首页 | 本学科首页   官方微博 | 高级检索  
     


An overview of near-infrared spectroscopy (NIRS) for the detection of insect pests in stored grains
Affiliation:1. School of Information Science and Technology, Zhengzhou 450001, China;2. Grain Information Processing and Control Key Laboratory of Ministry of Education, Henan University of Technology, Zhengzhou 450001, China;1. Department of Bio-systems Engineering, Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran;2. Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
Abstract:Applications of near-infrared spectroscopy for measuring various aspects of grain quality have expanded rapidly in recent years. One application that could be of particular use to growers and industry is the detection of insect pests across a range of stored grains. This prospect was first reported over 20 years ago, but the accuracy of this technique does not currently meet FDA standards for the quantification of insect fragments in bulk wheat and flour samples. When considering bulk samples, near-infrared spectroscopy may be suitable for identifying the presence of infestation in samples, followed by flotation testing to provide an accurate quantitative value. Much higher accuracy has been found for the detection of pest species at the single-kernel level. With faster spectrophotometers and kernel sorting systems, single-kernel analysis is likely to be utilised more in the future and could even render bulk analysis of samples redundant. This technology could allow for the detection and identification of pest species in every single kernel of a representative grain sample. The development and application of more sensitive spectrophotometers, such as FT-NIR (Fourier transform near infrared) and more powerful chemometric data analysis techniques are also likely to provide significant improvements, through allowing the minute chemical differences present in bulk infested grains to be accurately detected and quantified.
Keywords:Post-harvest insect pests  Food security  Chemometrics  Non-invasive analysis
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号