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Hyd: Researcher at ICRISAT develops scalable solution to assess soil degradation

Hyderabad, June 25 (UNI) Researchers at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) have developed an innovative and scalable approach to assess soil degradation across semi-arid agricultural landscapes using a combination of proximal and satellite-based diffuse reflectance spectroscopy (DRS).
The study titled “Assessing Soil Degradation in Agricultural Landscapes of Semi-Arid Tropics Using Proximal and Remote Sensing-Based Diffuse Reflectance Spectroscopy,” recently published by the British Society of Soil Science, offers an innovative, quick, and cost-effective alternative to traditional laboratory soil testing methods.
This method cuts assessment time from weeks to mere minutes, the Institute said in a release here today.
By linking degradation maps with real-world crop yields, the research also reveals a critical finding—that irrigation could shield farms from degradation’s worst impacts, offering a lifeline for rainfed agriculture in semi-arid zones.
“By enabling fast and cost-effective soil degradation assessment, we are empowering farmers and policymakers with timely insights to protect soil health, boost resilience, and secure food systems in the semi-arid tropics. This innovation perfectly aligns with India's and the global South's urgent need for climate-smart tools that bridge the lab-to-field gap,” stated Dr Stanford Blade, Deputy Director General–Research and Innovation, ICRISAT.
Soil degradation is a critical challenge in semi-arid tropics, threatening agricultural productivity and food security.
Traditional methods for assessing soil degradation involve labor-intensive laboratory analyses, making frequent monitoring difficult.
ICRISAT’s study demonstrates that DRS—a quick, non-destructive technique can accurately estimate a Soil Degradation Index (SDI) by analyzing key soil properties such as organic carbon, erodibility, and nutrient availability.
Using laboratory-based spectroscopy and Sentinel-2 satellite imagery, the team successfully mapped soil degradation across dryland agricultural landscapes in Maharashtra, India.
The results showed high accuracy, with laboratory DRS achieving an R² of 0.81 and satellite-based estimates an R² of 0.52, proving the feasibility of large-scale monitoring.
“This research is about democratizing soil health knowledge. Beyond diagnosing degradation, our goal is to catalyse a paradigm shift in how vulnerable food systems anticipate and adapt to soil threats, ensuring resilience becomes embedded in every acre and every policy decision,” noted Dr Rebbie Harawa, Global Research Program Director–Resilient Farm and Food Systems, ICRISAT.
Dr Kaushal K. Garg, Principal Scientist–Natural Resource Management at ICRISAT, emphasized that by fusing proximal spectroscopy with Sentinel-2 satellite data, the team has achieved an 81 per cent accuracy rate in quantifying soil degradation, a significant first for semi-arid agroecosystems. He underscored that this is not just remote sensing; it is a precision tool specifically calibrated to the realities of smallholder farms, where each data point can directly inform irrigation investments or guide restoration priorities.
DRS drastically reduces the time and cost of soil degradation assessment compared to traditional methods.
Sentinel-2 satellite data enabled SDI mapping at 10-meter resolution, identifying degradation hotspots.
The study revealed that rainfed crops experienced yield declines in degraded soils, while irrigated crops showed resilience, highlighting irrigation as a potential mitigation strategy.
The approach is particularly valuable for resource-limited regions, enabling policymakers and farmers to implement targeted soil restoration measures.
This research marks a major milestone in soil health monitoring.
Dr Israr Majeed, Lead Author and Associate Scientist at ICRISAT, noted that while the current model applies to bare soils, future models will seek to harness hyperspectral remote sensing to assess soil health even under crops and vegetation. This innovation could revolutionize monitoring across all farmlands, taking precision agriculture to new heights. UNI KNR SSP
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