Investigation of pigment degradation dynamics of garlic scapes in simulated hot-chain systems using hyperspectral imaging-guided kinetic modeling

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis Pub Date : 2025-09-23 DOI:10.1016/j.jfca.2025.108349

Haoyang Xu , Zhihua Li , Xiaowei Huang , Sihui Chen , Ke Zhang , Peipei Gao , Jiyong Shi , Xiaobo Zou

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引用次数: 0

Abstract

Maintaining color stability in vegetable dishes under hot-chain conditions remains challenging. This study explored pigment degradation kinetics using hyperspectral imaging with chemometrics, comparing three models (PLS, IPLS, SIPLS) for five pigments after 11 spectral preprocessing methods with PCA. Optimized models showed strong performance (calibration R²: 0.9707–0.9921; prediction R²: 0.9412–0.9739). Kinetic analysis revealed the Weibull model's superiority (R²: 0.9558–0.9988) over traditional kinetic models. Synergistic enzyme-thermal degradation mechanisms were proposed, incorporating enzyme catalytic/inactivation rates and non-enzymatic degradation. Pearson analysis identified thermal exposure duration (- 0.755 to - 0.864 correlation) as the primary degradation driver, followed by temperature-related mass loss rates (0.663 to −0.759). Quantitative visualization to study pigment distribution, mass change, and color change to study apparent changes. These findings provide mechanistic insights into pigment degradation pathways and practical strategies for optimizing vegetable dish quality in commercial hot-chain systems.

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利用高光谱成像引导动力学模型研究模拟热链系统中大蒜表皮色素降解动力学

在热链条件下保持蔬菜菜肴的颜色稳定性仍然具有挑战性。本研究利用化学计量学的高光谱成像技术研究了色素降解动力学，比较了5种色素经过11种PCA光谱预处理后的三种模型（PLS、IPLS、SIPLS）。优化后的模型具有较好的性能（校正R²：0.9707 ~ 0.9921；预测R²：0.9412 ~ 0.9739）。动力学分析表明，Weibull模型优于传统的动力学模型（R²：0.9558-0.9988）。提出了酶-热协同降解机制，结合酶催化/失活率和非酶降解。Pearson分析发现，热暴露时间（- 0.755至- 0.864相关）是主要的降解驱动因素，其次是与温度相关的质量损失率（0.663至- 0.759）。定量可视化用于研究色素分布、质量变化和颜色变化以研究表观变化。这些发现提供了色素降解途径的机理见解和优化商业热链系统蔬菜菜肴质量的实用策略。

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来源期刊

Journal of Food Composition and Analysis 工程技术-食品科技

CiteScore

6.20

自引率

11.60%

发文量

601

审稿时长

53 days

期刊介绍： The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects. The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.