Abstract
It is now widely accepted that weather conditions occurring several months prior to the onset of flowering have a major influence on various aspects of olive reproductive phenology, including flowering intensity. Given the variable characteristics of the Mediterranean climate, we analyse its influence on the registered variations in olive flowering intensity in southern Spain, and relate them to previous climatic parameters using a year-clustering approach, as a first step towards an olive flowering phenology model adapted to different year categories. Phenological data from Cordoba province (Southern Spain) for a 30-year period (1982–2011) were analysed. Meteorological and phenological data were first subjected to both hierarchical and “K-means” clustering analysis, which yielded four year-categories. For this classification purpose, three different models were tested: (1) discriminant analysis; (2) decision-tree analysis; and (3) neural network analysis. Comparison of the results showed that the neural-networks model was the most effective, classifying four different year categories with clearly distinct weather features. Flowering-intensity models were constructed for each year category using the partial least squares regression method. These category-specific models proved to be more effective than general models. They are better suited to the variability of the Mediterranean climate, due to the different response of plants to the same environmental stimuli depending on the previous weather conditions in any given year. The present detailed analysis of the influence of weather patterns of different years on olive phenology will help us to understand the short-term effects of climate change on olive crop in the Mediterranean area that is highly affected by it.
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Aguilera F, Ruiz Valenzuela L (2009) Study of the floral phenology of Olea europaea L. in Jaén province (SE Spain) and its relation with pollen emission. Aerobiologia 25(4):217–225
Andalusia Statistical Yearbook (2010) http://www.juntadeandalucia.es/institutodeestadisticaycartografia/anuario/anuario10/index.htm
Andreini L, Bartolini S, Guivarc’h A, Chriqui D, Vitagliano C (2008) Histological and immunohistochemical studies on flower induction in the olive tree (Olea europaea L.). Plant Biol 10:588–595
Aznarte JL, Benítez JM, Nieto D, de Linares C, Díaz de la Guardia F (2007) Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models. Expert Syst Appl 32:1218–1225
Barber D, de la Torre F, Feo F, Florido F, Guardia P, Moreno C, Quiralte J, Lombardero M, Villalba M, Salcedo G, Rodríguez R (2008) Understanding patient sensitization profiles in complex pollen areas a molecular epidemiological study. Allergy 63:1550–1558
Bishop CM (1995) Neural networks for pattern recognition. Clarendon, Oxford
Bonofiglio T, Orlandi F, Sgromo C, Romano B, Fornaciari M (2009) Evidences of olive pollination date variations in relation to spring temperature trends. Aerobiologia 25:227–237
IPCC (2007) Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Pachauri RK, Reisinger A (eds). IPCC, Geneva, Switzerland
D’Amato G, Cecchi L, Bonini S, Nunes C, Annesi-Maesano I, Behrendt H, Liccardi G, Popov T, van Cauwenberge P (2007) Allergenic pollen and pollen allergy in Europe. Allergy 62:976–990
Dag A, Bustan A, Avni A, Tzipri I, Lavee S, Riov J (2010) Timing of fruit removal affects concurrent vegetative growth and subsequent return bloom and yield in olive (Olea europaea L.). Sci Hortic 123:469–472
Dominguez-Vilches E, García-Pantaleón F, Galán C, Guerra F, Villamandos F (1993) Variations in the concentrations of airborne Olea pollen and associated polinosis in Cordoba (Spain): a study of the 10-year period 1982–199. J Invest Allergol Clin Immunol 3(3):121–129
Fernández-Escobar R, Benlloch M, Navarro C, Martín GC (1992) The time of floral induction in olive. J Am Soc Hortic Sci 117(2):304–307
Fisher RA (1936) The use of multiple measurements in taxonomic problems. Ann Eugenics 7:179–188
Frenguelli G (1998) The contribution of aerobiology to agriculture. Aerobiologia 14:95–100
Galán C, Cariñanos P, García-Mozo H, Alcázar P, Domínguez-Vilches E (2001a) Model for forecasting Olea europaea L. airborne pollen in South-West Andalusia, Spain. Int J Biometeorol 45:59–63
Galán C, García-Mozo H, Cariñanos P, Alcázar P, Domínguez-Vilches E (2001b) The role of temperature in the onset of the Olea europaea L. pollen season in southwestern Spain. Int J Biometeorol 45:8–12
Galán C, Vázquez L, García-Mozo H, Domínguez E (2004) Forecasting olive (Olea europaea) crop yield based on pollen emission. Field Crop Res 86:43–51
Galán C, García-Mozo H, Vázquez L, Ruíz L, Díaz de la Guardia C, Trigo M (2005) Heat requirement for the onset of the Olea europaea L. pollen season in several sites in Andalusia and the effect of the expected future climate change. Int J Biometeorol 49:184–188
Galán C, Cariñanos P, Alcázar P, Domínguez-Vilches E (2007) Spanish Aerobiology Network (REA): Management and Quality Manual. Servicio de publicaciones de la Universidad de Cordoba, Cordoba
Galán C, García-Mozo H, Vázquez L, Ruiz L, Díaz de la Guardia C, Dominguez E (2008) Modeling olive crop yield in Andalusia, Spain. Agron J 100:98–104
García-Mozo H (2011) The use of aerobiological data on agronomical studies. Ann Agric Environ Med 18:159–164
García-Mozo H, Chuine I, Perez-Badía R, Galán C (2008) Aerobiological and meteorological factors’ influence on olive (Olea europaea L.) crop yield in Castilla-La Mancha (Central Spain). Aerobiologia 24:13–18
García-Mozo H, Orlandi F, Galán C, Fornaciari M, Romano B, Ruiz L, Diaz de la Guardia C, Trigo MM, Chuine I (2009) Olive flowering phenology variation between different cultivars in Spain and Italy: modelling analysis. Theor Appl Climatol 95:385–395
García-Mozo H, Mestre A, Galán C (2010) Phenological trends in southern Spain: a response to climate change. Agric For Meteorol 150:575–580
Gutiérrez PA, Hervás C, Carbonero M, Fernández JC (2009) Combined projection and kernel basis functions for classification in evolutionary neural networks. Neurocomputing 72(13–15):2731–2742
Haykin S (1994) Neural networks. A comprehensive foundation. MacMillan College, New York
Hernández-Ceballos M, García-Mozo H, Adame JA, Domínguez-Vilches E, Bolívar JP, De la Morena BA, Pérez-Badía R, Galán C (2011) Determination of potencial sources of Quercus airborne pollen in Cordoba city (southern Spain) using back-trajectory analysis. Aerobiologia 27:261–276
Hirst JM (1952) An automatic volumetric spore trap. Ann Appl Biol 39:257–265
IOOC(1996) Biology and physiology of the olive. World Olive Encyclopedia, International Olive Oil Council (IOOC), Madrid, Spain
Kasprzyk I, Grinn-Gofrón A, Strzelczak A, Wolski T (2011) Hourly predictive artificial neural network and multivariate regression tress models of Ganoderma spore concentrations in Rzeszów and Szczecin (Poland). Sci Total Environ 409:949–956
Kirchner K, Tölle KH, Krieter J (2004) The analysis of simulated sow herd datasets using decision tree technique. Comput Electron Agric 42:111–127
Lavee S (2006) Biennial bearing in olive (Olea europaea L.). Olea FAO olive Netw 25:5–13
Linkosalo T, Ranta H, Oksanen A, Siljamo P, Luomajoki A, Kukkonen J, Sofiev M (2010) A double-threshold temperatures sum model for predicting the flowering duration and relative intensity of Betula pendula and B. pubescens. Agric For Meteorol 150:579–1584
Makra L, Juhász M, Mika J, Bartzokas A, Béczi R, Sümeghy Z (2006) An objective classification system of air mass types for Szeged, Hungary, with special attention to plant pollen levels. Int J Biometeorol 50:403–421
Mandrioli P (1987) Biometeorology and its relation to pollen count. Adv Aerobiol 51:37–41
Martínez-Estudillo AC, Hervás-Martínez C, Martinez-Estudillo FJ, García-Pedrajas N (2006) Hybridization of evolutionary algorithms and local search by means of a clustering method. IEEE T Syst Man Cy B 36(3):534–546
Morton J, Bye J, Pezza A, Newbigin E (2011) On the causes of variability in amounts of airborne grass pollen in Melbourne, Australia. Int J Biometeorol 55:613–622
Orlandi F, Garcia-Mozo H, Vazquez-Ezquerra L, Romano B, Dominguez E, Galan C, Fornaciari M (2004) Phenological olive chilling requirements in Umbria (Italy) and Andalusia (Spain). Plant Biosys 138:111–116
Orlandi F, Vazquez L, Ruga L, Bonofiglio T, Fornaciari M, Garcia-Mozo H, Domínguez E, Romano B, Galán C (2005) Bioclimatic requirements for olive flowering in two Mediterranean regions located at the same latitude (Andalucia, Spain, and Sicily, Italy). Ann Agric Environ Med 12:47–52
Orlandi F, García-Mozo H, Galán C, Romano B, Díaz de la Guardia C, Ruíz L, Trigo MM, Domínguez-Vilches E, Fornaciari M (2010) Olive flowering trends in a large Mediterranean area (Italy and Spain). Int J Biometeorol 54:151–16
Oteros J, García-Mozo H, Hervás C, Galán C (2012) Biometeorological and autoregressive indices for predicting olive pollen intensity. Int J Biometeorol. doi:10.1007/s00484-012-0555-5
Puc M (2012) Artificial neural network model of the relationship between Betula pollen and meteorological factors in Szczecin (Poland). Int J Biometeorol 56:395–401
Rallo L, Cuevas J (2004) Fructificación y producción, capítulo 5, in: Barranco D, Fernández-Escobar D, Rallo L, El Cultivo del Olivo. 5ª Ed. Madrid, España. Junta de Andalucía y Ediciones Mundi-Prensa, pp 159–183
Rallo L, Martin GC (1991) The role of chilling in releasing olive floral buds from dormancy. J Am Soc Hortic Sci 116(6):1058–1062
Recio M, Cabezudo B, Trigo M, Toro F (1996) Olea europaea pollen in the atmosphere of Málaga (S.Spain) and its relationship with meteorological parameters. Grana 35:308–313
Reynolds MP, Thethowan R, Crossa J, Vargas M, Sayre KD (2002) Physiological factors associated with genotype by environment interaction in wheat. Field Crop Res 75:139–160
Ribeiro H, Santos L, Abreu I, Cunha M (2006a) Influence of meteorological parameters on Olea flowering date and airborne pollen concentration in four regions of Portugal. Grana 45:115–121
Ribeiro H, Cunha M, Abreu I (2006b) Comparison of classical models for evaluating the heat requirements of olive (Olea europaea L.) in Portugal. J Integr Plant Biol 48(6):664–671
Ribeiro H, Cunha M, Abreu I (2008) Quantitative forecasting of olive yield in Northern Portugal using a bioclimatic model. Aerobiologia 24:141–150
Rodríguez-Rajo FJ, Astray G, Ferreiro-Lage JA, Aira MJ, Jato-Rodriguez MV, Mejuto JC (2010) Evoluation of atmospheric Poaceae pollen concentration using a neural network applied to a coastal Atlantic climate region. Neural Netw 23:419–425
Sánchez-Mesa JA, Galán C, Martínez-Heras JA, Hervás-Martínez C (2002) The use of neural network to forecast daily grass pollen concentration in a Mediterranean region: the southern part of the Iberian Peninsula. Clin Exp Allergy 32:1606–1612
Sánchez-Mesa JA, Galán C, Hervás C (2005) The use of discriminant analysis and neural networks to forecast with a typical Mediterranean climate. Int J Biometeorol 49:355–362
Subba-Reddi C, Reddi NS (1985) Relation of pollen release to pollen concentrations in air. Grana 24:109–113
Voukantsis D, Karatzas K, Damialis A, Vokou D (2010) Forecasting airborne pollen concentration of Poaceae (grass) and Oleaceae (olive), using artificial neural networks and genetic algorithms, in Thessaloniki, Greece. The International Joint Conference on Neural Networks (IJCNN), pp 1–6
Yu H, Eike L, Xu J (2010) Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc Natl Acad Sci USA 107(51):22151–22156
Acknowledgements
The authors are grateful to the European Social Fund for co-financing with the Spanish Science Ministry the “Ramón y Cajal” contract of G.M. Authors are grateful to the Spanish Inter-Ministerial Commission of Science and Technology (MICYT), FEDER funds, for funding the TIN2011-22794 and CGL2011-24146 projects. The authors also thank the Andalusia Regional Government for funding projects P10-RNM5958 and P08-TIC-3745. Finally, the authors appreciate the availability of meteorological data from the Spanish Meteorological Agency (AEMET) and from the Andalusian Government Agroclimatic Information Network (RIA).
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Oteros, J., García-Mozo, H., Hervás-Martínez, C. et al. Year clustering analysis for modelling olive flowering phenology. Int J Biometeorol 57, 545–555 (2013). https://doi.org/10.1007/s00484-012-0581-3
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DOI: https://doi.org/10.1007/s00484-012-0581-3