Abstract
Soil organic matter (SOM) is a major indicator of soil fertility and nutrients. In this study, a soil organic matter measuring method based on an artificial olfactory system (AOS) was designed. An array composed of 10 identical gas sensors controlled at different temperatures was used to collect soil gases. From the response curve of each sensor, four features were extracted (maximum value, mean differential coefficient value, response area value, and the transient value at the 20th second). Then, soil organic matter regression prediction models were built based on back-propagation neural network (BPNN), support vector regression (SVR), and partial least squares regression (PLSR). The prediction performance of each model was evaluated using the coefficient of determination (R2), root-mean-square error (RMSE), and the ratio of performance to deviation (RPD). It was found that the R2 values between prediction (from BPNN, SVR, and PLSR) and observation were 0.880, 0.895, and 0.808. RMSEs were 14.916, 14.094, and 18.890, and RPDs were 2.837, 3.003, and 2.240, respectively. SVR had higher prediction ability than BPNN and PLSR and can be used to accurately predict organic matter contents. Thus, our findings offer brand new methods for predicting SOM.
Highlights
Soil organic matter (SOM) is defined as the sum total of all organic carbon-containing substances in the soil, which consists of the plant and animal residues at various stages of decomposition, cells and tissues of soil organisms, and well-decomposed substances [1,2]
Soil organic matter regression prediction models were built based on back-propagation neural network (BPNN), support vector regression (SVR), and partial least squares regression (PLSR)
These results indicate that SOM content in the study area shows a spatial variation trend
Summary
Soil organic matter (SOM) is defined as the sum total of all organic carbon-containing substances in the soil, which consists of the plant and animal residues at various stages of decomposition, cells and tissues of soil organisms, and well-decomposed substances [1,2]. SOM is composed of elements and compounds; the main elements include C, H, O and N, accounting for 52%–58%, 34%–39%, 3.3%–4.8%, and 3.7%–4.1%, respectively, followed by P and S, while compounds include sugars, organic acids, aldehydes, alcohols, ketones, fibers, hemicellulose, lignin, nitrogen-containing compounds, fats, waxes, resins, and tannins [3]. SOM is a key indicator of soil fertility and nutrients [4,5]. Though organic matter accounts for less than 5% of soil mass [6], it is a major energy source for soil microbes and a key nutrition source (e.g., nitrogen, phosphorus, sulfur) for crops [7]. A decrease in SOM content usually implies a decline of soil quality [7].
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