In many African countries, including Zambia, actual crop yields are still much lower than the potential yields. Increasing agricultural productivity to reduce food insecurity is a major concern for many policy makers and governments.
Despite efforts such as subsidies on fertilizers, crop productivity has marginally increased in Zambia. This has been attributed to: (i) low soil fertility and (ii) blanket fertilizer recommendations limited to Nitrogen (N), Phosphorus (P) and Potassium (K) for an entire country ignoring soil heterogeneity. In addition, crop production may be limited by other nutrients than N, P and K, such as Calcium, Magnesium, Sulphur, Copper, Zinc, Molybdenum, Manganese and Boron. With climate change, yields could further be negatively affected. Currently, there is little knowledge on crop yield responses to applied multiple nutrients under variable environments. This holds especially for the long-term effects since nutrient additions change soil nutrient availabilities and their interactions in time, which in turn affect crop yields.
Aim of the project
The main objective of the project is to enhance the understanding of soil nutrient interactions and their dynamics, to improve crop productivity in the face of climate change in Zambia. This will be a contribution towards developing appropriately sustainable water and soil nutrient management practices in Zambia.
To assess short-term and long-term crop yield responses to inputs of multiple nutrients by combining multiple-nutrient omission trials with model-based approaches. Scientifically sound nutrient omission pot and field experiments will be carried, using maize as the study crop, being an important crop in Zambia. Nutrient omission trials are a good tool for nutrient assessments in the short- to medium term. The quantities applied per omission treatment will be a function of target crop yield, mean element concentrations in crop type, expected nutrient use efficiencies and available soil nutrients. Long term impacts of the multi-nutrient additions on soil quality will be assessed with the adapted dynamic soil model VSD+. Long term yield response to water- and nutrient inputs will be calculated with WOFOST. The crop simulation will be adjusted to suit local conditions and run with biased corrected climate data from Global Climate Models.