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A Near-Infrared Sensing Technique for Measuring the Quality of Potatoes

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  033137,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14074) @2003
Authors:   Sukwon Kang, Kang-Jin Lee, Wankyu Choi, Jae-Ryong Son, Dong-Soo Choi, Giyoung Kim
Keywords:   Potato, near-infrared, sorter, specific gravity, dry matter

Nearinfrared (NIR) spectroscopy is a promising technique for nondestructive sensing of agricultural product for multiple quality attributes. The objective of this research was to explore a NIR sensing technique in interaction mode for rapid acquisition of spectral information to predict the quality parameters of potatoes. The percentage of dry matter and specific gravity are important quality parameters for assessing the potential of potato tubers to produce acceptable yields of processed products with good textural and color quality attributes. In this research, the NIR calibration for dry matter and specific gravity was developed with an on-line system to predict and classify the specific gravity and dry matter of potatoes. The model predicted specific gravity of intact potatoes with 87% accuracy compared with the measured data, and the Standard Error of Correlation (SEC) was 0.0022. From the cross validation result, the correlation coefficient was 0.85 and the Standard Error of Prediction (SEP) was 0.0024. For the dry matter of intact potatoes, the correlation coefficient of calibration was 0.85 and the Standard Error of Correlation (SEC) was 0.60%. The correlation coefficient of prediction was 0.82 and the Standard Error of Prediction (SEP) was 0.66%. Thus, the developed model and the on-line VIS/NIR transmittance system were feasible to classify the potato by the specific gravity and dry matter.

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