Maize is a valuable crop with high genetic variability, and understanding this variability is essential for improving crop productivity and resilience to environmental stressors. This study evaluated the genetic variability and heritability of yield and yield-related traits among 27 drought-tolerant maize genotypes in a humid climate region of Southwestern Nigeria. The experiments followed rigorous agronomic, soil, and climatic requirements for maize cultivation. Our findings revealed significant genetic variability among the traits of the maize genotypes, particularly in the number of ears per plant, which had the highest genetic advancement as a percentage of the mean (68.25 % and 67.83 %) under both well-watered and drought conditions, respectively. This suggests that breeding programs targeting this trait could significantly improve maize productivity and resilience to drought stress. Additionally, most of the agronomic traits targeted were highly heritable with heritability values ranging from 0.76 to 0.99 under both environments where the genotypes were evaluated, thus indicating that selective breeding for these traits could lead to consistent improvements in maize yields over time. Overall, this study highlights the importance of evaluating yield-related traits’ genetic variability and heritability in maize breeding programs. Findings suggest that targeting the number of ears per plant in drought-tolerant maize genotypes as revealed in the study could be an effective approach for improving crop productivity and resilience in regions with variable moisture regimes.

Whitefly Bemisia tabaci (Gennadium, Hemiptera) causes severe damage to cassava plants through excessive feeding on leaves and transmitting viruses, such as African cassava mosaic virus (ACMV), East African cassava mosaic virus (EACMV), and ipomoviruses that cause cassava brown streak disease. Currently, little is known about the molecular diversity and distribution of whitefly species in the major cassava-growing zones of Nigeria. This study aimed to address the knowledge gap by assessing the genetic diversity, distribution, and associated cassava mosaic begomoviruses (CMBs) in whiteflies across South West and North Central, Nigeria. Whitefly samples were systematically collected from cassava plants during georeferenced epidemiological surveys in 2017, 2020, and 2022. The samples were genotyped using the mitochondrial cytochrome oxidase I (mtCOI) marker, and CMBs were detected by PCR with virus-specific primers. Phylogenetic analyses revealed four distinct genetic groups of B. tabaci: Sub-Saharan Africa 1 (SSA1; 84.8%), SSA2 (1.4%), SSA3 (13.1%), and Mediterranean (MED) (0.7%). The SSA1 group was the predominant and most widely distributed genotype across the surveyed zones, with three subgroups identified: SSA1-SG1, SSA1-SG3, and SSA1-SG5. The second most frequently identified genotype, SSA3, was restricted to the North Central zone, along with the SSA2 group, which was only identified in two North Central states (Niger and Plateau). African cassava mosaic virus (ACMV) was detected in SSA1-SG1, SSA1-SG5, and SSA3, whereas EACMV was found in only the SSA1-SG3. The findings of this study will aid in developing better whitefly management strategies to reduce the impact of CMD on cassava production in Nigeria.

The data presented here are agronomic indicators of cassava accessions collected during epidemiological surveys of cassava farms across South-West and North-Central Nigeria in 2021-2022. Cassava accessions were obtained from each farm surveyed and initially established in a randomized plot design at the WAVE Covenant University demonstration plot. Agronomic indicators were collected at 3-month intervals following the methods of (Fukuda et al., 2010) [1].

The whitefly vector remains a key factor in the continued prevalence of Cassava Mosaic Disease (CMD) and the threat of Cassava Brown Streak Disease (CBSD) to unaffected regions in Central and West Africa. Cross-border surveillance is critical because borders serve as the first entry point for pests and pathogens. This study identified the whitefly genotype groups prevalent in cassava-producing locations along the Nigeria–Cameroon border, and their associated Cassava mosaic begomovirus (CMB) strains. Mitochondrial cytochrome oxidase I (mtCOI) gene sequencing (97 sequences), sequence alignment, and phylogenetic analysis revealed several Bemisia tabaci (Gennadius) genotypes alongside Bemisia afer (Priesner & Hosny). B. tabaci sub-Saharan Africa 1-subgroup 1 (SSA1-SG1), SSA2, SSA3, and Mediterranean (MED) genotypes were recorded in Nigeria and Cameroon. MED and SSA3 genotypes were predominant in the North–East and South–South regions of Nigeria, respectively, while SSA2 and SSA3 were the predominant genotypes on the corresponding side of the Cameroon border. CMB-specific PCR amplification revealed the presence of African cassava mosaic virus (ACMV) and East African cassava mosaic virus (EACMV) in several B. tabaci genotypes and in B. afer. These findings demonstrate a distinct vector distribution pattern across the Nigeria–Cameroon border and emphasize the need for continued cross-border cassava virus surveillance.

Understanding the genetic variability among Nigerian cassava accessions is a crucial prerequisite for its improvement. The objective of this study was to estimate the genetic variability among 477 cassava accessions and to classify them based on their genetic similarities for effective utilization in breeding programs. The accessions were evaluated at the Federal University of Agriculture, Abeokuta experimental site from 2023–2024, using an augmented randomized complete block design with two checks (TME 419 and NR 87184). Agromorphological descriptors were collected at 3-month intervals for 12 months. Broad sense heritability and genetic advance as percent of mean (GAM) were high, indicating that the overall phenotypic expressions observed were largely influenced by genetic factors. Multiple correspondence analysis (MCA) showed that petiole color, number of leaf lobes, color of leaf veins, and parenchyma contributed the most to the overall variability observed in the study population. Principal component analysis (PCA) identified petiole length, length of leaf lobe, width of leaf lobe, and plant height as primary contributors to the overall phenotypic variations observed in the population. Hierarchical clustering of accessions using Euclidean distance revealed two and three clusters based on qualitative and quantitative traits respectively. This study has shown the existence of wide genetic variations in several cassava traits, providing a valuable resource for breeding programs.