Enhancing genomic-based forward prediction accuracy in wheat by integrating UAV-derived hyperspectral and environmental data with machine learning under heat-stressed environments.

Integrating genomic, hyperspectral imaging (HSI), and environmental data enhances wheat yield predictions, with HSI providing detailed spectral insights for predicting complex grain yield (GY) traits. Incorporating HSI data with single nucleotide polymorphic markers (SNPs) resulted in a substantial improvement in predictive ability compared to the conventional genomic prediction models. Over the course of several years, the prediction ability varied due to diverse weather conditions.

Enhancing Genetic Gains in Grain Yield and Efficiency of Testing Sites of Early-Maturing Maize Hybrids under Contrasting Environments.

The major challenges of maize production and productivity in Sub-Saharan Africa (SSA) include infestation, recurrent drought, and low soil nitrogen (low N). This study assessed the following: (i) accelerated genetic advancements in grain yield and other measured traits of early-maturing maize hybrids, (ii) ideal test environments for selecting early-maturing multiple-stress tolerant hybrids, and (iii) high-yielding and stable hybrids across multiple-stress and non-stress environments. Fifty-four hybrids developed during three periods of genetic enhancement (2008-2010, 2011-2013, and 2014-2016) were evaluated in Nigeria, The Republic of Benin, and Ghana under multiple stressors ( infestation, managed drought, and Low N) and non-stress environments from 2017 to 2019.

Diallel analysis of soybean (Glycine max L.) for biomass yield and root characteristics under low phosphorus soil conditions in Western Ethiopia.

Combining ability studies under low soil P conditions provides useful information on the inheritance of important traits to improve soybean for low P tolerance. The study aimed at determining the combining ability and gene actions of biomass yield and root traits in soybean under low phosphorus conditions. Nine parental genotypes and their 36 half diallel F2/F3 progenies were evaluated at two locations in Ethiopia on soils of low P availability.

Mapping quantitative trait loci and predicting candidate genes for resistance in maize using resistance donor line derived from .

The parasitic weed, is a major biological constraint to cereal production in sub-Saharan Africa (SSA) and threatens food and nutrition security. Two hundred and twenty-three (223) F mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four -adaptive traits and genotyped using the Diversity Arrays Technology (DArT) to determine the genomic regions responsible for resistance in maize. After removing distorted SNP markers, a genetic linkage map was constructed using 1,918 DArTseq markers which covered 2092.

SysBiolPGWAS: simplifying post-GWAS analysis through the use of computational technologies and integration of diverse omics datasets.

Motivation: Post-genome-wide association studies (pGWAS) analysis is designed to decipher the functional consequences of significant single-nucleotide polymorphisms (SNPs) in the era of GWAS. This can be translated into research insights and clinical benefits such as the effectiveness of strategies for disease screening, treatment and prevention. However, the setup of pGWAS (pGWAS) tools can be quite complicated, and it mostly requires big data.

Genetic diversity and population structure of early and extra-early maturing maize germplasm adapted to sub-Saharan Africa.

Background: Assessment and effective utilization of genetic diversity in breeding programs is crucial for sustainable genetic improvement and rapid adaptation to changing breeding objectives. During the past two decades, the commercialization of the early and extra-early maturing cultivars has contributed to rapid expansion of maize into different agro-ecologies of sub-Saharan Africa (SSA) where maize has become an important component of the agricultural economy and played a vital role in food and nutritional security. The present study aimed at understanding the population structure and genetic variability among 439 early and extra-early maize inbred lines developed from three narrow-based and twenty-seven broad-based populations by the International Iinstitute of Tropical Agriculture Maize Improvement Program (IITA-MIP).

Mathematical modelling and optimal cost-effective control of COVID-19 transmission dynamics.

The novel coronavirus disease (COVID-19) caused by a new strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains the current global health challenge. In this paper, an epidemic model based on system of ordinary differential equations is formulated by taking into account the transmission routes from symptomatic, asymptomatic and hospitalized individuals. The model is fitted to the corresponding cumulative number of hospitalized individuals (active cases) reported by the Nigeria Centre for Disease Control (NCDC), and parameterized using the least squares method.

Identification of QTLs for grain yield and other traits in tropical maize under Striga infestation.

Striga is an important biotic factor limiting maize production in sub-Saharan Africa and can cause yield losses as high as 100%. Marker-assisted selection (MAS) approaches hold a great potential for improving Striga resistance but requires identification and use of markers associated with Striga resistance for adequate genetic gains from selection. However, there is no report on the discovery of quantitative trait loci (QTL) for resistance to Striga in maize under artificial field infestation.

Genome-wide association study of Striga resistance in early maturing white tropical maize inbred lines.

Background: Striga hermonthica (Benth.) parasitism militates against increased maize production and productivity in savannas of sub-Saharan Africa (SSA). Identification of Striga resistance genes is important in developing genotypes with durable resistance.

Workplace tobacco policies and smoking cessation practices of physicians.

Objective: To further our understanding of the workplace smoking policies and smoking cessation practices of physicians in Nigeria.

Design: Cross-sectional survey distributed to 619 physicians practicing in two teaching hospitals in southwestern Nigeria.

Participants: Three-hundred-seventy-three physicians who returned completed surveys.