ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Hebbal, Bangalore, 560 024, Karnataka, India
2LISAH, Univ. Montpellier, IRD, INRAE, Institut Agro, AgroParisTech, Montpellier, France
3Indo-French Cell for Water Sciences, IRD, Indian Institute of Science, Bangalore, India
1ICAR-Central Coastal Agricultural Research Institute, Goa, India
The soils in India are highly diverse and spread across a vast geographic expanse. To address issues like food security, environmental sustainability, and economic progress, there is a need for systematic soil data. Traditional methods of evaluating soil resources are not sufficient to achieve the desired outcomes within the required timeframe. Furthermore, limited access to remote areas with rugged terrains, extreme temperatures, and challenging conditions both in terms of time and resources makes it difficult to use the conventional approaches. Therefore, an amalgamation of technology is a logical alternative. In the present article, we have reviewed a state-of-art technology – Visible and near-infrared (Vis-NIR, 350-2500 nm) and mid-infrared laboratory spectroscopy (MIR, 2500-25,000 nm) applications in different parts of India. We have primarily focused on Vis-NIR and MIR spectral range, soil parameters, predictive models, pre-processing techniques, significant statistical findings, and researchers’ opinions about the results. We also highlighted the limitations and constraints of soil spectroscopic studies. Our interpretation of the reviews suggests the potential utility of Vis-NIR and MIR spectroscopy as an efficient and effective tool for soil assessment. However, the limited number of studies available across the country indicates that there is a need for greater push and adoption of this technology. We conclude that with the growing adoption of the technology among young researchers and the strategic collaboration with global partners, spectroscopic soil studies will soon witness impressive achievements in India.
Spectroscopy, Visible, Near-infrared, Mid-infrared, Predictive models, Accuracy estimates