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Automatic discrimination of grapevine (Vitis vinifera L.) clones using leaf hyperspectral imaging and partial least squares

Published online by Cambridge University Press:  08 April 2014

A. M. FERNANDES ,
P. MELO-PINTO ,
B. MILLAN ,
J. TARDAGUILA  and
M. P. DIAGO
A. M. FERNANDES
Affiliation:
CITAB – Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-911, Vila Real, Portugal
P. MELO-PINTO
Affiliation:
CITAB – Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-911, Vila Real, Portugal Department of Engineering, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-911, Vila Real, Portugal
B. MILLAN
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja), C/Madre de Dios, 51. 26006 Logroño, Spain
J. TARDAGUILA
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja), C/Madre de Dios, 51. 26006 Logroño, Spain
M. P. DIAGO*
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja), C/Madre de Dios, 51. 26006 Logroño, Spain Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

A worldwide innovative method to discriminate grapevine clones is presented. It is an alternative to ampelography, isozyme and DNA analysis. The spectra and their first and second derivatives of 201 bands in the visible and near-infrared wavelength range between 634 and 759 nm were used as inputs to a classifier created using partial least squares. The spectra were acquired in the laboratory for the adaxial side of the apical part of the main lobe of fully hydrated grapevine leaves. The classifier created allowed the separation of 100 leaves of the Cabernet Sauvignon (Vitis vinifera L.) variety into four clones, namely CS 15, CS 169, CS 685 and CS R5, comprising 25 leaves each. The percentages of leaves correctly classified for these clones were 98·2, 99·2, 100 and 97·8%, respectively, when the classifier input was the second derivative of the normalized spectra. These percentages were determined by Monte-Carlo cross-validation. With the new method proposed, each leaf of a given variety can be classified in a few seconds according to its clone in an environmentally friendly way.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 153 , Issue 3 , April 2015 , pp. 455 - 465
Copyright
Copyright © Cambridge University Press 2014 

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