SPATIAL REGRESSION MODELS FOR YIELD MONITOR DATA: A CASE STUDY FROM ARGENTINA

Precision agricultural technology promises to move crop production closer to a manufacturing paradigm, but analysis of yield monitor, sensor and other spatial data has proven difficult because correlation among neighboring observations often violates the assumptions of classical statistical analysis. When spatial structure is ignored variance estimates tend to be inflated and significance levels of test statistics are reduced. The gap between data analysis and site-specific recommendations has been identified as one of the key constraints on widespread adoption of precision agriculture technology. This paper compares four approaches that explicitly incorporate spatial correlation into regression models: (1) a spatial econometric approach; (2) a polynomial trend regression approach; (3) a classical nearest neighbor analysis; and (4) and a geostatistic approach. In the Argentine data studied, the spatial econometric, geostatistical approach and spatial trend analysis offered stronger statistical evidence of spatial heterogeniety of nitrogen response than the ordinary least squares or nearest neighbor analysis. All the spatial models led to the same economic conclusion, which is that variable rate nitrogen is potentially profitable. The spatial econometric analysis can be implemented on relatively small data sets that do not have enough observations for estimation of the semivariogram required by geostatistics. The spatial trend analysis can be implemented with ordinary least squares functions that are already available in some GIS software. In this study, the main benefit of using spatial regression analysis is increased confidence in the corn yield response estimates by management zone, and conclusions about the profitability of precision agriculture technologies.Crop Production/Industries,

The impact of farmland price changes on farm size, financial structure enterprise choice

This research develops a theoretical framework within which the impact of farmland capital gains and losses on agricultural production, finance, and enterprise choice decisions can be analyzed. A preliminary test of this theoretical model is conducted using a deterministic dynamic programming model of a central Iowa farm firm in the period 1970-1984. Though the theoretical model was developed to examine the impact of farmland price changes, it may be extended to analyze decisions involving any durable assets which may earn capital gains or losses;The model suggests that real estate capital gains provide incentives to increase farm acreage, incur greater debt to purchase the appreciating land, and decrease holdings of more liquid nonland assets. Capital losses tend to have the opposite effect because decisionmakers seek to economize on land use to avoid the capital drain. Limited availability of land, the inability of many farm decisionmakers to attract outside nonfarm equity, and adjustment costs may dampen or even eliminate these effects in some cases, but the empirical work suggests that in recent years conditions are such that capital gains effects could be observed. The theoretical model suggests that if borrowing against unrealized capital gain is permitted, land price risk may force decisionmakers to build added financial flexibility into their operations by reducing farm acreage, cutting debt use, and increasing holdings of liquid, nonland assets;The empirical model suggests that the asset and financial restructuring on U.S. farms in the 1970s toward greater land investment, more debt, and smaller holdings of nonland assets was a response to the large farmland capital gains of the period. This research draws a direct link between land price increases of the 1970s and farm financial stress of the 1980s. With greater land investments, more debt and fewer liquid assets, many farmers were financially vulnerable in the situation of low farm income and dropping asset values that they encountered in the mid 1980s. The study suggests that in the environment of falling land prices experienced in the 1980s, farmers in general will seek to hold less land and reduce debt loads. In this context, the farm financial crisis of this period can be seen as a set of problems encountered in moving from a period of large farmland capital gains to a period of stagnant or declining land prices

MANAGING PHOSPHOROUS SOIL DYNAMICS OVER SPACE AND TIME

Understanding the relationship between soil fertility dynamics and crop response is conceptually appealing. Even more appealing is comprehension of the spatial and temporal heterogeneity of these connections over a production surface and across seasons. Knowledge of these interactions is complicated because nutrient carryover dynamics and crop response to inputs are determined simultaneously on the one-hand, and sequentially on the other. A second problem enters when crops are rotated, for example, in the corn-soybean system commonly practiced in the Corn Belt. This paper examines the nutrient carryover-crop response nexus using data from a corn-soybean, variable-rate nitrogen (N) and phosphorous (P) experiment conducted over five years. Site-specific corn response to N and P and soybean response to P are simultaneously estimated with a P carryover equation. These estimates are used in a dynamic programming model to map site-specific optimal N and P fertilizer policies, soil P evolution, and profitability. The net present value of managing N and P site-specifically is compared to a strategy where these inputs are managed uniformly following extension guidelines. The results suggest that when P-carryover is managed, site-specific returns to the variable-rate strategies are higher than returns to a conventional, uniform strategy.Crop Production/Industries,

A SYSTEMS APPROACH FOR EVALUATING ON-FARM SITE-SPECIFIC MANAGEMENT TRIALS: A CASE STUDY WITH VARIABLE RATE MANURE AND CROP QUALITY RESPONSE TO INPUTS

Site-specific application of manure has the potential to improve crop production and environmental quality. If manure is applied where it is needed, in the quantity required by the crop, over application, with attendant runoff and leaching problems can be reduced. To implement this approach growers need site-specific crop response information. Increasing availability of site-specific yield information offers a way to estimate such crop responses. The objective of this study is to develop a methodology for estimating site-specific response of corn and soybeans to manure given soil test information, and to use that methodology to analyze an on-farm manure management trial conducted near Sleepy Eye, Minnesota. Both quantity and quality of the crop is considered.Research Methods/ Statistical Methods,

Impact of Automated Guidance for Mechanical Control of Herbicide-Resistant Weeds in Corn

This study evaluated the feasibility of reintroducing mechanical weed control as an alternative for herbicide-resistance weed infestations. The production practice tested included row cultivation with a separate banded spray application using high-accuracy automated guidance systems. A range of ground speeds were tested for the row cultivation operation, each with a different per acre cost and timeliness penalty. A typical eastern Corn Belt farm with a rotation of corn and soybean served as the base for the linear programming model. It was found that if the farmer was willing to reintroduce tillage, row cultivation conducted at higher operating speeds in conjunction with separate banded application could be justified under a range of relatively inexpensive herbicide costs as low as $7 per acre. When effective herbicides were relatively expensive at$30 per acre, the optimal decision would be to use row cultivation and reduce herbicides via banding. At faster ground speeds, the majority of hours devoted to row cultivation shifted to earlier time periods so that yield penalties were avoided

An experimental approach to estimating the value of grain moisture information to farmers in Bangladesh

In the developing world grain storage losses are high and in humid areas inadequate grain drying is often a source of storage problems. Farmers and traders depend on traditional grain moisture estimation methods which are subject to a wide error margin. Grain storage decisions could be improved if farmers and traders had a low cost grain moisture meter that fit their needs. The goal of this study was to determine the desired grain moisture meter functionality and to estimate the value of grain moisture measurement for small holder farmers and for small-scale grain traders, using Bangladesh as a case study. This study was based on interviews with 140 randomly selected Bangladeshi rice farmers in 2016 and 2017, discussions with millers at 30 rice mills and a voucher based moisture meter sales program. It shows that except for rice kept for seed and home consumption, most Bangladeshi farmers sell their rice shortly after harvest to satisfy cash needs and to eliminate storage risks. They say that they would store more rice on-farm if they had better storage methods including cost-effective grain moisture testing. Survey results show that the average farm storage loss was 52 kg or 563 Taka (US$6.78) annually. Using experimental economics methods, farmers were given the opportunity to purchase a probe type grain moisture meter through vouchers with a range of prices. Twenty three of the 140 of the participants (i.e. 16$4.67). No farmer purchased a voucher price over 800 Taka (US$10.00). Those who purchased moisture meters had larger farms and produced more rice than those who did not exercise the voucher. They were also younger on average, have more education and more off farm income than non-purchasers

Substructurability:The effect of interface location on a real-time dynamic substructuring test

A full-scale experimental test for large and complex structures is not always achievable. This can be due to many reasons, the most prominent one being the size limitations of the test. Real-time dynamic substructuring is a hybrid testing method where part of the system is modelled numerically and the rest of the system is kept as the physical test specimen. The numerical–physical parts are connected via actuators and sensors and the interface is controlled by advanced algorithms to ensure that the tested structure replicates the emulated system with sufficient accuracy. The main challenge in such a test is to overcome the dynamic effects of the actuator and associated controller, that inevitably introduce delay into the substructured system which, in turn, can destabilize the experiment. To date, most research concentrates on developing control strategies for stable recreation of the full system when the interface location is given a priori. Therefore, substructurability is mostly studied in terms of control. Here, we consider the interface location as a parameter and study its effect on the stability of the system in the presence of delay due to actuator dynamics and define substructurability as the system’s tolerance to delay in terms of the different interface locations. It is shown that the interface location has a major effect on the tolerable delays in an experiment and, therefore, careful selection of it is necessary

Aircraft Emissions, Their Plume-Scale Effects, and the Spatio-Temporal Sensitivity of the Atmospheric Response:A Review

Non-CO2 aircraft emissions are responsible for the majority of aviation’s climate impact, however their precise effect is largely dependent on the environmental conditions of the ambient air in which they are released. Investigating the principal causes of this spatio-temporal sensitivity can bolster understanding of aviation-induced climate change, as well as offer potential mitigation solutions that can be implemented in the interim to low carbon flight regimes. This review paper covers the generation of emissions and their characteristic dispersion, air traffic distribution, local and global climate impact, and operational mitigation solutions, all aimed at improving scientific awareness of aviation’s non-CO2 climate impact

The Emissions of Water Vapour and NOx from Modelled Hydrogen-Fuelled Aircraft and the Impact of NOx Reduction on Climate Compared with Kerosene-Fuelled Aircraft

A kerosene fuelled aircraft was modelled within a performance tool and fuel burn and the emissions of nitrogen oxides (NOx) and water vapour at different stages of flight throughout the mission were estimated. Adaptions were made to engine and aircraft parameters within the performance tool to accommodate a liquid hydrogen fuel over the same given mission. Once an iterative design process had been completed to ensure the aircraft could perform the given mission, the performance tool was again used to calculate total fuel burn. Fuel burn results alongside predicted emission indices were used to estimate the emissions of NOx, water vapour from hydrogen-fuelled aircraft. The use of hydrogen fuel over kerosene fuel in the modelled aircraft resulted in the removal of carbon-based emission species alongside 86% reduction in NOx and 4.3 times increase in water vapour emission. The climate impact of this switch with the reduction in NOx emission was assessed by a 3D global atmospheric chemistry and transport model, STOCHEM-CRI, which found a significant reduction in the concentration of a potent greenhouse gas, ozone, and an oxidizing agent, OH, by up to 6% and 25%, respectively. The reduction of OH levels could induce a positive radiative forcing effect as the lifetime of another important greenhouse gas, methane, is increased. However, the magnitude of this increase is very small (~0.3%), thus the overall impact of the reduction in NOx emissions is likely to have a net negative radiative forcing effect, improving aviation’s impact on the environment. However, further work is warranted on effects of other emission species, specifically water vapour, particulate matter and unburned hydrogen