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中国精品科技期刊2020
沈海军,徐子昂,王文琪,等. 基于熵权法、灰色关联度法和低场核磁共振检测的苹果品质评价[J]. 食品工业科技,2024,45(1):231−238. doi: 10.13386/j.issn1002-0306.2023010032.
引用本文: 沈海军,徐子昂,王文琪,等. 基于熵权法、灰色关联度法和低场核磁共振检测的苹果品质评价[J]. 食品工业科技,2024,45(1):231−238. doi: 10.13386/j.issn1002-0306.2023010032.
SHEN Haijun, XU Ziang, WANG Wenqi, et al. Apple Quality Evaluation Based on Entropy Weight Method, Grey Relational Degree Method and Low-field Nuclear Magnetic Resonance Detection[J]. Science and Technology of Food Industry, 2024, 45(1): 231−238. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023010032.
Citation: SHEN Haijun, XU Ziang, WANG Wenqi, et al. Apple Quality Evaluation Based on Entropy Weight Method, Grey Relational Degree Method and Low-field Nuclear Magnetic Resonance Detection[J]. Science and Technology of Food Industry, 2024, 45(1): 231−238. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023010032.

基于熵权法、灰色关联度法和低场核磁共振检测的苹果品质评价

Apple Quality Evaluation Based on Entropy Weight Method, Grey Relational Degree Method and Low-field Nuclear Magnetic Resonance Detection

  • 摘要: 研究不同品种苹果的品质特性,建立苹果品质综合评价模型。以5个品种的苹果(天水花牛、阿克苏糖心、黄元帅、奶油富士、洛川红富士)作为研究对象,对其硬度、黏着性、咀嚼性、内聚性等4项质构特性和含水量、可滴定酸(Titratable acid,TA)、可溶性糖含量(Soluble sugar,SS)、可溶性固体含量(Soluble solid content,SSC)等4项理化指标进行检测,结合低场核磁共振检测技术,探究苹果水分分布与理化及质构特性间的关联性,通过主成分分析法确立可评价苹果品质的主要指标。基于熵权法对各核心指标赋予权重,并建立灰色关联度评价模型。结果表明,不同品种苹果的各指标存在显著性差异(P<0.05),其水分分布与质构特性和理化指标存在高度的相关性,确立了自旋-自旋弛豫时间T22(不易流动水)、T21(结合水)及TA、SS、SSC为核心指标。熵权法计算权重结果得出T22、T21之和为35.31%,占比最大,表明水分分布对苹果品质影响最大,由灰色关联度分析得出天水花牛和阿克苏糖心的品质较好。本研究所采用的方法,能够快速准确地建立苹果的品质评价模型,为包括苹果在内的果蔬品质评价提供新方法。

     

    Abstract: To study the quality characteristics of different apple varieties and establish a comprehensive evaluation model of apple quality, taking five varieties of apples (Tianshui Huaniu, Aksu Tangxin, Marshal Huang, Cream Fuji, and Luochuan Red Fuji) as the research object, the four texture characteristics, including hardness, adhesion, chewability, cohesion, and four physical and chemical indicators, including water content, titratable acid (TA), soluble sugar (SS), and soluble solid content (SSC) were tested. Combining the low-field nuclear magnetic resonance detection technology, the correlation between the water distribution and the physicochemical and texture characteristics of apple was explored, and the main indicators for evaluating apple quality were established by principal component analysis. Based on the entropy weight method, each core index was given weight, and a grey correlation degree evaluation model was established. The results showed that there were significant differences in various indexes of different varieties of apples (P<0.05), and there was a high correlation between their water distribution and texture characteristics and physical and chemical indexes. The spin-spin relaxation time T22 (immobilized water), T21 (bound water) and TA, SS, SSC were established as the core indexes. The weight calculated by entropy weight method showed that the sum of T22 and T21 was 35.31%, accounting for the largest proportion, indicating that the water distribution had the greatest impact on apple quality. The grey correlation analysis showed that the quality of Tianshui Huaniu and Aksu Tangxin was better. The method adopted in this study could quickly and accurately establish the quality evaluation model of apples, and provide a new method for the quality evaluation of fruits and vegetables including apples.

     

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