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Estimation of field working days for maize harvesting in the United States and China

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2018 ASABE Annual International Meeting  1800473.(doi:10.13031/aim.201800473)
Authors:   Xiqiang Shen, Tao Lin
Keywords:   Field working days, piecewise linear regression, Precipitation, model comparison.

Abstract. The changes of climate influences suitable field working days (FWDs) of farming activities. Improved estimation of FWDs would facilitate the plan of farm management, adapting to the increased weather variability. We compiled an 8-year (from 2002 to 2009) precipitation and maize progress data in the U.S. and China in this study. We developed a multiple linear regression model and a piecewise linear regression model to estimate suitable field working days for maize harvesting at the state-level in the U.S. The piecewise linear regression model had the better performance and it was used to predict the suitable field workdays in Northeast China. The spatio-temporal variation of suitable field working days was further quantified to facilitate agricultural machinery management.

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