利用激光反向散射成像技术鉴定印度尼西亚地区柑橘的地理产地

IF 6.3 Q1 AGRICULTURAL ENGINEERING Smart agricultural technology Pub Date : 2024-08-05 DOI:10.1016/j.atech.2024.100527
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引用次数: 0

摘要

据报道,印度尼西亚地区的柑橘(Citrus nobilis Lour.)因其诱人的营养、保健和感官特性而具有很高的经济价值。然而,由于掺假和视觉外观的相似性,鉴定地理原产地具有挑战性。因此,本研究旨在开发一种基于激光反向散射成像(LLBI)的有效方法,用于鉴定该地区柑橘的地理来源。研究人员从印尼四大柑橘主产区棉兰、玛琅、瞻博和班宇旺吉地区共采集了 200 份柑橘样本。大约发射了三种不同波长(即 450、532 和 648 纳米)的激光来生成反向散射图像。此外,还结合使用了灰度级共现矩阵(GLCM)方法和支持向量机(SVM)算法,分别提取纹理特征和建立分类模型。在此背景下,比较了线性、径向基函数和多项式等三种核函数在鉴定柑橘地理来源方面的作用。结果表明,所提出的技术在地理产地鉴定方面达到了 96.667 % 的准确率和 3.333 % 的表观误差。拟议的 LLBI 技术采用了 450 nm 的激光波长和多项式核函数作为最佳组合,以产生可靠的预测能力。这项研究对推动传感技术设备鉴定地理原产地(特别是柑橘类水果)具有重要意义。
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Implementation of laser-light backscattering imaging for authentication of the geographic origin of Indonesia region citrus

Citrus fruit (Citrus nobilis Lour.) from the Indonesian region is reported to have high economic value due to attractive nutritional, nutraceutical, and sensory attributes. However, authenticating the geographic origins is challenging because of adulteration and similarity in visual appearance. Therefore, this study aimed to develop an effective method based on laser-light backscattering imaging (LLBI) for authentication of the geographic origin of the region citrus. A total of 200 citrus samples were collected from Medan, Malang, Jember, and Banyuwangi regions, which were the four main citrus-producing areas in Indonesia. Approximately three different laser wavelengths, namely 450, 532, and 648 nm were beamed to produce the backscattering image. Furthermore, a combination of the gray-level co-occurrence matrix (GLCM) method and support vector machine (SVM) algorithm was applied to extract texture features and build a classification model, respectively. In this context, three kernel functions, such as linear, radial basis function, and polynomial, were compared in authenticating the geographic origin of citrus. The results showed that the proposed technique achieved 96.667 % accuracy and 3.333 % apparent error for authentication of the geographic origin. The proposed LLBI technique applied a laser wavelength of 450 nm and a polynomial kernel function as the best combination to produce reliable predictive power. This study held valuable implications for advancing sensing technology devices to authenticate geographic origin, specifically citrus fruit.

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