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[利用高光谱技术估算覆膜新鲜菠菜叶片的货架期]

[Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film].

作者信息

Zhou Li-ping, Zhao Yan-ru, Yu Ke-qiang, He Yong, Fang Hui, Ye Xu-jun

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2017 Feb;37(2):423-8.

Abstract

In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380~1 030 nm) and NIR (874~1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.

摘要

为延长水果和蔬菜的保质期,人们会在其表面覆盖塑料薄膜以提高保水性并防止外部细菌侵入。通过预测包装水果和蔬菜的保质期来准确评估其品质具有重要意义。本研究采用高光谱技术结合化学计量学方法,对处于相同环境下的新鲜菠菜叶片的保质期进行评估。从300片菠菜叶(75盘)中采集了覆盖可见 - 近红外(380~1 030 nm)和近红外(874~1 734 nm)范围的高光谱数据,这些菠菜叶在4℃下储存5个时间段(0天、2天、4天、6天、8天)。同时,测定了所有菠菜叶的叶绿素含量。提取了300片菠菜叶(训练集200片,预测集100片)的平均光谱。然后,对来自5个保质期时间段的200个光谱的训练集进行主成分分析(PCA),结果显示出明显的聚类。根据光谱数据和我们先前赋予不同储存期的虚拟水平建立了偏最小二乘判别分析(PLS - DA)模型。预测集的总判别准确率分别为83%(可见 - 近红外)和81%(近红外)。结果表明,利用高光谱技术结合化学计量学方法可实现对新鲜菠菜保质期的分类和预测,这为消费者评估包装菠菜的品质提供了理论指导,并为进一步研究开发用于检测水果和蔬菜保质期的仪器提供了技术支持。

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