Matches in SemOpenAlex for { <https://semopenalex.org/work/W2016571835> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2016571835 endingPage "1407" @default.
- W2016571835 startingPage "1395" @default.
- W2016571835 abstract "Multispectral vegetation indices calculated from canopy reflectance measurements have been used to simulatereal-time basal crop coefficients (Kcb), which have been validated to improve evapotranspiration (ETc) estimation for severalcrops. In this article, an application of the approach was evaluated for cotton using remote sensing observations of thenormalized difference vegetation index (NDVI) to estimate Kcb as a function of NDVI. The dual crop coefficient proceduresof FAO Paper 56 (FAO-56) were used to calculate ETc and determine irrigation scheduling using Kcb estimates from remotesensing (NDVI treatment) as well as from time-based Kcb curves (FAO treatment), which were developed locally for standardcrop conditions using FAO-56 procedures. Two cotton experiments, conducted in 2002 and 2003 in central Arizona, includedsub-treatments of three levels of plant density and two levels of nitrogen management to impose a wide range of cropdevelopment and water use. The NDVI-Kcb relationships used for 2002, developed from previous data for a different cottoncultivar, row orientation, and soil type, substantially underestimated ETc, resulting in significantly less irrigation waterapplied and lower lint yields for NDVI compared to the FAO treatment. The 2002 data were used to recalibrate the NDVI-Kcbrelationships, which were then used for the NDVI treatments in 2003. The FAO Kcb curve used in 2002 described ETc andirrigation scheduling reasonably well for sparse plots, but consistently underestimated water use and soil water depletionfor the higher plant densities during the first half of the season. Consequently, an adjusted FAO Kcb curve, based on 2002results, was employed for the FAO treatment in 2003. For the 2003 experiment, estimated cotton ETc for the NDVI treatmentresulted in a mean absolute error of 9% compared to 10% for the FAO treatment, where the difference was not significantbetween treatments. However, the NDVI-Kcb relations used in 2003 greatly improved estimates for ETc compared to theprevious year, where the mean absolute error for the NDVI treatment in 2002 was 22%. Predicted ETc using the FAO Kcb curveof 2003 for typical planting density and high nitrogen conditions resulted in a mean absolute error of 10% compared to 15%in 2002. Final lint yields for 2003 were not significantly different between the two Kcb methods. Although additional researchis needed to validate remote sensing Kcb estimation for other conditions than those in these experiments, this study did notshow significant advantages for the NDVI approach over a carefully derived single FAO Kcb application. However, the NDVIapproach has the potential to further extend our present crop coefficient estimation capabilities when weather, plant density,or other factors cause cotton canopy development and water use patterns to depart from typical conditions." @default.
- W2016571835 created "2016-06-24" @default.
- W2016571835 creator A5004587268 @default.
- W2016571835 creator A5049287559 @default.
- W2016571835 creator A5074382306 @default.
- W2016571835 creator A5091047501 @default.
- W2016571835 creator A5091127785 @default.
- W2016571835 date "2005-01-01" @default.
- W2016571835 modified "2023-10-06" @default.
- W2016571835 title "COTTON IRRIGATION SCHEDULING USING REMOTELY SENSED AND FAO-56 BASAL CROP COEFFICIENTS" @default.
- W2016571835 doi "https://doi.org/10.13031/2013.19197" @default.
- W2016571835 hasPublicationYear "2005" @default.
- W2016571835 type Work @default.
- W2016571835 sameAs 2016571835 @default.
- W2016571835 citedByCount "126" @default.
- W2016571835 countsByYear W20165718352012 @default.
- W2016571835 countsByYear W20165718352013 @default.
- W2016571835 countsByYear W20165718352014 @default.
- W2016571835 countsByYear W20165718352015 @default.
- W2016571835 countsByYear W20165718352016 @default.
- W2016571835 countsByYear W20165718352017 @default.
- W2016571835 countsByYear W20165718352018 @default.
- W2016571835 countsByYear W20165718352019 @default.
- W2016571835 countsByYear W20165718352020 @default.
- W2016571835 countsByYear W20165718352021 @default.
- W2016571835 countsByYear W20165718352022 @default.
- W2016571835 countsByYear W20165718352023 @default.
- W2016571835 crossrefType "journal-article" @default.
- W2016571835 hasAuthorship W2016571835A5004587268 @default.
- W2016571835 hasAuthorship W2016571835A5049287559 @default.
- W2016571835 hasAuthorship W2016571835A5074382306 @default.
- W2016571835 hasAuthorship W2016571835A5091047501 @default.
- W2016571835 hasAuthorship W2016571835A5091127785 @default.
- W2016571835 hasConcept C101000010 @default.
- W2016571835 hasConcept C127313418 @default.
- W2016571835 hasConcept C137660486 @default.
- W2016571835 hasConcept C1549246 @default.
- W2016571835 hasConcept C159390177 @default.
- W2016571835 hasConcept C159750122 @default.
- W2016571835 hasConcept C166957645 @default.
- W2016571835 hasConcept C176783924 @default.
- W2016571835 hasConcept C187320778 @default.
- W2016571835 hasConcept C18903297 @default.
- W2016571835 hasConcept C205649164 @default.
- W2016571835 hasConcept C25989453 @default.
- W2016571835 hasConcept C2777589951 @default.
- W2016571835 hasConcept C2778145279 @default.
- W2016571835 hasConcept C39432304 @default.
- W2016571835 hasConcept C6557445 @default.
- W2016571835 hasConcept C72551326 @default.
- W2016571835 hasConcept C76886044 @default.
- W2016571835 hasConcept C86803240 @default.
- W2016571835 hasConcept C88862950 @default.
- W2016571835 hasConceptScore W2016571835C101000010 @default.
- W2016571835 hasConceptScore W2016571835C127313418 @default.
- W2016571835 hasConceptScore W2016571835C137660486 @default.
- W2016571835 hasConceptScore W2016571835C1549246 @default.
- W2016571835 hasConceptScore W2016571835C159390177 @default.
- W2016571835 hasConceptScore W2016571835C159750122 @default.
- W2016571835 hasConceptScore W2016571835C166957645 @default.
- W2016571835 hasConceptScore W2016571835C176783924 @default.
- W2016571835 hasConceptScore W2016571835C187320778 @default.
- W2016571835 hasConceptScore W2016571835C18903297 @default.
- W2016571835 hasConceptScore W2016571835C205649164 @default.
- W2016571835 hasConceptScore W2016571835C25989453 @default.
- W2016571835 hasConceptScore W2016571835C2777589951 @default.
- W2016571835 hasConceptScore W2016571835C2778145279 @default.
- W2016571835 hasConceptScore W2016571835C39432304 @default.
- W2016571835 hasConceptScore W2016571835C6557445 @default.
- W2016571835 hasConceptScore W2016571835C72551326 @default.
- W2016571835 hasConceptScore W2016571835C76886044 @default.
- W2016571835 hasConceptScore W2016571835C86803240 @default.
- W2016571835 hasConceptScore W2016571835C88862950 @default.
- W2016571835 hasIssue "4" @default.
- W2016571835 hasLocation W20165718351 @default.
- W2016571835 hasOpenAccess W2016571835 @default.
- W2016571835 hasPrimaryLocation W20165718351 @default.
- W2016571835 hasRelatedWork W2009080236 @default.
- W2016571835 hasRelatedWork W2040693669 @default.
- W2016571835 hasRelatedWork W2048402716 @default.
- W2016571835 hasRelatedWork W2080917855 @default.
- W2016571835 hasRelatedWork W2155475491 @default.
- W2016571835 hasRelatedWork W2461280504 @default.
- W2016571835 hasRelatedWork W2471488128 @default.
- W2016571835 hasRelatedWork W2608840982 @default.
- W2016571835 hasRelatedWork W4324136265 @default.
- W2016571835 hasRelatedWork W2181902620 @default.
- W2016571835 hasVolume "48" @default.
- W2016571835 isParatext "false" @default.
- W2016571835 isRetracted "false" @default.
- W2016571835 magId "2016571835" @default.
- W2016571835 workType "article" @default.