Sensor Technologies for Precision Soil Nutrient Management and Monitoring

Abstract

Problem statement: Growing concerns about the need to increase crop productivity without causing environmental injury have led to the deployment of site-specific strategies in soil nutrient management, where nutrients are applied in variable rates to fit local requirements. Variable rate application of nutrients is typically based on a rigorous sampling regime and time-consuming data analyses. The ability to monitor soil nutrient concentration efficiently is highly desirable. Approach: Onsite monitoring of soil nutrient concentration offers the opportunity for higher density measurements at relatively lower costs. This would allow for an efficient mapping of nutrient variability to facilitate variable-rate nutrient application. Results: Implementation of nutrient management programs using sensor technology potentially promotes environmental stewardship while maintaining crop productivity and profitability. Rapid and non-destructive quantification of spatially-variable soil nutrients has been made possible with on-the-go sensors such as optical, electromagnetic and electrochemical sensors. Conclusion: This review demonstrates the potential of on-the-go sensors for non-destructive and rapid characterization of soil nutrient variability within crop fields.

Spectral Soil Analysis for Fertilizer Recommendations by Coupling with Quefts for Maize in East Africa: A Sensitivity Analysis

“…The trade-off between the growing need for large scale soil information and its high cost could be resolved by a widespread use of diffuse reflectance soil spectroscopy (DRSS) in the visible-near infrared (vis-NIR) and the mid infrared (MIR) regions. The diffusely reflected/ absorbed spectral signatures have been proven to reliably predict important soil properties (Viscarra Rossel et al, 2016;Lausch et al, 2013;Bah et al, 2016;Shepherd & Walsh, 2007). They were also applied in digital soil mapping (Paul et al, 2019;Morais et al, 2018;Hengl et al, 2021;Brodský et al, 2011), evaluated for crop productivity and performance estimation , and for fertilizer decision making using a soil fertility categorical approach (Ng et al, 2020).…”