%0 Journal Article
	%A Kaewkarn Phuangsombat and  Arthit Phuangsombat and  Anupun Terdwongworakul
	%D 2017
	%J International Journal of Agricultural and Biosystems Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 127, 2017
	%T Classification of Germinatable Mung Bean by Near Infrared Hyperspectral Imaging
	%U https://publications.waset.org/pdf/10007400
	%V 127
	%X Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.

	%P 502 - 505