Abstract
Precision agriculture is an agricultural concept doing the right things, in the right place, at the right time to increase production, decrease usage of fertilizer, pesticide, and water or protect the environment. It is necessary to understand accurate information of fields for proper field management. For this purpose, soil sensors have been studied to obtain soil information by predicting the amount of moisture and nitrogen in soil by using VIS-NIR spectrum. In this article, we built regression models between VIS-NIR spectrum and the amount of soil moisture, carbon, and nitrogen, electric conductivity, and pH by using PLS method. In addition, we proposed variable selection method, GAWLS, and validated availability and general versatility of the method. As a result, we revealed GAWLS is useful method for prediction of soil properties compared with PLS with all variables and GAPLS method.
