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A bioclimatic model for forecasting olive yield

Published online by Cambridge University Press:  09 September 2009

H. RIBEIRO ,
M. CUNHA  and
I. ABREU
H. RIBEIRO
Affiliation:
Departamento de Botânica and Centro de Geologia: Grupo de Ambiente, Sociedade e Educação, Faculdade de Ciências, Universidade do Porto, Rua Campo Alegre, S/N 4150 Porto, Portugal
M. CUNHA
Affiliation:
Secção Autónoma de Ciências Agrárias, Faculdade de Ciências, Universidade do Porto, Rua do Monte, 4485 661 Vairão, Portugal Centro de Investigação em Ciências Geo-espaciais, Faculdade de Ciências, Universidade do Porto, Rua Campo Alegre, 687 4150 Porto, Portugal
I. ABREU*
Affiliation:
Departamento de Botânica and Centro de Geologia: Grupo de Ambiente, Sociedade e Educação, Faculdade de Ciências, Universidade do Porto, Rua Campo Alegre, S/N 4150 Porto, Portugal
*
*To whom all correspondence should be addressed. Email: ianoronh@fc.up.pt
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Summary

The aim of the present study was to develop a hierarchical bioclimatic model for forecasting olive crop yields in the Alentejo region of south-eastern Portugal. The model was estimated for three different developmental stages: (1) at flowering, using only the regional pollen index (RPI); (2) at fruit growth using RPI and a plant water requirements index (PWRI) and (3) at fruit maturing using RPI plus a water requirements index plus a phytopathological index (PPI). Olive airborne pollen was sampled from 1999 to 2007, using a Cour trap installed in Reguengos de Monsaraz. The meteorological parameters used in the calculation of the post-flowering indices corresponded to data from a meteorological station located near the airborne sampling point. At the flowering stage, 0·66 of the regional olive yield can be explained by the RPI with an average deviation between observed and predicted production of 0·15 for the forecast model internal validation and of 0·19 for the cross-validation. The addition of the variable PWRI to the forecasting model explained an additional 0·26 of the variation, while the PPI explained an additional 0·05. The final bioclimatic model, with all the three variables tested, explained 0·97 of the regional olive fruit yield being the average deviation between observed and predicted production of 0·04 for the internal validation of the model and of 0·07 for the external validation. The hierarchical nature of this bioclimatic model, along three different development stages, enabled the prediction to be updated as the growing season progressed.

Type
Crops and Soils
Information
The Journal of Agricultural Science , Volume 147 , Issue 6 , December 2009 , pp. 647 - 656
Copyright
Copyright © Cambridge University Press 2009

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