Abstract
Nitrogen management for corn ( Zea mays L.) may be improved by applying a portion of N in‐season. This investigation was conducted to evaluate crop modeling (Maize‐N) and active crop canopy sensing approaches for recommending in‐season N fertilizer rates. These approaches were evaluated during 2012–2013 on 11 field sites, in Missouri, Nebraska, and North Dakota. Nitrogen management also included a no‐N treatment (check) and a non‐limiting N reference (all at planting). Nitrogen management treatments were assessed for two hybrids and at low and high seeding rates, arranged in a randomized complete block design. In 9 of 11 site‐years, the sensor‐based approach recommended lower in‐season N rates than the model (collectively 59% less N), resulting in trends of higher partial factor productivity of nitrogen (PFP N ) and higher agronomic efficiency (AE) than the model. However, yield was better protected by the model‐based approach. In some situations, canopy sensing excelled at optimizing the N rate for localized conditions. With abnormally warm and moist soil conditions for the 2012 Nebraska sites and presumed high levels of inorganic N from mineralization, N application was appropriately reduced, resulting in no yield decrease and N savings compared to the non‐limiting N reference. Depending on the site, both recommendation approaches were successful; a combination of model and sensor information may optimize in‐season decision support for N recommendation.
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Claims 8
Claim · model-written summary
The sensor approach recommended lower in-season nitrogen rates than the model in 9 of 11 site-years, collectively 59% less nitrogen.
- Taxon
- Corn
Zea mays subsp. mayst0 - Outcome
- in‐season N ratese0
- Direction
- lowere0
- Value
- 59% less Ne0
- Qualifier
- 9 of 11 site‐yearse0
- Comparator
- the modele0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“In 9 of 11 site‐years, the sensor‐based approach recommended lower in‐season N rates than the model (collectively 59% less N)”
t0“Corn”
Claim · model-written summary
The sensor approach showed a trend toward higher partial factor productivity of nitrogen than the model.
- Taxon
- CornZea mays subsp. mayst0
- Treatment
- the sensor‐based approache1
- Outcome
- partial factor productivity of nitrogen (PFP N )e0
- Direction
- highere0
- Qualifier
- trendse0
- Comparator
- the modele0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“trends of higher partial factor productivity of nitrogen (PFP N ) and higher agronomic efficiency (AE) than the model”
t0“Corn”
e1“the sensor‐based approach recommended lower in‐season N rates than the model”
Claim · model-written summary
The sensor approach showed a trend toward higher agronomic efficiency than the model.
- Taxon
- CornZea mays subsp. mayst0
- Treatment
- the sensor‐based approache1
- Outcome
- agronomic efficiency (AE)e0
- Direction
- highere0
- Qualifier
- trendse0
- Comparator
- the modele0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“trends of higher partial factor productivity of nitrogen (PFP N ) and higher agronomic efficiency (AE) than the model”
t0“Corn”
e1“the sensor‐based approach recommended lower in‐season N rates than the model”
Claim · model-written summary
The model approach protected yield better than the sensor approach.
- Taxon
- CornZea mays subsp. mayst0
- Treatment
- model‐based approache0
- Outcome
- yielde0
- Direction
- better protectede0
- Comparator
- the sensor‐based approache1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“yield was better protected by the model‐based approach”
e1“the sensor‐based approach recommended lower in‐season N rates than the model”
t0“Corn”
Claim · model-written summary
Canopy sensing sometimes optimized nitrogen rate for localized conditions.
- Taxon
- CornZea mays subsp. mayst0
- Outcome
- optimizing the N ratee0
- Qualifier
- In some situationse0
Not reportedComparatorDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“In some situations, canopy sensing excelled at optimizing the N rate for localized conditions”
t0“Corn”
Claim · model-written summary
For warm, moist 2012 Nebraska sites, nitrogen application was reduced with no yield decrease relative to the non-limiting reference.
- Taxon
- CornZea mays subsp. mayst0
- Treatment
- N application was appropriately reducede0
- Outcome
- yielde0
- Direction
- no yield decreasee0
- Comparator
- non‐limiting N referencee0
- Setting
- 2012 Nebraska sitese0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“With abnormally warm and moist soil conditions for the 2012 Nebraska sites and presumed high levels of inorganic N from mineralization, N application was appropriately reduced, resulting in no yield decrease and N savings compared to the non‐limiting N reference”
t0“Corn”
Claim · model-written summary
For the 2012 Nebraska sites, reduced nitrogen application saved nitrogen relative to the non-limiting reference.
- Taxon
- CornZea mays subsp. mayst0
- Treatment
- N application was appropriately reducede0
- Outcome
- N savingse0
- Direction
- savingse0
- Comparator
- non‐limiting N referencee0
- Setting
- 2012 Nebraska sitese0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“With abnormally warm and moist soil conditions for the 2012 Nebraska sites and presumed high levels of inorganic N from mineralization, N application was appropriately reduced, resulting in no yield decrease and N savings compared to the non‐limiting N reference”
t0“Corn”
Claim · model-written summary
The authors suggest combining model and sensor information to optimize in-season nitrogen recommendations.
- Taxon
- CornZea mays subsp. mayst0
- Outcome
- a combination of model and sensor information may optimize in‐season decision support for N recommendatione0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“a combination of model and sensor information may optimize in‐season decision support for N recommendation”
t0“Corn”
The same questions in other papers
nitrogen · yield · Zea mays (maize)Positive and negative results
1,905 papers in the same direction as this paper · 234 in the opposite direction · 45 reporting no difference from an alternative
- no effect
- no effect
- no effect
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See all 2,185 papers →Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.