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Predicting the flowering date of Portuguese grapevine varieties using temperature-based phenological models: a multi-site approach

Published online by Cambridge University Press:  24 October 2018

Mafalda Reis Pereira ,
Helena Ribeiro ,
Ilda Abreu ,
José Eiras-Dias ,
Teresa Mota  and
Mário Cunha
Mafalda Reis Pereira
Affiliation:
Department of Geosciences, Environment and Spatial Planning, Faculty of Sciences, University of Porto, Porto, Portugal
Helena Ribeiro*
Affiliation:
Earth Sciences Institute, Pole of the Faculty of Sciences, University of Porto, Porto, Portugal
Ilda Abreu
Affiliation:
Earth Sciences Institute, Pole of the Faculty of Sciences, University of Porto, Porto, Portugal Biology Department, Faculty of Sciences, University of Porto, Porto, Portugal
José Eiras-Dias
Affiliation:
Instituto Nacional de Investigação Agrária e Veterinária, I.P., Quinta da Almoinha, 2565-191 Dois Portos, Portugal
Teresa Mota
Affiliation:
Comissão de Viticultura da Região dos Vinhos Verdes, Academia do Vinho Verde e Estação Vitivinícola Amândio Galhano, Paçô, 4970-249 Arcos de Valdevez, Portugal
Mário Cunha
Affiliation:
Department of Geosciences, Environment and Spatial Planning, Faculty of Sciences, University of Porto, Porto, Portugal Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), CRIIS, Rua Dr Roberto Frias 4200-465 Porto, Portugal
*
Author for correspondence: Helena Ribeiro, E-mail: [email protected]
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Abstract

Phenological models for predicting the grapevine flowering were tested using phenological data of 15 grape varieties collected between 1990 and 2014 in Vinhos Verdes and Lisbon Portuguese wine regions. Three models were tested: Spring Warming (Growing Degree Days – GDD model), Spring Warming modified using a triangular function – GDD triangular and UniFORC model, which considers an exponential response curve to temperature. Model estimation was performed using data on two grape varieties (Loureiro and Fernão Pires), present in both regions. Three dates were tested for the beginning of heat unit accumulation (t0 date): budburst, 1 January and 1 September. The best overall date was budburst. Furthermore, for each model parameter, an intermediate range of values common for the studied regions was estimated and further optimized to obtain one model that could be used for a diverse range of grape varieties in both wine regions. External validation was performed using an independent data set from 13 grape varieties (seven red and six white), different from the two used in the estimation step. The results showed a high coefficient of determination (R2: 0.59–0.89), low Root Mean Square Error (RMSE: 3–7 days) and Mean Absolute Deviation (MAD: 2–6 days) between predicted and observed values. The UniFORC model overall performed slightly better than the two GDD models, presenting higher R2 (0.75) and lower RMSE (4.55) and MAD (3.60). The developed phenological models presented good accuracy when applied to several varieties in different regions and can be used as a predictor tool of flowering date in Portugal.

Keywords

Grapevine floweringoptimization algorithmphenologysimulated annealingthermal models
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 7 , September 2018 , pp. 865 - 876
Copyright
Copyright © Cambridge University Press 2018 

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