Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Volume
    • AJEV and Catalyst Archive
    • Best Papers
    • ASEV National Conference Technical Abstracts
    • Back Orders
  • Information For
    • Authors
    • Open Access Publishing
    • AJEV Preprint and AI Software Policy
    • Submission
    • Subscribers
      • Proprietary Rights Notice for AJEV Online
    • Permissions and Reproductions
  • About Us
  • Feedback
  • Alerts
  • Help
  • Login
  • ASEV MEMBER LOGIN

User menu

  • Log in

Search

  • Advanced search
American Journal of Enology and Viticulture
  • Log in
  • Follow ajev on Twitter
  • Follow ajev on Linkedin
American Journal of Enology and Viticulture

Advanced Search

  • Home
  • Content
    • Current Volume
    • AJEV and Catalyst Archive
    • Best Papers
    • ASEV National Conference Technical Abstracts
    • Back Orders
  • Information For
    • Authors
    • Open Access Publishing
    • AJEV Preprint and AI Software Policy
    • Submission
    • Subscribers
    • Permissions and Reproductions
  • About Us
  • Feedback
  • Alerts
  • Help
  • Login
  • ASEV MEMBER LOGIN
Article

Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards

José R. Rodríguez-Pérez, David Riaño, Eli Carlisle, Susan Ustin, David R. Smart
Am J Enol Vitic.  2007  58: 302-317  ; DOI: 10.5344/ajev.2007.58.3.302
José R. Rodríguez-Pérez
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Find this author on ADS search
  • Find this author on Agricola
  • Search for this author on this site
David Riaño
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Find this author on ADS search
  • Find this author on Agricola
  • Search for this author on this site
Eli Carlisle
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Find this author on ADS search
  • Find this author on Agricola
  • Search for this author on this site
Susan Ustin
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Find this author on ADS search
  • Find this author on Agricola
  • Search for this author on this site
David R. Smart
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Find this author on ADS search
  • Find this author on Agricola
  • Search for this author on this site
  • For correspondence: drsmart{at}ucdavis.edu
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Irrigation scheduling is critical as it affects both fruit yield and composition. We examined the potential to use field-measured hyperspectral remote sensing data (reflectance and transmission over the 350–2500 nm wavelength region) to estimate leaf water content, equivalent water thickness (EWT), and leaf water potential (Ψ) in a commercial vineyard of Vitis vinifera cv. Pinot noir. The data allowed us to evaluate a number of reflectance patterns to estimate vine water status through correlations using two spectral approaches: direct measurement of vegetation indexes (VIs) and continuum removal analysis (CRA). Continuum removal analysis was applied to obtain the maximum band depth (MBD) and the band area (BA) of several absorption features sensitive to water content. Correlations were high for EWT at the leaf level using a modification of the Simple Ratio VI (SR2; R2 = 0.916) and for CRA with MBD970 (R2 = 0.917) and BA1160 (R2 = 0.897). Correlations with EWT and water potential at the canopy level for SR2 were nonsignificant, which was characteristic for many VIs. For predawn water potential (ΨPD) and midday stem water potential (Ψstem) at the canopy level, best fits were realized for Modified Triangular VI (MTVI2; R2 = 0.360) and Red/Green VI (RGI, R695/R554; R2 = 0.462), respectively. For canopy level water status, the best results were obtained using the difference between the midday stem water potential and the pre-dawn leaf water potential (Ψstem - ΨPD) with R2 = 0.619 for RGI and R2 = 0.541 for Structure Intensive Pigment Index (SIPI, R800-R445/R800-R680), while for CRA R2 = 0.477 for BA1600 and R2 = 0.509 for MBD970. Results suggest that noninvasive monitoring using hyperspectral data could improve current methods for estimating water status in individual vines. Applications of similar measurements could be produced from airborne hyperspectral imagers to provide spatially resolved estimates of water stress for use in water management of large-scale commercial vineyards.

  • vineyard remote sensing
  • vine water stress
  • leaf reflectance
  • canopy reflectance
  • vegetation index
  • Ψleaf, midday leaf water potential (MPa)
  • ΨPD, predawn leaf water potential (MPa)
  • Ψstem, midday stem water potential (MPa)
  • Ψs, osmotic potential (MPa)
  • Ψt, turgor pressure (MPa)
  • gs, stomatal conductance to water vapor (mmol m−2 s−1)
  • E, transpiration rate (mmol H2O m−2 s−1)
  • A, net photosynthetic rate (μmol CO2 m−2 s−1)
  • LA, leaf area (cm2)
  • LAI, leaf area index (m2 m−2)
  • Wt, total leaf weight (g)
  • Wd: oven dry leaf weight (g)
  • RWC, relative water content (%)
  • WCd, water content as percent of dry mass (%)
  • WCt, water content as percent of total fresh mass (%)
  • EWT, equivalent water thickness (g cm−2)
  • SLW, specific leaf weight dry mass (kg m−2)
  • TSLW, total specific leaf fresh weight (kg m−2)
  • CRA, continuum removal analysis
  • BA, band area of the absorption feature in CRA
  • D, band depth in CRA
  • R, measured reflectance
  • MBD, maximum band depth of the absorption feature in CRA
  • lMBD, wavelength of the maximum band depth of the absorption feature in CRA (nm)
  • FWHM, full band width at half maximum (nm)
  • REIP, red-edge inflection position (nm)
  • REIPv, derivative value of REIP (nm)
  • ASD, Analytical Spectral Device (350–2500 nm)
  • VIS, visual light spectrum (400–700 nm)
  • IR, infrared light (750 nm–1 mm)
  • NIR, near-IR (700–1300 nm)
  • MIR, mid-IR (1300–2500 nm)
  • SWIR, shortwave IR reflectance (1400–3000 nm)
  • Rs, reflectance (relative units)
  • Is, leaf reflectance (relative units)
  • Id, leaf reflectance in the dark (relative units)
  • Ir reference reflectance (relative units)
  • VI, vegetation index(es) (waveband ratios)
  • Received October 2006.
  • Revision received December 2006.
  • Copyright © 2007 by the American Society for Enology and Viticulture
View Full Text

Sign in for ASEV members

ASEV Members, please sign in at ASEV to access the journal online.

Sign in for Institutional and Non-member Subscribers

Log in using your username and password

Forgot your user name or password?

Pay Per Article - You may access this article (from the computer you are currently using) for 2 day for US$10.00

Regain Access - You can regain access to a recent Pay per Article purchase if your access period has not yet expired.

Forgot your user name or password?

PreviousNext
Back to top

Vol 58 Issue 3

  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
View full PDF
Email Article

Thank you for your interest in spreading the word on AJEV.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards
(Your Name) has forwarded a page to you from AJEV
(Your Name) thought you would like to read this article from the American Journal of Enology and Viticulture.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
You have accessRestricted access
Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards
José R. Rodríguez-Pérez, David Riaño, Eli Carlisle, Susan Ustin, David R. Smart
Am J Enol Vitic.  2007  58: 302-317  ; DOI: 10.5344/ajev.2007.58.3.302
José R. Rodríguez-Pérez
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Riaño
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eli Carlisle
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Susan Ustin
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David R. Smart
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: drsmart{at}ucdavis.edu

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero

Share
You have accessRestricted access
Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards
José R. Rodríguez-Pérez, David Riaño, Eli Carlisle, Susan Ustin, David R. Smart
Am J Enol Vitic.  2007  58: 302-317  ; DOI: 10.5344/ajev.2007.58.3.302
José R. Rodríguez-Pérez
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Riaño
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eli Carlisle
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Susan Ustin
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David R. Smart
1Universidad de León, Área de Ingeniería Cartográfica, Geodésica y Fotogrametría, Avda. de Astorga, s/n, 24400 Ponferrada León, Spain; 2Center for Spatial Technologies and Remote Sensing and 3Department of Viticulture and Enology, University of California, Davis, CA 95616.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: drsmart{at}ucdavis.edu
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Save to my folders

Jump to section

  • Article
    • Abstract
    • Materials and Methods
    • Results
    • Discussion
    • Conclusions
    • Footnotes
    • Literature Cited
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More from this TOC section

  • Sensory and Chemical Characterization of Phenolic Polymers from Red Wine Obtained by Gel Permeation Chromatography
  • N, P, and K Supply to Pinot noir Grapevines: Impact on Vine Nutrient Status, Growth, Physiology, and Yield
  • Sparkling Wines Produced from Alternative Varieties: Sensory Attributes and Evolution of Phenolics during Winemaking and Aging
Show more Articles

Similar Articles

AJEV Content

  • Current Volume
  • Archive
  • Best Papers
  • ASEV National Conference Technical Abstracts
  • Back Orders

Information For

  • Authors
  • Open Access Publishing
  • AJEV Preprint and AI Software Policy
  • Submission
  • Subscribers
  • Permissions and Reproductions

Other

  • Home
  • About Us
  • Feedback
  • Help
  • Alerts
  • ASEV
asev.org

© 2026 American Society for Enology and Viticulture.  ISSN 0002-9254.

Powered by HighWire