INVESTIGADORES
ROUSSEAUX Maria Cecilia
artículos
Título:
Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model and growth regulators
Autor/es:
AYBAR, V. E.; DE MELO-ABREU, J. P.; SEARLES, P.S.; MATIAS, C.; DEL RIO C., ; CABALLERO, J. M.; ROUSSEAUX, M. C.
Revista:
SPANISH JOURNAL OF AGRICULTURAL RESEARCH
Editorial:
SPANISH NATL INST AGRICULTURAL & FOOD RESEARCH & TECHNOLO
Referencias:
Lugar: Madrid; Año: 2015 vol. 13
ISSN:
1695-971X
Resumen:
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.