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Prediction of Moisture content in Maize leaves based on Near-infrared Spectroscopy

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

Citation:  Paper number  131618865,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: http://dx.doi.org/10.13031/aim.20131618865) @2013
Authors:   Jifeng Ning, Yu Sun, Shanshan Chen, Wenting Han
Keywords:   maize leaves moisture content near-infrared spectroscopy partial least squares regression nondestructive detection

Abstract. In this paper, we propose a novel measure method of the moisture content in maize leaves under different moisture treatment by the near-infrared spectroscopy technique. The reflectance spectral of maize leaves is acquired in the spectral range of 300 to 2500 nm by near-infrared imaging system. And the moisture content of the maize leaves is acquired by traditional baking method. Then the partial least square regression (PLSR) model was used to analyze the correlation between near-infrared data and moisture content measured by tradition baking method. Good correlations were found between moisture content in maize leaves and near-infrared spectral information. By our experimental results, the coefficient of determination is equal to 0.97 with SEC of 0.004 and SEP of 0.0032. This work provides an effective method for prediction of moisture content of maize leaves by near-infrared spectral technique.

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