Modelling future potato (Solanum tuberosum L.) production in Tasmania and Kenya
Borus, DJ and Mohammed, C and Parsons, D and Boersma, M and Schulte-Geldermann, E, Modelling future potato (Solanum tuberosum L.) production in Tasmania and Kenya, Acta Horticulturae, 1118 pp. 217-223. ISSN 0567-7572 (2016) [Refereed Article]
Potato (Solanum tuberosum L.), like many other crops, will be affected by changes in temperature, rainfall and other factors related to climate change.
Global warming due to increased greenhouse gases concentrations continue to be felt with many of the observed changes since the 1950s unprecedented over decades to millennia.
In Africa, the increase in mean annual temperature is likely to be more than 2°C and by about 2.9°C in Tasmania by 2100 in the high emission scenario.
In eastern Africa, precipitation and intensity of high-rainfall events are projected to increase while in Tasmania the seasonal and regional distribution will change although the mean annual rainfall for Tasmania will not vary significantly.
In north-west Tasmania where potatoes are grown, a reduction in the total annual rainfall is predicted.
Potato is planted in more than 125 countries and consumed daily by more than a billion people, making it the worldRSQUOs most important non-grain crop.
In Tasmania, potato represents 70% of the vegetable industry total value and 9% of the stateRSQUOs total agricultural value.
It is the second most important food crop in Kenya.
The new APSIM-potato model can be used to simulate the effects of N-fertilizer levels, sowing dates, plant density and irrigation treatments but has only been tested in a limited range of locations and for limited cultivars.
This is the first time that the APSIM potato module is being tested and compared under both Tasmanian and Kenyan conditions.
Field trials using a range of cultivars were conducted both in Tasmania (2012/13) and Kenya (2013/14) where input data (management, soil, crop and daily weather data) were measured.
The analysis of Kenyan data is on-going but for Tasmania, the preliminary simulation results highlight the need for parameter adjustment to improve its predictive performance.