Abstract
Olive oil is a major economic resource of the Mediterranean region. Olive crop management can be improved by models that forecast the variable reproductive biology of olive tree. However, the processes controlling olive harvest are complex on large scales. Here, we study the parameters that influence olive fruit production for developing accurate forecasting models. Seventeen aerobiological sampling points have monitored olive pollen grains in Spain, Italy and Tunisia from 1993 to 2012. Six crop models have been developed at two provinces and country scales. The modelling has been done in two steps: (1) typification and (2) modelling by partial least square regression. Results show that higher pollen indexes and water availability during spring are related to an increase of final fruit production in all the studied area. Higher pollen indexes are also positively correlated with air temperature during early spring and autumn. Furthermore, a decrease of fruit production is related with increasing air temperature during winter and summer. To conclude, we have designed accurate models that allow accurate predictions of olive production.
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Acknowledgments
The authors are grateful to the following projects for funding this work: “Análisis de la dinámica del polen atmosférico en Andalucía (P10-RNM-5958)”, Research Project of Excellence of the Andalusia Regional Government; “Impacto del Cambio Climático en la fenología de especies vegetales del centro y sur de la Península Ibérica, FENOCLIM (CGL 2011-24146)” of the Spanish Ministry of Science and Innovation, and to the project “Aplicación y optimización del análisis polínico en el desarrollo de modelos de previsión de cosecha en olivo en Túnez (11-CAP2-0932)” of the Spanish Cooperation and Development Agency (AECID). Authors also are grateful to Ramón Areces Fundation (Madrid, Spain) by the post-doctoral grant of Dr. Aguilera. We appreciate the special contribution of Dr. José Guerrero-Casado.
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Oteros, J., Orlandi, F., García-Mozo, H. et al. Better prediction of Mediterranean olive production using pollen-based models. Agron. Sustain. Dev. 34, 685–694 (2014). https://doi.org/10.1007/s13593-013-0198-x
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DOI: https://doi.org/10.1007/s13593-013-0198-x