Abstract
The crop yield potential of world soybean from 2019 to 2028 has been projected using ARIMA model based on the yields from 1961 to 2018. Both annual global mean temperature and the yields of world soybean have been projected to rise during the ensuing decade 2019-2028. Projected average yields of world soybean varies from 2841 to 3276 kg ha-1 while 4324 to 4807 kg ha-1 in the case of top (national) yields of world soybean. Annual global mean temperatures may vary from 15.0 to 15.3oC and likely to exert positive impact on average yield (R squared = 0.80) while negative on top yield (R squared = 0.40) of world soybean. It may be concluded that for world soybean yields in 2019 to 2028, the opportunities for improving production should be dependent on both high and low-yielding countries as the yield remained between 30 and 70 per cent of potential limit i.e. in middle place around the turn-point of S-shaped curve in long-term trend partly affected by global warming.
Highlights
Soybean crop has been attracting academic attention for improving its potential yield in the future under climate change
The regression models constructed for estimating the yield of soybean in Far Eastern Federal District (FEFD) of Russia, which showed the soybean yield forecast for 2018 having a deviation from the actual yield in the range of 2.1-7.3 per cent based on 2007-2017 data (Stepanov et al, 2019)
Citing the soil water balance modeled, Petry et al (2020) investigated the crop coefficients, grain yield prediction, and economic return of soybean grown in Brazil at different levels of water deficit and price quotations, and found that crop yield and economic return were higher at 75 per cent of total available water (TAW) than the others
Summary
Soybean crop has been attracting academic attention for improving its potential yield in the future under climate change. Using the AquaCrop model, Tovjanin et al, (2019) estimated the impact of climate change on main field crops (maize and soybean) in the Republic of Serbia, and found an increase in maize (1 and 1.3 t ha-1) and soybean (1.9 and 2.8 t/ha) yields for the 2041-2070 and 2071-2100 periods. There is no lack of research reports on the yield or its potential of soybean modelled and partly related to climatic factors, but most are based on the principle of production function for specific variety from static biological dimension and at local or regional level, while few based on the theory of stochastic process for generic soybean from dynamic evolutionary dimension and at global level. In this paper, ‘time series’ model ARIMA (Autoregressive Integrated Moving Average) based on stationary stochastic process to estimate potential yield of world soybean under global warming was used. It is aimed to provide information on directing the production of soybean in the world facing global food insecurity deteriorated by the contradiction between the increase of human demand and the degradation of arable land
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