Abstract
Precision N management based on crop reflectance can be used to reduce over‐ and under‐application of N fertilizer to cotton ( Gossypium hirsutum L.). The objective of this study was to evaluate the effects of variable‐rate nitrogen management systems (VNMS) based on optical sensing of crop canopy relative to a farmer's uniform‐rate nitrogen application system (FUNS) on N fertilizer consumption, post‐harvest soil N level, and cotton productivity. Eight field strip‐plot trials were conducted on cotton across West Tennessee during 2012 to 2014. Four sensor‐based VNMS were compared with FUNS in a randomized complete block design with three replicates. Two VNMS were based on optical sensing of canopy alone with different algorithms, while the other two were developed from optical sensing and crop yield maps of previous years but differed in algorithms. The variable and uniform fertilizer application systems had similar leaf N concentrations between early bloom and mid‐bloom and similar canopy normalized difference vegetation index (NDVI) values at mid‐bloom. The VNMS produced similar lint yield as FUNS. The VNMS reduced N consumption by 10.3 to 16.9% and improved nitrogen use efficiency (NUE) by 8.3 to 11.0% compared with FUNS. Both VNMS and FUNS had similar post‐harvest N levels in soil profile. Benefits from incorporating yield maps into sensor‐based VNMS were not noticeable. Thus, the in‐season sensor‐based VNMS are reliable in precision N management for cotton resulting in comparable lint yield, less N consumption, and higher NUE, which could lead to environmental and economic benefits. Core Ideas Leaf N concentration and canopy normalized difference vegetation index were comparable under variable‐rate N management systems relative to a farmer's uniform‐rate N application system. Variable‐rate N management systems produced similar lint yield but better fiber quality compared with a farmer's uniform‐rate N application system. Variable‐rate N management systems reduced N use by 10.3 to 16.9% but increased nitrogen use efficiency by 8.3 to 11.0% over a farmer's uniform‐rate N application system. No effect of variable‐rate N management systems was observed on post‐harvest soil N level relative to a farmer's uniform‐rate N application system. Benefits with incorporating yield maps into sensor‐based variable‐rate N management systems were not noticeable.
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Claims 9
Claim · model-written summary
Variable-rate N management systems reduced N consumption by 10.3 to 16.9% compared with the farmer uniform-rate system.
- Taxon
- Gossypium hirsutum
Gossypium hirsutume0 - Treatment
- VNMSe1
- Outcome
- N consumptione1
- Direction
- reducede1
- Value
- 10.3 to 16.9%e1
- Comparator
- FUNSe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e1“The VNMS produced similar lint yield as FUNS. The VNMS reduced N consumption by 10.3 to 16.9% and improved nitrogen use efficiency (NUE) by 8.3 to 11.0% compared with FUNS”
Claim · model-written summary
Variable-rate N management systems improved nitrogen use efficiency by 8.3 to 11.0% compared with the farmer uniform-rate system.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- VNMSe1
- Outcome
- nitrogen use efficiency (NUE)e1
- Direction
- improvede1
- Value
- 8.3 to 11.0%e1
- Comparator
- FUNSe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e1“The VNMS produced similar lint yield as FUNS. The VNMS reduced N consumption by 10.3 to 16.9% and improved nitrogen use efficiency (NUE) by 8.3 to 11.0% compared with FUNS”
Claim · model-written summary
Variable-rate N management systems produced lint yield similar to the uniform-rate system.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- VNMSe1
- Outcome
- lint yielde1
- Direction
- no_changeinferrede1
- Comparator
- FUNSe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e1“The VNMS produced similar lint yield as FUNS. The VNMS reduced N consumption by 10.3 to 16.9% and improved nitrogen use efficiency (NUE) by 8.3 to 11.0% compared with FUNS”
Claim · model-written summary
Variable-rate and uniform fertilizer application systems had similar leaf N concentrations between early bloom and mid-bloom.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- variable and uniform fertilizer application systemse2
- Outcome
- leaf N concentrationse2
- Direction
- no_changeinferrede2
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e2“The variable and uniform fertilizer application systems had similar leaf N concentrations between early bloom and mid‐bloom and similar canopy normalized difference vegetation index (NDVI) values at mid‐bloom”
Claim · model-written summary
Variable-rate and uniform fertilizer application systems had similar canopy NDVI values at mid-bloom.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- variable and uniform fertilizer application systemse2
- Outcome
- canopy normalized difference vegetation index (NDVI) valuese2
- Direction
- no_changeinferrede2
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e2“The variable and uniform fertilizer application systems had similar leaf N concentrations between early bloom and mid‐bloom and similar canopy normalized difference vegetation index (NDVI) values at mid‐bloom”
Claim · model-written summary
Variable-rate and uniform systems had similar post-harvest N levels in the soil profile.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- VNMSe3
- Outcome
- N levels in soil profilee3
- Direction
- no_changeinferrede3
- Comparator
- FUNSe3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e3“Both VNMS and FUNS had similar post‐harvest N levels in soil profile”
Claim · model-written summary
Variable-rate N management systems gave better fiber quality than the farmer uniform-rate system while producing similar lint yield.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- Variable‐rate N management systemse6
- Outcome
- fiber qualitye6
- Direction
- bettere6
- Comparator
- a farmer's uniform‐rate N application systeme6
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e6“Variable‐rate N management systems produced similar lint yield but better fiber quality compared with a farmer's uniform‐rate N application system”
Claim · model-written summary
Incorporating yield maps into sensor-based variable-rate N systems gave no noticeable benefit.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Treatment
- incorporating yield maps into sensor‐based VNMSe5
- Outcome
- Benefitse5
- Direction
- no_changeinferrede5
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e5“Benefits from incorporating yield maps into sensor‐based VNMS were not noticeable”
Claim · model-written summary
The authors conclude that in-season sensor-based variable-rate N systems are reliable for precision N management in cotton.
- Taxon
- Gossypium hirsutumGossypium hirsutume0
- Outcome
- precision N managemente4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“cotton ( Gossypium hirsutum L.)”
e4“Thus, the in‐season sensor‐based VNMS are reliable in precision N management for cotton resulting in comparable lint yield, less N consumption, and higher NUE”
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See all 202 papers →8 of 9 groups shown: named compounds and organisms first, then groups whose results differ (checked claim by claim), then those with positive and negative results, then the smaller groups.
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.