Development and performance tests of an on-the-go detector of soil total nitrogen concentration based on near-infrared spectroscopy

Abstract

Soil total nitrogen (TN) concentration is an important soil nutrient parameter. However, the high-precision measurement of TN concentration in real time remains a challenge. Accordingly, an on-the-go TN concentration detector was developed on the basis of near-infrared spectroscopy. The modular concept and the extreme learning machine (ELM) algorithm were applied to design and model the detector, respectively. The detector consisted of three modules: a mechanical unit used to support the entire detection system, an optical unit for sensing soil in the soil detection trench and a control unit including the embedded ELM model for obtaining real-time readings of TN concentration. The ELM model was established using absorbance data at 1680, 1550, 1375, 1245, 1130 and 1070\xa0nm. Laboratory calibration and validation experiments were conducted to verify the performance of the detector. The coefficient of determination (R2) of the TN concentration of the ELM estimation model was 0.90, and the validation R2 was 0.82. Laboratory results showed that the developed detector exhibited stable performance and high precision. Field tests were conducted and the correlation coefficients between standard laboratory measurements and the detector were 0.82 in field operation and 0.91 in the laboratory. The experimental results showed that the detector can quantify TN in the field in real time with stable performance and high accuracy.