Predicting suitable days for field machinery operations in a whole farm simulation

Clarence Alan Rotz, Timothy M. Harrigan

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

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 type of operation. This information is normally difficult to obtain for a given location. A model was developed to predict suitable day information from 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. Incorporation of the suitable day model into a whole-farm simulation 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, machinery effects and interactions with other parts of the farm, and the economics of production systems.

Original languageEnglish (US)
Pages (from-to)563-571
Number of pages9
JournalApplied Engineering in Agriculture
Volume21
Issue number4
StatePublished - Jul 1 2005

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'Predicting suitable days for field machinery operations in a whole farm simulation'. Together they form a unique fingerprint.

Cite this