Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI)

Disa M. El-Shikha, Edward M. Barnes, Thomas R. Clarke, Douglas J. Hunsaker, Julio A. Haberland, Paul J. Pinter, Peter M Waller, Thomas L. Thompson

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.

Original languageEnglish (US)
Pages (from-to)73-82
Number of pages10
JournalTransactions of the ASABE
Volume51
Issue number1
StatePublished - Jan 2008

Fingerprint

Chlorophyll
Cotton
remote sensing
cotton
Remote sensing
chlorophyll
Nitrogen
canopy
nitrogen
Crops
Water
Water Purification
Dehydration
Infrared radiation
Water treatment
index
near infrared
water treatment
water stress
crop

Keywords

  • Canopy reflectance
  • Fertility detection
  • Radiometers
  • Spectral analysis
  • Water stress

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Biomedical Engineering
  • Food Science
  • Forestry
  • Soil Science

Cite this

El-Shikha, D. M., Barnes, E. M., Clarke, T. R., Hunsaker, D. J., Haberland, J. A., Pinter, P. J., ... Thompson, T. L. (2008). Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI). Transactions of the ASABE, 51(1), 73-82.

Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI). / El-Shikha, Disa M.; Barnes, Edward M.; Clarke, Thomas R.; Hunsaker, Douglas J.; Haberland, Julio A.; Pinter, Paul J.; Waller, Peter M; Thompson, Thomas L.

In: Transactions of the ASABE, Vol. 51, No. 1, 01.2008, p. 73-82.

Research output: Contribution to journalArticle

El-Shikha, DM, Barnes, EM, Clarke, TR, Hunsaker, DJ, Haberland, JA, Pinter, PJ, Waller, PM & Thompson, TL 2008, 'Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI)', Transactions of the ASABE, vol. 51, no. 1, pp. 73-82.
El-Shikha DM, Barnes EM, Clarke TR, Hunsaker DJ, Haberland JA, Pinter PJ et al. Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI). Transactions of the ASABE. 2008 Jan;51(1):73-82.
El-Shikha, Disa M. ; Barnes, Edward M. ; Clarke, Thomas R. ; Hunsaker, Douglas J. ; Haberland, Julio A. ; Pinter, Paul J. ; Waller, Peter M ; Thompson, Thomas L. / Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI). In: Transactions of the ASABE. 2008 ; Vol. 51, No. 1. pp. 73-82.
@article{6f6a64a61da6486da838738ef9b2ab51,
title = "Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI)",
abstract = "Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30{\%}. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30{\%} cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.",
keywords = "Canopy reflectance, Fertility detection, Radiometers, Spectral analysis, Water stress",
author = "El-Shikha, {Disa M.} and Barnes, {Edward M.} and Clarke, {Thomas R.} and Hunsaker, {Douglas J.} and Haberland, {Julio A.} and Pinter, {Paul J.} and Waller, {Peter M} and Thompson, {Thomas L.}",
year = "2008",
month = "1",
language = "English (US)",
volume = "51",
pages = "73--82",
journal = "Transactions of the ASABE",
issn = "2151-0032",
publisher = "American Society of Agricultural and Biological Engineers",
number = "1",

}

TY - JOUR

T1 - Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI)

AU - El-Shikha, Disa M.

AU - Barnes, Edward M.

AU - Clarke, Thomas R.

AU - Hunsaker, Douglas J.

AU - Haberland, Julio A.

AU - Pinter, Paul J.

AU - Waller, Peter M

AU - Thompson, Thomas L.

PY - 2008/1

Y1 - 2008/1

N2 - Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.

AB - Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.

KW - Canopy reflectance

KW - Fertility detection

KW - Radiometers

KW - Spectral analysis

KW - Water stress

UR - http://www.scopus.com/inward/record.url?scp=41749095347&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=41749095347&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:41749095347

VL - 51

SP - 73

EP - 82

JO - Transactions of the ASABE

JF - Transactions of the ASABE

SN - 2151-0032

IS - 1

ER -