Agronomy Journal · 1970 · 62 citations · 0 references
AgricultureAgronomyCrop SciencesCrop ManagementCrop ProductionFarm ManagementAgricultural Production SystemsAgricultural TechnologyCrop Production EconomicsAgricultural Climate ImpactsClimate - Yield Temporal RelationshipsLinear Trend EstimationTime Series Trend AnalysisWeather-driven Yield AnalysisWeather-driven Yield PredictionYield-weather Correlation Analysis
Abstract Multiple curvilinear regression analysis was used to measure the influence of weather on the yield of soybeans. A linear time trend was introduced to measure the influence of technology. In the five states, Illinois, Indiana, Iowa, Missouri, and Ohio, yields increased at an annual rate of 21.5 kg per ha from 1930 to 1968. Highest yields have been associated with warmer than normal temperatures in June but with cooler than normal temperatures in July and August. Highest yields have been associated with normal precipitation from September through June and with above normal rainfall in July and August.