New model to predict the timing of olive<i>(Olea europaea)</i>flowering: A case study in central Italy

Orlandi, Fabio; Lanari, Donatella; Romano, Bruno; Fornaciari, Marco

doi:10.1080/01140671.2006.9514392

Cited by 22 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, our study evaluated fewer flowering dates (21) than the De Melo- Abreu et al (2004) study (83 dates), which may have led to greater variability in our study. Using a different model proposed for Central Italy, Orlandi et al (2006) reported that 86% of the predicted maximum pollen concentration values, a surrogate for flowering date, were within ±5 days of the observed dates.…”

Section: Discussionmentioning

confidence: 95%

“…Physiologically-based models were later developed using phenological records in the Mediterranean Basin to predict the flowering response of olive to temperature (e.g. ; Alcalá & Barranco, 1992;Osborne et al, 2000;Cesaraccio et al, 2004;Orlandi et al, 2006;Motisi et al, 2008, Pérez-López et al, 2008. A potential limitation of many such models is that differences between cultivars were little considered.…”

Section: Study Area and Plant Materialsmentioning

confidence: 99%

“…Olive flowering at low latitude fruit trees require several years of monitoring, simulation models can provide useful predictions before field trials are undertaken or before orchards are commercially established. Quite a number of temperaturedriven flowering models have been developed and evaluated for olive trees for Mediterranean climates (e.g., Alcalá & Barranco, 1992;Osborne et al, 2000;Cesaraccio et al, 2004;De Melo-Abreu et al, 2004;Orlandi et al, 2006;Motisi et al, 2008;Pérez-López et al, 2008), while fewer models have been attempted for non-Mediterranean areas (Denney & McEachern, 1983;Denney et al, 1985). Temperature-driven models typically either predict the chilling requirements or heat accumulation needed to predict the flowering date of olive (Olea europaea L.) as a species.…”

Section: Model Prediction Of Flowering Datesmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Aybar

Melo-Abreu

Searles

et al. 2015

Span. j. agric. res.

View full text Add to dashboard Cite

Olive production has expanded significantly from the Mediterranean Basin into the New World over the last two decades. In some cases, cultivars of European origin have been introduced at a large commercial scale with little previous evaluation of potential productivity. The objective of this study was to evaluate whether a temperature-driven simulation model developed in the Mediterranean Basin to predict normal flowering occurrence and flowering date using cultivar-specific thermal requirements was suitable for the low latitude areas of Northwest Argentina. The model was validated at eight sites over several years and a wide elevation range (350–1200 m above mean sea level) for three cultivars (‘Arbequina’, ‘Frantoio’, ‘Leccino’) with potentially different chilling requirements. In ‘Arbequina’, normal flowering was observed at almost all sites and in all years, while normal flowering events in ‘Frantoio’ and ‘Leccino’ were uncommon. The model successfully predicted if flowering would be normal in 92% and 83% of the cases in ‘Arbequina’ and ‘Frantoio’, respectively, but was somewhat less successful in ‘Leccino’ (61%). When flowering occurred, the predicted flowering date was within ± 7 days of the observed date in 71% of the cases. Overall, the model results indicate that cultivar-specific simulation models may be used as an approximate tool to predict whether individual cultivars will be successful in new growing areas. In Northwest Argentina, the model could be used to identify cultivars to replace ‘Frantoio’ and ‘Leccino’ and to simulate global warming scenarios.

show abstract

Section: Discussionmentioning

confidence: 95%

Section: Study Area and Plant Materialsmentioning

confidence: 99%

Section: Model Prediction Of Flowering Datesmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Aybar

Melo-Abreu

Searles

et al. 2015

Span. j. agric. res.

View full text Add to dashboard Cite

show abstract

“…To make calculations, the following formula was used: gdd (i.e., growing degree days) = Σ(T m -T threshold), where "T m" is the daily mean temperature and "T threshold" is the minimum temperature below which biothermic accumulation stops or is reduced to the lowest terms. for the olive, the T threshold value considered was 7.5°C given that all the study areas are characterised by a mesomediterranean climate where optimum threshold ranges are indicated between 5°C and 7°C whereas other studies indicated the higher correlation values from 6°C to 9°C (mancuso 2000; Bongi et al 2002;orlandi et al 2006;ribeiro et al 2006). using the same method, the gdd values were calculated until the start date of flowering to verify possible behaviour differences of various cultivars between initial and maximum intensity of the anthesis phenomenon.…”

Section: Climatic Analysismentioning

confidence: 99%

Influence of temperature and rainfall on timing of olive (Olea europaea) flowering in southern Italy

Bonofiglio

Orlandi²,

Sgromo

et al. 2008

New Zealand Journal of Crop and Horticultural Science

Self Cite

View full text Add to dashboard Cite

This study concerns the flowering of the olive (Olea europaea) in a large southern Italian area. It was carried out using the "volumetric" method of pollen sampling and the analysis of the meteorological parameters of temperature and rainfall. The results show that flowering occurs mainly in May, with the maximum values in the second half of the month. Meteorological analysis showed that the biological cycle of the olive was greatly influenced by the temperature. The relationship between an increase of temperature before the beginning of flowering and the advance of flowering was 2.5 days/°C. Another important result concerns the value of the mean temperature which by the beginning of flowering was 16°C at all monitoring stations, even if the growing degree day (GDD) requirements were different. The temperature accumulation evidenced the homogeneity of plant behaviour in dependence of latitude, except for the province of Taranto. Also, our study showed that rainfall determined a considerable decline of pollen concentration in the atmosphere, until the maximum of 80% when the value of 8 mm of rainfall/day was reached.

show abstract

“…The bulk of studies is based on information from one or a few stations within a limited region (e.g. Orlandi et al, 2006;Moriondo et al, 2001;Alba and Diaz De La Guardia, 1998;Frenguelli et al, 1989;Galán et al, 2005;Fornaciari et al, 1998). Several wider-area studies were also undertaken to aim at more general statistical characteristics of the season, e.g.…”

Section: Introductionmentioning

confidence: 99%

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

et al. 2017

View full text Add to dashboard Cite

Abstract. The paper presents the first modelling experiment of the European-scale olive pollen dispersion, analyses the quality of the predictions, and outlines the research needs. A 6-model strong ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run throughout the olive season of 2014, computing the olive pollen distribution. The simulations have been compared with observations in eight countries, which are members of the European Aeroallergen Network (EAN). Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimised combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season was reported to start too early by 8 days, but for some models the error mounted to almost 2 weeks. For the end of the season, the disagreement between the models and the observations varied from a nearly perfect match up to 2 weeks too late. A series of sensitivity studies carried out to understand the origin of the disagreements revealed the crucial role of ambient temperature and consistency of its representation by the meteorological models and heat-sum-based phenological model. In particular, a simple correction to the heat-sum threshold eliminated the shift of the start of the season but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better, suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport, were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous days' observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

show abstract

New model to predict the timing of olive(Olea europaea)flowering: A case study in central Italy

Cited by 22 publications

References 17 publications

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Influence of temperature and rainfall on timing of olive (Olea europaea) flowering in southern Italy

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

Contact Info

Product

Resources

About