Can soil fertility mapping affect management decisions? Can we map our fields more “efficiently”?
Proper management of soil fertility can generate benefits for farmers (e.g., higher yields or lower input costs), society, and the environment (e.g., higher quality food and water, lower environmental impacts, etc.). However, a successful soil management strategy depends on knowing the fertility conditions of the soil. Traditionally, this information is obtained by taking soil cores from the field, mixing them, preparing a composite sample, and sending it for lab analysis.
Lately, with advancements in technology and precision agriculture practices, zone or grid sampling has become a popular approach – multiple samples are used to create a soil fertility map within a field. Also, techniques involving the combination of soil sampling and the use of sensors to map fields have been researched, and some solutions are available on the market. During this session, an analysis of how different soil sampling strategies can affect management decisions and the latest advances in soil fertility mapping will be discussed – including the presentation of exciting results obtained through the HyperLayer Data Concept project developed at Olds College of Agriculture & Technology. The achievement of the HyperLayer project represents early results but has proven its potential to be a promising solution to challenges faced by the ag industry concerning soil fertility mapping.
CEU Credits: 0.5
Felippe Karp, Olds College of Agriculture & Technology: Originally from Brazil, Felippe obtained an agronomic engineering degree from the University of Sao Paulo, campus “Luiz de Queiroz” College of Agriculture (ESALQ). He then received his MS in Plant, Environmental Management, and Soil Sciences from Louisiana State University. Currently, Felippe is a Ph.D. candidate in Bioresource Engineering at McGill University (Canada) and is a member of the Precision Agriculture and Sensors Systems (PASS) research team led by Dr. Viacheslav Adamchuk. Felippe is also a Research Assistant – Digital Ag and has been working with the HyperLayer Data Project. Felippe is passionate about the concept of Precision Agriculture.
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Felippe Karp, Olds College of Agriculture & Technology
