The primary impetus behind this research was to provide a boost to the characterization of the Italian olive biodiversity by acquiring reliable and homogeneous data over the course of an eight-year trial on the floral and fruiting biology of 120 molecularly analyzed cultivars, most of which have either low or very low diffusion. The obtained data highlighted a considerable variability to almost all of the analyzed parameters, which given the uniformity of environment and crop management was indicative of a large genetic variability in the accessions under observation, as confirmed through the molecular analysis. Several cases of synonymy were reported for the first time, even among plants cultivated in different regions, whilst all of the varieties examined, with only one exception, showed very low percentages of self-fruit-set, indicating a need for the employment of suitable pollinator plants. Eventually, a fitted model allowed us to evaluate the clear effects of the thermal values on blossoming, particularly in the months of March and April, whereas the climatic conditions during the flowering time had only a modest effect on its duration.

Knowledge of the flowering dates of black locust trees (Robinia pseudoacacia L.) is crucial information of both economic significance and scientific interest. Black locust is in fact an excellent melliferous plant and can provide information on climate change impacts due to its large distribution throughout the world as planted and naturalized trees. This paper presents the calibration and validation of a phenological model targeted at the simulation of the whole process of black locust flowering (from BBCH 51—inflorescence of flower buds visible—to BBCH 69—end of flowering). The work relies on the phenological observations gathered in the context of IPHEN, the Italian PHEnological Network, with a broad latitudinal distribution of the observational sites (from 37.53° to 46.28° N) and a long time span, from 2010 to 2021. Phenology modeling is based on the Normal Heat Hours approach, which translates air temperature into thermal units based on a plant specific response curve. As meteorological input data, a high resolution (0.045°) gridded dataset was obtained by spatial interpolation of GSOD (NOAA) weather stations.

Flowering dynamics of Robinia pseudoacacia L. (black locust), a key honey plant in southern Europe, are highly sensitive to climate variability and thus serve as a reliable indicator of environmental change. Despite the ecological and economic importance of this species, long-term studies on its flowering behaviour remain limited in Italy. This study analyses a multi-decadal time series of flowering onset dates collected in Piedmont (1981–2025) and validated at the regional scale using data from the IPHEN – Italian Phenological Network (2011–2025). Seasonal thermal indices, derived from the AgERA5 dataset, were evaluated through linear regressions and Monte Carlo cross-validation. During 1981–2025, flowering onset advanced by about 0.5 days per year (p-value < 0.01), consistent with the local warming trend observed over the same period. Among the thermal indices tested, spring temperatures were the main drivers: a 1°C increase in the spring maximum temperature index (mTmax_spring) advanced flowering onset by more than 4 days on average. The winter index (mTmax_winter) also showed a significant, though weaker, negative association, suggesting that milder winters may contribute to earlier flowering, likely by modulating dormancy processes. In contrast, autumn correlations appeared to result from spurious trends linked to global warming. Validation with the IPHEN dataset confirmed the robustness of the spring signal and the predictive role of the winter index, which allows estimates as early as late February, with an average error of about 5 days. The results help clarify the climatic mechanisms driving flowering onset in black locust and provide practical insights for apicultural planning in a changing climate.

Flowering dynamics of Robinia pseudoacacia L. (black locust), a key honey plant in southern Europe, are highly sensitive to climate variability and represent a useful indicator of environmental change. Despite its ecological and economic importance, long-term studies on black locust flowering behaviour remain limited in Italy. This study analyses a multi-decadal time series of flowering onset dates collected in Piedmont (1981–2025) and assesses the robustness of the observed relationships by incorporating data from the Italian Phenological Network (IPHEN, 2011–2025). Seasonal thermal indices, derived from the AgERA5 dataset, were used to assess the influence of autumn, winter, and spring temperatures on flowering timing. Over the study period, flowering onset advanced by about 0.5 days per year (p-value < 0.01), in parallel with a significant warming trend. Spring temperatures emerged as the main drivers: a 1 °C increase in the spring maximum temperature index was associated with an advance of more than 4 days in flowering onset. The winter temperatures also showed a significant, though weaker, negative association, suggesting a modulatory role on interannual phenological variability. In contrast, correlations with autumn temperatures reflected shared long-term trends rather than independent climatic control. Analyses on the pooled Montaldo + IPHEN dataset, including internal k-fold cross-validation, confirmed the robustness of the spring signal and highlighted the operational value of the winter index, which can be computed by late February, and predicts flowering onset with an average error of about 5 days. These results clarify the relative role of seasonal thermal signals in regulating the black locust flowering and provide useful information to support apicultural planning under ongoing climate change.