Precision organic agriculture

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Montana State University - Bozeman, College of Agriculture


Organic agriculture addresses some of the shortcomings of industrialized conventional agriculture, but is prevented from more mainstream uptake by reduced yields. Organic agriculture relies on knowledge of intricate biological interactions in place of synthetic inputs used in other forms of agriculture, and in this way reflects an older way of practicing agriculture. Precision agriculture (PA) conversely is a technologically driven method of farming and combines guidance and data collection via remote sensing technologies to bring new efficiencies to farm operations. In this dissertation PA tools were used to explore the potential of improving organic production through site-specific management. By conducting on farm precision experiments (OFPE) with PA farmers can learn quickly about spatial variability across fields enabling well defined management templates. In organic systems this experimentation can be conducted with varied seeding rate inputs of both cover and cash crops. Here, we explored the relevancy of PA in organic settings, first broadly laying the philosophical foundation for the paradigm shift from production-oriented agriculture to precision agroecology. Secondly, a greenhouse experiment was used to develop the first-principle relationship between cover crop and cash crop seeding rates to maximize net return, establishing the basis for field experiments. Field scale experiments on five organic grain farms across the northern great plains deployed OFPE to optimize net returns, or suppress weeds, with varied seeding rates of cover and cash crops. Based on OFPE data, simulations across all sites found net returns could be improved on average by $45.82 ha-1 if economically optimum variable seeding rates were used. While seeding rates were found to have variable effects on weeds across fields, an optimized site-specific seeding strategy to balance net return and weed minimization improved net return and weed suppression compared to farmer-chosen seeding rates in every field tested. Overall, these results reveal the relevancy of precision agriculture to be deployed in organic systems to improve management for increased farmer net returns, and as a weed management method. In this way modern tools can be used to augment farmer knowledge about their local spaces to enable greater understanding and improved management of complex agroecosystems.




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