On-farm adoption of individual and groups of precision agriculture technologies has grown in the past 15 years. Based on a sample of 545 farm observations collected by the Kansas Farm Management Association, farm adoption of bundles of embodied knowledge and information intensive technologies was analyzed using a Markov transition approach. Three separate analyses estimated transition probabilities to show the adoption of bundles of embodied knowledge technologies, the adoption of bundles of information intensive technologies, and the adoption of variable rate technologies contingent on prior adoption of embodied knowledge and/or information intensive technologies. Each analysis was estimated for two separate time periods (2009–2012) and (2013–2016). The probability that farms retain the same bundle or transition to a different bundle by the next time period are reported. The results indicate that persistence with the same technology bundle is the predominant behavior and that this behavior has strengthened in the study’s most recent time period.
Farmers may be interested in claiming remedies after farm data are misappropriated. Expert witnesses must valuate farm data within the farm gate and aggregated as a community for each player before estimating damages. Estimated actual damages, unjust enrichment, and reasonable royalty are presented from the farmer’s perspective and misappropriating defendant’s rebuttal.
Miller, N.J, Griffin, T.W., Goeringer P., Ellixson A., Shanoyan, A. 2018, Choices
Rosburg Farms is a crop farm in Northwest Iowa specializing in corn and soybean production. The oldest farm operator was looking toward retirement while the youngest generation was identifying an entry strategy into the operation. The overall goal of this research was to demonstrate how whole-farm planning models can be adapted to evaluate a potential intergenerational transition. Specific objectives were 1) to present how whole farm resources such as machinery, labor, and time constraints were collected and inventoried and 2) determine how additional rented land affects crop mix and machinery resource requirements. Data specific to Rosburg Farms were entered into an existing whole-farm linear programming model for regional- and farm-specific information. Farm-specific parameters included labor, machinery, crop rotations, and available acreage. Results indicated additional fieldwork could be completed with available labor and machinery. The process of adapting planning models is of interest to a wide spectrum of Extension personnel; and model results are applicable beyond the case study farm to other beginning farmers, farms anticipating intergenerational transition, and succession planning specialists.
Rosburg, B., Griffin, T.W. 2018, Journal of the National Association of County Agricultural Agents
Financial vulnerability has been observed across agricultural production regions; however, uncertainty regarding farms’ persistence within specific profitability categories exists. This study compared farm characteristics that persist in most and least profitable categories and then evaluated the probability that farms transitioned among profitability categories. Using 425 Kansas Farm Management Association (KFMA) farms that were present for the 20-year period 1994–2013, the persistence of remaining or transitioning to another profitability category was tested. Specifically, Markov transition probabilities were estimated for Kansas and the six regional KFMA regions. Comparisons of farms that persist in the highest and lowest profitability categories revealed no dramatic differences in acreage or other physical characteristics. Kansas farms tend to persist in their current profitability category, suggesting that operator skill and/or quality of farmland dominate random factors. In general, transition probabilities were greater for the highest and lowest profitability categories than for the middle categories. Farms were observed switching from highest to lowest profitability categories between 5% and 20% of the time within one year. Farmers were likely to stay in the highest profitability group more than half the time. By contrast, farmers were likely to stay in the lowest profitability group 42% of the time. Just like with the most profitable group, the least profitable group has a greater likelihood of remaining at the bottom, indicating that random events do not cause persistence.
Stabel, J.S., Griffin, T., Ibendahl, G. 2018, Journal of Applied Farm Economics
The conventional ethanol mandates set forth by the renewable fuel standards in the Energy Independence and Security Act of 2007 resulted in increased demand for corn. This study compares the economic viability of planting corn in the Southern Mississippi River Basin (SMRB), an area traditionally characterized by rice and cotton farms. The Purdue Crop-Linear Programming model analyzed financial data to optimize crop selection. The cropping optimization was performed at eight commodity price levels and three input cost levels for 24 scenarios. The investigation indicated corn competed favorably with established SMRB crops only at specific price/input cost levels (7 of the 24 scenarios).
Wright R., Griffin T.W., Guha G., Bouldin J. 2018, Journal of the American Society of Farm Managers and Rural Appraisers
This article examines the challenge and opportunities of Big Data, and concludes that these technologies will lead to relevant analysis at every stage of the agricultural value chain. Big Data is defined by several characteristics beyond size, particularly, the volume, velocity, variety, and veracity of the data. We discuss a set of analytical techniques that are increasingly relevant to our profession as one addresses these issues. Ultimately, we resolve that agricultural and applied economists are uniquely positioned to contribute to the research and outreach agenda on Big Data. We believe there are relevant policy, farm management, supply chain, consumer demand, and sustainability issues where our profession can make major contributions. The authors are thankful to the anonymous reviewers and editor Craig Gundersen for helpful comments. Support was provided by the Mississippi Agricultural and Forestry Experiment Station Special Research Initiative.