Innovative research methods inspire land health action
Land degradation is an environmental and developmental problem with ramifications for food security. World-leading soil analysis by the World Agroforestry Centre is helping to overcome the lack of existing information systems addressing land degradation.
“Evidence-based knowledge of soil health helps to determine where and how land degradation occurs,” says Keith Shepherd, Head of the Centre’s Land Health Research Program. “Records of soil analysis show us that the availability of phosphorus in African soils is low, a major concern when few smallholder farmers on the continent can afford mineral fertilizers”
“While land degradation is clearly known to be a major environmental and developmental problem, there is little concrete evidence and existing information systems to address it.”
Shepherd and his team are using tools such as infrared spectroscopy to achieve cost effectiveness and faster results for soil analysis. While the technology is available off the shelf, most of the techniques and methods have been developed in-house by Centre scientists and technicians. The data generated also serves as the premier data for Africa Soil Information Services (AfSIS).
The primary machine the team uses is the mid-infrared (MIR) Fourier spectrometer because it can handle 1000 samples a day as opposed to 400 which was all that could be achieved with older technology. The strength of MIR data has been boosted by regional infrared labs in Cote D’Ivoire, Kenya, Malawi, Mali, Mozambique, and Tanzania set up by the team to speed up data acquisition. In the near future, Shepherd’s team will be able to submit spectra over the internet to the Centre’s prediction engine and receive estimated values of various soil properties in return. This will ultimately mean there will be reliable data across Africa concerning key land health indicators such as soil organic carbon.
Other land health indicators are a soil’s ability to resist erosion. A laser diffraction particle analyser is used by the team to simulate the behaviour of soils during water and wind erosion, and to diagnose susceptibility to erosion and other soil physical problems.
Lab Technician, Emily Barasa comments, “Data collected ultimately leads to knowledge about soil hydrology, and unlike the previous tedious and error-prone ways, sample preparation is almost not required since the soil can be used just as it is”. This is important information because the extent to which erosion affects soils depends mostly on soil hydrology and soil mineralogy.
Soil mineralogy in turn has a bearing on many other soil functions such as nutrient content and its ability to retain organic matter. The team sees that soil mineralogy can be used as a key component of a model that can predict many other soil qualities and therefore give a quick overall indication of soil health. Faster data means quicker responses can be undertaken to combat land health issues.
Looking to the future, the team is aiming for full automation of their data management process. As data analyst Andrew Sillar says, “The data captured from different machines come in different formats and these have to be harmonized.” Once done, the combination of data allows everything to be known about a soil sample quickly and in a user-friendly format. A consistent data format across Africa will be used to inform policy and action towards preventing and reversing land degradation in Africa and improving farmer livelihoods.