Jianjun Liu
https://www.osapublishing.org/jot/abstract.cfm?uri=jot-83-10-627&origin=search
Because traditional detection of genetically modified organisms (GMOs) has the disadvantages of being costly, time consuming, and awkward to perform, a novel method for the detection of GMOs based on terahertz spectroscopy combined with chemometrics methods is proposed. In this work, terahertz spectrum data of a genetically modified sugar beet and its parents are pretreated by using principal component analysis and then using the weighted discriminant analysis model, which is an improved discriminant analysis that applys a weighted algorithm to the detection of a genetically modified sugar beet and its parents. It is found from the experimental results that the samples are expressed by the zonation of saline minerals. By analyzing this phenomenon, it is easy to identify these genetically modified sugar beets. By combining terahertz spectroscopy with chemometrics methods, this paper provides a precise, fast, convenient, and nondestructive method for the detection of GMOs.
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