Optimizing crop seeding rates on organic grain farms using on farm precision experimentation

Organic agriculture is often regarded as less damaging to the environment than conventional agriculture, though at the expense of lower yields. Field-specific precision agriculture may benefit organic production practices given the inherent need of organic farmers to understand spatiotemporal variation on large-scale fields. Here the primary research question is whether on-farm precision experimentation (OFPE) can be used as an adaptive management methodology to efficiently maximize farmer net returns using variable cover crop and cash crop seeding rates. Inputs of cash crop seed and previous-year green manure cover crop seed were experimentally varied on five different farms across the Northern Great Plains from 2019 to 2022. Experiments provided data to model the crop yield response, and subsequently net return, in response to input (seeding) rates plus a suite of other spatially explicit data from satellite sources. New, field-specific spatially explicit optimum input rates were generated to maximize net return including temporal variation in economic variables. Inputs were spatially optimized and using simulations it was found that the optimization strategies consistently out-performed other strategies by reducing inputs and increasing yields, particularly for non-tillering crops. By adopting site specific management, the average increase in net return for all fields was $50 ha −1 . These results showed that precision agriculture technologies and remote sensing can be utilized to provide organic farmers powerful adaptive management tools with a focus on within-field spatial variability in response to primary input drivers of economic return. Continued OFPE for seeding rate optimization will allow quantification of temporal variability and subsequent probabilistic recommendations. • Precision agriculture can improve organic agriculture net return by $50 ha −1 . • Remote sensing can improve precision agriculture applications on organic farms. • Non-tillering crops gain more from spatially optimized input rates than tillering ones.

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Publication Details

Journal
Field Crops Research
Published
2024-09-27
DOI
https://doi.org/10.1016/j.fcr.2024.109593
Citations
8
Primary Topic
Agricultural economics and policies
Type
article
Field-Weighted Citation Impact
4.21

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article

Optimizing crop seeding rates on organic grain farms using on farm precision experimentation

Bruce D. Maxwell, Sasha Loewen
8 citations
Field Crops Research
Agricultural economics and policies
4.21
article

Optimizing crop seeding rates on organic grain farms using on farm precision experimentation

Bruce D. Maxwell, Sasha Loewen
article en
8 citations

Abstract

Organic agriculture is often regarded as less damaging to the environment than conventional agriculture, though at the expense of lower yields. Field-specific precision agriculture may benefit organic production practices given the inherent need of organic farmers to understand spatiotemporal variation on large-scale fields. Here the primary research question is whether on-farm precision experimentation (OFPE) can be used as an adaptive management methodology to efficiently maximize farmer net returns using variable cover crop and cash crop seeding rates. Inputs of cash crop seed and previous-year green manure cover crop seed were experimentally varied on five different farms across the Northern Great Plains from 2019 to 2022. Experiments provided data to model the crop yield response, and subsequently net return, in response to input (seeding) rates plus a suite of other spatially explicit data from satellite sources. New, field-specific spatially explicit optimum input rates were generated to maximize net return including temporal variation in economic variables. Inputs were spatially optimized and using simulations it was found that the optimization strategies consistently out-performed other strategies by reducing inputs and increasing yields, particularly for non-tillering crops. By adopting site specific management, the average increase in net return for all fields was $50 ha −1 . These results showed that precision agriculture technologies and remote sensing can be utilized to provide organic farmers powerful adaptive management tools with a focus on within-field spatial variability in response to primary input drivers of economic return. Continued OFPE for seeding rate optimization will allow quantification of temporal variability and subsequent probabilistic recommendations. • Precision agriculture can improve organic agriculture net return by $50 ha −1 . • Remote sensing can improve precision agriculture applications on organic farms. • Non-tillering crops gain more from spatially optimized input rates than tillering ones.

Field Crops ResearchVol. 318
Montana State University (US)
Western SARE, Natural Resources Conservation Service
Zero hunger
Openalex Percentile: Top 5%
Agricultural economics and policies
4.21
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