By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields.
Abstract. This study addresses the problem of balancing the trade-offs between the need for animal production, profit, and the goal of achieving persistence of desirable species within grazing systems. The bioeconomic framework applied in this study takes into account the impact of climate risk and the management of pastures and grazing rules on the botanical composition of the pasture resource, a factor that impacts on livestock production and economic returns over time. The framework establishes the links between inputs, the state of the pasture resource and outputs, to identify optimal pasture development strategies. The analysis is based on the application of a dynamic pasture resource development simulation model within a seasonal stochastic dynamic programming framework. This enables the derivation of optimum decisions within complex grazing enterprises, over both short-term tactical (such as grazing rest) and long-term strategic (such as pasture renovation) time frames and under climatic uncertainty. The simulation model is parameterised using data and systems from the Cicerone Project farmlet experiment. Results indicate that the strategic decision of pasture renovation should only be considered when pastures are in a severely degraded state, whereas the tactical use of grazing rest or low stocking rates should be considered as the most profitable means of maintaining adequate proportions of desirable species within a pasture sward. The optimal stocking rates identified reflected a pattern which may best be described as a seasonal saving and consumption cycle. The optimal tactical and strategic decisions at different pasture states, based on biomass and species composition, varies both between seasons and in response to the imposed soil fertility regime. Implications of these findings at the whole-farm level are discussed in the context of the Cicerone Project farmlets.
Autonomous equipment for crop production is on the verge of technical and economic feasibility, but government regulation may slow its adoption. Key regulatory issues include requirements for on‐site human supervision, liability for autonomous machine error, and intellectual property in robotic learning. As an example of the impact of regulation on the economic benefits of autonomous crop equipment, analysis from the United Kingdom suggests that requiring 100% on‐site human supervision almost wipes out the economic benefits of autonomous crop equipment for small and medium farms and increases the economies‐of‐scale advantage of larger farms.
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