基于高光谱成像的阳山地区桃子产地认证

摘要：阳山地区桃子是中国地理标志产品（（ CGIIA），品质优良，经济价值高，价格高于普通桃子。然而，由于市场上掺 假现象严重，不同品种的外观相似，该地区桃子的产地认证具有挑战性。本研究旨在开发一种基于高光谱成像结合群组 稀疏表示（（ GSR）分类器的有效方法，用于阳山地区桃子的产地认证，并使用高效液相色谱（（ HPLC）分析来解释生理代 谢的高光谱指纹。从阳山和南京两个相距不远的桃子产地县采集了两个品种，‘白凤’和‘胡菁’。阳山地区的桃子总糖含量 较高，糖酸比也较高，这可能是由于昼夜温差较大造成的。在400–1000nm范围内，区分阳山地区桃子的有效波段与花青 素等色素含量有关，而在近红外波段（（ 1000–1900nm），蔗糖和酸对不同类型桃子的区分起着重要作用。本研究将提出的 GSR分类器与其他5个分类器进行了比较，结果表明，GSR分类器在几毫秒的在线认证时间内实现了99.3%的总体分类 准确率。此外，对另一收获季节的桃子的分析表明，GSR 分类器的平均验证准确率为 95.8%。高光谱成像结合生理代谢 分析对阳山地区桃子的产地认证具有潜在的应用价值。

关键词：高光谱成像 桃子 地理产地 群体稀疏表示分类器 高效液相色谱 生理代谢

期刊：Postharvest Biology and Technology

DOI：https://DOI.org/10.1016/j.postharvbio.2020.111320

设备：GaiaField

Authentication of the geographic origin of Yangshan region peaches based on hyperspectral imaging

Abstract：Peaches from the Yangshan region, a China-protected geographical indication product (CGIIA), has high eco nomic value because of excellent quality, and price is premium over ordinary peaches. However, authentication of the origin of peaches from this region is challenging because of adulteration in the market and the similar appearance of different cultivar. This research was aimed at developing an effective method based on hyper spectral imaging combined with a group sparse representation (GSR) classifier for the geographic origin authentication of Yangshan region peaches and to interpret the hyperspectral fingerprint with physiological metabolism using high-performance liquid chromatography (HPLC) analysis. Two cultivars, ‘Baifeng’ and ‘Huj ing’, were collected from two peach-producing counties a short distance, from Yangshan and Nanjing regions. Higher contents of total sugars and a higher sugar-acid ratios were found in peaches from Yangshan region probably due to the large differences between day and night temperature. The effective bands for distinguishing fruit from Yangshan region in the range of 400–1000 nm were related to the contents of anthocyanin and some other pigments, while in the near-infrared range (1000–1900 nm), sucrose and acids played important roles in distinguishing different peach types. This research compared the proposed GSR classifier with five other clas sifiers, and the results showed that the GSR classifier achieved an overall classification accuracy of 99.3% in a few milliseconds of online authentication time. Moreover, analysis of peaches from another harvest season resulted in an average accuracy of 95.8% verification of the GSR classifier. Hyperspectral imaging combined with physiological metabolism analysis has potential for the origin authentication of Yangshan region peaches.

Keywords：Hyperspectral imaging Peach Geographic origin Group sparse representation classifier HPLC Physiological metabolism