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中国精品科技期刊2020
安宇宁,赵云财,霍俊伟,等. 26个软枣猕猴桃品种果实品质分析及综合评价[J]. 食品工业科技,2025,46(14):1−11. doi: 10.13386/j.issn1002-0306.2024080079.
引用本文: 安宇宁,赵云财,霍俊伟,等. 26个软枣猕猴桃品种果实品质分析及综合评价[J]. 食品工业科技,2025,46(14):1−11. doi: 10.13386/j.issn1002-0306.2024080079.
AN Yuning, ZHAO Yuncai, HUO Junwei, et al. Quality Analysis and Comprehensive Evaluation of 26 Varieties of Actinidia arguta Fruits[J]. Science and Technology of Food Industry, 2025, 46(14): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024080079.
Citation: AN Yuning, ZHAO Yuncai, HUO Junwei, et al. Quality Analysis and Comprehensive Evaluation of 26 Varieties of Actinidia arguta Fruits[J]. Science and Technology of Food Industry, 2025, 46(14): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024080079.

26个软枣猕猴桃品种果实品质分析及综合评价

Quality Analysis and Comprehensive Evaluation of 26 Varieties of Actinidia arguta Fruits

  • 摘要: 软枣猕猴桃品种繁多,为探究不同品种间品质的差异,确定影响品质的关键指标,筛选优良软枣猕猴桃种质资源。本研究以26个软枣猕猴桃品种为材料,从果实的外观理化指标、营养成分指标、活性物质含量、抗氧化能力以及降脂能力方面对其进行综合评价,并结合相关性分析和主成分分析方法建立一套综合评价模型。通过聚类热图分析方法对26个软枣猕猴桃品种进行分类,并结合感官评价,分析每类特点挖掘潜在应用价值。结果表明:不同软枣猕猴桃品种的果实品质指标具有显著性差异(P<0.05)。综合相关性分析和主成分分析结果简化评价指标,确定总酚、糖酸比、可溶性固形物含量、铁和维生素C为评价软枣猕猴桃果实品质的关键指标,通过建立综合评价模型得到综合品质前五名的品种为,‘A15’、‘桓优一号’、‘JL01’、‘J061403’、‘J141901’,极具定向培育及开发加工价值。聚类热图分析将26个软枣猕猴桃品种分为Ⅰ、Ⅱ、Ⅲ、Ⅳ类,各类分别含6、13、2、5个品种,第Ⅰ类活性物质含量占优势,适合开发高附加值的功能性保健产品;第Ⅱ类感官品质上乘,感官评分高,适合鲜食;第Ⅲ类VC含量高,适合制作成VC类膳食补充剂产品;第Ⅳ类加工品质好,适合加工为果酒、果汁、果脯、果酱、罐头等普通食品。本研究建立的综合评价体系可为我国软枣猕猴桃品种的选育、推广种植及加工利用提供理论参考。

     

    Abstract: Actinidia arguta is a specialty berry of the Northeast region. We aimed to establish a scientific evaluation method to compare the advantages and disadvantages of the different quality characteristics and to facilitate the comprehensive use of A. arguta resources. In this study, 26 different varieties of A. arguta were used for a comprehensive evaluation of the appearance, nutritional, and functional indices (active substance content, antioxidant capacity, and lipid-lowering ability) of the fruits. The 26 varieties of A. arguta were classified using the clustering heat map analysis method combined with sensory evaluation, and each category of characteristic was analyzed to explore its potential application value. The results showed significant differences in 20 quality indicators among the 26 varieties of A. arguta. Based on the correlation and principal component analysis results, the evaluation indicators were simplified and total phenols, sugar-acid ratio, soluble solid content, iron content, and vitamin C (VC) content were identified as critical indicators for evaluating the quality of A. arguta. Using principal component analysis to establish a comprehensive quality evaluation model for A. arguta, among the 26 samples tested, the five samples with the best comprehensive quality were ‘A15’, ‘Huanyou No.1’, ‘JL01’, ‘J061403’, and ‘J141901’, which have great value for targeted cultivation and development processing. After clustering heat map analysis of the 26 varieties of A. arguta into Class Ⅰ, Ⅱ, Ⅲ, Ⅳ, each category contained 6, 13, 2, and 5 varieties, respectively. Class Ⅰ had a high content of active substances and was suitable for the development of high-value-added functional health food products. Class II had superior sensory quality and was suitable for fresh consumption. Class Ⅲ had high VC content and was suitable for the preparation of VC dietary supplements. Class Ⅳ had good processing quality and was suitable for the processing of fruit wine, fruit juice, fruit preserves, jams, canned food, and other general food. A evaluation system established in this study may provide a theoretical reference for selecting and breeding A. arguta varieties and promoting their planting and processing in China.

     

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