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作 者:于宏威 王强[1] 刘丽[1] 石爱民[1] 胡晖[1] 刘红芝[1] YU Hong-wei WANG Qiang LIU Li SHI Ai-min HU Hui LIU Hong-zhi(Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Products Processing, Ministry of Agriculture, Beijing 100193, China)
机构地区:[1]中国农业科学院农产品加工研究所,农业部农产品加工综合性重点实验室,北京100193
出 处:《光谱学与光谱分析》2016年第11期3643-3650,共8页Spectroscopy and Spectral Analysis
基 金:国家科技支持计划课题(2012BAD29B03);中国农业科学院科技创新工程项目(CAAS-ASTIP-201X-IAPPST)资助
摘 要:粮油品质安全至关人类营养健康与生命安全。常规检测粮油品质安全方法,由于操作困难、破坏性强、费用高、试剂污染等缺点,不能满足快速无损,高效无污染的要求,难以与工业4.0接轨。整合光谱和图像手段的高光谱成像技术,伴随着化学计量学的发展,突破了常规检测方法局限性,是粮油品质安全检测技术的发展趋势。在大量文献的基础上,综述了高光谱成像技术原理,以及在品质方面(组分测定、发芽检测、品种分类)和安全方面(真菌检测、虫害检测)的研究进展,特别分析了高光谱成像技术检测粮油品质安全的应用光谱范围、化学计量学方法、仪器设备和模型准确性,指出了现阶段在粮油品质安全检测中存在的主要问题,并对今后的研究方向和重点进行了展望,以期推动高光谱成像技术在粮油领域的应用发展。The quality and safety of grain and oils are related to the national nutrition and health safety of the public.Owing to the difficulties in operation,destruction,high cost,reagent pollution and other shortcomings,conventional detection method cannot meet the fast,non-destructive,efficient and pollution-free requirements,which pose great difficulties in integrating with Industry 4.0.With the development of chemometrics,hyperspectral imaging(HSI)technology integrates the advantages of spectroscopy and image technology to overcome the defects of conventional detection method,which has become the developingt trend of grain and oils quality testing technology.Based on many interrelated research papers,this paper reviews the principles of HSI and the existing research in quality(component determination,germination test,variety classification)and safety(fungal detection,pest detection)of grain and oils.Meanwhile,in order to promote the application and development of hyperspectral imaging technology in the field of grain and oils,we specially analyze the aspect of HSI including spectral range,chemometrics,equipment and the accuracy of model,pointing out the current problems and prospecting the direction and priority.
分 类 号:S126[农业科学—农业基础科学] TP391.4[自动化与计算机技术—计算机应用技术]
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