The test reports published by Nebraska Tractor Test Laboratory (NTTL) can be extremely useful for selecting tractors or for comparing the performance of different makes and models of tractors. For example, when farmers are in the market for a tractor, the performance data in the NTTL reports can be used to select a tractor that will meet their needs. These reports can also serve as an effective tool for making tractor sales. Dealership personnel can use the performance data to compare their products to those of their competitors.

Ability to predict tractor fuel consumption is very useful for budgeting and management. The objective of this factsheet is to develop relationships using field measurements and Nebraska Tractor Test Laboratory results to estimate tractor fuel consumption. Using these equations, farmers can estimate and compare the fuel consumption for different operating and loading conditions.

“Gear-up and throttle-down” (GUTD) is a fuel-saving practice that can be used for saving fuel when drawbar loads are lighter (<75 percent of rated power) and PTO (power takeoff) speed can be reduced.

Machinery ownership and operation is a major crop and livestock production cost. Several strategies when combined can significantly affect costs, improve machine reliability, and improve profit margins.

One of the current research projects at the Eastern Virginia AREC involves the development of soybean varieties and germplasm with added values. Soybean meal is widely used in animal feed; however, soybean has several anti-nutritional factors that prevent animals from digesting protein efficiently.

The On-Farm Wheat Variety and Research Test Plots results presented in this publication are a collaborative effort between Virginia Cooperative Extension (VCE) Agents and Specialists, producer-cooperators, and agribusinesses to provide research-based information and results on not only variety selection and performance, but other emerging management practices of interest through replicated on-farm trials to assist producers in making sound agronomic management decisions based on unbiased information. Introduction