Sensory evaluation, physical and chemical composition analysis and spectroscopy method, used to evaluate the quality of dried fruits of Ningxia Lycium, are mostly destructive, time consuming and labor intensive, and the processing procedures are also complex and costly. It is urgent to establish a reliable, fast and nondestructive method for the quality detection of dried fruits of Ningxia Lycium. Electronic nose (E-nose) is detection method using responses of sensor array to the volatile compounds of food, agricultural products, possessing the advantages of objective, rapid and nondestructive. In this study, the composition and content of volatile compounds of dried fruits of Ningxia lycium are identified using Gas Chromatography-Mass Spectrometer (GC-MS) with optimized parameters. The characteristic volatiles are confirmed and the correlation between the quality parameters and characteristic volatiles would be illustrated, laying foundation for the inner quality detection of dried fruits of Ningxia Lycium using the overall aroma of volatile compounds. The sensor array of E-nose is chosen based on the characteristic volatiles of dried fruits of Ningxia lycium. The response mechanism of sensors to characteristic volatiles and the correlation between odor information obtained by E-nose and inner quality of dried fruits of Ningxia lycium are studied to reveal the nondestructive quality detection mechanism of E-nose for dried fruits of Ningxia lycium. On these basis, the sensor array is optimized by response sensitivity, stability and discrimination ability. The E-nose odor fingerprint for dried fruits of Ningxia lycium are established by extraction of useful information and elimination of redundant information of sensor responses to volatile compounds emitted by dried fruits of Ningxia lycium. Pattern recognition methods are employed and optimized to build models for identification of dried fruits of Ningxia lycium with different quality and prediction the content of active compounds, such as Lycium barbanan polysaccharide (LBP), Flavonoids and Betaine. All these achievements would lay technical basis for the nondestructive quality detection of dried fruits of Ningxia lycium, and also theoretical foundation for the development and application of E-nose specialized in quality detection of dried fruits of Ningxia lycium.
针对宁夏枸杞子内部品质评价存在前处理复杂、破坏样品完整性等问题,亟需快速、无损的方法衡量其品质。利用气敏传感器对挥发物呈香响应识别气味的电子鼻技术可实现食品、农产品客观、快速、无损的品质检测。本项目拟在优化GC-MS检测条件的基础上,分析鉴定宁夏枸杞子特征挥发物组成与含量,探明特征挥发物与品质间的关联性,奠定通过挥发物外部呈香揭示宁夏枸杞子内部品质的基础;针对特征挥发物确定电子鼻传感器阵列,探明传感器对特征挥发物的响应机理,建立电子鼻气味信息与内部品质间的关联关系,明确电子鼻无损检测宁夏枸杞子品质的机理;优化特征参数提取方法并剔除冗余信息,获得代表宁夏枸杞子品质的特征气味指纹图谱及数据库,研究宁夏枸杞子品质对传感器响应信号的影响规律;优化模式识别方法,建立宁夏枸杞子内部品质的定性判别模型与活性成分的定量预测模型,为快速无损检测宁夏枸杞子品质提供技术支撑和开发专用电子鼻系统提供理论依据。
在宁夏枸杞子内部品质评价中,快速、无损的判别和预测具有重要意义。挥发性组分在枸杞子表面呈味能直接反应其内部品质,项目在鉴定宁夏枸杞子特征挥发物组成和含量的基础上,阐明挥发物组成与内部品质的关联性;研究不同品质枸杞子挥发物对气敏传感器响应的响应规律,阐明了枸杞子内部品质与电子鼻传感器响应之间的相关性;研究了冗余信号剔除的方法,建立了较佳的气味指纹图谱;提出了模式识别的方法并建立了品质指标(产地、贮藏时间等)的定量检测方法。.通过项目的实施,建立了宁夏枸杞子内部品质判别和指标定量检测的方法,共发表和录用论文11篇,其中SCI收录论文6篇,中文期刊5篇;拟申请国家专利2项;培养博士研究生1名,硕士研究生3名(含在读研究生1名)、本科生1名、博士后1人。完成了研究内容并达到预期目标。通过课题的研究,对检测专用电子鼻开发和枸杞品质快速无损检测技术的应用等具有借鉴作用。
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数据更新时间:2023-05-31
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