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Animal Transportation Database for Beef Cattle

    Currently, there are inaccuracies in the energy use and greenhouse gas emission estimates of cattle transport reported by LCA studies because of their simplistic assumptions. The purpose of this database is to provide the necessary data for accurate estimation of the energy use and greenhouse gas emissions associated with cattle transport. The database has 28 different trailers under three categories namely pot belly, gooseneck, and bumper pull. It describes space available (length and width), maximum weight allowed in the trailer, along with a compatible vehicle that can haul the trailer. Gross vehicle weight, maximum payload allowed, and fuel use are available for the compatible vehicle. Using this database one can directly identify the number of cattle of a particular weight category that can be transported in a particular trailer-vehicle combination. This database also helps to identify economical and eco-friendly ways to transport cattle.

    SGA

      Stored Grain Advisor (SGA) is a decision support system for managing insect pests of farm-stored wheat. The program predicts the likelihood of insect infestation, and recommends appropriate preventative actions . It also provides advice on how to sample and identify insect pests of stored wheat. SGA Pro was designed for use in commercial elevators as part of the Areawide IPM Project for stored grain. Grain samples are taken with a vacuum probe and processed over an inclined sieve. SGA Pro analyzes the insect data, grain temperatures and moistures, and determines which bins need to be fumigated.

      SPUR2

        SPUR2 DOS ver. 2.2 is a general grassland ecosystem simulation model designed to determine beef cattle performance and production by simultaneously simulating production of up to 15 plant species on 36 heterogeneous grassland sites. SPUR2 simulates grassland hydrology, nitrogen cycling, and soil organic matter on grazed ecosystems as well as rangeland production under different climatic regimes, environmental conditions, and management alternatives.

        SHOOTGRO

          SHOOTGRO emphasizes the development and growth of the shoot apex of small-grain cereals such as winter and spring wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.). To better incorporate the variability typical in the field, up to six cohorts, or age classes, of plants are followed using a daily time step.

          OTUshuff

            OTUshuff is a set of tools written in Perl to identify and correct for the presence of pseudo-diversity in contrasts between microbial communities. The variably weighted Odum dissimilarity (DwOdum) allows for down-weighting the influence of either abundant or rare taxa in calculating a measure of similarity between two communities. We show that down-weighting the influence of rare taxa can be used to minimize pseudo b-diversity arising from incomplete sampling. Down-weighting the influence of abundant taxa can increase the sensitivity of hypothesis testing. OTUshuff is an associated test for identifying the presence of pseudo-diversity in pairwise community contrasts.

            AgroAtlas

              The Russian-English Agricultural Atlas is the world’s most comprehensive source of information on the geographic distribution of plant-based agriculture in Russia and neighboring countries. The Atlas contains 1500 maps that illustrate the distribution of 100 crops, 560 wild crop relatives, 640 diseases, pests and weeds, and 200 environmental parameters. Additionally, the Atlas provides detailed biological descriptions, illustrations, metadata and reference lists. Currently, individual maps can be downloaded and viewed using freely available AgroAtlas GIS Utility software, which can also be downloaded at this site.

              Data from: Long-Distance Transportation Causes Temperature Stress in the Honey Bee, Apis mellifera (Hymenoptera: Apidae)

                To test how temperature may contribute to bee (*Apis mellifera*) transportation stress, temperature sensors were placed in hives in different locations and orientations on the trailer during shipping. Colony size prior to shipping significantly contributed to loss of population immediately after shipping which contributed to colony failure with smaller colonies more likely to fail and fail faster. Colony size also affects thermoregulation and temperature stress.

                Non-dominated Sorting Genetic Algorithm-II

                  This code is implements the nondominated sorting genetic algorithm (NSGA-II) in the R statistical programming language. The function is theoretically applicable to any number of objectives without modification. The function automatically detects the number of objectives from the population matrix used in the function call. NSGA-II has been applied in ARS research for automatic calibration of hydrolgic models (whittaker link) and economic optimization (whittaker link).

                  Varroa Pop

                    Varroa Pop simulates the growth of Varroa mite population in honey bee colonies. The program demonstratres how Varroa mites influence colony population growth throughout the year. You can change many factors through the menus in the model such as the initial population size, queen egg laying potential, and mite reproduction rates, so you can see how these factors influence both colony and mite population growth. We hope that the model will help you understand the interactions between the honey bee and mite populations and provide insights on how best to control Varroa in colonies.

                    Redapol

                      A computer-based model simulating the interactions of weather, bloom and honey bee foraging activity that culminate in 'Delicious' apple fruit-set. The model predicts the percentage of blossoms setting fruit based upon weather conditions, orchard design, tree characteistics, and honey bee colonies per hectare.