Modeling Phenological Phases across Olive Cultivars in the Mediterranean

Author:

Didevarasl Ali12ORCID,Costa Saura Jose M.123ORCID,Spano Donatella123ORCID,Deiana Pierfrancesco1ORCID,Snyder Richard L.4ORCID,Mulas Maurizio13ORCID,Nieddu Giovanni1,Zelasco Samanta5,Santona Mario1ORCID,Trabucco Antonio123ORCID

Affiliation:

1. Department of Agricultural Sciences, University of Sassari, 07100 Sassari, SS, Italy

2. Impacts on Agriculture, Forestry and Ecosystem Services (IAFES) Division, Euro-Mediterranean Center on Climate Changes (CMCC), 07100 Sassari, SS, Italy

3. National Biodiversity Future Center (NBFC), Palazzo Steri, 90133 Palermo, PA, Italy

4. Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA

5. Council for Agricultural Research and Economics, Research Centre for Olive, Citrus and Fruit Crops, 87036 Rende, CS, Italy

Abstract

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.

Funder

Programma Operativo Nazionale

Publisher

MDPI AG

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

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