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Breeding jassid-resistant okra (Abelmoschus esculentus): from morpho-biochemical traits to precision breeding
Fabrice Vihou1, Barthélémy B Yarou1, Ya-Ping Lin2
1World Vegetable Center, West and Central Africa, Cotonou, Benin.
Abstract:
Okra, an economically important vegetable in tropical and subtropical regions, faces severe yield constraints due to sap-sucking pests, particularly jassids (Amrasca spp.). These insects cause hopper burn, leaf curling, and chlorosis, leading to estimated yield losses of 30-100% under severe infestation. Farmers' heavy reliance on chemical control to manage these insects poses environmental, economic, and health risks, underscoring the need for host-plant resistance as a sustainable component of integrated pest management. Successful breeding for jassid resistance requires in-depth knowledge of its underlying mechanisms. This review synthesizes current knowledge on jassid resistance in okra, focusing on morphological (trichome density, leaf thickness), biochemical (phenolics, defensive enzymes), and physiological traits that confer antixenosis and antibiosis, as well as the largely untapped potential of wild Abelmoschus species as reservoirs of novel and durable resistance alleles. We examine advances in genomics, including QTL mapping, genome-wide association studies, and transcriptomics, as tools for dissecting complex resistance mechanisms in okra's polyploid genome. We further discuss biotechnological and precision breeding strategies such as genomic selection, gene editing, and speed breeding, as avenues to accelerate the development of jassid-resistant cultivars. We conclude by proposing a multi-trait ideotype that integrates morphological, biochemical, and genetic resistance while maintaining high yield and product quality and is supported by an integrated breeding framework that combines conventional and genomic approaches. Key research priorities include discovering new sources of resistance, functionally validating resistance loci, and integrating high-throughput phenotyping with genomic selection to enhance breeding precision and efficiency in okra improvement programs.
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