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Feasibility of Near-Infrared Spectroscopy for Rapid Detection of Available Nitrogen in Vermiculite Substrates in Desert Facility Agriculture

Pengfei Zhao, Jianfei Xing, Can Hu, Wensong Guo, Long Wang, Xiaowei He, Zhengxin Xu and Xufeng Wang
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Pengfei Zhao: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Jianfei Xing: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Can Hu: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Wensong Guo: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Long Wang: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Xiaowei He: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Zhengxin Xu: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
Xufeng Wang: College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China

Agriculture, 2022, vol. 12, issue 3, 1-13

Abstract: Fast and precise estimation of the available nitrogen content in vermiculite substrates promotes prescription fertilization in desert facility agriculture. This study explored near-infrared spectroscopy for rapid detection of the available nitrogen content in vermiculite substrates in desert facility agriculture. The spectra of vermiculite matrices with different available nitrogen contents were collected through a self-assembled near-infrared spectrometer. Partial least squares expression (PLSR) established the available nitrogen spectrum prediction model optimized using different pretreatments. After pretreatment, the prediction model of the available nitrogen spectrum was simplified by adopting three feature extraction methods. A comprehensive comparison of the results of each prediction model showed that the prediction model combining the first derivative with SG smoothing pretreatment was the best. The correlation coefficients of the corresponding calibration and prediction sets were 0.9972 and 0.9968, respectively. The root mean square errors of the calibration and prediction sets were 149.98 and 159.65 mg/kg, respectively, with 12.57 RPD. These results provide a feasible method for rapidly detecting the available nitrogen content of vermiculite substrates in desert facility agriculture.

Keywords: vermiculite; near-infrared spectroscopy; nondestructive detection; available nitrogen (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
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