Estimating Cotton Nitrogen Nutrition Status Using Leaf Greenness and Ground Cover Information

dc.creatorMuharam, Farrah Melissa (TTU)
dc.creatorMaas, Stephen J. (TTU)
dc.creatorBronson, Kevin F.
dc.creatorDelahunty, Tina
dc.date.accessioned2023-01-31T17:05:39Z
dc.date.available2023-01-31T17:05:39Z
dc.date.issued2015
dc.description© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.description.abstractAssessing nitrogen (N) status is important from economic and environmental standpoints. To date, many spectral indices to estimate cotton chlorophyll or N content have been purely developed using statistical analysis approach where they are often subject to site-specific problems. This study describes and tests a novel method of utilizing physical characteristics of N-fertilized cotton and combining field spectral measurements made at different spatial scales as an approach to estimate in-season chlorophyll or leaf N content of field-grown cotton. In this study, leaf greenness estimated from spectral measurements made at the individual leaf, canopy and scene levels was combined with percent ground cover to produce three different indices, named TCCLeaf, TCCCanopy, and TCCScene. These indices worked best for estimating leaf N at early flowering, but not for chlorophyll content. Of the three indices, TCCLeaf showed the best ability to estimate leaf N (R2 = 0.89). These results suggest that the use of green and red-edge wavelengths derived at the leaf scale is best for estimating leaf greenness. TCCCanopy had a slightly lower R2 value than TCCLeaf (0.76), suggesting that the utilization of yellow and red-edge wavelengths obtained at the canopy level could be used as an alternative to estimate leaf N in the absence of leaf spectral information. The relationship between TCCScene and leaf N was the lowest (R2 = 0.50), indicating that the estimation of canopy greenness from scene measurements needs improvement. Results from this study confirmed the potential of these indices as efficient methods for estimating in-season leaf N status of cotton.en_US
dc.identifier.citationMuharam FM, Maas SJ, Bronson KF, Delahunty T. Estimating Cotton Nitrogen Nutrition Status Using Leaf Greenness and Ground Cover Information. Remote Sensing. 2015; 7(6):7007-7028. https://doi.org/10.3390/rs70607007en_US
dc.identifier.urihttps://doi.org/10.3390/rs70607007
dc.identifier.urihttps://hdl.handle.net/2346/90496
dc.language.isoengen_US
dc.subjectSpectroradiometeren_US
dc.subjectGround Coveren_US
dc.subjectNitrogenen_US
dc.subjectLeafen_US
dc.subjectCanopyen_US
dc.subjectSceneen_US
dc.titleEstimating Cotton Nitrogen Nutrition Status Using Leaf Greenness and Ground Cover Informationen_US
dc.typeArticleen_US

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