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不同采收期不同品种莲藕的营养品质变化规律及评价
引用本文:吴宇昊,戴芳,丛欣,祝振洲,李书艺,梅新,陈学玲.不同采收期不同品种莲藕的营养品质变化规律及评价[J].食品安全质量检测技术,2024,15(3):9-17.
作者姓名:吴宇昊  戴芳  丛欣  祝振洲  李书艺  梅新  陈学玲
作者单位:1. 武汉轻工大学硒科学与工程现代产业学院/国家富硒农产品加工技术研发专业中心/湖北省绿色富硒农产品精深加工工程技术研究中心; 2.农业农村部农产品冷链物流技术重点实验室/湖北省农业科学院农产品加工与核农技术研究所;3.湖北省农业科技创新中心农产品加工研究分中心,1. 武汉轻工大学硒科学与工程现代产业学院/国家富硒农产品加工技术研发专业中心/湖北省绿色富硒农产品精深加工工程技术研究中心; 2.农业农村部农产品冷链物流技术重点实验室/湖北省农业科学院农产品加工与核农技术研究所;3.湖北省农业科技创新中心农产品加工研究分中心,1. 武汉轻工大学硒科学与工程现代产业学院/国家富硒农产品加工技术研发专业中心/湖北省绿色富硒农产品精深加工工程技术研究中心,1. 武汉轻工大学硒科学与工程现代产业学院/国家富硒农产品加工技术研发专业中心/湖北省绿色富硒农产品精深加工工程技术研究中心,1. 武汉轻工大学硒科学与工程现代产业学院/国家富硒农产品加工技术研发专业中心/湖北省绿色富硒农产品精深加工工程技术研究中心,2.农业农村部农产品冷链物流技术重点实验室/湖北省农业科学院农产品加工与核农技术研究所;3.湖北省农业科技创新中心农产品加工研究分中心,2.农业农村部农产品冷链物流技术重点实验室/湖北省农业科学院农产品加工与核农技术研究所;3.湖北省农业科技创新中心农产品加工研究分中心
基金项目:国家重点研发计划项目(2018YFD0401301)、湖北省农业科技创新项目(2021-620-000-001-025)、湖北省高校优秀中青年科技创新团队(T2020012)
摘    要:目的 探究不同采收期不同品种莲藕的营养成分和活性成分的变化规律。方法 选取5个采收期的4个品种莲藕,测定蛋白质、淀粉等指标。采用主成分分析和聚类分析进行综合评价,并建立莲藕品质评价模型。结果 在采收期内,莲藕淀粉含量呈现先上升后下降再上升的趋势,可溶性糖的变化趋势与其相反;总酚含量整体呈现先上升后下降的趋势;蛋白质、膳食纤维等指标呈现不同的变化规律。主成分分析法提取出PC1、PC2、PC3 3个主成分因子,特征值依次为2.274、1.933、1.023,累积方差贡献率达87.170%。不溶性膳食纤维、可溶性膳食纤维、可溶性总糖、淀粉、总酚和总黄酮6个指标可以用来综合评价莲藕营养品质。综合评价发现, 9月采收的八月粉,10月的鄂莲6号,2月的鄂莲10号和鄂莲11号,营养品质较好,优于其他采收期。3月采收的4个品种莲藕的综合营养品质较低。结论 在采收期内, 4个品种莲藕的营养物质动态规律存在一定差异。基于主成分分析和聚类分析的分析方法能够科学评价不同采收期莲藕的综合营养品质,为莲藕育种、加工等提供支撑。

关 键 词:莲藕  营养品质  评价  主成分分析  聚类分析
收稿时间:2023/11/30 0:00:00
修稿时间:2024/2/2 0:00:00

The change and evaluation of nutritional quality of different varieties of lotus root in different harvest periods
WU Yu-Hao,DAI Fang,CONG Xin,ZHU Zhen-Zhou,LI Shu-Yi,MEI Xin and CHEN Xue-Ling.The change and evaluation of nutritional quality of different varieties of lotus root in different harvest periods[J].Food Safety and Quality Detection Technology,2024,15(3):9-17.
Authors:WU Yu-Hao  DAI Fang  CONG Xin  ZHU Zhen-Zhou  LI Shu-Yi  MEI Xin and CHEN Xue-Ling
Affiliation:1. School of Modern Industry for Selenium Science and Engineering, Wuhan Polytechnic University/National R&D Center for Se-Rich Agricultural Products Processing/ Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products2. Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs/Institute of Agro-product Processing and Nuclear Agricultural Technology, Hubei Academy of Agricultural Sciences 3. Agro-product Processing Research Sub-center of Hubei Innovation Center of Agriculture Science and Technology,1. School of Modern Industry for Selenium Science and Engineering, Wuhan Polytechnic University/National R&D Center for Se-Rich Agricultural Products Processing/ Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products2. Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs/Institute of Agro-product Processing and Nuclear Agricultural Technology, Hubei Academy of Agricultural Sciences 3. Agro-product Processing Research Sub-center of Hubei Innovation Center of Agriculture Science and Technology,1. School of Modern Industry for Selenium Science and Engineering, Wuhan Polytechnic University/National R&D Center for Se-Rich Agricultural Products Processing/ Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products,1. School of Modern Industry for Selenium Science and Engineering, Wuhan Polytechnic University/National R&D Center for Se-Rich Agricultural Products Processing/ Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products,1. School of Modern Industry for Selenium Science and Engineering, Wuhan Polytechnic University/National R&D Center for Se-Rich Agricultural Products Processing/ Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products,2. Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs/Institute of Agro-product Processing and Nuclear Agricultural Technology, Hubei Academy of Agricultural Sciences 3. Agro-product Processing Research Sub-center of Hubei Innovation Center of Agriculture Science and Technology,2. Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs/Institute of Agro-product Processing and Nuclear Agricultural Technology, Hubei Academy of Agricultural Sciences 3. Agro-product Processing Research Sub-center of Hubei Innovation Center of Agriculture Science and Technology
Abstract:Objective To investigate the changing law of nutrients and active ingredients of different varieties of lotus root at different harvesting periods. Methods Four varieties of lotus root from five harvesting periods were selected to measure protein, starch and others . Principal component analysis and cluster analysis were used for comprehensive evaluation, and a lotus root quality evaluation model was established. Results During the harvest period, the starch content of lotus roots showed a trend of initially increasing, then decreasing, and then increasing again, the trend of soluble sugars was the opposite. The total phenolic content showed an overall trend of increasing and then decreasing. Protein and dietary fiber indicators showed different patterns of change. Principal component analysis extracted three main component factors, PC1, PC2, and PC3, with eigenvalues of 2.274, 1.933, and 1.023, respectively, contributing to a cumulative variance of 87.17%. Insoluble dietary fiber, soluble dietary fiber, total soluble sugar, starch, total phenols and total flavonoids can be used to comprehensively evaluate the nutritional quality of lotus root. The comprehensive evaluation revealed that the August-farinose lotus harvested in September, E Lian No.6 harvested in October, E Lian No.10 and E Lian No.11 harvested in February had better nutritional quality compared to other harvest periods. The comprehensive nutritional quality of the four varieties of lotus roots harvested in March was relatively low.. Conclusion During the harvest period, there were some differences in the nutrient dynamics of the four varieties of lotus root. The analysis method based on principal component analysis and cluster analysis can scientifically evaluate the comprehensive nutritional quality of lotus root at different harvest times, and provide support for lotus root breeding, processing and so on.
Keywords:Lotus root  Nutritional quality  Evaluation  Principal component analysis  Cluster analysis
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