Bioscience Methods 2025, Vol.16, No.4, 218-227 http://bioscipublisher.com/index.php/bm 221 4.3 Pruning and canopy control to optimize nutrient partitioning Pruning and controlling the structure of the crown are important practices to help fruit trees better distribute nutrients. Proper pruning allows fruit trees to better absorb sunlight and helps ventilation, so that the fruit can get more nutrients. By cutting off some excess branches, the tree can transfer more nutrients to the growing fruits and reduce nutrient competition between branches. In this way, the size, color and uniformity of the fruit will be more ideal. Crown management can also reduce the adverse effects of weather changes and is conducive to precise fertilization and irrigation operations. These methods, combined with modern agricultural technology, can help us continue to grow high-quality fruits and increase the yield of the entire orchard (Yadav et al., 2023; Bacelar et al., 2024). The Dongkui, which has a relatively high and large canopy, is best pruned with three-dimensional concave convex wavy and large branch pruning. This can transform the surface shape of the Bayberry tree from a round head shape to a three-dimensional concave convex shape, increase the number of fruiting branches in the inner and lower parts of the crown, and improve the yield and quality of Yangmei (Figure 2) (Huang and Liang, 2020). Figure 2 The bayberry (Dongkui) concave convex pruning technique (Photo by Jindao Huang) Image caption: A Concave convex pruning; B Mature Performance 5 Role of Smart Agricultural Technologies 5.1 Decision support systems for nutrient scheduling Decision support systems (DSS) are helping farmers make better fertilization decisions. These systems combine data from soil conditions, crop status, and weather to optimize fertilization methods. The system uses data analysis and predictive models to give accurate fertilization recommendations, which can improve efficiency and reduce environmental impact. For example, some DSS platforms can process real-time field data and then tell farmers where and how to apply fertilizer, which can increase yields and use resources more rationally (Bacenetti et al., 2020; Cesco et al., 2023). DSS can also be connected to farm management tools and open data platforms to enable farmers and agricultural technicians to make more informed decisions (Cambra-Baseca et al., 2019). 5.2 IoT-based sensors for real-time monitoring of soil and crop status Internet of Things (IoT) technology has been widely used in agriculture. Tools such as wireless sensors and automatic monitoring devices can monitor various data in the field online, such as soil moisture, nutrient concentration, pH and temperature. The information collected by these sensors is uploaded to the cloud platform, which can then be viewed remotely and fertilized automatically according to the needs of the crops (Rehman et al., 2022; Jani and Chaubey, 2024; Rajagopalakrishnan et al., 2025). This system can greatly reduce manual operations and avoid fertilizer waste. Once problems are found, they can be dealt with in time, thus ensuring efficient and environmentally friendly growth of crops (Shaikh et al., 2022; Pathmudi et al., 2023; Rajak et al., 2023). 5.3 Machine learning and modeling tools for predictive fertilization Now, more and more people are using machine learning and modeling tools to predict the most appropriate fertilization. These tools can process large amounts of data from sensors, remote sensing, and past records, and then analyze what nutrients crops need and when, and make personalized fertilization arrangements (Agrahari et al., 2021). For example, by combining hyperspectral imagery and machine learning technology, it is possible to accurately determine whether crops are lacking fertilizer, especially nitrogen fertilizer, and then manage them in a
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