Modeling Phenological Phases across Olive Cultivars in the Mediterranean.
Ali Didevarasl, Jose M Costa Saura, Donatella Spano, Pierfrancesco Deiana, Richard L Snyder, Maurizio Mulas, Giovanni Nieddu, Samanta Zelasco, Mario Santona, Antonio Trabucco
Author Information
Ali Didevarasl: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Jose M Costa Saura: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Donatella Spano: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Pierfrancesco Deiana: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Richard L Snyder: Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA. ORCID
Maurizio Mulas: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Giovanni Nieddu: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy.
Samanta Zelasco: Council for Agricultural Research and Economics, Research Centre for Olive, Citrus and Fruit Crops, 87036 Rende, CS, Italy.
Mario Santona: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Antonio Trabucco: Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy. ORCID
Modeling phenological phases in a Mediterranean environment often implies tangible challenges to reconstructing regional trends over heterogenous areas using limited and scattered observations. The present investigation aimed to project phenological phases (i.e., sprouting, blooming, and pit hardening) for early and mid-late olive cultivars in the Mediterranean, comparing two phenological modeling approaches. Phenoflex is a rather integrated but data-demanding model, while a combined model of chill and anti-chill days and growing degree days (CAC_GDD) offers a more parsimonious and general approach in terms of data requirements for parameterization. We gathered phenological observations from nine experimental sites in Italy and temperature timeseries from the European Centre for Medium-Range Weather Forecasts, Reanalysis v5. The best performances of the CAC_GDD (RMSE: 4 days) and PhenoFlex models (RMSE: 5-9.5 days) were identified for the blooming and sprouting phases of mid-late cultivars, respectively. The CAC_GDD model was better suited to our experimental conditions for projecting pit hardening and blooming dates (correlation: 0.80 and 0.70, normalized RMSE: 0.6 and 0.8, normalized standard deviation: 0.9 and 1.0). The optimization of the principal parameters confirmed that the mid-late cultivars were more adaptable to thermal variability. The spatial distribution illustrated the near synchrony of blooming dates between the early and mid-late cultivars compared to other phases.
