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An ISE-based On-Site Soil Nitrate Nitrogen Detection System.
Li, Yanhua; Yang, Qingliang; Chen, Ming; Wang, Maohua; Zhang, Miao.
Afiliação
  • Li Y; Key Laboratory on Modern Precision Agriculture System Integration Research of Ministry of Education, China Agricultural University, Beijing 100083, China. 15001228421@163.com.
  • Yang Q; Key Laboratory on Modern Precision Agriculture System Integration Research of Ministry of Education, China Agricultural University, Beijing 100083, China. qingliangyang@cau.edu.cn.
  • Chen M; Key Laboratory on Modern Precision Agriculture System Integration Research of Ministry of Education, China Agricultural University, Beijing 100083, China. mercury@cau.edu.cn.
  • Wang M; Key Laboratory on Modern Precision Agriculture System Integration Research of Ministry of Education, China Agricultural University, Beijing 100083, China. wangmh@cau.edu.cn.
  • Zhang M; Key Lab of Agricultural Information Acquisition Technology of Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China. wangmh@cau.edu.cn.
Sensors (Basel) ; 19(21)2019 Oct 28.
Article em En | MEDLINE | ID: mdl-31661786
ABSTRACT
Soil nitrate-nitrogen (NO3--N) is one of the primary factors used to control nitrogen topdressing application during the crop growth period. The ion-selective electrode (ISE) is a promising method for rapid lower-cost in-field detection. Due to the simplification of sample preparation, the accuracy and stability of ISE-based in-field detection is doubted. In this paper, a self-designed prototype system for on-site soil NO3--N detection was developed. The procedure of spinning centrifugation was used to avoid interference from soil slurry suspension. A modified Nernstian prediction model was quantitatively characterized with outputs from both the ISE and the soil moisture sensor. The measurement accuracy of the sensor fusion model was comparable with the laboratory ISE detections with standard sample pretreatment. Compared with the standard spectrometric method, the average absolute error (AE) and root-mean-square error (RMSE) were found to be less than 4.7 and 6.1 mg/L, respectively. The on-site soil testing efficiency was 4-5 min/sample, which reduced the operation time by 60% compared with manual sample preparation. The on-site soil NO3--N status was dynamically monitored for 42 consecutive days. The declining peak of NO3--N was observed. In all, the designed ISE-based detection system demonstrated a promising capability for the dynamic on-site monitoring of soil macronutrients.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article