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DETECTION OF BLACK MOLD INFECTED FIGS BY USING TRANSMITTANCE SPECTROSCOPY

机译:通过使用透射光谱检测感染无感染的无花果的检测

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摘要

Environmental conditions (humidity, temperature, wind, etc.) and inappropriate processing and storage conditions effects the quality of agricultural products. Figs, like other agricultural products, are mostly affected by molds during drying and processing and the damage given by molds are hardly detected by visual controls. Aspergillus niger is a type of mold that penetrates into figs and turns the color into black when grows inside figs and that black structures cannot be usually observed from outside. These figs are usually detected by nailing method, which depends on penetrating a needle into the figs and taking some specimen to examine visually. However, this procedure is labor expensive and includes the risk of transmitting the molds to the sound figs. In this study, we propose a non-destructive and fast method to detect the black-mold contaminated figs by using transmittance spectroscopy. Figs are screened at 3648 spectral bands between 200 nm -1100 nm and classified by using the most relevant spectral bands. By using the most discriminative 5 spectral bands, 100% classification accuracy has been achieved.
机译:环境条件(湿度,温度,风等)和不恰当的加工和储存条件影响农产品的质量。如其他农产品,如其他农产品,在干燥和加工过程中主要受模具的影响,并且通过视觉控制难以检测模具的损坏。曲霉尼日尔是一种渗透到图1和图中的模具,并在图中生长时将颜色变为黑色,并且通常从外部观察到黑色结构。这些无花果通常通过钉状方法检测,这取决于将针穿透到图1和图2中并采取一些标本来视觉检查。然而,该程序劳动昂贵并且包括将模具传递到声音图的风险。在这项研究中,我们提出了一种非破坏性和快速的方法来通过使用透射光谱来检测黑模污染的无花果。图3是在200nm -1100nm之间的3648个频谱频带处筛选,并通过使用最相关的光谱频带进行分类。通过使用最辨别的5个光谱带,已经实现了100%的分类精度。

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