Department of Bromatology and Food Technology, University of Cordoba, Córdoba, Spain.
Pest Manag Sci. 2010 Jun;66(6):580-6. doi: 10.1002/ps.1910.
Peppers are a frequent object of food safety alerts in various member states of the European Union owing to the presence in some batches of unauthorised pesticide residues. This study assessed the viability of near-infrared reflectance spectroscopy (NIRS) for the measurement of pesticide residues in peppers. Commercially available spectrophotometers using different sample-presentation methods were evaluated for this purpose: a diode-array spectrometer for intact raw peppers and two scanning monochromators fitted with different sample-presentation accessories (transport and spinning modules) for crushed peppers and for dry extract system for infrared analysis (DESIR), respectively.
Models developed using partial least squares-discriminant analysis (PLS2-DA) correctly classified between 62 and 68% of samples by presence/absence of pesticides, depending on the instrument used. At model validation, the highest percentage of correctly classified samples-75 and 82% for pesticide-free and pesticide-containing samples respectively-were obtained for intact peppers using the diode-array spectrometer.
The results obtained confirmed that NIRS technology may be used to provide swift, non-destructive preliminary screening for pesticide residues; suspect samples may then be analysed by other confirmatory analytical methods.
由于某些批次的农药残留未经授权,辣椒经常成为欧盟各成员国食品安全警报的对象。本研究评估了近红外反射光谱(NIRS)用于测量辣椒中农药残留的可行性。为此目的,评估了使用不同样品呈现方法的市售分光光度计:用于完整生辣椒的二极管阵列分光光度计,以及分别用于粉碎辣椒和用于红外分析的干提取物系统(DESIR)的两个带有不同样品呈现附件(传输和旋转模块)的扫描单色仪。
使用偏最小二乘判别分析(PLS2-DA)建立的模型根据所用仪器的不同,正确地将 62%至 68%的样品分为有/无农药残留。在模型验证时,使用二极管阵列分光光度计对无农药和含农药样品分别获得了最高的正确分类样品百分比-75%和 82%。
获得的结果证实,NIRS 技术可用于快速、非破坏性地初步筛选农药残留;可疑样品可随后通过其他确认性分析方法进行分析。