechanically inoculated plants. Agronomic and disease-related traits were analysed by two-way analysis of variance (ANOVA), principal component analysis (PCA), hierarchical clustering on principal components (HCPC), and the Multi-trait Genotype–Ideotype Distance Index (MGIDI). RYMV infection significantly affected all measured traits (P < 0.001), reducing grain yield (65.3%), above-ground biomass (23.6%), plant height (13.6%), panicle length (11.2%), panicle number (13.3%), and thousand-grain weight (16.2%), while increasing spikelet sterility by 208.0%. Significant genotype × health interactions revealed contrasting responses among genotypes. PCA explained 59.0% of the total phenotypic variation and showed that yield-related traits were negatively associated with spikelet sterility and disease severity. HCPC grouped the genotypes into four distinct clusters according to their agronomic performance and disease response. MGIDI identified ten superior genotypes (Remar2, Remar4, Remar11, Remar13, Remar28, RemarGT, K20-26, K20-Germ13, Basmati370, and the highly resistant control TOG5681) that combined high yield potential with reduced disease impact. These genotypes constitute valuable genetic resources for breeding high-yielding, RYMV-resistant aromatic rice cultivars.

Targeted Genome-Wide Association of Streak Virus Severity and Nutrition in Biofortified Maize

Multivariate Analysis in Maize (Zea mays L.) Inbred Lines

Maize (Zea mays L.) is a leading cereal crop whose genetic improvement depends largely on the availability of diverse and divergent parents. The present investigation was undertaken to assess the mean performance and to quantify the genetic divergence among thirty maize inbred lines for sixteen quantitative characters. The experiment was conducted during the Kharif season of 2023–24 at the Research Farm of the Faculty of Agriculture Science and Technology, AKS University, Satna (M.P.), India, using a randomised complete block design with three replications. Analysis of variance revealed highly significant differences among the genotypes for all sixteen characters, and wide ranges were recorded, particularly for grain yield per plant (108.69–223.99 g), flag leaf length and shelling percentage, indicating the presence of substantial genetic variability. Genetic divergence was estimated using Mahalanobis’ D² statistic, and the genotypes were grouped into four clusters by the non-hierarchical Euclidean clustering method. Clusters I and IV were the largest, each comprising ten genotypes, whereas Clusters II and III contained five genotypes each. The maximum inter-cluster distance was observed between Clusters II and III (55.18) and the minimum between Clusters I and IV (22.00). Cluster I recorded the highest mean grain yield per plant, Cluster II the tallest plants and highest test weight, and Cluster IV the highest shelling percentage with the earliest flowering, although the clusters differed only modestly in mean performance for most yield components. The genotypes HKL-163, AMI-106 and AMI-118 emerged as the most promising parents. Hybridisation between genotypes drawn from the divergent Clusters II and III is suggested for exploiting heterosis and recovering desirable transgressive segregants in maize.

Agronomic Evaluation and MGDI-Based Multi-Trait Selection of S4 Sweet Corn Inbred Lines

Sweet corn is a high-value commodity whose productivity can be improved through hybrid variety development. The development of superior hybrids depends on establishing inbred lines with superior agronomic performance and broad phenotypic variability as the basis for parental selection. This study aimed to evaluate agronomic traits and phenotypic variability, analyze correlations among traits, perform principal component analysis (PCA), and apply the Multi-Trait Genotype–Ideotype Distance Index (MGIDI) for multi-trait selection in S4 sweet corn inbred lines. The experiment was conducted at the Experimental Farm of Universitas Andalas from January to April 2025. An Augmented II design consisting of two blocks was used with 36 S4 inbred lines, comprising 33 test lines and 3 check lines. Results revealed wide phenotypic variability for most agronomic traits, except ear diameter and total soluble solids. Yield exhibited positive correlations with plant height, ear length, and ear diameter, but negative correlations with flowering and harvest traits. In contrast, total soluble solids were not significantly correlated with the other agronomic traits. Principal component analysis (PCA) showed that most agronomic traits contributed to the variation among inbred lines, whereas total soluble solids had a relatively small contribution. Based on multi-trait selection using MGIDI, seven inbred lines, i.e. CD3, MM1, AG2, PN1, CD2, IN2, and SL1, were identified as the closest to the ideotype. These lines have the potential to be prioritized as parental lines and should be further evaluated in the S5 generation and subjected to combining-ability evaluations in hybrid sweet corn breeding.