Title : A multiple regression model of wheat grain yield in response to meteorological conditions in Gyeongsangnam province, Republic of Korea
Abstract:
We analyzed climate change and the relationship between weather conditions and wheat yield from the 1990/1991 to the 2019/2020 growing seasons. Growth stages of wheat were classified as seedling (phase I, early Nov. to mid-Dec.), overwintering (phase II, late Dec. to early Feb.), tillering (phase III, mid-Feb. to mid-Mar.), stem elongation (phase IV, late Mar. to mid-Apr.), ripening (phase V, late Apr. to late May). Mean daily air temperature during the wheat growing season in 2011-2020 was 0.2 ? higher than that from 1991-2000. Mean daily air temperature at the tillering and stem elongation stages was 0.7?, 0.6? higher, respectively in 2011-2020 than in 1991-2000. Precipitation during the wheat growing season in 2011-2020 was 61.7 mm greater than that from 1991-2000. Maximum daily air temperature at the overwintering stage was positively correlated with wheat yield in simple linear regression (R2=0.231, P=0.015), while other weather conditions were not significantly correlated with the yield. A multiple regression model of wheat yield and weather conditions at each growing stage was estimated as follows; wheat yield (Mg ha-1 ) = 7.60-0.133*Tmax(I)+0.059*Tmax(II)+0.114*Tmax(III)-0.228*Tmax(IV)-0.118*Tmax(V)+0.380* Tmin(IV)-0.132*Tmin(V)+0.001*P(I)-0.005*P(II)+0.002*P(III)-0.007*P(IV)-0.001*P(V). The model parameters having a high variance inflation factor were excluded. A root mean squared error (RMSE) and an adjusted coefficient of determination (R2 ) for the model were 0.390 Mg ha-1 , 0.369, respectively. Considering the poor goodness of fit, other factors such as agronomic practices or a government policy should be necessary for predicting wheat yield.
Auidence Take Away Notes:
- Climate change is a major issue in sustainability of agriculture. We evaluated changes in weather conditions for 30 years, analyzed correlation between wheat yield and weather conditions, and estimated wheat yield prediction model.
- The audience will know how weather conditions during the wheat growing season changed for past three decades in Republic of Korea
- The audience will be helpful to understand what climate change will affect wheat productivity.