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a Unidad Integrada Facultad de Ciencias Agrarias (UNMdP), Estación Experimental Agropecuaria INTA Balcarce, CC.C. 276, 7620 Balcarce, Argentina, and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, Argentina)
b Facultad de Ciencias Agropecuarias, Universidad Nacional de Cordoba, Av. Valparaiso s/n. Ciudad Universitaria, 5000 Córdoba, Argentina
* Corresponding author (laguirre{at}mdp.edu.ar)
Received for publication March 21, 2005. Oil quality highly depends on its fatty acid composition. In traditional sunflower (Helianthus annuus L.) hybrids, fatty acid composition is affected by night temperature during grain filling. It is unknown if the increase of oleic acid concentration when night temperature increases saturates at a temperature threshold. Modeling the response of fatty acid composition to temperature could lead to oil quality prediction. The objectives of this work were: (i) to develop precise models to estimate fatty acid composition, and (ii) to use the established models to assess differences in final fatty acid composition among regions, sowing dates, and years. The traditional hybrid Dekasol 3881 was exposed to different daynight temperature regimes during grain filling (28 and 20°C, 25 and 23°C, and 20 and 28°C). To model the response of fatty acid composition to temperature data from two field experiments, eight field crops and five growth chamber experiments were analyzed. Night minimum temperature during the 100 to 300 ddaf (degree-days after flowering) period (base temperature = 6°C) accounted for most of the variability in oleic acid concentration (r2 = 0.84). The relationship was linear up to 22.6°C, the temperature at which the maximum value of oleic acid was reached. The model also estimated other fatty acid contents. The relationships accurately predicted independent data from Dekasol 3881 and other hybrids. Our model explained most of the variation in oleic acid concentration observed in a large region were sunflower is cultivated (27°37° S) and it is feasible for a wide range of environmental conditions.
Abbreviations: ddaf, degree-days after flowering CYT, comparative yield trials LCS, lack of correlation weighted by the standard deviations MSD, mean square deviation SB, square bias SDSD, squared difference between standard deviations
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