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

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 correspondin

SUBMITTER: Zhang F 

PROVIDER: S-EPMC11322523 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature