While farmers have traditionally relied on their own knowledge to profit suitably from their farms, the use of artificial intelligence in the agricultural sector in Canada has proved to be a turning point. The use of advanced technologies makes it possible for farmers to cut down on the use of fertilizers and herbicides, which reduces expenditure and minimizes environmental damage.

Similarly, in dairy farming, AI provides farmers with accurate information regarding the progesterone levels in milk, so that they can be inseminated at the optimum time. AI brings numerous benefits—it improves farming practices, reduces unnecessary antibiotic usage, manages mastitis, and drastically cuts down on the addition of low-quality milk into bulk storage tanks.

In 2016, Bethany Deshpande and Nicholas Clermont, her husband and business partner, founded SomaDetect, Inc. SomaDetect enables dairy farmers to measure various milk quality and herd health indicators, directly through the milking line. SomaDetect’s automatic technology does away with the need for cartridges, chemicals, and lost milk.

It uses sensors, which are installed in milking stalls to identify the cow, test its milk, and provide a list of metrics including protein and fat counts, disease indicators, levels of reproductive hormones, and antibiotic residues. The company is now gearing up to deliver commercial systems to test milk. SomaDetect aims to maximize the profitability of dairy farmers through the use of AI.

Another company that uses AI for farming is the Quebec-based Motorleaf, Inc. Motorleaf has created a system, which can acquire data from indoor growing operations, and uses AI and machine learning to identify the growing pattern. This system effectively enhances the quality and increases the quantity of products by identifying and adjusting to the specific needs of the crop automatically.

Motorleaf builds individual components, each with a specific set of functions, which can operate on their own. Alternately, these components can be added onto Motorleaf HEART to operate together as a larger whole. The Motorleaf Heart lies at the center of its monitoring and automation system. It can individually monitor the light levels, relative humidity, and air temperature, and also connect to the other components, such as Driplet, Droplet, Powerleaf, Space Sensor and Space Sensor Plus to control important metrics.

The technology has proved highly beneficial in the production of vegetables. SunSelect, a California greenhouse, made use of Motorleaf’s technology during a trial, which brought about a 50 percent reduction in the yield prediction error in tomatoes. The effectiveness of the trial led to the adoption of Motorleaf’s algorithms by SunSelect soon after.

Check out: Top AgTech Startups