目的为充分利用榕树叶资源,研究超声提取榕树叶总黄酮的工艺条件。方法以总黄酮含量为考察指标,采用正交设计的方法研究超声波辅助提取榕树叶总黄酮的工艺条件。结果影响榕树叶总黄酮超声提取效果的主次因素为:乙醇浓度>溶剂量>...目的为充分利用榕树叶资源,研究超声提取榕树叶总黄酮的工艺条件。方法以总黄酮含量为考察指标,采用正交设计的方法研究超声波辅助提取榕树叶总黄酮的工艺条件。结果影响榕树叶总黄酮超声提取效果的主次因素为:乙醇浓度>溶剂量>提取次数>超声时间,榕树叶总黄酮最佳提取工艺为16倍量70%乙醇超声提取3次,40 m in/次。结论优化的提取方法效率高,稳定性好,提取总黄酮含量可达2.42%。展开更多
[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] T...[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.展开更多
文摘目的为充分利用榕树叶资源,研究超声提取榕树叶总黄酮的工艺条件。方法以总黄酮含量为考察指标,采用正交设计的方法研究超声波辅助提取榕树叶总黄酮的工艺条件。结果影响榕树叶总黄酮超声提取效果的主次因素为:乙醇浓度>溶剂量>提取次数>超声时间,榕树叶总黄酮最佳提取工艺为16倍量70%乙醇超声提取3次,40 m in/次。结论优化的提取方法效率高,稳定性好,提取总黄酮含量可达2.42%。
基金Supported by National Natural Science Foundation of China under Grant(No.60968001,61168003)Natural Science Foundation of Yunnan Province under Grant(No.2011FZ079,2009CD047)National Training Programs of Innovation and Entrepreneurship for Undergraduates under Grant(No.201210681005,201310681004)~~
文摘[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.
