Bioscience Methods 2024, Vol.15, No.6, 264-274 http://bioscipublisher.com/index.php/bm 271 Figure 2 Analysis of storage root yield and inorganic phosphorus content in transgenic sweet potato (IbVP1 overexpression) (Adapted from Fan et al., 2021) Image caption: a: Storage root morphology of different sweet potato plants; b: Comparison of storage root yield, with IA lines significantly higher than WT; c: Pyrophosphatase activity in storage roots; d: Pyrophosphate concentration in storage roots; e: Phosphorus content in roots; f: Phosphorus content in leaves (Adapted from Fan et al., 2021) 9 Future Directions for Increasing Sweet Potato Yield and Starch Content 9.1 Application of high-throughput phenotyping High-throughput phenotyping (HTP) platforms have revolutionized the efficiency of phenotypic data collection in crop breeding. These platforms utilize advanced imaging technologies, such as hyperspectral cameras and thermal sensors, to capture detailed plant responses to environmental stimuli non-destructively (Araus and Cairns, 2014; Yang et al., 2020; Tiwari et al., 2021). The integration of HTP with aeroponic culture systems allows for precise phenotyping of both above- and below-ground plant parts, which is particularly beneficial for root crops like sweet potatoes (Tiwari et al., 2021). Field-based HTP platforms, which combine remote sensing methods with automated environmental data collection, are paving the way for more efficient crop genetic improvement (Araus and Cairns, 2014; Shakoor et al., 2017). These advancements in HTP can significantly enhance the selection efficacy for traits such as yield potential, tuber quality, and stress tolerance, thereby accelerating the development of high-yield and high-starch sweet potato varieties (Shakoor et al., 2017; Yang et al., 2020; Tiwari et al., 2021). 9.2 Adaptive breeding under climate change Climate change poses significant challenges to crop production, necessitating the development of stress-tolerant varieties. Breeding for stress tolerance in sweet potatoes can benefit from large-scale phenotyping, which enables continuous monitoring of plant growth under various stress conditions. For instance, X-ray computed tomography (CT) has been used to monitor potato tuber development under combined heat and drought stress, revealing the potential for similar applications in sweet potatoes (Harsselaar et al., 2021). Additionally, the identification of genetic markers associated with key traits, such as starch content and stress tolerance, can facilitate the development of sweet potato varieties that are better adapted to changing environmental conditions (Kar et al., 2022; Haque et al., 2023). By leveraging these genetic insights and advanced phenotyping techniques, breeders can enhance the adaptability of sweet potatoes to diverse environments, ensuring stable yields and improved starch content under climate stress (Harsselaar et al., 2021; Kar et al., 2022; Haque et al., 2023). 9.3 Data-driven precision breeding The advent of big data and machine learning offers unprecedented opportunities for precision breeding in sweet potatoes. High-throughput phenotyping generates vast amounts of data that, when combined with genomic
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