By Nicholas Bannon, Sean Mitchell and Alfons Weersink
Farm size, crop types, topography, climate, and labour use are only some of the differences between farming operations located in Ontario, the Prairies, and in the U.S.A. Midwest States. Surprisingly, despite these differences farmers in these regions face nearly identical barriers to further adoption of precision agriculture technologies.
During the summer of 2019, the Department of Food, Agricultural and Resource Economics (FARE) at the University of Guelph sent out separate surveys to two groups: 1) members of the Ontario Agri Business Association (OABA) and 2) members of the Canadian Association of Agri Retailers (CAAR). The purpose was to determine the level of adoption for precision agriculture technology in crop production. Rather than survey farmers directly, this survey interviewed input suppliers given the past success Purdue University had through a long-standing survey with CropLife.
One of the questions that respondents were asked was their perceptions of barriers that are preventing more of their customers (farmers) from adopting precision agriculture. Detailed in Table 1 are the percentage of respondents from the Prairies, Ontario and the USA Midwest, that agree or strongly agree each barrier is preventing producers in their area from further adopting precision agriculture technologies and services.
Not only was the percentage of respondents who agreed or strongly agreed that each factor was a barrier in producer adoption of precision agriculture technologies similar across regions, but the exact rankings of the barriers, especially the largest barriers, between regions are almost indistinguishable.
The three most agreed upon barriers for further adoption were identical for the Prairies, Ontario and the Midwest. The most important barriers to adoption across all regions were:
1. Pressure on farm incomes preventing precision agriculture use;
2. Cost of precision agriculture technologies and services is greater than the benefit received; and
3. Producers lacking confidence in the agronomic recommendations made based on the data generated by site-specific data.
The order of the remaining barriers was commonly only one spot below or above the ranking of the same barrier in the Prairies. For example, interpreting and making decisions with precision agriculture takes too much time was ranked as the 4th largest barrier for producers in the Prairies, and the 5th largest barrier for producers in Ontario and the USA Midwest.
Interestingly, the only noticeable difference in the ranking of producer barriers between the three regions was that respondents from the USA Midwest ranked the barrier; soil types in their area limit the profitability of precision agricultural practices for producers, as the 4th largest barrier to adoption. Respondents from the Prairies ranked this barrier 6th, and Ontario respondents ranked it 7th. The difference between the ranking of this barrier in the USA Midwest and Ontario is most interesting, as the two areas have similar crop rotations (largely corn and soy), so it would have been expected that the influence soil types have on precision agriculture adoption would have been more similar between the Midwest and Ontario.
Overall, the barriers preventing more farmers from adopting precision agriculture technologies is extremely similar between the Prairies, Ontario and the USA Midwest, despite the differences in the structure of farms.
The high adoption rates for certain categories of precision agriculture technologies, such as guidance systems and observational mapping, are due to the value provided to farmers relative to the cost. In contrast, the uptake for variable rate technologies is lower due to the high upfront costs and the benefits that are less certain. Regardless of the net benefits, low crop prices will slow the adoption of new technologies.
Recommended citation format: Bannon, Nicholas, S. Mitchell, and A. Weersink. "Barriers to Precision Agriculture Adoption Across Canada and in the United States ". Food Focus Guelph (94), Department of Food, Agricultural and Resource Economics, University of Guelph, August 7, 2020.