Plant Gene and Trait 2025, Vol.16, No.1, 15-22 http://genbreedpublisher.com/index.php/pgt 19 6.3 Challenges and solutions in practical breeding applications One of the biggest problems faced by MAS technology in Sapindus breeding is how to truly apply the research results to breeding, which will encounter limitations in terms of logistics and genetics in the process. Su et al. (2019) found that complex traits such as stress resistance are influenced by the environment and the interactions among multiple genes. Therefore, it is necessary to have a deeper understanding of the relationship between genotypes and the environment, as well as the interactions among genes (also known as abogenicity). To solve these problems, it becomes very important to develop high-throughput phenotypic and genotypic analysis techniques. There are also some more efficient breeding strategies, such as backcrossing breeding and enrichment of target traits in the F2 generation population, which have also been proven to improve breeding efficiency (Thomson et al., 2009). 7 Potential of Whole-Genome and Big Data Analysis inSapindus Breeding 7.1 Progress and applications of whole-genome sequencing inSapindus Whole genome sequencing (WGS) can provide detailed genetic information and help breeders formulate breeding strategies more precisely. WGS can be used in the breeding of Sapindus to identify genetic markers related to target traits and improve breeding efficiency. Meuwissen et al. (2021) hold that by using these data, the gene regions (QTL) related to traits can be located more accurately, which is very beneficial for understanding the genetic basis of the complex traits of Sapindus. Combining WGS with some genomic prediction models (such as GBLUP and Bayesian models) can also improve the accuracy of trait prediction, especially among different Sapindus species. 7.2 Role of big data and artificial intelligence in phenotype-genotype analysis In the breeding of Sapindus, a large amount of genotype and phenotype data has been accumulated. These data can help predict the expression of traits more accurately and also make the selection process more efficient. Especially machine learning (ML) algorithms are very useful when processing and analyzing these huge amounts of data. They can identify the genetic structure behind traits and provide strong support for breeding decisions (Tempelman, 2015). Singh and Prasad demonstrated in their 2021 study that the addition of AI is helpful for discovering new genetic associations and predicting the results of complex traits with higher precision, thereby enhancing the efficiency of Saponus breeding. 7.3 Future prospects of genomic selection (GS) in precise Sapindus breeding GS can select complex traits more accurately by using whole-genome data, accelerate the breeding process and improve the breeding effect. The combination of GS and WGS (whole genome sequencing) data can identify key genetic variation points and directly apply these variations in breeding to achieve the target traits (De Los Campos et al., 2013). Ros-Freixedes et al. (2022) indicated that sequencing technology is becoming increasingly advanced and the cost is getting lower and lower. This means that the application of GS in soapy seed breeding will increase more and more, and it is expected to accelerate the development of excellent new varieties such as disease resistance and high yield. 8 Concluding Remarks This study demonstrates how to apply superior trait screening and molecular marker-assisted breeding methods to Sapindus plants. There is a study found significant genetic differences between Sapindus mukorossi and S. delavayi through the use of ISSR markers. These plants have high economic value because they are rich in compounds such as vegetable oil and saponins. The study also established the association between ISSR markers and some important fruit traits, laying the foundation for breeding efforts to improve these traits. The application of these markers provides a reliable tool for screening high-quality resources and significantly improves the efficiency of Sapindus breeding. Future research should pay more attention to expanding the genetic basis of Sapindus. Introducing more germplasm resources from different sources can enhance the stability and adaptability of the breeding program. Combining high-throughput phenotypic determination techniques with MAS (marker-assisted selection) can
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