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    Towards a Low-Cost Comprehensive Process for On-Farm Precision Experimentation and Analysis
    (MDPI, 2023-02) Hegedus, Paul B.; Maxwell, Bruce; Sheppard, John; Loewen, Sasha; Duff, Hannah; Morales-Luna, Giorgio; Peerlinck, Amy
    Few mechanisms turn field-specific ecological data into management recommendations for crop production with appropriate uncertainty. Precision agriculture is mainly deployed for machine efficiencies and soil-based zonal management, and the traditional paradigm of small plot research fails to unite agronomic research and effective management under farmers’ unique field constraints. This work assesses the use of on-farm experiments applied with precision agriculture technologies and open-source data to gain local knowledge of the spatiotemporal variability in agroeconomic performance on the subfield scale to accelerate learning and overcome the bias inherent in traditional research approaches. The on-farm precision experimentation methodology is an approach to improve farmers’ abilities to make site-specific agronomic input decisions by simulating a distribution of economic outcomes for the producer using field-specific crop response models that account for spatiotemporal uncertainty in crop responses. The methodology is the basis of a decision support system that includes a six-step cyclical process that engages precision agriculture technology to apply experiments, gather field-specific data, incorporate modern data management and analytical approaches, and generate management recommendations as probabilities of outcomes. The quantification of variability in crop response to inputs and drawing on historic knowledge about the field and economic constraints up to the time a decision is required allows for probabilistic inference that a future management scenario will outcompete another in terms of production, economics, and sustainability. The proposed methodology represents advancement over other approaches by comparing management strategies and providing the probability that each will increase producer profits over their previous input management on the field scale.
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    A hydro-economic analysis of end-of-century climate projections on agricultural land and water use, production, and revenues in the U.S. Northern Rockies and Great Plains
    (Elsevier BV, 2022-08) Lauffenburger, Zachary H.; Maneta, Marco P.; Cobourn, Kelly M.; Jencso, Kelsey; Chaffin, Brian; Crockett, Anna; Maxwell, Bruce; Kimball, John S.
    Study region,Montana, U.S.A. Study focus Creating adaptation plans for projected imbalances in the western U.S. agricultural water demand-supply system are difficult given uncertainty in climate projections. It is critical to understand the uncertainties and vulnerabilities of the regional agricultural system and hydrologic impacts of climate change adaptation. We applied a stochastic, integrated hydro-economic model that simulates land and water allocations to analyse Montana farmer adaptations to a range of projected climate conditions and the response of the hydrologic system to those adaptations. Satellite observations of crop types, productivity, water use, and land allocation were used for model calibration. A suite of climate models was employed to quantify end-of-century impacts on streamflows, water and land use, production, and net revenues.New hydrological insights for the region Simulations showed summer streamflows were influenced by a state-wide 18.2% increase in agricultural water use. Decreased summer water availability with increased demand could have far reaching impacts downstream. Land use for irrigated crops increased 1.6%, while rainfed crops decreased 6.5%, implying state-level decrease in planted area. Even with increased land and water use for irrigated crops, production decreased 0.5%, while rainfed production decreased 2.7%. Corresponding losses in net revenues totaled 1.5% and 7.2% for irrigated and rainfed crops, respectively.Results highlight vulnerabilities of semi-arid agricultural regions and can aid water managers in sustaining agriculture in these regions.
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    On-Farm Experimentation to transform global agriculture
    (Springer Science and Business Media LLC, 2021-12) Lacoste, Myrtille; Cook, Simon; McNee, Matthew; Gale, Danielle; Ingram, Julie; Bellon-Maurel, Véronique; MacMillan, Tom; Sylvester-Bradley, Roger; Kindred, Daniel; Bramley, Rob; Tremblay, Nicolas; Nicolas, Louis; Thompson, Laura; Ruiz, Julie; Oscar García, Fernando; Maxwell, Bruce; Griffin, Terry; Oberthür, Thomas; Huyghe, Christian; Zhang, Weifeng; McNamara, John; Hall, Andrew
    Restructuring farmer–researcher relationships and addressing complexity and uncertainty through joint exploration are at the heart of On-Farm Experimentation (OFE). OFE describes new approaches to agricultural research and innovation that are embedded in real-world farm management, and reflects new demands for decentralized and inclusive research that bridges sources of knowledge and fosters open innovation. Here we propose that OFE research could help to transform agriculture globally. We highlight the role of digitalization, which motivates and enables OFE by dramatically increasing scales and complexity when investigating agricultural challenges.
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