Analysis methods for landscape-scale site-specific agricultural datasets have been adapted from a wide range of quantitative disciplines. Due to spatial effects expected at landscape scales with respect to yield affecting factors, inference from aspatial analyses may lead to inefficient statistical inference. When spatial correlation exists within a random variable e.g. explanatory variables such as elevation or soil characteristics, spatial statistical methods can provide unbiased and efficient estimates on which to base economic analyses and farm management decisions. Simple continuous terrain variables derived from spatially lagged independent variable transformation of relative terrain position allowed models to be estimated using familiar linear aspatial models without introducing the problems associated with interpolated data in inferential spatial statistics. Using site-specific data from three example fields, cross regressive elevation variables complemented topographic attributes, rather than replacing them in a range of statistical models. Results indicated that cross regressive elevation variables, especially relative elevation, reduced estimation problems due to correlation among independent variables and bias arising from spatially interpolated data in statistical analysis.

Griffin, T., Lowenberg-DeBoer, J. 2019, Precision Agriculture 

Seedlings
Sunrise over the Wheat Field

We combined field studies to regional soil databases with the objective of presenting a protocol to forecast regional gains in winter wheat (Triticum aestivum L.) forage and grain yield and revenue, from liming or selecting a variety tolerant to acidic soils. First, we developed forage and grain yield response curves to soil pH using a variety by soil pH study conducted during 3 yr (2013–2015) at two Oklahoma locations. Second, we used a database of soil pH samples representing 93% of the wheat growing region of the state (n = 11,905) coupled with 15‐yr average county yield and harvested area to estimate potential gains for grain‐only and dual‐purpose scenarios. Relative grain yield maximized at soil pH of 5.8 for sensitive varieties and 4.8 for tolerant varieties. Forage yield maximized at soil pH of 6.0 for sensitive varieties and 5.5 for tolerant varieties. About 35% of the region had pH limiting to dual‐purpose and 28% to grain‐only production. Liming could improve grain‐only statewide yield in 0.14 Mg ha−1 and revenue in US$19 ha−1, and adoption of tolerant varieties could increase yield in 0.11 Mg ha−1 and revenue in $10 ha−1. Liming could improve dual‐purpose revenue in $37 ha−1 and variety selection in $28 ha−1 due to improved yield and forage. Potential additional statewide wheat production resulting from variety selection is 53,800 Mg and from liming 82,500 Mg. Our protocol can be used to aid development of agricultural policies and research prioritization at regional levels where acidic soils are prevalent.

Lollato, R.P., Ochsner, T.E., Arnall, D.B., Griffin, T.W., Edwards, J.T. 2019, Agronomy Journal

Judeo-Christian beliefs and tradition include observing a Sabbath, or day of rest, by abstaining from work one day each week. In modern times, followers of the Jewish faith mark the Sabbath from Friday evening to Saturday evening and Christians do so on Sunday. For both groups, this practice is firmly entrenched to the point that many contend that working on Sunday is morally wrong. For many Christian workers in the United States, this practice often fits with their work schedule as Saturday and Sunday are typical days off doe many schools, government organizations, and businesses. There are exceptions to this and farmers are one of the most obvious. The demands of managing a farm do not conform to uniform weekly work schedules. To meet labor requirements, many Americans family farms rely upon unpaid family labor to perform tasks such as conducting field operations. Reliance on unpaid labor is becoming more prevalent due to lack of available laborers in many locations in the United States. A whole-farm linear programming model was parameterized as a limited resource Midwestern USA crop-producing farm. Model results estimate the costs of shutting down farm operations for differing levels of Sabbath observation across peak and non-peak seasonal time periods. Results indicate substantial costs are likely to occur, indicating that Sabbath-observing farm operators must perceive at least a base level of perceived benefits. These results are of interest to multi-generational farms attempting to balance work-life issues, researchers evaluating economics of religion, and rural development labor economists studying impacts of decaying populations on rural communities.

Rosburg, B., Griffin, T.W., Coffey B. 2019, FAITH & ECONOMICS

Church
Vegetable Farm

Farmers’ ability to “own” data has been debated, along with its value and consequences of misappropriation. Although no specific law or precedent addresses farm data, it may be protectable as a “trade secret” if farmers actively protect it. Questions remain if seeking protection is practical or if highest value may be realized by sharing data. 

Ellixson, A., Griffin, T.W., Ferrell S., Goeringer P. 2019, Drake Journal of Agricultural Law

Low commodity prices combined with high input costs have deteriorated net farm income over the last several years. As a result, management decisions have become extremely important, as any less than optimal decision could result in the farm losing money. Understanding which factors of production have the greatest effect on net farm income can help producers focus their efforts. This study analyzed various factors affecting net farm income to determine those that were most important to the profitability of an operation. Results varied depending upon the set of years analyzed and the region of the state. This may reflect an environment where the factors important to a top farm vary by the overall condition of the farm economy.

Carls, E., Ibendahl, G., Griffin, T., Yeager, E. 2019, Journal of the American Society of Farm Managers and Rural Appraisers 

Cow and Calf

© 2020 by Ty G. Griffin.