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Mycotoxin affects the world's food crops and creates a large economical loss in the developed and developing countries. Aflatoxins are a group of mycotoxins that mainly produced by Aspergillus species viz., A. flavus, and A. parasiticus. An aflatoxins contamination of maize grains has exhibiting a serious threat to human and animal health over the past two decades. Toprotect the safety of food commodities, regular monitoring and diagnosis of the presence and amount of non-permissible levels of aflatoxins in food is necessary to take appropriate management measures. Maize grain samples were collected from Ilu Galan and Bako districts of West Shoa and Gobu Sayo district of East Wollega zones of Oromiya; from different grain storage types. About 500 gr of maize grains were sampled from each sampling spot. PDA media was used for isolation of associated maize grains sample associated fungi. Sun-culturing and purification of the associated fungi were done and preserved using agar slant technique. The associated fungal mycoflora were characterized based on morphological and growth sporulation properties. Enzyme Linked Immuno Sorbent Assay (ELISA) diagnostic kit were used for identification and quantification of aflatoxins. Aspergillus, Fusarium Penicillium and Trichoderma species were identified and characterized. Aflatoxin B1 was identified and quantified from zero to 381.6µg/kg. About 34.4% of the samples were positive to aflatoxin B1 compared to Food and Drug Administration (20µg/kg) and European Union (4µg/kg), respectively. The management of mycotoxigenic fungi, improvement of storage methods, development of resistant maize varieties and awareness creations could be possible solutions

Breeding maize lines with the improved level of desired agronomic traits under optimum and drought conditions as well as increased levels of resistance to several diseases such as maize lethal necrosis (MLN) is one of the most sustainable approaches for the sub-Saharan African region. In this study, 879 doubled haploid (DH) lines derived from 26 biparental populations were evaluated under artificial inoculation of MLN, as well as under well-watered (WW) and water-stressed (WS) conditions for grain yield and other agronomic traits. All DH lines were used for analyses of genotypic variability, association studies, and genomic predictions for the grain yield and other yield-related traits. Genome-wide association study (GWAS) using a mixed linear FarmCPU model identified SNPs associated with the studied traits i.e., about seven and eight SNPs for the grain yield; 16 and 12 for anthesis date; seven and eight for anthesis silking interval; 14 and 5 for both ear and plant height; and 15 and 5 for moisture under both WW and WS environments, respectively. Similarly, about 13 and 11 SNPs associated with gray leaf spot and turcicum leaf blight were identified. Eleven SNPs associated with senescence under WS management that had depicted drought-stress-tolerant QTLs were identified. Under MLN artificial inoculation, a total of 12 and 10 SNPs associated with MLN disease severity and AUDPC traits, respectively, were identified. Genomic prediction under WW, WS, and MLN disease artificial inoculation revealed moderate-to-high prediction accuracy. The findings of this study provide useful information on understanding the genetic basis for the MLN resistance, grain yield, and other agronomic traits under MLN artificial inoculation, WW, and WS conditions. Therefore, the obtained information can be used for further validation and developing functional molecular markers for marker-assisted selection and for implementing genomic prediction to develop superior elite lines.

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