A Portable in-situ Near-infrared LEDs-based Soil Nitrogen Sensor
AbstractMonitoring soil Nitrogen content for palm oil cultivation is paramount to produce high-quality palm oil. This study aims to investigate the feasibility of a designed portable near-infrared (NIR) light emitting diodes (LEDs)-based soil Nitrogen in predicting the soil Nitrogen content using NIR light. First, soil samples that collected from a local oil palm plantation were scanned using the developed sensor and followed by a conventional method, i.e. Kjeldahl analysis. A chemometric analysis was applied in this study to develop a predictive model by choosing the best result from an artificial neural network (ANN). The performance of ANN was validated using leave one out cross-validation. Results indicate that ANN with one hundred number of hidden neurons outperformed with a root mean square error of cross-validation of 0.031. This finding suggests that the proposed sensor coupled with ANN is promising to satisfactorily predict soil Nitrogen content.
Open access licenses
Open Access is by licensing the content with a Creative Commons (CC) license.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.