食品科学 ›› 2025, Vol. 46 ›› Issue (20): 57-65.doi: 10.7506/spkx1002-6630-20250217-066

• 基础研究 • 上一篇    下一篇

不同线椒品种对剁椒品质影响及剁椒加工适宜性评价模型的构建

文亚诗,刘家祺,周泉,邓放明,赵玲艳,覃业优,秦丹,曾璐   

  1. (1.湖南农业大学食品科学技术学院,湖南 长沙 410128;2.湖南坛坛香食品科技有限公司,湖南 长沙 410331)
  • 出版日期:2025-10-25 发布日期:2025-09-16
  • 基金资助:
    现代农业产业技术体系建设专项(CARS-24-E-02);“十四五”国家重点研发计划重点专项(2023YFD1600200); 长沙现代食品创新研究院科研项目(ZLSSJ2186);湖南省蔬菜产业技术体系加工岗位专家项目(HARS-04-03)

Effects of Line Pepper Varieties on the Quality of Fermented Chopped Chili and Construction of a Suitability Evaluation Model for Fermented Chopped Chili Processing

WEN Yashi, LIU Jiaqi, ZHOU Quan, DENG Fangming, ZHAO Lingyan, QIN Yeyou, QIN Dan, ZENG Lu   

  1. (1. College of Food Science and Technology, Hunan Agricultural University, Changsha 410128, China; 2. Hunan Tantanxiang Food Co., Ltd., Changsha 410331, China)
  • Online:2025-10-25 Published:2025-09-16

摘要: 为探究不同品种线椒对其发酵剁辣品质的影响,构建剁椒加工适宜性评价模型。以45 个线椒品种作为研究对象,将其制成剁椒,对发酵前后辣椒的外观特征、理化指标及感官评分进行测定,并采用相关性分析、偏最小二乘法和随机森林算法等方法筛选影响线椒加工品质的关键指标,进而构建线椒品种品质预测模型。结果表明,不同品种线椒制备的发酵剁椒的品质存在显著差异,结合相关性分析与偏最小二乘判别分析,筛选出9 个重要指标,并利用随机森林算法构建了剁椒品质预测模型(训练集决定系数Rt2=0.934 3,测试集决定系数Rp2=0.849 8),经变量重要性和沙普利可加性解释值分析,确定水分含量、辣椒素含量、L*值和果胶含量是决定剁椒品质的核心指标,能对剁椒品质进行有效预测。本研究可为剁椒加工品种的高效筛选及系统性品质评价提供技术支撑。

关键词: 线椒;生物学特性;营养特性;加工适用性;随机森林

Abstract: To investigate the effects of different line pepper varieties on the quality of fermented chopped chili, a suitability evaluation model for chopped chili processing was constructed. A total of 45 line pepper varieties were selected and processed into fermented chopped chili. The appearance characteristics, physicochemical indicators and sensory evaluation scores of fresh and fermented pepper samples were measured. Correlation analysis, partial least squares discriminant analysis (PLS-DA), and random forest algorithm were applied to identify key indicators affecting the processing quality of line peppers and to develop a quality prediction model. The results showed significant differences in the quality of fermented chopped chili prepared from different line pepper varieties. Based on correlation analysis and PLS-DA, nine key indicators were selected, and a quality prediction model was constructed using random forest algorithm with coefficient of determinations for the training (Rt2) and prediction (Rp2) sets of 0.934 3 and 0.849 8, respectively. Variable importance and Shapley Additive exPlanations (SHAP) analysis identified moisture content, capsaicin, L* value, and pectin as the core indicators for determining chopped chili quality, enabling effective quality prediction. This study provides technical support for the efficient selection of line pepper varieties suitable for the processing of fermented chopped chili as well as its systematic quality evaluation.

Key words: line pepper; biological characteristics; nutritional properties; processing suitability; random forest

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