Molecular Plant Breeding 2024, Vol.15, No.5, 295-307 http://genbreedpublisher.com/index.php/mpb 302 salt tolerance gene LEA12, regulates the expression of 9-is-epoxycarotenoid dioxygenase OsNCED3, a key enzyme in the ABA biosynthesis pathway, thus enhancing salt tolerance and providing a new way to improve salt tolerance and yield in rice. 6.2 Environmental and economic benefits of high-yielding varieties High-yielding rice varieties not only improve productivity but also offer significant environmental and economic benefits. The adoption of these varieties can lead to more efficient use of land and resources, reducing the need for expansion into ecologically sensitive areas. For example, the development of low glycemic index rice with preferred grain quality can cater to specific dietary needs while maintaining high yield, thus addressing both health and environmental concerns (Selvaraj et al., 2021). Economically, the increased productivity from high-yielding varieties translates to higher incomes for farmers. In Yunnan, China, the adoption of improved rice varieties increased both rice income and total household income, demonstrating the economic viability of these varieties (Wang et al., 2020). Furthermore, the genetic diversity introduced through the International Rice Genebank has been shown to significantly boost rice productivity, thereby contributing to economic stability in farming communities (Villanueva et al., 2020). 6.3 Acceptance and adoption by the farming community The acceptance and adoption of tailor-made rice varieties by the farming community are crucial for their success. Factors such as educational attainment, experience in rice farming, and access to extension services and credit have been identified as significant determinants of IRV adoption in Nigeria (Bello et al., 2020). Government programs and extension services also play a vital role in promoting the adoption of these varieties, as evidenced by the increased adoption rates in Yunnan due to government initiatives (Wang et al., 2020). Additionally, the development of varieties that are stable across different environmental conditions, such as those evaluated for heat tolerance, ensures that farmers can rely on these varieties under varying climatic conditions, thereby increasing their acceptance (Senguttuvel et al., 2021). The positive correlation between yield and traits such as grain width and number of grains per panicle further supports the adoption of these varieties, as they meet the farmers’ expectations for high productivity (Ayyenar et al., 2022; Singh et al., 2022a). 7 Integration and Scalability of HBB 7.1 Implementing haplotype analysis on a large scale Implementing haplotype analysis on a large scale involves leveraging advanced genomic technologies to identify and utilize genetic variations effectively. The process begins with the collection of extensive genomic data from diverse rice cultivars. For instance, Brinton et al. (2020) demonstrated the utility of genome assemblies from multiple wheat cultivars to identify haplotypes and their potential for trait improvement. Similarly, the identification of superior haplotypes for drought tolerance in pigeonpea highlights the importance of whole-genome re-sequencing data in HBB programs (Sinha et al., 2020). By integrating high-throughput sequencing and advanced computational tools, large-scale haplotype analysis can be systematically applied to rice breeding programs to enhance precision and efficiency. 7.2 Overcoming technical and logistical challenges The technical and logistical challenges in HBB include accurate haplotype phasing, data management, and the integration of diverse datasets. Consensus strategies for haplotype phasing, such as combining multiple independent phasing estimates, have been shown to improve accuracy and reduce errors (Bkhetan et al., 2020). Additionally, the development of specialized software, like PolyOrigin for tetraploid species, facilitates haplotype reconstruction and enhances QTL detection power (Zheng et al., 2020). Addressing these challenges requires robust computational infrastructure, standardized protocols, and collaboration among researchers to ensure the seamless integration of haplotype data into breeding programs. 7.3 Strategies for enhancing farmer and industry adoption To enhance the adoption of HBB by farmers and the industry, it is crucial to demonstrate the tangible benefits of this approach. Data-driven decentralized breeding, which combines genomics, farmers’ knowledge, and environmental analysis, has shown promise in improving local adaptation and productive performance in
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