Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems

Bibliographic Details
Main Author: Lopes, C.M.
Publication Date: 2005
Other Authors: Gruber, B., Schultz, H.R.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.5/23024
Summary: The performance of a mathematical model developed for non-destructive estimation of primary leaf area per shoot of Tempranillo grapevines, was tested using independent datasets from two vineyards with simplified pruning techniques. The first dataset was collected in Portugal on Cabernet Sauvignon grapevines subjected to mechanical hedge pruning and the second one in Germany on minimal pruned Riesling grapevines. For both datasets the model presented a very good fit between observed and estimated values with the error increasing with the increase in leaf area per shoot. The mean absolute percent error for all systems was lower or equal to 10% with lower absolute values (7.7%) for the Riesling dataset. Both linear regression between observed (dependent variable) and estimated (independent variable) leaf area had high and significant R2 with an intercept not significantly different from zero. Fitted lines were not significantly different from 1 for Cabernet Sauvignon, but slightly yet significantly different from 1 for Riesling fitted line (1.03), indicating that the model underestimated the leaf area per shoot. The good results obtained with this validation test show that the model can be used to accurately predict primary leaf area per shoot independent of variety, training system and climatic conditions
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spelling Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systemsgrapevineleaf areastatistical modelTempranilloCabernet SauvignonRieslingvalidationThe performance of a mathematical model developed for non-destructive estimation of primary leaf area per shoot of Tempranillo grapevines, was tested using independent datasets from two vineyards with simplified pruning techniques. The first dataset was collected in Portugal on Cabernet Sauvignon grapevines subjected to mechanical hedge pruning and the second one in Germany on minimal pruned Riesling grapevines. For both datasets the model presented a very good fit between observed and estimated values with the error increasing with the increase in leaf area per shoot. The mean absolute percent error for all systems was lower or equal to 10% with lower absolute values (7.7%) for the Riesling dataset. Both linear regression between observed (dependent variable) and estimated (independent variable) leaf area had high and significant R2 with an intercept not significantly different from zero. Fitted lines were not significantly different from 1 for Cabernet Sauvignon, but slightly yet significantly different from 1 for Riesling fitted line (1.03), indicating that the model underestimated the leaf area per shoot. The good results obtained with this validation test show that the model can be used to accurately predict primary leaf area per shoot independent of variety, training system and climatic conditionsGESCORepositório da Universidade de LisboaLopes, C.M.Gruber, B.Schultz, H.R.2022-01-12T14:33:15Z20052005-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.5/23024engLopes, C.M., Gruber, B., Schultz, H.R., 2005. Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems. Proceedings XIV GESCO Symposium, Forschungsanstalt Geisenheim, Geisenheim, Alemanha, 23-27 Agosto 2005, Vol. 2: 236-241info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T16:01:36Zoai:repositorio.ulisboa.pt:10400.5/23024Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:00:18.656791Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
title Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
spellingShingle Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
Lopes, C.M.
grapevine
leaf area
statistical model
Tempranillo
Cabernet Sauvignon
Riesling
validation
title_short Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
title_full Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
title_fullStr Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
title_full_unstemmed Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
title_sort Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems
author Lopes, C.M.
author_facet Lopes, C.M.
Gruber, B.
Schultz, H.R.
author_role author
author2 Gruber, B.
Schultz, H.R.
author2_role author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Lopes, C.M.
Gruber, B.
Schultz, H.R.
dc.subject.por.fl_str_mv grapevine
leaf area
statistical model
Tempranillo
Cabernet Sauvignon
Riesling
validation
topic grapevine
leaf area
statistical model
Tempranillo
Cabernet Sauvignon
Riesling
validation
description The performance of a mathematical model developed for non-destructive estimation of primary leaf area per shoot of Tempranillo grapevines, was tested using independent datasets from two vineyards with simplified pruning techniques. The first dataset was collected in Portugal on Cabernet Sauvignon grapevines subjected to mechanical hedge pruning and the second one in Germany on minimal pruned Riesling grapevines. For both datasets the model presented a very good fit between observed and estimated values with the error increasing with the increase in leaf area per shoot. The mean absolute percent error for all systems was lower or equal to 10% with lower absolute values (7.7%) for the Riesling dataset. Both linear regression between observed (dependent variable) and estimated (independent variable) leaf area had high and significant R2 with an intercept not significantly different from zero. Fitted lines were not significantly different from 1 for Cabernet Sauvignon, but slightly yet significantly different from 1 for Riesling fitted line (1.03), indicating that the model underestimated the leaf area per shoot. The good results obtained with this validation test show that the model can be used to accurately predict primary leaf area per shoot independent of variety, training system and climatic conditions
publishDate 2005
dc.date.none.fl_str_mv 2005
2005-01-01T00:00:00Z
2022-01-12T14:33:15Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/23024
url http://hdl.handle.net/10400.5/23024
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Lopes, C.M., Gruber, B., Schultz, H.R., 2005. Validation of an empirical model for grapevine leaf area estimation with data from simplified pruning systems. Proceedings XIV GESCO Symposium, Forschungsanstalt Geisenheim, Geisenheim, Alemanha, 23-27 Agosto 2005, Vol. 2: 236-241
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv GESCO
publisher.none.fl_str_mv GESCO
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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