Potential Of On-The-Go Gamma-Ray Spectrometry For Estimation And Management Of Soil Potassium Site Specifically
High resolution data on plant available potassium (Ka) is crucial to optimize variable rate potassium fertilizer recommendations, and subsequently improve crop growth and yield. A gamma-ray passive spectrometry sensor was evaluated for on-the-go mapping and management of the spatial distribution of...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021
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| Online Access: | http://eprints.utem.edu.my/id/eprint/25531/2/J%20202101%20SUSTAINABILITY%20SMALL.PDF http://eprints.utem.edu.my/id/eprint/25531/ https://www.mdpi.com/2071-1050/13/2/661/htm |
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| Summary: | High resolution data on plant available potassium (Ka) is crucial to optimize variable rate potassium fertilizer recommendations, and subsequently improve crop growth and yield. A gamma-ray passive spectrometry sensor was evaluated for on-the-go mapping and management of the spatial distribution of Ka over a 8.4 ha field at Huldenberg, Belgium. During the on-the-go measurement, a 5 s sampling interval was used while driving at 3 km/h speed along 10 m parallel transects. Two calibration models to predict Ka across the field were developed and compared: (1) a simple third order polynomial function (3DPF) was established between the sensor reading of the naturally occurring radioactive isotope of potassium (K-40) and laboratory measured Ka and (2) a partial least squares regression (PLSR) model linking gamma-ray spectra and laboratory measured Ka. Although a relatively small number of samples (45 samples) were used for the development of the PLSR calibration model, the cross-validation analysis resulted in a very good performance with a coefficient of determination (R2) of 0.85, a residual prediction deviation (RPD) of 2.67, a root mean square error of cross-validation (RMSECV) of 2.29 (mg/100 g) and a ratio of performance to interquartile distance (RPIQ) of 2.61. This was a much better result that that obtained with the 3DPF model (R2 = 0.69). The spatial distribution of Ka developed based on 3DPF and PLSR
methods showed great similarity with the corresponding map developed using the data from the laboratory analysis. The calculated variable rate fertilizer recommendation based on gamma-ray data showed marginal differences in the amount of K2O fertilizer applied, compared to the uniform rate fertilization based on the conventional laboratory chemical soil analyses. The on-the-go measurement of Ka using gamma-ray spectrometry shows high potential, although the technology needs to be evaluated in a larger number of fields |
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