Today, AI and its corollary of machine learning have recently become buzzwords everywhere, including agriculture. The implementation of both requires data. It is readily available but, in the area of harvest data, sorely lacks veracity.

The Canadian Food Inspection Agency (CFIA) recently approved gene editing for use in breeding new crop varieties. Plant breeders will now be able to apply the technology to their work. Gene editing has the potential to quickly develop new varieties with greater accuracy in targeting traits such as drought and disease resistance. The agronomic and trade implications are promising for farmers.

For developers of next-generation agricultural equipment and systems, the gap between drawing board and commercialization can be a lonely wilderness. To support the efforts of such innovators in the agri-food and technology sectors, the Canadian Agri-Food Automation and Intelligence Network (CAAIN) was formed in 2019 with a $49.5 million grant from Innovation, Science and Economic Development Canada’s Strategic Innovation Fund.

It seems all economic sectors are now talking about how artificial intelligence (AI) and machine learning will change the way business is done.