New Zealand Journal of Crop and Horticultural Science abstracts

---

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

Fabio Orlandi
Donatella Lanari
Bruno Romano
Marco Fornaciari

Department of Plant Biology, Agroenvironmental and Animal Biotechnology
University of Perugia
Borgo XX Giugno 74
06121 Perugia, Italy
email: fabor@unipg.it

Abstract The aim of this study was to analyse the statistical relationships among climatic variables and flowering dates for olive species (Olea europaea). Data were collected over 21 years (1982–2002) from the study area located in the province of Perugia, central Italy. Flowering was studied through the aerobiological method and daily pollen concentrations (expressed as pollen grains/m3) were recorded. A new flowering forecasting indicator (modified chilling unit, CUm) is proposed to identify the beginning and the central phase of anthesis (maximum pollen concentration) in olive groves. Correlation and regression analyses were carried out regarding two different flowering stages and meteorological variables expressed as thermal amounts. A mean temperature variable was introduced to consider the current conditions during flowering (from the first pollen concentrations to the maximum). The best fitting model was obtained considering the maximum pollen concentration date and the modified chilling unit formula with a cut-off temperature of 12°C. The validity of this model was tested using data from 1999 to 2002 (not included in the model parameterisation). The results showed that this new climatic indicator is able to accurately forecast the timing of flowering for olive trees.

Keywords Olea europaea; flowering; temperature amount

New Zealand Journal of Crop and Horticultural Science, 2006, Vol. 34: 93–99
0014–0671/06/3401–0093      © The Royal Society of New Zealand 2006
H04029; Online publication date 13 March 2006. Received 15 March 2004; accepted 22 December 2005

PDF file of entire paper: Print-quality (504K) | screen-quality (270K)

---

This year's abstracts | Journal home page | All abstracts | Publishing home page