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Laser-Based imaging for Cocoa Pods Maturity Detection
Food and Bioprocess Technology ( IF 5.3 ) Pub Date : 2019-10-25 , DOI: 10.1007/s11947-019-02350-7
Nuradila Athirah Lockman , Norhashila Hashim , Daniel I. Onwude

Non-destructive and laser-based technologies have been explored widely in recent years as a way to monitor fresh produce and crops quality in the agriculture sector. In this study, the effectiveness of laser-induced backscattering imaging (LLBI) was investigated to determine the firmness and colour of cocoa pods at different maturity stages. The LLBI system with 1 mm laser diode beam diameter emitting at 658 nm and 705 nm wavelengths were used to capture backscattered images of Theobroma cacao at three different maturity stages, which were unripe, ripe and over-ripe. The samples were also measured using reference measurement such as colorimeter and handheld penetrometer for measuring colour and firmness, respectively, in order to compare with the LLBI. Results indicated that chroma (C) regressed linearly well with the backscattering parameters with a coefficient of determination (R2) of 0.755 for 658 nm and 0.800 for 705 nm. Classification of samples according to their maturity stages resulted in 90% correctly classified samples into an unripe group using a laser diode at 658 nm and 95% at 705 nm. These findings also revealed that LLBI with laser diode emitted light at 705 nm wavelength gave better evaluation and classification results compared with 658 nm. This study has demonstrated the ability of non-destructive LLBI technique to evaluate the maturity stages of cocoa pods.



中文翻译:

基于激光的可可豆成熟度检测成像

近年来,无损和基于激光的技术已被广泛探索,作为一种监测农业部门新鲜农产品和农作物质量的方法。在这项研究中,研究了激光诱导的反向散射成像(LLBI)的有效性,以确定在不同成熟阶段的可可豆荚的硬度和颜色。使用在658 nm和705 nm波长处发射的直径为1 mm的激光二极管光束的LLBI系统捕获可可可可的反向散射图像在三个不同的成熟阶段,分别是未成熟,成熟和过度成熟。还使用参考测量(例如色度计和手持式渗透计)分别测量样品的颜色和硬度,以便与LLBI进行比较。结果表明,色度(C)与反向散射参数线性回归良好,具有确定系数(R 2658 nm的0.755)和705 nm的0.800)。根据样品的成熟阶段对样品进行分类,使用激光二极管在658 nm和705 nm在95%的样品中,将90%的样品正确分类为未成熟的组。这些发现还表明,与658 nm相比,带有激光二极管的LLBI在705 nm波长处发出的光给出了更好的评估和分类结果。这项研究证明了非破坏性LLBI技术评估可可豆荚成熟期的能力。

更新日期:2019-10-25
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