Optimization of 4R nitrogen fertilization practices in response to production system uncertainties

IPNI-2014-CAN-4RC03

06 Apr 2015

2014 Annual Interpretive Summary


Nitrogen fertilization provides essential benefits for food production but its optimal management is subject to a high level of complexity. The fertilizer industry, agronomists, consultants and farmers recognize the 4Rs as the basis for optimum fertilization, but their implementation is knowledge-intensive and site-specific. For a full implementation of the 4R strategy in the specific context of N applications, it is necessary to address the risks and opportunities of N fertilization management at the field-scale with respect to weather, crop response and economics.

Our goal is to quantify the influence of soil and weather conditions (i.e., temperature, precipitation): 1) experienced prior to the growing season; 2) from sowing to topdressing application (if applicable); and 3) after the last N application on the potential for crop yield response and N losses. For this matter, it will be necessary to study the accuracy of site-specific weather forecasts and the opportunity for their inclusion in a probabilistic strategy to optimize N use efficiency while safeguarding crop yield potential, and to explore system sensitivity to possible interactions with other soil amendments, cultivar specification, tillage systems and different influential management-induced factors.

The project will utilize past and new datasets from researchers involved in the other activities supported by the 4R Fund, as well as those already available, to perform meta-analyses in order to identify crop yield responses and losses to fertilizer N as influenced by soil properties, climatic conditions and 4R management practices. The first step is to create a unified database of past and new N fertilization experiments dealing with rates, sources, timing and placement on yield production, nitrous oxide and ammonia emissions and leaching, including relevant meta-data (weather dynamics, cropping practice, soil characteristics) explaining regional differences. This unified database of Canadian observations on corn, canola, wheat, and potato is currently being assembled as a part of this project.

Meta-analyses have recently emerged as a necessity in agriculture to review accumulated evidence and extract new, meaningful information from knowledge fragments that need to be consolidated. Combination of spatial analysis methods and modelling techniques like multifactorial analysis, state equation representation, and fuzzy inference systems will then be used to analyze the relationships between crop response to N fertilization and information on soil properties, crop growth status, meteorological conditions and market status (commodity and N prices). The outcome of this project is a framework model to manage the sources of uncertainties affecting 4R practice outcomes on a site-specific basis.