Objective:To develop and validate an image analysis method for quantitative analysis ofγ-oryzanol in cold pressed rice bran oil.Methods:TLC-densitometric and TLC-image analysis methods were developed,validated,and us...Objective:To develop and validate an image analysis method for quantitative analysis ofγ-oryzanol in cold pressed rice bran oil.Methods:TLC-densitometric and TLC-image analysis methods were developed,validated,and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil.The results obtained by these two different quantification methods were compared by paired t-test.Results:Both assays provided good linearity,accuracy,reproducibility and selectivity for determination of γ-oryzanol.Conclusions:The TLC-densitomelric and TLC-image analysis methods providett a similar reproducibility,accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil.A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods.As both methods were found to be equal,they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.展开更多
Germinated brown rice(GBR)is rich in gamma oryzanol which increase its consumption popularity,particularly in the health food market.The objective of this research was to apply the near infraredspectroscopy(NIRS)for e...Germinated brown rice(GBR)is rich in gamma oryzanol which increase its consumption popularity,particularly in the health food market.The objective of this research was to apply the near infraredspectroscopy(NIRS)for evaluation of gamma oryzanol of the germinated brown rice.The germinated brown rice samples were prepared from germinated rough rice(soaked for 24 and 48 h,incubated for 0,6,12,18,24,30 and 36 h)and purchased from local supermar kets.The germinated brown rice sampleswere subjected to NIR scanning before the evaluation of gamma oryzanol by using partial extractionmet hodology.The prediction model was established by partial least square regression(PLSR)andvalidated by full cross validation method.The NIRS model established from various varieties of germinated brown rice bought from diferent markets by first derivatives+vector normalizationpretreated spectra showed the optimal prediction with the correlation of determination(R?),root mean squared error of cross validation(RMSECV),and bias of 0.934,8.84×10^(-5) mg/100 g drymatter and 1.06×10^(-5) mg/100 g dry matter,respectively.This is the first report on the application of NIRS in the evaluation of gamma oryzanol of the germinated brown rice.This information is veryuseful to the germinated brown rice production factory and consumers.展开更多
基金Supported by the Research Institute of Rangsit University,Pathum Thani,Thailand(Grant No.73/55)
文摘Objective:To develop and validate an image analysis method for quantitative analysis ofγ-oryzanol in cold pressed rice bran oil.Methods:TLC-densitometric and TLC-image analysis methods were developed,validated,and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil.The results obtained by these two different quantification methods were compared by paired t-test.Results:Both assays provided good linearity,accuracy,reproducibility and selectivity for determination of γ-oryzanol.Conclusions:The TLC-densitomelric and TLC-image analysis methods providett a similar reproducibility,accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil.A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods.As both methods were found to be equal,they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.
文摘Germinated brown rice(GBR)is rich in gamma oryzanol which increase its consumption popularity,particularly in the health food market.The objective of this research was to apply the near infraredspectroscopy(NIRS)for evaluation of gamma oryzanol of the germinated brown rice.The germinated brown rice samples were prepared from germinated rough rice(soaked for 24 and 48 h,incubated for 0,6,12,18,24,30 and 36 h)and purchased from local supermar kets.The germinated brown rice sampleswere subjected to NIR scanning before the evaluation of gamma oryzanol by using partial extractionmet hodology.The prediction model was established by partial least square regression(PLSR)andvalidated by full cross validation method.The NIRS model established from various varieties of germinated brown rice bought from diferent markets by first derivatives+vector normalizationpretreated spectra showed the optimal prediction with the correlation of determination(R?),root mean squared error of cross validation(RMSECV),and bias of 0.934,8.84×10^(-5) mg/100 g drymatter and 1.06×10^(-5) mg/100 g dry matter,respectively.This is the first report on the application of NIRS in the evaluation of gamma oryzanol of the germinated brown rice.This information is veryuseful to the germinated brown rice production factory and consumers.
