International Journal of Horticulture, 2025, Vol.15, No.3, 105-112 http://hortherbpublisher.com/index.php/ijh 107 3 Meta-Analytic Insights on Genetic Diversity 3.1 Global diversity patterns Pineapple germplasm showed significant genetic diversity among different regions and varieties, and SSR, AFLP and ISSR molecular markers were used to reveal rich genetic variation. According to the study of Ismail et al. (2020), the SSR study in Malaysia showed moderate polymorphism, with an average of 3.9 alleles detected at each locus and an average PIC value of 0.433, indicating that its genetic diversity was at a medium level. Paz et al. (2012) showed that the genetic diversity of Cuban germplasm was low through AFLP analysis, and most of the materials were clustered at genetic distance less than 0.20, indicating a limited range of variation. Hayati and Kasiamdari (2024) showed that Indonesian varieties showed high genetic diversity with 89.38% polymorphisms detected by ISSR markers. 3.2 Population structure across studies Studies in different regions revealed the differences in population structure of pineapple germplasm resources. Ismail et al. 's study in 2020 showed that the population structure analysis in Malaysia used the delta K method to identify two major genetic clusters, and the findings were supported by UPGMA systematic cluster maps. Rattanathawornkiti et al. ’s study in 2016 showed that AFLP studies in Thailand identified 9 independent genetic populations in 37 materials, which were closely related to morphological characteristics of breeds (such as Cayenne and Queen taxa). The population structure of pineapple is complex, which can be influenced by both genetic and environmental factors. 3.3 Variation among germplasm types Variability between different types of pineapple germplasm has been demonstrated in multiple studies. According to Zhao and Qin (2018), the genetic diversity of pineapple is driven by cross-pollination and somatic variation, resulting in wide differences in plant morphology and fruit traits among different varieties. Zhou et al. (2015) reported that the application of SNP markers revealed high genetic redundancy in the germbank, and somatic mutations were considered to be the main source of intraspecific variation. Continuous intraspecific variability in wild species such as Ananas ananassoides and Ananas parguazensis is an important contributor to overall genetic diversity (Duval et al., 2001). 4 Trait Discovery through Meta-Analysis 4.1 Fruit quality traits The fruit quality traits of pineapple are critical for fresh food and processing purposes. Several studies have highlighted that genetic diversity in germplasm resources is beneficial for improving fruit quality traits (such as size, sweetness, and flesh color). Ismail et al. (2020) used SSR markers to study Malaysian pineapple materials and found that they had moderate polymorphism, which could be used to improve fruit sweetness and taste traits. Genes associated with flesh color, such as carotenoid cleaved dioxygenase 4 (AcCCD4), identified in Nashima et al. (2022) provide the genetic basis for the development of high-quality fruit color varieties through marker-assisted selection (Figure 2). Zhou et al. 's study in 2015 showed that the application of SNP markers revealed significant variability within varieties, providing rich selection resources for the improvement of fruit quality traits. 4.2 Stress tolerance and resistance Stress and pest resistance traits help ensure sustainable cultivation of pineapples in a varied environment. Studies on genetic diversity of AFLP and ISSR markers suggest that genetic variation in pineapple germplasm can be used to breed cultivars with high resistance (Paz et al., 2012; Wang et al., 2017). Studies of pineapple germplasm from Cuba and Indonesia have revealed material resources with great potential to resist biological and abiotic stresses (Paz et al., 2012; Hayati and Kasiamdari, 2024). The identification of genetic populations with specific stress resistance traits provides a scientific basis for parental selection (Rattanathawornkiti et al., 2016).
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