Agriculture moving to customized nitrogen fertilization

Photo courtesy of Effigis.

By Yacine Bouroubi
Effigis Chief Scientist, Earth Observation Division

Canadian agriculture has an international reputation for being highly productive and modern. It plays a major role in the country’s economy, and contributes to 8 percent of GDP and 12 percent of jobs.

Everyone involved in Canada’s agricultural sector is aware of the environmental issues associated with farming. To optimize performance and revenue while respecting the environment, for the past few years producers have been counting on a new ally: precision agriculture.

Using technologies such as GPS, auto-guidance, variable rate technology, yield sensors, satellite images and drones, precision agriculture is now part of the day-to-day life of farmers. The application of agricultural inputs based on the four Rs (the right source at the right rate, in the right place at the right time) must be based on scientific knowledge and technical know-how. Such knowledge and know-how are based on reliable, accurate and complete information, which is often necessary on a global scale, but with a rather fine spatial resolution. Satellite images are the ideal tool to provide much of the information required.

The SCAN program extracts agronomic knowledge related to nitrogen fertilization to make more accurate models. (Image: Effigis)

Using Satellite Images. For about 15 years now, sensors on very high spatial resolution (VHR) Earth observation (EO) satellites have been offering a source of data that can provide information on soils and crops at adequate spatial scales (around 2 meters using multispectral imagery) with an unbeatable price/quality ratio. Products derived from satellite images for estimating the quantity of nitrogen fertilization to meet plants’ nutritional requirements are a concrete example of an operational use of this data.

Determining the optimal dose of nitrogen is not easy, since it depends on complex interactions between plants, the soil, weather conditions and management practices. By wanting to avoid performance loss due to nitrogen deficiencies, current practices favor overfertilization, which leads to unnecessary costs as well as serious environmental problems.

Agriculture and Agri-Food Canada developed a model based on statistical analyses for understanding the direct relationship between the properties that influence nitrogen requirements (soil, growth, weather and management) and the response to nitrogen fertilization, based on a large number of fertilization trials. These relationships were implemented in a system called SCAN (Soil, Crops and Atmosphere for Nitrogen). Satellite imagery acquired at a specific growth stage provides information required for the operation of SCAN.

SCAN includes two major innovations: extracting agronomic knowledge related to nitrogen fertilization and modeling this knowledge in the form of inference rules in a fuzzy logic system. Work is ongoing to advance these two aspects of SCAN and validate it for various agricultural regions, as well as adapt it to various types of crops.

A SCAN web platform will be tested by 100 users starting in the summer of 2016, in anticipation of its commercial use in 2017.

To read Yacine Bouroubi’s full blog, go to www.effigis.com/blog.