Next Article in Journal
Cold Tolerance Mechanisms in Mungbean (Vigna radiata L.) Genotypes during Germination
Previous Article in Journal
Spatiotemporal Variation in the Land Use/Cover of Alluvial Fans in Lhasa River Basin, Qinghai–Tibet Plateau
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

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

1
National Engineering Research Center for AgroEcological Big Data Analysis & Application, School of Internet, Anhui University, Hefei 230039, China
2
Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
3
Zhongke Hefei Institutes of Collaborative Research and Innovation for Intelligent Agriculture, Hefei 231131, China
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(2), 313; https://doi.org/10.3390/agriculture13020313
Submission received: 30 December 2022 / Revised: 19 January 2023 / Accepted: 25 January 2023 / Published: 28 January 2023
(This article belongs to the Section Artificial Intelligence and Digital Agriculture)

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 capacitively coupled contactless conductivity detection; available nutrients; partition management of soil nutrients; cluster analysis

Share and Cite

MDPI and ACS Style

Wei, Y.; Wang, R.; Zhang, J.; Guo, H.; Chen, X. Partition Management of Soil Nutrients Based on Capacitive Coupled Contactless Conductivity Detection. Agriculture 2023, 13, 313. https://doi.org/10.3390/agriculture13020313

AMA Style

Wei Y, Wang R, Zhang J, Guo H, Chen X. Partition Management of Soil Nutrients Based on Capacitive Coupled Contactless Conductivity Detection. Agriculture. 2023; 13(2):313. https://doi.org/10.3390/agriculture13020313

Chicago/Turabian Style

Wei, Yuanyuan, Rujing Wang, Junqing Zhang, Hongyan Guo, and Xiangyu Chen. 2023. "Partition Management of Soil Nutrients Based on Capacitive Coupled Contactless Conductivity Detection" Agriculture 13, no. 2: 313. https://doi.org/10.3390/agriculture13020313

APA Style

Wei, Y., Wang, R., Zhang, J., Guo, H., & Chen, X. (2023). Partition Management of Soil Nutrients Based on Capacitive Coupled Contactless Conductivity Detection. Agriculture, 13(2), 313. https://doi.org/10.3390/agriculture13020313

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop