Partition Management of Soil Nutrients Based on Capacitive Coupled Contactless Conductivity Detection

Yuanyuan Wei, Rujing Wang, Junqing Zhang, Hongyan Guo and Xiangyu Chen ()
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Yuanyuan Wei: National Engineering Research Center for AgroEcological Big Data Analysis & Application, School of Internet, Anhui University, Hefei 230039, China
Rujing Wang: Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Junqing Zhang: Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Hongyan Guo: Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Xiangyu Chen: Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

Agriculture, 2023, vol. 13, issue 2, 1-13

Abstract: A method based on capacitively coupled contactless conductivity detection (C4D), which has been proven effective for the rapid detection of available soil potassium content, was firstly proposed to apply to soil nutrient detection. By combining a detection signal spectrum analysis, geographic information system (GIS) data, and a cluster analysis, a soil nutrient management system to match the detection device was developed. This system included six modules: soil sample information management, electrophoresis analysis, quantitative calculation, nutrient result viewing, cluster analysis, and nutrient distribution map generation. The soil samples, which were collected from an experimental field in Xuchang City of Henan Province, were analyzed using the C4D and flame photometer methods. The results showed that the detection results for the soil samples obtained via the two methods were in good agreement. C4D technology was feasible for the detection of the soil available nutrients and had the advantages of a high timeliness, low sample volume, and low pollution. The soil nutrient management system adopted the hierarchical clustering method to classify the grid cells of the experimental field according to the nutrient detection results. A soil nutrient distribution map displayed the spatial difference in nutrients. This paper provides a systematic solution for soil nutrient zone management that includes nutrient detection, signal analysis, data management for the nutrient zone, and field nutrient distribution map generation to support decision making in variable fertilization.

Keywords: capacitively coupled contactless conductivity detection; available nutrients; partition management of soil nutrients; cluster analysis (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: 2023
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