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Agronomy Journal 95:329-334 (2003)
© 2003 American Society of Agronomy

MODELING

Modeling the Oleic Acid Content in Sunflower Oil

Eduardo Sobrino*,a, Ana M. Tarquisb and M. Cruz Díazc

a Departamento de Producción Vegetal, Botánica, Polytechnic University of Madrid, Ciudad Universitaria, 28040 Madrid, Spain
b Departamento de Matemática Aplicada, Polytechnic University of Madrid, Ciudad Universitaria, 28040 Madrid, Spain
c Departamento de Edafología, Escuela Técnica Superior Ingenieros Agrónomos, Polytechnic University of Madrid, Ciudad Universitaria, 28040 Madrid, Spain

* Corresponding author (esobrino{at}pvb.etsia.upm.es)

Received for publication January 5, 2002. Knowledge of the effects of temperature and geographic variables on the oleic acid content of sunflower (Helianthus annuus L.) oil allows us to predict the type of oil that will be produced in a particular area. This study was designed to establish a simple empirical model, which uses available variables of previously established effects, to estimate the final oleic acid composition of sunflower oil. Over two growing seasons, sunflower seeds were collected from Spain's main producing areas, and the oleic acid concentration of oil extracted from these samples was analytically determined. The effects of two types of variables (geographical position and temperature) on oil oleic acid content were determined according to three models based on the input variables: latitude, longitude, and altitude (Model I); mean minimum and maximum temperatures during the phenological stages of sunflower seed development and maturation (Model II); and a combination of both types of data (Model III). Through stepwise regression, it was established that best results were obtained using the temperature model (Model II) and the variables' mean minimum development and mean minimum and maximum maturation temperatures (r2 = 0.99, P < 0.001, n = 88). Of the three variables included in this model, the mean minimum maturation temperature provided the closest estimate of percentage oleic acid content. This regression model was statistically validated and is proposed as a method for crop managers to estimate oleic acid content based on local temperatures.

Abbreviations: MAE, mean absolute error • MSE, mean square error • tmaxd, mean monthly maximum temperature corresponding to the time of achene development • tmaxmat, mean monthly maximum temperature corresponding to the time of physiological maturity before harvesting • tmind, mean monthly minimum temperature corresponding to the time of achene development • tminmat, mean monthly minimum temperature corresponding to the time of physiological maturity before harvesting




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Soil Science Society of America Journal
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