ArticlePlant phenomics (Washington, D.C.)2024
Study on the Optimal Leaf Area-to-Fruit Ratio of Pear Trees on the Basis of Bearing Branch Girdling and Machine Learning.
Article in Plant phenomics (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Improving pear fruit quality without yield loss through 3D point cloud-based estimation of reasonable fruit load.Plant phenomics (Washington, D.C.) · 2026Article
- Multimodal learning on RGB-D image for precise litchi phenotyping and weight estimation.Plant methods · 2025Article
- Informed-Learning-Guided Visual Question Answering Model of Crop Disease.Plant phenomics (Washington, D.C.) · 2024Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
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 dm
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Registered trials
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