The Value of Soil Sampling and Sampling Density: Conceptual Framework (Part 1)

When considering variable-rate nitrogen or seed application, soil sampling can provide farmers and their consultants with valuable information about the spatial distributions of soil properties such as organic matter, micro- and macro-nutrients, and pH. Conceptually, that information may be especially valuable for site-specific input management. But just as farmers make decisions about input applications, they also must make decisions about soil sampling, and in particular, must choose soil sampling density. It is standard practice for U.S. corn and soybean farmers to take soil samples on their fields every three or four years at a density of one sample per 2.5 acres. But whether that 2.5-acre density is economically optimal, and how the optimal density might change under different field and weather situations is largely unknown. Some producers choose one sample per acre and others choose one sample per ten acres. This article aims to present an analytical microeconomic framework to help non-economists systematically address these economic questions

Providing quality recreation experiences in Japan

This paper uses a choice experiment to evaluate the benefits to trekkers of the natural environment and the provision of appropriate recreation experiences in the Uryu-numa Mire, northern Japan. The result, applying a conditional logit model, shows that restoration of the natural environment are positively valued by trekkers, and their respective willingness to pay for one percentage point improvement are JPY 32.6 and 59.6. Likewise, provision of appropriate recreation experiences, setting a limit on the number of trekkers a day, is also positively valued. The results indicate that the optimal number of trekkers is 458, and the willingness to pay for controlling the number of trekkers from 800 to 458 is JPY 1,457. In Japan, importance of the quality of recreation experiences is not well recognized by park managers. However, our results indicate that both restoring the environment and providing excellent recreation experiences are significant challenges for recreation areas.

The Impact of Saturated Thickness to Protect Farmers from Severe Drought in High Plains Aquifer

The High Plains Aquifer comprises eight states of Nebraska, Oklahoma, Texas, New Mexico, Wyoming, Colorado, South Dakota with an area of 175,000 square miles. High Plains Aquifer (HPA) has been the primary source of water supply for irrigation in this region. Groundwater depletion varies across the region of the aquifer due to differences in surface water interaction with groundwater, water recharge, precipitation temperature and hydrological characteristics of the aquifer. With the uncertainty in the future of climate, we expect extreme climatic events such as drought. The drought is associated with dry and hot weather in which irrigation plays a vital role to mitigate its effects on crop yield. In this paper, we develop a county-level regression that allows us to estimate the effect of saturated thickness to sustain crop yields during severe drought for the entire HPA and highlight the role of irrigation in response to climate change. The model provides inferences on how drought affects saturated thickness effects on yield

The Impact of Different Data Processing Methods on Site-specific Management Recommendation

Precision agriculture has the potential to enhance farming profitability substantially via site-specific management of fields. One of the promising ways of generating such profitability-enhancing input is to a use recommendation map is on-farm randomized trials. The process of generating an input (say nitrogen) using a recommendation map typically involves the following steps: 1. Design and implement randomized input use trial 2. Collect yield data along with other field characteristics (Slope, Electrical Conductivity, and Organic Matter) 3. Process the data for statistical analysis 4. Conduct regression analysis to estimate production function (how the input affect crop yield) 5. For each of the management units, find the input rate that maximizes profit for that uni

The Impact of Different Data Processing Methods on Site-specific Management Recommendation

Precision agriculture has the potential to enhance farming profitability substantially via site-specific management of fields. One of the promising ways of generating such profitability-enhancing input is to a use recommendation map is on-farm randomized trials. The process of generating an input (say nitrogen) using a recommendation map typically involves the following steps: 1. Design and implement randomized input use trial 2. Collect yield data along with other field characteristics (Slope, Electrical Conductivity, and Organic Matter) 3. Process the data for statistical analysis 4. Conduct regression analysis to estimate production function (how the input affect crop yield) 5. For each of the management units, find the input rate that maximizes profit for that uni

Input Use Under Crop Insurance: The Role of Actual Production History

The impact of crop insurance on changes in input use has attracted much attention by economists. While there are a number of studies on this topic, they frame moral hazard in inputs use in a static model. However, when agricultural producers are forward-looking, they would make input allocation decisions realizing that their decisions would affect their future actual production history. This, in turn, affects the probability and size of future indemnity payments. Thus, moral hazard should be framed in a dynamic input use decision model. We first show theoretically that under certain feasible conditions, a static analysis always results in lower optimal input use when compared to a dynamic one with endogenous actual production history. This is because static models fail to recognize the role of actual production history. We then run numerical simulations using nitrogen application rates as a case study. We find that static models indicate significant reduction in nitrogen use compared to the no-insurance scenario, whereas the dynamic models with a role for actual production history indicate almost no reduction in applied nitrogen. The dynamic analysis not only suggests a near absence of moral hazard, but, for low coverage rates, it results in an optimal nitrogen rate higher than that under the no-insurance scenario. These findings illustrate the importance of recognizing the role of actual production history in mitigating moral hazard possibilities in crop insurance and the dynamic nature of moral hazard in crop insurance

Economics of Experimental Design: Finding the Optimal Design of a Whole Field Randomized Experiment

An April 2017 Cornhusker Economics article Getting to Know Your Yield Response Better through Whole-field Randomized Experiments discussed a case study detailing a whole-field randomized agronomic experiment (nitrogen and seed rate). The study was conducted in Kentucky and funded through the USDA-NIFA Data Intensive Farm Management (DIFM) project. The project has so far resulted in more than 50 experiments across several states, including Illinois, Nebraska, Kansas, and Washington. The overarching goal of the project is to provide agricultural producers with the best input rate, variable or uniform, which maximizes their farm profits. This involves statistically estimating the crop response function and then the mathematical optimization to identify the best input rate based on the estimated response function

Assessing Determinants of Participation in Conservation Programs in the U.S.

In order to generate ecosystem services (ES) from privately owned intensively managed agricultural land, the United States Department of Agriculture (USDA)’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS) have implemented many conservation programs such as the Conservation Reserve Program (CRP), Conservation Stewardship Program (CSP), and Environmental Quality Incentives Program (EQIP), to name a few. These programs provide financial and technical assistance to farmers and ranchers to adopt land management practices that generate ES

Simulated dataset of corn response to nitrogen over thousands of fields and multiple years in Illinois

Nitrogen (N) fertilizer recommendations for corn (Zea mays L.) in the US Midwest have been a puzzle for several decades, without agreement among stakeholders for which methodology is the best to balance environmental and economic outcomes. Part of the reason is the lack of long-term data of crop responses to N over multiple fields since trial data is often limited in the number of soils and years it can explore. To overcome this limitation, we designed an analytical platform based on crop simulations run over millions of farming scenarios over extensive geographies. The database was calibrated and validated using data from more than four hundred trials in the region. This dataset can have an important role for research and education in N management, machine leaching, and environmental policy analysis. The calibration and validation procedure provides a framework for future gridded crop model studies. We describe dataset characteristics and provide thorough descriptions of the model setup

Toward an effective approach for on‑farm experimentation: lessons learned from a case study of fertilizer application optimization in Japan

On-farm experimentation (OFE) is increasing worldwide. Appropriate OFE procedures may differ depending on the characteristics and circumstances surrounding farms, such as climate, field conditions, farm size, degree of agricultural digitalization, and a farmer’s socioeconomic background. This study aims to guide the future development of OFE in Japanese grain farming by examining the experimental setup, data analysis, and farmers’ activities within their socioeconomic and institutional communication and learning networks. The results of this typical OFE case study, which estimates a field’s economicallyoptimal fertilizer variable-rate application map for winter wheat production, are reported. The outcomes of the case study, which are intended to guide the direction of OFE development in Japan, were used as reference materials for a survey taken while interviewing farmers who had never been involved in OFE. Farmers’ answers showed that the economic return of site-specific management depends on farm and field size and exhibits economies of scale. A very high share of the profit increases provided by OFE data came from improvements in field-specific uniform rate management, not from within-field site-specific management. The interviews revealed that farmers open to OFE are more interested in increasing rice crop quality to earn price premiums than in increasing yield. Increased engagement with farmers in conducting OFEs could play a key role not only in generating data to guide farmers’ input management but also in fostering farmer collaboration to develop marketing strategies. This study is the first to propose future orientations of OFE research that target typical moderately-sized Japanese grain farms