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The objective of this study is to measure the growth status of garlic crops in open-field using VIS/NIR hyperspectral imaging system. A hyperspectral imaging system capable of acquiring a wavelength of 400 nm to 1000 nm was used, and the hyperspectral image data were analyzed by PLSR (Partial Least Square Regression), LS-SVM (Least Square Support Vector Machine), CNN (Convolutional Neural). Networks) and Spatial-Spectral Residual network (SSRN). The optimal model was able to classify the difference by fertilization levels with an accuracy of 80 to 99%, and the difference by soil covering with an accuracy of 93-99. These results show that the Vis/NIR hyperspectral imaging system and data can be utilized to predict the growth status of garlic.
Hwanjo Chung,Seunghwan Wi, andHoonsoo Lee
"Application of hyperspectral imaging technique for monitoring the growth status of garlic (allium sativum) (Conference Presentation)", Proc. SPIE PC12545, Sensing for Agriculture and Food Quality and Safety XV, PC1254503 (13 June 2023); https://doi.org/10.1117/12.2663747
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Hwanjo Chung, Seunghwan Wi, Hoonsoo Lee, "Application of hyperspectral imaging technique for monitoring the growth status of garlic (allium sativum) (Conference Presentation)," Proc. SPIE PC12545, Sensing for Agriculture and Food Quality and Safety XV, PC1254503 (13 June 2023); https://doi.org/10.1117/12.2663747