International Journal of Horticulture, 2025, Vol.15, No.3, 105-112 http://hortherbpublisher.com/index.php/ijh 110 diversity assessment (Wang et al., 2017; Ismail et al., 2020; Hayati and Kasiamdari, 2024). AFLP markers show low diversity in some germplasm populations (Gerber et al., 2000; Paz et al., 2012). Existing studies mainly focus on some specific geographical regions or germplasm banks, which cannot fully represent the global genetic diversity of pineapple (Paz et al., 2012; Ismail et al., 2020), it is difficult for researchers to fully reveal the genetic relationships and diversity patterns among germplasm (Wang et al., 2017). 7.2 Uncovered traits and geographic gaps Scientists have now identified genes associated with leaf margin morphology and pulp color (Nashima et al., 2022), but further research is needed on other traits such as yield, fruit quality and productivity (Zhao and Qin, 2018; Junior et al., 2021). In terms of geographical representation, current genetic diversity studies mainly focus on Malaysia, Cuba, Indonesia and Thailand (Paz et al., 2012; Rattanathawornkiti et al., 2016; Ismail et al., 2020; Hayati and Kasiamdari, 2024), while other important pineapple production areas have not been adequately sampled, geographic gaps may cause breeders to bias their perceptions of global genetic diversity, limiting the effectiveness of breeding programs. 7.3 Multi-omics integration in future meta-analyses Future meta-analysis studies should focus more on the integration of multi-omics data to analyze the germplasm resources of pineapple more comprehensively. Integrating genomic, transcriptome, proteome, and metabolome data is helpful for identifying key genes and their pathways that regulate important traits (Zhao and Qin, 2018; Nashima et al., 2022). The use of SNP markers can provide robust and comparable DNA fingerprints for the identification and management of global germplasm resources (Zhou et al., 2015). Through the multi-omics integration method, researchers can break through the limitation of single marker study, fully grasp the genetic diversity and character framework of pineapple, and promote the management of germplasm resources, the formulation of breeding strategies and the protection of varieties (Zhou et al., 2015; Wang et al., 2017). Acknowledgments The authors appreciate the comments from Mr. Rudi Mai and Mr. Qixue Liang on the manuscript of this study. Funding This study was supported by the Research and Training Fund of the Hainan Institute of Tropical Agricultural Resources (Project No. H2025-02). Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Adje C.A.O., Achigan-Dako E.G., d'Eeckenbrugge G.C., Yedomonhan H., and Agbangla C., 2019, Morphological characterization of pineapple (Ananas comosus) genetic resources from Benin, Fruits, 74(4): 167-179. https://doi.org/10.17660/th2019/74.4.2 Ali M., Hashim N., Aziz A., and Lasekan O., 2020, Pineapple (Ananas comosus): A comprehensive review of nutritional values, volatile compounds, health benefits, and potential food products, Food Research International, 137: 109675. https://doi.org/10.1016/J.FOODRES.2020.109675 Carlier J., Sousa N., Santo T., d'Eeckenbrugge G., and Leitão J., 2010, A genetic map of pineapple (Ananas comosus (L.) Merr.) including SCAR, CAPS, SSR and EST-SSR markers, Molecular Breeding, 29: 245-260. https://doi.org/10.1007/s11032-010-9543-9 Chaudhary V., Kumar V., Singh K., Kumar R., Kumar V., and Chaudhary C.V., 2019, Pineapple (Ananas comosus) product processing: a review, Journal of Pharmacognosy and Phytochemistry, 8: 4642-4652. Chen B., Hou J.F., Cai Y.F., Wang G.Y., Cai R.X., and Zhao F.C., 2024a, Utilizing genetic diversity for maize improvement: strategies and success stories, Maize Genomics and Genetics, 15(3): 136-146. https://doi.org/10.5376/mgg.2024.15.0014 Chen B., Hou J.F., Cai Y.F., Wang G.Y., Cai R.X., and Zhao F.C., 2024b, Genetic diversity in the genus zea: insights from chloroplast genome variability, Maize Genomics and Genetics, 15(5): 228-238.
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