Rapid, low-cost technologies generate high-value soils information for planners and farmers

by | October 7, 2016
Categories: Blog, News

By Keith Shepherd

Soil samples awaiting infrared scanning at the CGIAR’s Soil-Plant Spectral Diagnostic Laboratory based at ICRAF. Photo by Keith Shepherd/ICRAF

Soil samples awaiting infrared scanning at the CGIAR’s Soil-Plant Spectral Diagnostic Laboratory based at ICRAF. Photo by Keith Shepherd/ICRAF

A big, risky decision for smallholder farmers is what type and how much fertilizer to apply to their crops. There is lot of uncertainty about how the crops will respond, with a risk that the farmers will even lose when they harvest and sell the produce. Testing the soil beforehand and knowing how plants will respond can play an important role in reducing this risk. But the high cost and lack of access to testing services have been major bottlenecks for famers in developing countries.

Similarly, planners in governments, the private sector and non-governmental organizations who are working out what to supply to smallholder farmers are also faced with large uncertainties on what types and combinations of inputs to supply and where, in relation to the local soils. For example, a number of agencies in Africa are designing fertilizer blending and liming programmes and so need to know how strongly acid soils are and what soil micronutrients may be limiting in different areas. Existing soil maps do not provide up-to-date information on specific soil properties that are needed to guide such decisions.

New advances in rapid, low-cost soil analytical techniques in the laboratory that simply measure light reflecting from a soil sample are reducing the cost of measuring soil properties.

Time and cost savings

Soil infrared spectroscopy allows a soil sample to be scanned in just 30 seconds and the resulting fingerprint used to predict a number of soil properties based on calibration databases. And this costs just $1 compared with at least $100 using conventional soil testing methods.

These new approaches are being deployed by the Africa Soil Information Service (AfSIS), which has recently launched a 250-metre resolution soil-properties map of Africa.

Collecting soil samples. Photo: ICRAF

Collecting soil samples. Photo: ICRAF

AfSIS is helping Ethiopia, Ghana, Nigeria and Tanzania to establish national soil information systems and services based on soil spectroscopy and digital soil-mapping technology. The CGIAR’s Soil-Plant Spectral Diagnostic Laboratory, one of the founding members of AfSIS, based at the World Agroforestry Centre (ICRAF) in Nairobi, now supports a network of spectral laboratories across 10 African countries.

Our Soil Spectral Lab supports a number of sustainable land management projects, new predictive agronomy projects, private and NGO enterprises providing farm advisory services, as well as agricultural monitoring initiatives, including Vital Signs and the CGIAR’s own network of Sentinel Landscapes sites.

Spectral technology has the capability to provide affordable soil testing and advisory services to smallholder farmers and is already beginning to be deployed by rural soil testing services.

Georeferencing for better decisions

However, up until now the spectral technology has only been used to predict conventional soil diagnostic tests, which are themselves not that good at predicting yield response to inputs. The future lies with calibrating crop responses directly to spectral tests and linking these with decision models that can tell farmers what is the likelihood of obtaining a given level of response. In addition the private sector and development agents promoting soil improving interventions, or wishing to demonstrate good soil management practice, can now afford to monitor soil organic matter levels at their field sites.

Another benefit of the spectral technology is that countries can now afford to analyse large numbers of georeferenced samples, with sufficient sample density per unit area, to map soil properties in 3D (depth wise and area wise). This is done by calibrating the georeferenced spectral estimates of soil properties to reflectance measurements from remote sensing imagery. The resulting predictive models, which use new machine learning techniques, allow estimates of soil properties to be made for each pixel of the satellite image. With the availability of satellite imagery and from space and now unmanned aerial vehicles at ever increasing spatial resolution (250 metres to sub-metre), it is becoming possible to make high resolution soil property maps at low cost. This information can then be included in decision models to better target and optimise programmatic interventions.

It is appropriate to celebrate these successes and to further promote the scaling out this technology in this coincidence of the International Year of Soils (IYS 2015) and the International Year of Light and Light-based Technologies (IYL 2015) and in support of the achievement of the Sustainable Development Goals during this Global Soil Week 2015.

Keith Shepherd is Principal Soil Scientist at the World Agroforestry Centre (ICRAF).

For more information see:





Further reading

Shepherd KD and Walsh MG (2007) Infrared spectroscopy—enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries. Journal of Near Infrared Spectroscopy 15: 1-19.

Shepherd, K.D., Shepherd, G. Walsh, M.G. (2015). Land health surveillance and response: a framework for evidence-informed land management. Agricultural Systems  (2015), pp. 93-106. DOI information: 10.1016/j.agsy.2014.09.002

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