biostudies-literatureZeng JHu Yang Talent (Doctoral) Program of the President's Fund of Tarim University3795https://www.ebi.ac.uk/biostudies/studies/S-EPMC12737044biostudies-literatureUnknown14(24)Apple fruit quality is primarily determined by Vitamin C (VC), Soluble Saccharides (SSs), Titratable Acid (TA), and the Soluble Saccharides/Titratable Acid (SSs/TA). This study aims to establish a prediction model based on the Back Propagation (BP) neural network by analyzing the intrinsic relationships between these quality indicators and the photosynthetic physiological characteristics of fruit trees, providing a new method for the precise prediction and regulation of fruit quality. Using 'Fuji' apple as the material, fruit quality indicators, leaf photosynthetic parameters, canopy structure indicators, and carbon-water-nitrogen metabolism indicators were systematically measured. Correlation analysis was employed to identify key influencing factors, BP neural network models with differenPlants (Basel, Switzerland)A Precise Apple Quality Prediction Model Integrating Driving Factor Screening and BP Neural Network.PMC12737044TDZKBS202424Li XYu MBao JZeng JChen YPu XfalseA Precise Apple Quality Prediction Model Integrating Driving Factor Screening and BP Neural Network.Apple fruit quality is primarily determined by Vitamin C (VC), Soluble Saccharides (SSs), Titratable Acid (TA), and the Soluble Saccharides/Titratable Acid (SSs/TA). This study aims to establish a prediction model based on the Back Propagation (BP) neural network by analyzing the intrinsic relationships between these quality indicators and the photosynthetic physiological characteristics of fruit trees, providing a new method for the precise prediction and regulation of fruit quality. Using 'Fuji' apple as the material, fruit quality indicators, leaf photosynthetic parameters, canopy structure indicators, and carbon-water-nitrogen metabolism indicators were systematically measured. Correlation analysis was employed to identify key influencing factors, BP neural network models with differen2025-01-01T00:00:00Z2025 Dec2026-06-10T03:08:07.9Z2026-06-10T03:07:02.429ZS-EPMC127370444147067710.3390/plants14243795