著者
Kittipon APARATANA Daitaro ISHIKAWA Kanvisit MARAPHUM Khwantri SAENGPRACHATANARUG Hitoshi AGARIE Takeshi SHIKANAI Munehiro TANAKA Eizo TAIRA
出版者
Asian Agricultural and Biological Engineering Association
雑誌
Engineering in Agriculture, Environment and Food (ISSN:18818366)
巻号頁・発行日
vol.15, no.2, pp.72-80, 2022 (Released:2022-12-04)
参考文献数
33

The production of sugar is adversely affected by unhealthy sugarcane, which decreases the yield and quality and is difficult to detect through non-destructive tests. This study aims to accurately differentiate between healthy and unhealthy sugarcane in a laboratory environment using a portable visible near-infrared spectrometer with multivariate analyses. The spectra of 100 each of healthy and unhealthy sugarcane parts are analyzed in this study. The classification rates of the partial least-squares discriminant analysis and support vector machine classification of healthy models are 100 % and 91.9 %, respectively, while the classification rates of unhealthy models are 65.2 % and 78.3 %, respectively. The overall results demonstrate that NIR spectroscopy and multivariate analyses are effective at classifying healthy and unhealthy sugarcane.