Seeding Food Innovation - Awarded Project 2017

Stewardship science technology for monitoring the socio-ecological outcomes of farming practices

Project Description

The rise in digital technology and data (smart phones, internet, satellite observations, climate monitoring networks, crop models, statistical learning) offer a way to help assist farmers manage their holdings with higher input efficiently, and for higher profits. This has been well recognized by leading commercial farm management technology providers. Knowledge built from pooling data across farmer networks also offers a way to learn about best practices, and to improve productivity. However, the use of data driven advances for improving sustainability and profits simultaneously has received less attention, and their application to highly diversified vegetable and fruit farming systems has been neglected. To fill this gap, our project will work with existing networks of diversified farmers in Canada to co-design a solution that helps them improve the both their productivity and environmental sustainability in tandem.

Relevance to the field of food innovation

Most agricultural research and funding has been directed at large monoculture farming systems for commodity crops based on reductionist ideas of how ecosystems operate. This has come at high environmental costs to climate change, soil degradation, and biodiversity, and at high social costs to human health. Less research attention and funding has been given to producing food of high nutritional value, and to diversified, vegetable, fruit, organic, ecological, and mixed farming systems. This bias can be readily seen in leading agricultural industry field trial databases, and in the scientific literature. Our knowledge of how to manage farming systems to maximize both yield and environmental outcomes is extremely limited. Our project aims to help bridge that gap.

Anticipated outcome

Our anticipated outcome is to design, and test, a software solution that enables farmers to benefit from the current advances in big data and technology, and allows them to learn across networks of similar farmers. Our research aims to generate a stronger understanding of existing technology use, as well as needs and desires for simultaneously tracking profitability and provision of environmental and social outcomes by the farming community. We will work with farmers to tailor a solution to meet their current and future needs. All of our work will made free as a public good, through an open source code base, and our project will hopefully serve as a prototype for how new technology can be used to help improve environmental sustainability in farming practices in Canada and beyond.

Grantees:

 

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