Cassava is an important crop in Sub-Saharan Africa with relevance in the food economy and calorie intake of the population 1–3; however, the yields in most of the countries of this region are low (<10 t/ha)4. The African Cassava Agronomy Initiative (ACAI) project lead by The International Institute of Tropical Agriculture (IITA) aims to improve the quality and yields of cassava through the provision of feasible technologies in Nigeria, Tanzania, Democratic Republic of the Congo and Kenya.
One of the approaches of the project is to work in a decision support tool which will use available information on soils, weather and management to provide recommendation to farmers. This approach also includes the establishment of new trials to get additional information of the responses of the crop to different technologies. Additionally, the project is going to use the information collected for the development of models that represent the performance of the crop under different conditions which will be incorporated on the decision support tool.
As one of the PhD students of this project, my research focuses on the developing of a cassava model to simulate dynamics of the starch content in this crop under different management and environmental conditions. Because the rainfall pattern is one of the main factors affecting the starch content of cassava5–7, new trials have been established considering different planting and harvesting dates in Nigeria and Tanzania.
Although some people could think that modelers are just behind a computer generating simulations, the truth is that information must be collected to create and evaluate the models. Thus as part of my PhD work and my International Agroecology Experience required for the Global Agroecology Certificate, I was visiting some of the trials that will provide important inputs to the cassava starch model between May and July of 2017.
One of the main challenges of the trials has been the low rainfall at planting and the proliferation of weeds that have led to discard some of the planting dates and treatments due to low germination (on the left).
Given the amount of trials established in the project (more than 100 including other topics as fertilizer rates, intercropping and best planting practices), it is difficult to do frequent destructive sampling for all of them. Therefore, a non-destructive methodology is being implemented in most of the trials, which is complemented with the use of barcodes and forms available in Android mobile devices using the Open Data Kit (ODK) tool (on the right).
During my visit to Tanzania, the dry period (especially in the Lake zone) allowed the capture of images that illustrate the drought tolerance of cassava: one of the few food plants that was still green and surviving under those stressful condition (see left).
- Udensi, U. et al. Adoption of selected improved cassava varieties among smallholder farmers in South-Eastern Nigeria. Journal of Food, Agriculture and Environment 9, 329–335 (2011).
- Awotide, B. A., Abdoulaye, T., Alene, A. & Manyong, V. M. Assessing the extent and determinants of adoption of improved cassava varieties in south-western Nigeria. J. Dev. Agric. Econ. 6, 376–385 (2014).
- Ezedinma, C., Kormawa, P., Manyong, V. & Dixon, A. Challenges, opportunities and strategy for cassava subsector development in Nigeria. in Proceedings of the 13th ISTRC-Govt symposium (eds. Kapinga, R., Msabaha, M., Ndunguru, J. *, Lemaga, B. & Tusiime, G. *) 627–640 (2007).
- FAO. FAOSTAT. Food and Agriculture Organization of the United Nations, Statistics Division (2017).
- Sriroth, K., Piyachomkwan, K., Santisopasri, V. & Oates, C. G. Environmental conditions during root development: Drought constraint on cassava starch quality. Euphytica 120, 95–102 (2001).
- Santisopasri, V. et al. Impact of water stress on yield and quality of cassava starch. Ind. Crops Prod. 13, 115–129 (2001).
- Howeler, R. Agronomic practices for sustainable cassava production in Asia. (2007).