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분광분석법을 이용한 형질전환 작물 판별 기술 현황

Current Status of GM Crop Discrimination Technology Using Spectroscopy

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초록

BACKGROUND: This paper describes the successful discrimination of GM crops from the respective wild type (WT) controls using spectroscopy and chemometric analysis. Despite the many benefits that GM crops, their development has raised concerns, particularly about their potential negative effects on food production and the environment. From this point of view, the introduction of GM crops into the market requires the development of rapid and accurate identification technologies to ensure consumer safety. METHODS AND RESULTS: The development of a GM crop discrimination model using spectroscopy involved the pre-processing of the collected spectral information, the selection of a discriminant model, and the verification of errors. Examples of GM versus WT discrimination using spectroscopy are available for soybeans, tomatoes, corn, sugarcane, soybean oil, canola oil, rice, and wheat. Here, we found that not only discrimination but also cultivar grouping was possible. CONCLUSION: Since for the determination of GM crop there is no pre-defined pre-processing method or calibration model, it is extremely important to select the appropriate ones to increase the accuracy in a case-by-case basis.

Abstract

BACKGROUND: This paper describes the successful discrimination of GM crops from the respective wild type (WT) controls using spectroscopy and chemometric analysis. Despite the many benefits that GM crops, their development has raised concerns, particularly about their potential negative effects on food production and the environment. From this point of view, the introduction of GM crops into the market requires the development of rapid and accurate identification technologies to ensure consumer safety. METHODS AND RESULTS: The development of a GM crop discrimination model using spectroscopy involved the pre-processing of the collected spectral information, the selection of a discriminant model, and the verification of errors. Examples of GM versus WT discrimination using spectroscopy are available for soybeans, tomatoes, corn, sugarcane, soybean oil, canola oil, rice, and wheat. Here, we found that not only discrimination but also cultivar grouping was possible. CONCLUSION: Since for the determination of GM crop there is no pre-defined pre-processing method or calibration model, it is extremely important to select the appropriate ones to increase the accuracy in a case-by-case basis.

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