Legume Genomics and Genetics 2024, Vol.15, No.5, 232-243 http://cropscipublisher.com/index.php/lgg 238 Figure 3 Phenotypic observations for seeds of U 4-7-5 and JL 24 during aflatoxin production (AP) by A. flavus at different time points along with microscopic observation and aflatoxin estimation (Adopted Soni et al., 2020) Image caption: This figure shows the diagrammatic representation of phenotypic observations for seeds of JL 24 and U 4-7-5 at different time points (A,B), microscopic observation during AP at different time points (C) and graphical representation of AP estimation at different time points under control and infection conditions clearly showing the presence of highest amount of toxin at Day 7 after inoculation (D) (Adopted Soni et al., 2020) 5.4 Future directions and challenges Future breeding efforts should focus on integrating advanced molecular techniques with traditional breeding to enhance resistance to aflatoxin contamination. The development of transgenic peanuts with genes that inhibit aflatoxin biosynthesis or enhance antifungal properties appears promising (Nigam et al., 2009). Additionally, a deeper understanding of the genetic and molecular mechanisms underlying resistance, coupled with effective phenotyping strategies, will be crucial for developing durable resistance in commercial peanut varieties (Bhatnagar-Mathur et al., 2015; Korani et al., 2018). However, challenges such as the complexity of resistance traits, environmental interactions, and the need for reliable screening protocols must be addressed to achieve significant progress in breeding aflatoxin-resistant peanuts. 6 Integrative Approaches for Peanut Improvement 6.1 Genomics and transcriptomics in peanut breeding Genomics and transcriptomics have become pivotal in peanut breeding, offering insights into the genetic architecture and expression profiles of peanut plants. Recent advancements have led to the development of molecular markers, genetic and physical maps, and functional genomics platforms that facilitate the identification of quantitative trait loci (QTLs) and genes associated with tolerance to abiotic and biotic stresses, as well as agronomic traits (Pandey et al., 2012). Genome-wide association studies (GWAS) have been particularly useful, identifying significant marker-trait associations (MTAs) for various traits, which can be leveraged to improve
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