基于可见-近红外光谱和主成分分析的水果无损分类

K. Kusumiyati, Y. Hadiwijaya, I. Putri
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引用次数: 10

摘要

水果是健康所需的营养来源之一。水果的品质一般通过物理和化学性质来评定。水果内部品质的测量通常是通过破坏性技术来完成的。紫外、可见和近红外光谱(UV-Vis-NIR)是一种无损检测水果品质的技术。该技术可快速测定果实品质,测定后的果实完好无损,可用于市场销售。此外,紫外-可见-近红外光谱也可用于水果分类。利用300 ~ 1041 nm紫外-可见-近红外光谱和主成分分析(PCA)对不同品种水果进行分类。采用带9个平滑点的一阶导数savitzky-golay (dg1)和乘法散射校正(MSC)对光谱进行校正。结果表明,利用紫外-可见-近红外光谱法和主成分分析法结合MSC方法的光谱预处理,可以对各种类型的水果进行分类,成功率为100%,包括山瓜、冬瓜、芒果、番石榴、苹果和西葫芦。
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Non-Destructive Classification of Fruits Based on Vis-nir Spectroscopy and Principal Component Analysis
Fruits are one of the sources of nutrition needed for health. Fruit quality is generally assessed by physical and chemical properties. Measurement of fruit internal quality is usually done by destructive techniques. Ultraviolet, visible and near-infrared (UV-Vis-NIR) spec-troscopy is a non-destructive technique to measure fruit quality. This technique can rapidly measure the fruit quality, the measured fruit still remains intact, and can be marketed. Besides, UV-Vis-NIR spectrosco-py can also be used to classify fruits. The study aimed to classify var-ious types of fruits using UV-Vis-NIR spectroscopy with wavelengths of 300-1041 nm and Principal Component Analysis (PCA). First de-rivative savitzky-golay with 9 smoothing points (dg1) and multiplica-tive scatter correction (MSC) were applied to correct the spectra. The results showed that the use of uv-vis-nir spectroscopy and PCA com-bined with spectra pre-treatment of the MSC method were able to clas-sify various types of fruits with 100% success rate in all fruit samples including sapodilla, ridge gourd, mango, guava, apple and zucchini. 
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发文量
15
审稿时长
4 weeks
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