International Journal of Molecular Ecology and Conservation, 2025, Vol.15, No.6, 294-302 http://ecoevopublisher.com/index.php/ijmec 299 yellow pitaya can show excellent growth in arid areas and Mediterranean climate zones. Modern breeding has included resistance to abiotic stress as a basic screening standard to ensure that new varieties maintain stable productivity under different cultivation modes (Trivellini et al., 2020; Almeida et al., 2021; Trindade et al., 2023). Net cultivation combined with artificial light environment regulation can effectively promote flowering synchronization and stabilize yield performance (Huang et al., 2022; Chien et al., 2024). 6.3 Market-oriented diversified breeding The diversification of consumer markets has driven breeding goals towards characteristic traits such as high anthocyanin, high sugar content, and thornless stems. These characteristics not only improve the appearance quality and nutritional value of the fruit, but also optimize the efficiency of harvesting and logistics. Post-harvest characteristic improvement (such as maintaining fruit hardness and extending storage period) plays a key role in supply chain optimization and market competitiveness. Comparative trials of facility cultivation have identified a number of high-yield, high-antioxidant activity and excellent-quality varieties, providing rich germplasm resources for differentiated market supply. These breeding breakthroughs will accelerate the penetration of yellow pitaya in the mainstream market and specialty consumption areas. 7 Future Prospects and Development Directions 7.1 Construction of multi-omics database Multi-omics data is driving a paradigm shift in yellow pitaya research. The yellow pitaya Genome and Multi-omics Database (PGMD) integrates multi-level information such as genome, transcriptome, miRNA group, metabolome and proteome, covering different tissue types and developmental stages. This systematic resource lays a solid foundation for functional genomics research and population genetic analysis (Li et al., 2025). Relying on chromosome-level genome assembly and fine genetic maps, the regulatory networks and candidate genes of key agronomic traits can be efficiently analyzed, which significantly accelerates the process of precision breeding. The multi-dimensional data association analysis supported by the platform makes the design of breeding programs more scientific and efficient (Khokhar et al., 2023). 7.2 International germplasm sharing and joint breeding International collaboration is of strategic significance for expanding the genetic diversity of pitaya and rapidly cultivating disease-resistant varieties. Practice has shown that the use of shuttle breeding or interspecific hybridization strategies, based on the sharing of germplasm resources and breeding technology, can significantly shorten the R&D cycle and improve the efficiency of trait innovation. Molecular marker tools (such as SSR and SNP) and unified phenotypic evaluation standards have improved the operability and scientificity of international joint breeding, and are also conducive to the precise positioning and rapid transfer of resistance genes. The global breeding network and open database platform provide effective support for responding to challenges such as disease outbreaks and climate adaptation (Nashima et al., 2021; Chen et al., 2022). 7.3 Intelligent platform and precise improvement The intelligent breeding system integrating high-throughput phenotypic groups, molecular markers and multi-omics data is revolutionizing the traditional breeding model. This type of platform can achieve rapid screening of excellent germplasm and targeted aggregation of important traits by establishing a precise phenotype-genotype association model. With the breakthrough development of genomics, transcriptomics and gene editing technologies, new tools such as CRISPR/Cas9 have opened up new avenues for improving stress resistance, quality and disease resistance breeding (Chen et al., 2022; Khokhar et al., 2023). Establishing an intelligent breeding decision-making system based on big data analysis will become the core technical support for achieving sustainable development of the yellow pitaya industry. 8 Concluding Remarks Yellow pitaya breeding faces a series of long-standing challenges, including complex genetic structure, lengthy breeding cycle and high incidence of diseases, which together affect the planting efficiency and environmental adaptability of crops. The crop shows strong genetic diversity, many key agronomic traits are regulated by multiple genes, and are deeply disturbed by interspecific or interploid hybridization, which makes it difficult to
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