Skip to main content
Advertisement

Main menu

  • Home
  • AJEV Content
    • Current Volume
    • Papers in Press
    • Archive
    • Best Papers
    • ASEV National Conference Technical Abstracts
    • Collections
    • Free Sample Issue
  • Information For
    • Authors
    • Open Access and Subscription Publishing
    • Submission
    • Subscribers
      • Proprietary Rights Notice for AJEV Online
    • Permissions and Reproductions
    • Advertisers
  • About Us
  • Feedback
  • Alerts
    • Alerts
    • RSS Feeds
  • 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
  • AJEV Content
    • Current Volume
    • Papers in Press
    • Archive
    • Best Papers
    • ASEV National Conference Technical Abstracts
    • Collections
    • Free Sample Issue
  • Information For
    • Authors
    • Open Access and Subscription Publishing
    • Submission
    • Subscribers
    • Permissions and Reproductions
    • Advertisers
  • About Us
  • Feedback
  • Alerts
    • Alerts
    • RSS Feeds
  • Help
  • Login
  • ASEV MEMBER LOGIN
Article

Predicting Berry Quality Attributes in cv. Xarel·lo Rain-Fed Vineyards Using Narrow-Band Reflectance-Based Indices

Cristina González-Flor, Lydia Serrano Porta, Gil Gorchs Altarriba
Am J Enol Vitic. March 2013 64: 88-97; published ahead of print October 22, 2012 ; DOI: 10.5344/ajev.2012.11124
Cristina González-Flor
1Assistant Professor Departament d’Enginyeria Agroalimentària i Biotecnologia, Universitat Politècnica de Catalunya, c/ Esteve Terradas 8, 08860 Castelldefels, Barcelona, Spain.
  • 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: cristina.gonzalez-flor@upc.edu
Lydia Serrano Porta
2Lecturer, Departament d’Enginyeria Agroalimentària i Biotecnologia, Universitat Politècnica de Catalunya, c/ Esteve Terradas 8, 08860 Castelldefels, Barcelona, Spain.
  • 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
Gil Gorchs Altarriba
2Lecturer, Departament d’Enginyeria Agroalimentària i Biotecnologia, Universitat Politècnica de Catalunya, c/ Esteve Terradas 8, 08860 Castelldefels, Barcelona, Spain.
  • 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
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

In rain-fed vineyards, water availability strongly influences vegetative and reproductive growth and, thus, berry quality. Narrow-band spectral indices might provide information on vine structure and physiological status and might be a useful tool for predicting berry quality. The present study tested the feasibility of using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) to assess berry quality in five commercial vineyards (cv. Xarel·lo) in 2009 and 2010. Measurements of predawn water potential (Ψpd), canopy to air temperature difference, fractional intercepted photosynthetic active radiation (fIPAR), exposed leaf area, and canopy reflectance were taken at veraison. Berry weight, total soluble solids (TSS), and titratable acidity (TA) were determined at harvest. Values of Ψpd indicated mild to moderate water deficits. NDVI characterized the effects of water availability on vine vigor (fIPAR), while PRI was related to water status (Ψpd). The extent of water deficits was a key factor in determining the aptitude of spectral indices at estimating berry quality attributes. Thus, consistent with the influence of vine vigor and water status on berry quality attributes, NDVI was related to both TA (r2 = 0.46) and IMAD (the ratio of TSS to TA; r2 = 0.27), whereas PRI was related to both TSS and IMAD (r2 = 0.23 and r2 = 0.34, respectively). In addition, PRI was positively related to berry weight (r2 = 0.68). The results suggest the potential of reflectance indices of canopy vigor (i.e., NDVI) and photosynthetic functioning (i.e., PRI) at estimating berry quality attributes in vineyards experiencing mild to moderate water deficits.

  • Vitis vinifera
  • berry quality attributes
  • narrow-band spectral reflectance
  • water status
  • vine vigor
  • ©2013 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 64 Issue 1

  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
View full PDF
Article Alerts
Sign In to Email Alerts with your Email Address
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.
Predicting Berry Quality Attributes in cv. Xarel·lo Rain-Fed Vineyards Using Narrow-Band Reflectance-Based Indices
(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
Predicting Berry Quality Attributes in cv. Xarel·lo Rain-Fed Vineyards Using Narrow-Band Reflectance-Based Indices
Cristina González-Flor, Lydia Serrano Porta, Gil Gorchs Altarriba
Am J Enol Vitic.  March 2013  64: 88-97;  published ahead of print October 22, 2012 ; DOI: 10.5344/ajev.2012.11124

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
Predicting Berry Quality Attributes in cv. Xarel·lo Rain-Fed Vineyards Using Narrow-Band Reflectance-Based Indices
Cristina González-Flor, Lydia Serrano Porta, Gil Gorchs Altarriba
Am J Enol Vitic.  March 2013  64: 88-97;  published ahead of print October 22, 2012 ; DOI: 10.5344/ajev.2012.11124
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google 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
    • Acknowledgments
    • Footnotes
    • Literature Cited
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More from this TOC section

  • Sensory and Compositional Characteristics of Blanc Du Bois Wine
  • Glucose and Ethanol Tolerant Enzymes Produced by Pichia (Wickerhamomyces) Isolates from Enological Ecosystems
  • Sensory and Chemical Characterization of Phenolic Polymers from Red Wine Obtained by Gel Permeation Chromatography
Show more Article

Similar Articles

AJEV Content

  • Current Volume
  • Papers in Press
  • Archive
  • Best Papers
  • ASEV National Conference Technical Abstracts
  • Collections
  • Free Sample Issue

Information For

  • Authors
  • Open Access/Subscription Publishing
  • Submission
  • Subscribers
  • Permissions and Reproductions
  • Advertisers

Alerts

  • Alerts
  • RSS Feeds

Other

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

© 2023 American Society for Enology and Viticulture.  ISSN 0002-9254.

Powered by HighWire