A method for using monthly average temperatures in phenology models for grapevine (<i>Vitis vinifera</i> L.)
Omar Garcia-Tejera,
Raül Marcos-Matamoros,
Boris Basile,
Alessandro Mataffo,
Pasquale Scognamiglio,
Henar Prieto,
Luis Mancha,
Inês Cabral,
Jorge Queiroz,
Joana Valente,
Fernando Alves,
Nube González-Reviriego,
Sara Hernández-Barrera,
Mercè Mata,
Joan Girona
Affiliations
Omar Garcia-Tejera
Universidad de La Laguna, Departamento de Ingeniería Agraria y del Medio Natural. Ctra. Geneto, 2, La Laguna, 38200 Tenerife - Instituto de Agricultura Sostenible-CSIC, Av. Menéndez Pidal s/n, 14080 Cordoba - Efficient Use of Water Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Parc de Gardeny, Edifici Fruitcentre, 25003 Lleida
Raül Marcos-Matamoros
Barcelona Supercomputing Center (BSC), c/Jordi Girona, 29, 08034 Barcelona - University of Barcelona, Faculty of Physics, c/Martí i Franquès 1, 08028 Barcelona
Boris Basile
Department of Agricultural Sciences, University of Naples Federico II, Portici (Napoli)
Alessandro Mataffo
Department of Agricultural Sciences, University of Naples Federico II, Portici (Napoli)
Pasquale Scognamiglio
Department of Agricultural Sciences, University of Naples Federico II, Portici (Napoli)
Henar Prieto
Center for Scientific and Technological Research of Extremadura (CICYTEX). Agricultural Research Institute “Finca La Orden-Valdesequera”. Highway A-5 km. 372, 06187 Guadajira (Badajoz)
Luis Mancha
Center for Scientific and Technological Research of Extremadura (CICYTEX). Agricultural Research Institute “Finca La Orden-Valdesequera”. Highway A-5 km. 372, 06187 Guadajira (Badajoz)
Inês Cabral
GreenUPorto – Sustainable Agrifood Production Research Centre / Inov4Agro, DGAOT, Faculty of Sciences of University of Porto, Campus de Vairão, Rua da Agrária, 747, 4485-646 Vairão
Jorge Queiroz
GreenUPorto – Sustainable Agrifood Production Research Centre / Inov4Agro, DGAOT, Faculty of Sciences of University of Porto, Campus de Vairão, Rua da Agrária, 747, 4485-646 Vairão
Joana Valente
Symington Family Estates, Vinhos, S.A., Travessa Barão de Forrester 86, 4400-034 Vila Nova de Gaia
Fernando Alves
Symington Family Estates, Vinhos, S.A., Travessa Barão de Forrester 86, 4400-034 Vila Nova de Gaia
Nube González-Reviriego
Barcelona Supercomputing Center (BSC), c/Jordi Girona, 29, 08034 Barcelona
Sara Hernández-Barrera
Instituto Tecnológico y de Energías Renovables, S.A. (ITER), Polígono Industrial de Granadilla s/n, 38600 Granadilla (Santa Cruz de Tenerife)
Mercè Mata
Efficient Use of Water Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Parc de Gardeny, Edifici Fruitcentre, 25003 Lleida
Joan Girona
Efficient Use of Water Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Parc de Gardeny, Edifici Fruitcentre, 25003 Lleida
In recent years, there have been increasing efforts to link phenology models with seasonal climate predictions in so-called Decision Support Systems (DSS) to tailor crop management strategies. However, temporal discrepancies between phenology models with temperature data gathered on a daily basis and seasonal forecasting systems providing predictability on monthly scales have limited their use. In this work, we present a novel methodology to use monthly average temperature data in phenology models. Briefly stated, we modelled the timing of the appearance of specific grapevine phenological phases using monthly average temperatures. To do so, we computed the cumulative thermal time (Sf ) and the number of effective days per month (effd). The effd is the number of days in a month on which temperatures would be above the minimum value for development (Tb). The calculation of effd is obtained from a normal probability distribution function derived from historical weather records. We tested the methodology on four experimental plots located in different European countries with contrasting weather conditions and for four different grapevine cultivars. The root mean square deviation (RMSD) ranged from 4 to 7 days for all the phenological phases considered, at all the different sites, and for all the cultivars. Furthermore, the bias of observed vs predicted comparisons was not significantly different when using either monthly mean or daily temperature values to model phenology. This new methodology, therefore, provides an easy and robust way to incorporate monthly temperature data into grapevine phenology models.