Abstract
A key goal of precision agriculture is to achieve the maximum crop yield while minimizing inputs and loses from cropping systems. The challenge of precision agriculture is these factors interact with one another on a subfield scale. The seeding density and the nitrogen (N) fertilizer application rate are two of the most important inputs influencing agronomic, economic and environmental outcomes including yield, return on investment (ROI) and nitrate (NO3-) leaching. A cropping system simulation framework is used to predict site-specific subfield optimum seeding density and (N) fertilizer application rates for the economic optimum (maximum ROI) versus agronomic optimum (maximum yield). The framework couples the process-based APSIM cropping system model with the SSURGO soils database, Daymet weather data service, land grant university estimates of crop production costs and commodity price estimates, and the R statistics software. The framework performance was evaluated using multiple years of precision yield monitor data obtained from a continuous maize (Zea mays L.) cropping system field experiment with varying N-fertilizer rates. Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field and had an r2 = 0.65 and a root mean square error of 2356.0 kg ha-1. A site-specific application of the framework comparing economic optimum seeding density and N-fertilizer rates with agronomic optimum values estimated the average ROI benefit to be up to 12.1% with a NO3- leaching reduction of up to 15.2 kg ha-1 at the economic optimum. However, in a minority of cases NO3- leaching was greater at the economic optimum, indicating that managing to maximize ROI rather than yield may not always reduce environmental impacts. Our results suggest that managing cropping systems for the economic optimum is plausible using publicly available data with our framework and may likely lead to improved environmental outcomes.
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Claims 7
Claim · model-written summary
Subfield yield estimates were sensitive to initial conditions related to past field management.
- Outcome
- Subfield model estimates of crop yielde1
- Qualifier
- initial conditions related to historical management of the fielde1
Zea maysNot reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field”
Claim · model-written summary
The model had r2 = 0.65 for subfield crop yield estimates.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field and had an r2 = 0.65 and a root mean square error of 2356.0 kg ha-1”
Claim · model-written summary
The model root mean square error for yield was 2356.0 kg ha-1.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“root mean square error of 2356.0 kg ha-1”
Claim · model-written summary
Economic optimum seeding and nitrogen rates raised mean ROI by up to 12.1% compared with agronomic optima.
- Treatment
- economic optimum seeding density and N-fertilizer ratese1
- Outcome
- average ROI benefite1
- Direction
- benefite1
- Value
- up to 12.1%e1
- Comparator
- agronomic optimum valuese1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“comparing economic optimum seeding density and N-fertilizer rates with agronomic optimum values estimated the average ROI benefit to be up to 12.1%”
Claim · model-written summary
Economic optimum rates lowered nitrate leaching by up to 15.2 kg ha-1 compared with agronomic optima.
- Treatment
- economic optimum seeding density and N-fertilizer ratese1
- Outcome
- NO3- leachinge1
- Direction
- reductione1
- Value
- up to 15.2 kg ha-1e1
- Comparator
- agronomic optimum valuese1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“comparing economic optimum seeding density and N-fertilizer rates with agronomic optimum values estimated the average ROI benefit to be up to 12.1% with a NO3- leaching reduction of up to 15.2 kg ha-1 at the economic optimum”
Claim · model-written summary
In a minority of cases nitrate leaching was greater at the economic optimum.
- Treatment
- economic optimume1
- Outcome
- NO3- leachinge1
- Direction
- greatere1
- Qualifier
- in a minority of casese1
- Comparator
- agronomic optimume2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“in a minority of cases NO3- leaching was greater at the economic optimum”
e2“economic optimum (maximum ROI) versus agronomic optimum (maximum yield)”
Claim · model-written summary
The authors suggest economic optimum management is plausible with public data and may improve environmental outcomes.
- Outcome
- managing cropping systems for the economic optimume1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“continuous maize (Zea mays L.) cropping system”
e1“managing cropping systems for the economic optimum is plausible using publicly available data with our framework and may likely lead to improved environmental outcomes”
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