近红外光谱定量和定性分析技术在鲜食葡萄果实无损检测中的应用

doi:10.3969/j.issn.1004-1524.2018.02.21

浙江农业学报 ›› 2018, Vol. 30 ›› Issue (2): 330-338.DOI: 10.3969/j.issn.1004-1524.2018.02.21

近红外光谱定量和定性分析技术在鲜食葡萄果实无损检测中的应用

章林忠^{1, 2}, 蔡雪珍¹, 方从兵^{1, *}

1.安徽农业大学园艺学院,安徽合肥 230036;
2.安徽农业大学理学院,安徽合肥 230036

收稿日期:2017-07-01 出版日期:2018-02-20 发布日期:2018-02-11
通讯作者: 方从兵,E-mail:fcb_ah@ahau.edu.cn
作者简介:章林忠(1980—),男,安徽太湖人,博士,讲师,主要从事生物统计和果树学研究。E-mail:zhanglinzhong@ahau.edu.cn
基金资助:
安徽省高等教育振兴计划人才项目(皖教秘人[2013]189号); 安徽省大别山农林特色产业协同创新中心项目

Application of NIR spectroscopy for nondestructive qualitative and quantitative analysis of table grapes berries

ZHANG Linzhong^{1, 2}, CAI Xuezhen¹, FANG Congbing^{1, *}

1.School of Horticulture, Anhui Agricultural University, Hefei 230036, China;
2.School of Sciences, Anhui Agricultural University, Hefei 230036, China

Received:2017-07-01 Online:2018-02-20 Published:2018-02-11

摘要/Abstract

摘要： 选取10种不同鲜食葡萄品种、3个不同成熟期和1种病害的果实共计188个葡萄果实样品,并采集果实样品的近红外光谱。建立了以葡萄果实的总酚、总糖、果糖、蔗糖和可溶性固形物为指标的偏最小二乘(PLS)定量分析模型,模型的可信度较高,除少数指标的相关系数在0.77~0.89,其余指标均在0.90以上,均方根误差在0.022~1.410。结合主成分分析法,对谱区为4 119.20~9 881.46 cm^-1的光谱建立了区分葡萄果实品种、成熟度和是否受病害的判别分析(DA)模型,模型的正识率依次为92.11%、88.89%和96.15%。研究表明,近红外检测技术可用于鲜食葡萄果实的5个主要内含物的定量分析以及果实品种、果实成熟度和有病虫害的二次果进行的定性识别。

关键词: 葡萄果实, 无损检测, 光谱分析, 近红外光谱, 化学计量学

Abstract: Ten different varieties of fresh grapes, 3 different mature period and 1 kind of diseased fruit with a total of 188 samples were selected as the research object, and the near infrared spectra of these samples collected by near-infrared spectrometers. Using partial least squares (PLS), the quantitative analysis model with higher credibility by determining the content of total phenol, total sugar, fructose, sucrose and soluble solids. The correlation coefficients of indicators were above 0.90 except minority were between 0.77 and 0.89, and root mean square error were all between 0.022 and 1.410. By combining with principal component analysis in 4 199.20~9 881.46 cm^-1 spectral region, the discriminant analysis (DA) model with correctness of 92.11%, 88.89% and 96.15% for variety identification, maturity identification and diseased fruit identification respectively has been established. This study showed that near infrared detection technology can not only be used for quantitative analysis of 5 main inclusions in fresh grape, but also be used for identification of varieties, maturity and diseased fruit of fresh grape.

Key words: fresh grape, nondestructive detection, spectroscopic analysis, NIR, chemometrics

中图分类号:

S123

章林忠, 蔡雪珍, 方从兵. 近红外光谱定量和定性分析技术在鲜食葡萄果实无损检测中的应用[J]. 浙江农业学报, 2018, 30(2): 330-338.

ZHANG Linzhong, CAI Xuezhen, FANG Congbing. Application of NIR spectroscopy for nondestructive qualitative and quantitative analysis of table grapes berries[J]. , 2018, 30(2): 330-338.

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近红外光谱定量和定性分析技术在鲜食葡萄果实无损检测中的应用

Application of NIR spectroscopy for nondestructive qualitative and quantitative analysis of table grapes berries

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