Vol. 115 No. 1 (2021)
Research Papers

Sensitivity of Potato Yield and Biomass to Climate Change Effects in Gisozi, Burundi, and Washington, USA, and Assessment of LINTUL4 Model Behavior

Abate Feyissa Senbeta
Hawassa University, Biology Department, Hawassa, Ethiopia
Iwan Supit
Wageningen UR, Wageningen, The Netherlands
Dieudonne Harahagazwe
International Potato Center (CIP)
Published June 29, 2021
How to Cite
Senbeta, A. F., Supit, I., & Harahagazwe, D. (2021). Sensitivity of Potato Yield and Biomass to Climate Change Effects in Gisozi, Burundi, and Washington, USA, and Assessment of LINTUL4 Model Behavior. Journal of Agriculture and Environment for International Development (JAEID), 115(1), 5-30. https://doi.org/10.12895/jaeid.20211.1132

Abstract

 Understanding climate change effects on crop production and evaluate the effectiveness of adaptation strategies in both developed and developing countries is of key importance. Crop simulation models can provide useful insight on the effects of increasing temperatures and rising CO2 concentrations [CO2] as well as rainfall variations. In this study, the LINTUL4 model was used to study the sensitivity effect of five temperature (T) levels (-3, 0, 3, 6, and 9oC above/below minimum/maximum temperatures), three precipitation (W) changes (30% decrease, baseline and 30% increase), and CO2 levels (baseline(360), 450, 540, 630 and 720ppm) on nutrient limited yield (Yn), water limited yield (Yw), water and nutrient limited yield (Ynw) and potential yield (Yp) of potato crop in high-input Washington, USA and low-input Gisozi, Burundi. The maximum weight of the tuber yield and aboveground biomass for Yp and Yw in Gisozi, and Yn and Yp in Washington was observed at combinations of lower temperature and elevated [CO2]. For Gisozi, maximum tuber yield for Yn and Ynw was observed at [CO2] of less than 720ppm. The results suggest that nutrient supply will continue to be the major limiting factor for potato production under elevated [CO2] in Gisozi, and water availability will limit Yw and Ynw rain-fed production in Washington. Generally, the LINTUL4 model performs well with few data input, but fails to predict the differential effect of high temperature on assimilate partitioning to aboveground and belowground biomass.