Research Article | Open Access

Volume 2024 |Article ID 0233 | https://doi.org/10.34133/plantphenomics.0233

Study on the Optimal Leaf Area-to-Fruit Ratio of Pear Trees on the Basis of Bearing Branch Girdling and Machine Learning

Fanhang Zhang,^1,4 Qi Wang,^1,4 Haitao Li,² Qinyang Zhou,² Zhihao Tan,¹ Xiaochao Zu,¹ Xin Yan,¹ Shaoling Zhang,¹ Seishi Ninomiya ,³ Yue Mu ,² and Shutian Tao ¹

¹Sanya Institute, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
²Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, Jiangsu 210095,China
³Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 188-0002, Japan
⁴These authors contributed equally to this work

Abstract

The leaf area-to-fruit ratio (LAFR) is an important factor affecting fruit quality. Previous studies on LAFR have provided some recommendations for optimal values. However, these recommendations have been quite broad and lack effectiveness during the fruit thinning period. In this study, data on the LAFR and fruit quality of pears at 5 stages were collected by continuously girdling bearing branches throughout the entire fruit development process. Five different clustering algorithms, including KMeans, Agglomerative clustering, Spectral clustering, Birch, and Spectral biclustering, were employed to classify the fruit quality data. Agglomerative clustering yielded the best results when the dataset was divided into 4 clusters. The least squares method was utilized to fit the LAFR corresponding to the best quality cluster, and the optimal LAFR values for 28, 42, 63, 91, and 112 days after flowering were 12.54, 18.95, 23.79, 27.06, and 28.76 dm2 (the corresponding leaf-to-fruit ratio values were 19, 29, 36, 41, and 44, respectively). Furthermore, field verification experiments demonstrated that the optimal LAFR contributed to improving pear fruit quality, and a relatively high LAFR beyond the optimum value did not further increase quality. In summary, we optimized the LAFR of pear trees at different stages and confirmed the effectiveness of the optimal LAFR in improving fruit quality. Our research provides a theoretical basis for managing pear tree fruit load and achieving high-quality, clean fruit production.