Drew D. Blasi, Kansas State University Christopher Redmond, Kansas State University
Abstract
This project aimed to project pasture hay yields based on annual precipitation totals in relation to climatology. Pasture hay is a vital crop to the success of Kansas producers. Kansas produces 6.03 billion pounds of red meat yearly resulting in a high demand for pasture hay to feed these cattle. This equates to 11% of the United States' total production and is the 3rd most by any state. This in turn generates about 11.2 billion dollars in yearly revenue and provides Kansans with ~17,000 jobs. Therefore, the need to project yields can have a substantial impact on the Kansas economy. Hay is cattle's main source of food with fields often grazed or hayed for feed later in the year. Regardless, harvested/provided hay gives cattle important nutrients and protein that allow maximum output later in sales, typically by weight. Without the availability of adequate hay, available food to raise cattle is limited, often resulting in large cattle sell-offs.
With the current beef trade hitting new highs, pasture hays play an even more important part in the future of Kansas and our nation economically.
This projection is done by using historical precipitation data to develop a running projection of hay yield (tons/acre) based on various thresholds at the state level. Historically normal precipitation was used in combination with percentiles to determine the likelihood of obtaining similar hay production as observed in history. Daily precipitation data is utilized with accumulated running totals during the optimal hay growing season, April through August. This period captures the optimal growth of both warm and cool-season grasses. Using these daily projections of statewide averages and percentages, we can project estimated amounts of moisture based on historical thresholds and provide estimates of hay production from archived yield data.
These projections showed a correlation between precipitation and pasture hay growth which stands at ~80%. This is statistically significant and proposed that such projections can be an accurate assessment of final hay yields. Running tests on May 1st, June 22nd, and August 1st has helped the model's accuracy in providing a more focused range of dates/years for the potential yield outcome. In comparing above-normal precipitation years to below-normal and average years the model was less accurate. However, historical projections accurately predict the yield for 70% of the last 25 years on all dates listed above. When analyzing below-normal and average precipitation years, projections resulted in 94% and 88% respectively. The model can be utilized throughout the hay growing season but becomes increasingly accurate as the growing season goes on. This would be expected due to the lack of potential outcomes becoming more limited as the season window for hay becomes smaller. However, even looking at data in late April/May we were able to accurately predict pasture yield in most case scenarios. With confidence in hay projections, producers can make better decisions on forage/production estimates which will result in a higher probability of profit and Kansas economic benefit.
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