A novel on-line dual sensing system for soil property measurement and mapping
Real-time assessment of within-field soil fertility variation is crucial for making informed and sustainable decisions, like crop nitrogen (N) fertilization. Two commonly used soil sensors i.e., visible-near-infrared (vis-NIR) spectroscopy and ion-selective electrodes (ISE) have been reported to suc...
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Elsevier
2024-12-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524002454 |
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| author | Rukayat Afolake Oladipupo Muhammad Abdul Munnaf Parsat Sanganta Ajit Borundia Abdul Mounem Mouazen |
| author_facet | Rukayat Afolake Oladipupo Muhammad Abdul Munnaf Parsat Sanganta Ajit Borundia Abdul Mounem Mouazen |
| author_sort | Rukayat Afolake Oladipupo |
| collection | DOAJ |
| description | Real-time assessment of within-field soil fertility variation is crucial for making informed and sustainable decisions, like crop nitrogen (N) fertilization. Two commonly used soil sensors i.e., visible-near-infrared (vis-NIR) spectroscopy and ion-selective electrodes (ISE) have been reported to successfully estimate various soil macronutrients and nitrate-N, respectively, however, their integrated use for mapping a full-scale soil fertility variation has not been taken into consideration to date. The aim of this study is to use an integrated on-line dual-sensor system of vis-NIRS and ISE to estimate and map within-field variation in multiple soil fertility parameters including pH, organic carbon (OC), extractable- phosphorus (P), potassium (K), calcium (Ca), moisture content (MC) and nitrate-N. The sensing system was mounted to the three-point linkage of a tractor and surveyed two arable fields in Belgium. Partial least squares regression models for vis-NIRS sensor were calibrated and validated, while a linear regression model was established for validation of the ISE sensor. Geostatistical surface maps for on-line measured soil attributes were generated using the inverse distance weighting and ordinary kriging methods for ISE data and vis-NIR, respectively. The linear correlation confirms a very high similarity between ISE-measured nitrate-N and laboratory-analyzed nitrate-N (coefficient of determination (R2) = 0.93). Besides, the vis-NIRS demonstrates very good prediction accuracies for all the fertility attributes with R2 = 0.70–0.78, root mean square error (RMSE) =0.52–2.46 %, residual of prediction deviation (RPD) = 1.89–2.13 and the ratio of the performance to interquartile distance (RPIQ) = 1.72 – 6.56. Validation between laboratory and on-line measured soil maps also shows quite comparable spatial distribution patterns. Therefore, the proposed dual on-line sensor system has a high potential to estimate and map within-field spatial distributions of soil fertility attributes including nitrate-N, offering a basis for sustainable management decisions for precision soil and crop management. |
| format | Article |
| id | doaj-art-f0f7dc9caa8744f8b5ccd84c8911b9d1 |
| institution | DOAJ |
| issn | 2772-3755 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-f0f7dc9caa8744f8b5ccd84c8911b9d12025-08-20T02:50:09ZengElsevierSmart Agricultural Technology2772-37552024-12-01910064010.1016/j.atech.2024.100640A novel on-line dual sensing system for soil property measurement and mappingRukayat Afolake Oladipupo0Muhammad Abdul Munnaf1Parsat Sanganta2Ajit Borundia3Abdul Mounem Mouazen4Department of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumDepartment of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumDepartment of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumDepartment of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumCorresponding author.; Department of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumReal-time assessment of within-field soil fertility variation is crucial for making informed and sustainable decisions, like crop nitrogen (N) fertilization. Two commonly used soil sensors i.e., visible-near-infrared (vis-NIR) spectroscopy and ion-selective electrodes (ISE) have been reported to successfully estimate various soil macronutrients and nitrate-N, respectively, however, their integrated use for mapping a full-scale soil fertility variation has not been taken into consideration to date. The aim of this study is to use an integrated on-line dual-sensor system of vis-NIRS and ISE to estimate and map within-field variation in multiple soil fertility parameters including pH, organic carbon (OC), extractable- phosphorus (P), potassium (K), calcium (Ca), moisture content (MC) and nitrate-N. The sensing system was mounted to the three-point linkage of a tractor and surveyed two arable fields in Belgium. Partial least squares regression models for vis-NIRS sensor were calibrated and validated, while a linear regression model was established for validation of the ISE sensor. Geostatistical surface maps for on-line measured soil attributes were generated using the inverse distance weighting and ordinary kriging methods for ISE data and vis-NIR, respectively. The linear correlation confirms a very high similarity between ISE-measured nitrate-N and laboratory-analyzed nitrate-N (coefficient of determination (R2) = 0.93). Besides, the vis-NIRS demonstrates very good prediction accuracies for all the fertility attributes with R2 = 0.70–0.78, root mean square error (RMSE) =0.52–2.46 %, residual of prediction deviation (RPD) = 1.89–2.13 and the ratio of the performance to interquartile distance (RPIQ) = 1.72 – 6.56. Validation between laboratory and on-line measured soil maps also shows quite comparable spatial distribution patterns. Therefore, the proposed dual on-line sensor system has a high potential to estimate and map within-field spatial distributions of soil fertility attributes including nitrate-N, offering a basis for sustainable management decisions for precision soil and crop management.http://www.sciencedirect.com/science/article/pii/S2772375524002454Near-infrared spectroscopyIon selective electrodeSoil fertilityOn-line sensing |
| spellingShingle | Rukayat Afolake Oladipupo Muhammad Abdul Munnaf Parsat Sanganta Ajit Borundia Abdul Mounem Mouazen A novel on-line dual sensing system for soil property measurement and mapping Smart Agricultural Technology Near-infrared spectroscopy Ion selective electrode Soil fertility On-line sensing |
| title | A novel on-line dual sensing system for soil property measurement and mapping |
| title_full | A novel on-line dual sensing system for soil property measurement and mapping |
| title_fullStr | A novel on-line dual sensing system for soil property measurement and mapping |
| title_full_unstemmed | A novel on-line dual sensing system for soil property measurement and mapping |
| title_short | A novel on-line dual sensing system for soil property measurement and mapping |
| title_sort | novel on line dual sensing system for soil property measurement and mapping |
| topic | Near-infrared spectroscopy Ion selective electrode Soil fertility On-line sensing |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524002454 |
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