ABSTRACT
During cooking, aromatic rice has a pleasant and characteristic aroma, a relevant factor to add sale value and attract consumer interest. This work studied the volatile compounds of aromatic rice (IAC 500) aiming at identifying those responsible for the aroma and flavor of the cooked rice. The description of the aromatic notes of the IAC 500 rice was carried out by a trained and selected sensory panel, followed by olfactometry (OSME) and identification by GC-MS of the rice volatile compounds extracted by SPME. A total of 80 volatiles was sensorially perceived and/or detected in the chromatographic effluent, of which 65 were identified, 44 presented some odor, and 36 were odorless. Among the odorous compounds, 15 were not detected by GC-FID or GC-MS. This study confirmed the compound 2-acetyl-1-pyrroline as the impacting volatile compound to the aroma of aromatic rice since it presented a very low percentage of area in the chromatogram and a high odor intensity. Other 43 compounds presented odor in lower intensities, but also contributed to the overall aroma of IAC 500 rice. From the 11 aromatic notes mentioned by the trained panel (cooked vegetable/seed, corn, hominy, green, porridge, popcorn, fresh baked cake/bread, milk, caramel, tapioca flour and flower), eight were related to the volatile compounds responsible for their aroma.
Subject(s)
Odorants , Oryza , Gas Chromatography-Mass Spectrometry , Odorants/analysis , Olfactometry , Solid Phase MicroextractionABSTRACT
Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm-2, day-1. The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%).
Foram desenvolvidas duas equações de estimativa da produtividade do arroz irrigado por inundação, para as variedades: IAC-242, IAC-100, IAC-101 e IAC-102, em função da temperatura do ar e da radiação solar, no período crítico de formação da produção, para a região de Pindamonhangaba (SP). Os valores de temperatura do ar e de radiação solar ótimos encontrados para as variedades foram, respectivamente, 25,0oC e 475 cal.cm-2.dia-1. O modelo agrometeorológico desenvolvido para previsão da produtividade da cultura que apresentou melhores resultados quando testado com dados independentes foi o que relacionou o menor desvio dos dois elementos climáticos em relação ao valor ótimo obtido através de uma equação de regressão linear múltipla. Os valores de produtividade estimados pelo modelo mostraram diferenças menores que 10% quando comparados com os valores obtidos no campo.
ABSTRACT
Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm-2, day-1. The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%).
Foram desenvolvidas duas equações de estimativa da produtividade do arroz irrigado por inundação, para as variedades: IAC-242, IAC-100, IAC-101 e IAC-102, em função da temperatura do ar e da radiação solar, no período crítico de formação da produção, para a região de Pindamonhangaba (SP). Os valores de temperatura do ar e de radiação solar ótimos encontrados para as variedades foram, respectivamente, 25,0oC e 475 cal.cm-2.dia-1. O modelo agrometeorológico desenvolvido para previsão da produtividade da cultura que apresentou melhores resultados quando testado com dados independentes foi o que relacionou o menor desvio dos dois elementos climáticos em relação ao valor ótimo obtido através de uma equação de regressão linear múltipla. Os valores de produtividade estimados pelo modelo mostraram diferenças menores que 10% quando comparados com os valores obtidos no campo.