Statistical models reveal temperature impacts on olive oil accumulation in the Iberian Peninsula, suggesting urgent adaptation measures.
Oil content is a critical component of yield production in Mediterranean olive orchards, but it has received limited attention in modeling olive cultivation under extreme weather conditions. To address this gap, statistical and regression models based on multiple oil content measurements from field trials conducted with representative olive cultivars in the Guadalquivir basin (southern Iberian Peninsula), together with the latest future climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for the Iberian Peninsula, were integrated to improve the modeling of its behavior under future climate conditions. Temperature was the most influential factor affecting the olive oil accumulation pattern. Summer temperature was negatively correlated with the onset of oil accumulation, the accumulation rate, and the maximum oil content (MOC), while it was positively correlated with the date at which MOC was reached. When these relationships were combined with CMIP6 climate projections, inland southern Spain emerge as one of the most affected areas in the Iberian Peninsula. In the near future period (2040–2069), projected climate warning is expected to result in an earlier onset of oil accumulation, delays of up to 33 days in reaching MOC, and reductions in MOC of up to 17.5 percentage points, corresponding to an average olive oil yield loss of up to 30.3%, considering only the olive oil yield loss associated with the reduction in MOC. These changes vary in intensity depending on the location, cultivar, climate period and the greenhouse gas emission scenario considered. This study confirms the critical importance of temperature in olive oil production, highlights the need to incorporate functions that account for the effects of rising temperature on MOC, and emphasizes the identification of adaptation measures to cope with increasing temperatures and more frequent heat waves.
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Cabezas et al. (2025) studied this question.
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