Soil nitrogen is one of the crucial components for plant growth. An accurate diagnosis based on soil nitrogen information is the premise of scientific fertilization in precision agriculture. Soil nitrogen content acquisition based on near-infrared (NIR) spectroscopy shows the significant advantages of high accuracy, real-time analysis, and convenience. However, soil texture, soil moisture content, and drying temperature all affect soil nitrogen detection by NIR spectroscopy. In order to investigate the effects of drying temperature on calcium soil nitrogen detection and its characteristic bands, soil samples were detected at a 25 °C placement (ambient temperature) after 40 °C drying (medium temperature), 60 °C drying (medium-high temperature), 80 °C drying (high temperature), and 105 °C drying (extreme high temperature), respectively. Besides that, the original spectra were pretreated with five preprocessing methods, and the characteristic variables were selected by competitive adaptive reweighted squares (CARS) and backward interval partial least squares (BIPLS). The partial least squares (PLS) method was used for modeling and analysis. The predictive abilities were assessed using the coefficients of determination (R2
), the root mean squared error (RMSE), and the residual predictive deviation (RPD). As a result, the characteristic bands focus on 928–960 nm and 1638–1680 nm when soil was detected after 40 °C, 60 °C, and 80 °C drying. Calcium soil obtained the best prediction accuracy
after 40 °C drying by the method of CARS-BIPLS-PLS. Meanwhile, the prediction model also performed well when soil was detected after 60 °C drying
and 80 °C drying
. However, the calcium soil obtained the worst detection result when soil was placed at 25 °C. In conclusion, a low or extremely high drying temperature had an adverse influence on the soil nitrogen detection, and the 40 °C drying temperature as well as the CARS-BIPLS-PLS method were optimal to enhance the soil nitrogen detection accuracy.
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