|Rotz, Clarence - Al|
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer reviewed journal
Publication Acceptance Date: 2/16/2005
Publication Date: 7/25/2005
Citation: Rotz, C.A., Harrigan, T.M. 2005. Predicting suitable days for field machinery operations in a whole farm simulation. Applied Engineering in Agriculture. 21(4):563-571. Interpretive Summary: Owning and operating machinery remains one of the largest costs in crop production. The development or selection of optimal machinery systems can help reduce costs while providing timely field operations that optimize the yield and quality of the crops produced. When determining the best equipment for use on a given farm, it is important to know the time that is normally available for performing each operation within a period that avoids or reduces loss in crop value. This time varies considerably among locations and from year to year as weather conditions vary. Thus, selection of the best machinery set depends upon accurate assessment of the days when the soil is suitable for performing each operation. This type of information is not available for most locations. Therefore, a tool is needed that can readily develop suitable day information for essentially any location, field operation, and soil characteristics. A computer simulation model was developed that predicts the days suitable for fieldwork across a wide range in soil, crop, and machinery conditions using historical weather data. This model is available through the Internet where it can be used by others to predict available field working days for specific locations and conditions. More accurate information on the available time for fieldwork helps engineers and other machinery management specialists design more optimal and cost effective machinery systems for farm production.
Technical Abstract: Accurate information on the days suitable for field operations is important in the design, development, and selection of efficient machinery systems for crop production. The number of days suitable varies widely with climate, soil characteristics, and time of year but this information is normally difficult to obtain for a given location. A model was developed to predict suitable day information from the long-term weather records and soil characteristics of a location. This model forms a component of a farm model where it is used in the simulation of the timeliness, productivity, and costs of machinery systems in crop production. Optional output provides annual, long-term average, and 80 and 90% probable values for the days suitable each month. The model was verified to predict suitable day information similar to field observations for recent years in northwestern Indiana and similar to long-term historical data for a few other locations across the Midwest. The number of suitable days predicted each month was moderately sensitive to some soil characteristics and highly sensitive to the tractability coefficients used to determine a suitable day. Recommended tractability coefficients were developed for spring and fall operations on various soil textures. Usefulness of the model was further demonstrated by determining the 80% probable number of suitable days each month in central Michigan using conventional, mulch, and no-till systems on clay loam, loam, and sandy loam soils. The model provides a useful research and teaching tool for studying the influence of weather on the days suitable for fieldwork, the performance of field machinery operations, and machinery effects and interactions with other parts of the farm.