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http://dx.doi.org/10.5762/KAIS.2021.22.1.208

Discrimination of Internally Browned Apples Utilizing Near-Infrared Non-Destructive Fruit Sorting System  

Kim, Bal Geum (National Institute of Agricultural Sciences, Department of Agricultural Engineering)
Lim, Jong Guk (National Institute of Agricultural Sciences, Department of Agricultural Engineering)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.22, no.1, 2021 , pp. 208-213 More about this Journal
Abstract
There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.
Keywords
Non-Destructive; NIR Spectrum; Internal Flaw; Browning; Quality Evaluation;
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