Plant Soil Environ., 2023, 69(12):596-607 | DOI: 10.17221/421/2023-PSE

Hyperspectral analysis of the content of the alkali-hydrolysed nitrogen in the soil of a millet fieldOriginal Paper

Tingyu Zhu1, Zhiqiang Wang1, Zilin Zhang1, Xiuhan He1, Gangao Li1, Zongbao Huang2, Lili Guo3, Zhiwei Li1,2, Huiling Du4
1 College of Agricultural Engineering, Shanxi Agricultural University, Jinzhong, P.R. China
2 College of Information Science and Engineering, Shanxi Agricultural University, Jinzhong, P.R. China
3 Agricultural Extension Center, Qin County, Changzhi, P.R. China
4 Department of Basic Sciences, Shanxi Agricultural University, Jinzhong, P.R. China

Hyperspectral imaging technology has emerged as a prominent research area for quantitatively estimating soil nutrient content owing to its non-destructive, rapid, and convenient features. Our work collected the data from soil samples using the hyperspectrometer. Then, the data were processed. The competitive adaptive reweighted sampling (CARS) algorithm reduced the original 148 bands to 13, which accounted for 8.8% of the total bands. These selected bands possess a certain level of interpretability. Based on the modelling results, it can be concluded that the prediction model constructed by the least squares support vector machine (LSSVM) exhibited the highest accuracy. The coefficient determination, root mean square error, and ratio performance deviation were 0.8295, 2.95, and 2.42, respectively. These findings can provide theoretical support for the application of hyperspectral technology in detecting the content of the AHN in soil. Moreover, they can also serve as a reference for the rapid detection of other soil components.

Keywords: modern precision agriculture; soil fertility; characteristic bands selection; model building; content prediction

Received: October 18, 2023; Revised: November 12, 2023; Accepted: November 13, 2023; Prepublished online: December 13, 2023; Published: December 20, 2023  Show citation

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Zhu T, Wang Z, Zhang Z, He X, Li G, Huang Z, et al.. Hyperspectral analysis of the content of the alkali-hydrolysed nitrogen in the soil of a millet field. Plant Soil Environ. 2023;69(12):596-607. doi: 10.17221/421/2023-PSE.
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