As the use of Cannabis products as natural medicines burgeons,it is also appearing as a food ingredient.It is important to screen Cannabis samples as ingredients by profiling their chemical compositions,which is refer...As the use of Cannabis products as natural medicines burgeons,it is also appearing as a food ingredient.It is important to screen Cannabis samples as ingredients by profiling their chemical compositions,which is referred to as chemotyping.Two sets of botanical extracts were studied.The first set is referred to as Cannabis contained plant materials from 15 samples of the sativa,indica,and hybrids of the two species.The second set contained 20 extracts from the variety of Cannabis sativa with low tetrahydrocannabinol(THC)concentrations,i.e.,below 0.3%,and,henceforth,will be referred to as hemp.An ultraviolet(UV)microplate reader provides a cost-effective and high-throughput method for identifying chemotypes of plant extracts by their spectra.The microplate reader affords rapid measurements of small volumes,e.g.,50μL,which demonstrates a potential to significantly reduce the analysis time and cost for Cannabis and hemp chemotyping or chemi-cal profiling.Replicate samples were measured on different days to demonstrate the robustness of the method.Projected difference resolution(PDR)maps were used to visualize the separations among the classes.Five multivariate classifiers,fuzzy rule-building expert system(FuRES),super partial least squares-discriminant analysis(sPLS-DA),support vector machine(SVM),and two tree-based support vector machines(SVMtreeG and SVMtreeH)were evaluated.The classifiers were validated with ten bootstrapped Latin partitions(BLPs).For the Cannabis extracts,the SVMtreeG yielded the best performance and the classification accuracy was 99.1±0.4%for spectra collected in the nonlinear absorbance range.For the hemp extracts,the SVM classifier performed the best with a 97.4±0.6%classification accuracy.These results demonstrate that the UV microplate reader coupled with multivariate classifiers can be used as a high-throughput and cost-effective approach for chemotyping Cannabis.展开更多
汉麻籽分离蛋白(Hemp Seed Protein Isolate,HPI)是汉麻籽深加工过程中的产物之一,尚未被完全利用开发。本文采用酶法水解脱脂汉麻籽粉辅助碱提HPI,以提取率和沉淀率为指标,设计单因素实验和正交实验,研究碱提料液比、碱提温度、碱提pH...汉麻籽分离蛋白(Hemp Seed Protein Isolate,HPI)是汉麻籽深加工过程中的产物之一,尚未被完全利用开发。本文采用酶法水解脱脂汉麻籽粉辅助碱提HPI,以提取率和沉淀率为指标,设计单因素实验和正交实验,研究碱提料液比、碱提温度、碱提pH值、酶解pH值对纤维素酶辅助碱提酸沉法提取汉麻籽蛋白法的影响,并评估对比产品质量。结果表明,最佳工艺条件为酶解pH=4.0,料液比1∶20,碱提温度45℃,碱提pH=10.0。此条件下制备HPI沉淀率达到了77.9%,蛋白含量为83.69%。展开更多
以火麻籽为原料,对碱提酸沉法提取火麻蛋白工艺参数进行研究,在单因素试验的基础上,采用响应面分析法对提取温度、提取时间、提取pH和料液比进行优化并得到回归模型。确定的碱提酸沉法提取火麻蛋白最佳工艺参数为:提取温度60℃,提取时间...以火麻籽为原料,对碱提酸沉法提取火麻蛋白工艺参数进行研究,在单因素试验的基础上,采用响应面分析法对提取温度、提取时间、提取pH和料液比进行优化并得到回归模型。确定的碱提酸沉法提取火麻蛋白最佳工艺参数为:提取温度60℃,提取时间1 h,提取pH 10,料液比1∶9。在最佳工艺条件下,火麻蛋白的提取率为63.5%。回归模型的预测值与实测值的相对误差为2.3%,该回归方程与实际情况拟合较好。DSC分析得出火麻蛋白的变性温度为83.0℃,纯化后的火麻蛋白相对分子质量分布均小于40 k Da。展开更多
采用超声波以及微波辅助萃取火麻籽油,通过单因素实验确定最佳工艺条件,比较不同萃取方法的油脂收率。通过气质联用仪(GC–MS)测定油品中α–亚麻酸的含量。实验结果表明:超声波辅助萃取火麻籽油最佳工艺条件为料液比1∶16(g/m L)、超...采用超声波以及微波辅助萃取火麻籽油,通过单因素实验确定最佳工艺条件,比较不同萃取方法的油脂收率。通过气质联用仪(GC–MS)测定油品中α–亚麻酸的含量。实验结果表明:超声波辅助萃取火麻籽油最佳工艺条件为料液比1∶16(g/m L)、超声波功率180 k W、萃取时间40 min和萃取温度20℃,此时油脂最大收率为36.49%;微波辅助萃取火麻籽油最佳工艺条件为料液比1∶16(g/m L)、微波功率800 k W、萃取时间8 min和萃取温度50℃,此时油脂最大收率为37.86%;超声波与微波辅助萃取油品中α–亚麻酸的含量分别为21.02%、26.39%。展开更多
文摘As the use of Cannabis products as natural medicines burgeons,it is also appearing as a food ingredient.It is important to screen Cannabis samples as ingredients by profiling their chemical compositions,which is referred to as chemotyping.Two sets of botanical extracts were studied.The first set is referred to as Cannabis contained plant materials from 15 samples of the sativa,indica,and hybrids of the two species.The second set contained 20 extracts from the variety of Cannabis sativa with low tetrahydrocannabinol(THC)concentrations,i.e.,below 0.3%,and,henceforth,will be referred to as hemp.An ultraviolet(UV)microplate reader provides a cost-effective and high-throughput method for identifying chemotypes of plant extracts by their spectra.The microplate reader affords rapid measurements of small volumes,e.g.,50μL,which demonstrates a potential to significantly reduce the analysis time and cost for Cannabis and hemp chemotyping or chemi-cal profiling.Replicate samples were measured on different days to demonstrate the robustness of the method.Projected difference resolution(PDR)maps were used to visualize the separations among the classes.Five multivariate classifiers,fuzzy rule-building expert system(FuRES),super partial least squares-discriminant analysis(sPLS-DA),support vector machine(SVM),and two tree-based support vector machines(SVMtreeG and SVMtreeH)were evaluated.The classifiers were validated with ten bootstrapped Latin partitions(BLPs).For the Cannabis extracts,the SVMtreeG yielded the best performance and the classification accuracy was 99.1±0.4%for spectra collected in the nonlinear absorbance range.For the hemp extracts,the SVM classifier performed the best with a 97.4±0.6%classification accuracy.These results demonstrate that the UV microplate reader coupled with multivariate classifiers can be used as a high-throughput and cost-effective approach for chemotyping Cannabis.
文摘汉麻籽分离蛋白(Hemp Seed Protein Isolate,HPI)是汉麻籽深加工过程中的产物之一,尚未被完全利用开发。本文采用酶法水解脱脂汉麻籽粉辅助碱提HPI,以提取率和沉淀率为指标,设计单因素实验和正交实验,研究碱提料液比、碱提温度、碱提pH值、酶解pH值对纤维素酶辅助碱提酸沉法提取汉麻籽蛋白法的影响,并评估对比产品质量。结果表明,最佳工艺条件为酶解pH=4.0,料液比1∶20,碱提温度45℃,碱提pH=10.0。此条件下制备HPI沉淀率达到了77.9%,蛋白含量为83.69%。
文摘以火麻籽为原料,对碱提酸沉法提取火麻蛋白工艺参数进行研究,在单因素试验的基础上,采用响应面分析法对提取温度、提取时间、提取pH和料液比进行优化并得到回归模型。确定的碱提酸沉法提取火麻蛋白最佳工艺参数为:提取温度60℃,提取时间1 h,提取pH 10,料液比1∶9。在最佳工艺条件下,火麻蛋白的提取率为63.5%。回归模型的预测值与实测值的相对误差为2.3%,该回归方程与实际情况拟合较好。DSC分析得出火麻蛋白的变性温度为83.0℃,纯化后的火麻蛋白相对分子质量分布均小于40 k Da。
文摘采用超声波以及微波辅助萃取火麻籽油,通过单因素实验确定最佳工艺条件,比较不同萃取方法的油脂收率。通过气质联用仪(GC–MS)测定油品中α–亚麻酸的含量。实验结果表明:超声波辅助萃取火麻籽油最佳工艺条件为料液比1∶16(g/m L)、超声波功率180 k W、萃取时间40 min和萃取温度20℃,此时油脂最大收率为36.49%;微波辅助萃取火麻籽油最佳工艺条件为料液比1∶16(g/m L)、微波功率800 k W、萃取时间8 min和萃取温度50℃,此时油脂最大收率为37.86%;超声波与微波辅助萃取油品中α–亚麻酸的含量分别为21.02%、26.39%。
