科研之友
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摘要
Maize (Zea mays L.) production accounts for the largest share of crop land area in the United States and is the largest consumer of nitrogen (N) fertilizers. Routine application of N fertilizer in excess of crop demand has led to well-documented environmental problems and social costs. Current N rate recommendation tools are highly generalized over space and time and therefore do not allow for precision N management through adaptive and site-specific approaches. Adapt-N is a computational tool that combines soil, crop, and management information with near-real-time weather data to estimate optimum N application rates for maize. We evaluated this precision nutrient management tool during four growing seasons (2011 through 2014) with 113 on-farm strip trials in Iowa and New York. Each trial included yield results from replicated field-scale plots involving two sidedress N rate treatments: Adapt-N-estimated and grower-selected (conventional). Adapt-N rates were on average 53 and 31 kg ha(-1) lower than Grower rates for New York and Iowa, respectively (-34% overall), with no statistically significant difference in yields. On average, Adapt-N rates increased grower profits by $65 ha(-1) and reduced simulated environmental N losses by 28 kg ha(-1) (38%). Profits from Adapt-N rates were noticeably higher under wet early-season conditions when higher N rate recommendations than the Grower rates prevented yield losses from N deficiencies. In conclusion, Adapt-N recommendations resulted in both increased grower profits and decreased environmental N losses by accounting for variable site and weather conditions.
- 出版日期2016-8
