Unverified paper record
High-throughput phenotyping of sweetness and sourness components in tomato fruits by near-infrared spectroscopy and chemometrics methods
Current Research in Food Science · 17 Nov 2025 · 10.1016/j.crfs.2025.101247
Abstract
Tomato ( S. lycopersicum ) is a precious fruit crop, and flavor quality is one of the most important commodity traits and directly affects the commodity value and economic returns. The composition and content of sugars and acids in tomato fruits, as well as their balance, are closely related to tomato quality, especially soluble sugars and organic acids, and so on. However, the lack of an efficient approach for quality evaluation of tomato significantly hinders progress in flavor quality breeding. Near infrared spectroscopy technology (NIRS) utilizes the absorption characteristics of near-infrared light by molecular vibrations of substances, and establishes a quantitative relationship model between spectra and component content through chemometric methods. Therefore, this study aimed to establish an NIRS assay for high-throughput analysis of tomato fruit quality, including fructose, sucrose, glucose, malic acid, and citric acid content. A total of 190 representative samples were utilized, and a dual-optimized strategy (optimization of sample subset partitioning and variable selection) was applied to NIRS modeling. Partial least squares regression (PLSR) model were developed with an excellent coefficient of determination for the coefficient of determination of calibration (R C 2 ) and coefficient of determination of validation (R v 2 ) of this model, with 0.962 and 0.942, respectively. what's more, the root mean square error of calibration (RMSEc) and root mean square error of prediction (RMSEP) were 0.36 mg/g and 0.44 mg/g,respectively.This model can effectively compress useless variables and interference information in near-infrared spectra. Overall, these NIRS models provide a feasible approach for high-throughput analysis of fruit quality and permit large-scale screening of elite germplasm in future tomato breeding.
Plant phenotyping relevance
トマト果実の糖・酸含量という植物器官形質を対象に、NIRSとケモメトリクスによるハイスループット測定法を開発・検証しており、表現型取得法が研究の中心である。
abstractthis study aimed to establish an NIRS assay for high-throughput analysis of tomato fruit quality, including fructose, sucrose, glucose, malic acid, and citric acid content.
abstractPartial least squares regression (PLSR) model were developed with an excellent coefficient of determination for the coefficient of determination of calibration (R C 2 ) and coefficient of determination of validation (R v 2 ) of this model, with 0.962 and 0.942, respectively.
abstractOverall, these NIRS models provide a feasible approach for high-throughput analysis of fruit quality and permit large-scale screening of elite germplasm in future tomato breeding.
Code and data availability
The paper reports NIRS/PLSR phenotyping of tomato sugars and acids, but no public dataset, spectra, code, or models are deposited. The only availability statement is 'Data will be made available on request,' which is request-only, not a public asset. FAOSTAT and the DOI links are generic/citation references, not paper-
No evidence-backed public reproduction asset is currently recorded.
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