{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zeng J"],"funding":["Hu Yang Talent (Doctoral) Program of the President's Fund of Tarim University"],"pagination":["3795"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12737044"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(24)"],"pubmed_abstract":["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 differen"],"journal":["Plants (Basel, Switzerland)"],"pubmed_title":["A Precise Apple Quality Prediction Model Integrating Driving Factor Screening and BP Neural Network."],"pmcid":["PMC12737044"],"funding_grant_id":["TDZKBS202424"],"pubmed_authors":["Li X","Yu M","Bao J","Zeng J","Chen Y","Pu X"],"additional_accession":[]},"is_claimable":false,"name":"A Precise Apple Quality Prediction Model Integrating Driving Factor Screening and BP Neural Network.","description":"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 differen","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-10T03:08:07.9Z","creation":"2026-06-10T03:07:02.429Z"},"accession":"S-EPMC12737044","cross_references":{"pubmed":["41470677"],"doi":["10.3390/plants14243795"]}}