There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Statistics for Spatial Data.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1000&context=biosysengfacpub

On-the-go soil sensors for precision agriculture

Burgeoning consumer interest in organically produced foods has made organic farming one of the fastest growing segments of agriculture. This growth has not been supported adequately by rigorous research to address challenges such as arthropod pest management. The research that has been conducted, however, is complemented by research in aspects of conventional agriculture that may have applicability in organic systems, as well as by research in underpinning fields such as applied ecology. This article synthesizes the available literature in relation to a conceptual model of arthropod pest management strategies suitable for organic systems. The present work uses the four phases of the model to review the strategies in an agroecological context and provides a synthesis of the factors that influence the success of each phase. Rather than constituting a fringe science, pest management research for organic systems draws on cutting edge science in fields such as landscape and chemical ecology and has a bright future.

/pdf/arthropod-pest-management-in-organic-crops-1rmgtgljyj.pdf

Arthropod pest management in organic crops

Agricultural robots for field operations: Concepts and components

Sensors exist that allow rapid mapping of bulk soil electrical conductivity (EC); however, the utility of these sensors for Kentucky producers is unknown. The purpose of this study was to assess the nature and the causes of soil EC variability and to make a first assessment of its potential utility in Kentucky, particularly for fields containing soils derived from limestone residuum overlain by loess. Various geostatistical, correlation, and regression analyses were conducted at seven locations to examine EC map variability. Sensor drift and errors associated with changes in coulter depth were minimal. Bulk soil EC related fairly well with day content across locations and sample dates (r 2 = 0.40); however, many site- and time-specific correlations were better. Clay (maximum r 2 = 0.75), moisture content (maximum 6 = 0.76), Ca (maximum r 2 = 0.67), and Mg (maximum r 2 = 0.64) were positively correlated with EC, and depth to argillic or cambic horizon (maximum r 2 = 0.62), depth to fragipan (maximum r 2 = 0.81), and depth to bedrock (maximum r 2 = 0.32) were negatively correlated with EC. A multiple-regression model (R 2 = 0.70) was developed to predict EC that included nine factors: day, sand, soil moisture, buffer pH, base saturation, Ca, soil temperature, depth to cambic and argillic horizon, and slope. Soil EC variability was spatially structured, and spatial patterns were stable over time; however, the degree to which these patterns could be observed depended on the mapping procedures used. Our research suggested that EC mapping may have utility for Kentucky farmers.

Soil Electrical Conductivity Map Variability in Limestone Soils Overlain by Loess

Site-specific farming is dependent on having large amounts of reliable data. The gap between acquiring this information and using it effectively in making agricultural management decisions has widened. Collecting only the data that can be used effectively for management decisions is important. In this paper we identify the data needed to make site-specific management decisions, describe traditional and non-traditional data collection methods, discuss how these data might be used in the decision making process, and identify future needs.

Site-specific farming: A perspective on information needs, benefits and limitations

A whole farm economic analysis was conducted to provide a detailed assessment into the economic, risk, and production implications due to the adoption of auto-steer navigation. It was determined that auto-steer navigation was profitable for a grain farmer in Kentucky with net returns increasing up to 0.90% ($3.35/acre). Additionally, the technology could be used in reducing production risk. Adoption of the technology also alters production practices for optimal use.

/pdf/a-whole-farm-analysis-of-the-influence-of-auto-steer-t8zdu0v45p.pdf

A Whole Farm Analysis of the Influence of Auto-Steer Navigation on Net Returns, Risk, and Production Practices

The traditional means of tracking animal location in a field is by visual observation. Not only is this method labor
intensive, it is also prone to error as the observer can alter cattle movement, observation periods are often too short to obtain
confidence in general daily behavior patterns, and observer fatigue becomes an issue. In the 1990s, the University of Kentucky
began using GPS collars on cattle to track their position with the goal of incorporating this information into cattle management
practices. One of the key unanswered questions regarding the GPS collars is the accuracy of the position data recorded
by the collar. The objective of this work was to assess the capabilities and limitations of using GPS collars to track animal
movement in grazed watersheds. Static tests were conducted in an open field, under trees, and near fence lines to ascertain
the impacts of various field features on collar performance. Dynamic tests were carried out to examine the errors associated
with the collars while operated under real-world conditions. Results from these tests indicate that the collars generally provide
data with horizontal accuracies of 4 to 5 m. This information will assist researchers in the development of experiments
based on collar capabilities and limitations.

https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1024&context=bae_facpub

Suitability of a gps collar for grazing studies

Automatic section control was analyzed in a whole farm decision-making framework when implemented on an agricultural sprayer and/or planter. In addition, various field types and navigational scenarios were examined to determine their impact on profitability. It was determined that automatic section control increased net returns under all scenarios; up to $36/ha. This investigation highlighted the importance of considering field size in addition to field shape as well as initial navigational scenarios when determining the profitability of automatic section control.

Timothy S. Stombaugh

Papers

Soil Electrical Conductivity Map Variability in Limestone Soils Overlain by Loess

Site-specific farming: A perspective on information needs, benefits and limitations

A Whole Farm Analysis of the Influence of Auto-Steer Navigation on Net Returns, Risk, and Production Practices

Suitability of a gps collar for grazing studies

Whole farm analysis of automatic section control for agricultural machinery