Machine Learning and Agriculture

The Survey of Software to Perform/Assist in Agriculture Data Analysis will discuss the most often used software applications applied to agricultural data analysis. ML/AI (Machine Learning/Artificial Intelligence) applications exist for some of the data analysis a farming operation might wish to employ. This microcredential includes a description of each application, and how to install it and use it. There are eight microcredentials within the Precision Farming series and they can be taken in any order or on their own.

The ideal learner will be looking to adopt sustainable farming practices and already be employed in the farming industry, either as an employee or owner. It is expected that the learner will have at least basic digital skills. The learners will complete the modules at their own pace. Therefore, the microcredential has been developed fully online.

Prior Learning

• It is recommended, but not necessary, to complete Farming Using Smart Technology before enrolling.

Learning Outcomes 

• Discuss the most common software packages that perform ML model generation from data collected in a typical farming operation
• Investigate Software to assist ML and application to crop forecasting and yield prediction
• Discuss acquiring, installing, and using software for precision farming operations to support decision making for the future

Assessment 

• The learner must achieve a minimum score of 80% on each of the 3 quizzes. 

Precision farming practices using the latest techniques and technologies address various aspects of carbon footprint and clean technologies. For example, using data of field conditions and states of weed growth, latest sprayer technology can target spray weeds without carpet-spraying the entire field. By analyzing growth and temporal soil conditions, such as moisture content, and soil nutrient levels, targeted fertilizing can reduce overall fertilizer use thereby reducing greenhouse gas emissions. It is well known that much of the applied fertilizer runs off into waterways, or is broken down by microbes in the soil, releasing the potent greenhouse gas nitrous oxide into the atmosphere. By only targeting the field locations that require the fertilizer and applying only what is needed in those areas, the greenhouse threat is reduced. An understanding of how smart equipment can assist with the reduction of greenhouse gases, not only regarding fertilizer application but also pesticide use and seeding practices, is vital: 

• Canada’s Climate Action Plan 
• Responsible consumption and production- Ensure sustainable consumption and production patterns
• Priority: Advancing innovation – Agriculture 

Innovative solutions, including clean technologies, are required to reduce emissions from agriculture. Promising new technologies are being developed to reduce emissions from livestock and crop production, including from the use of precision farming and “smart” fertilizers, which time the release to match plant needs, and from feed innovations that reduce methane production in cattle. Actions pertaining to the agriculture sector will be developed collaboratively through Canada’s Next Agriculture Policy Framework.