Discrimination of transgenic tomatoes based on visible/near-infrared spectra Original Research Article

VIS–NIR spectroscopy combined with multivariate analysis after the appropriate spectral data pre-treatment has been proved to be a very powerful tool for judgment of the relative pattern of the objects that have very similar properties. In this study, seventy transgenic tomatoes with antisense LeETR2 and 94 of their parents, non-transgenic ones were measured in VIS–NIR diffuse reflectance mode. Principal component analysis (PCA), discriminant analysis (DA) and partial least-squares discriminant analysis (PLSDA) were applied to classify tomatoes with different genes into two groups. Calibrations were developed using PLS regression with the leave-one-out cross-validation technique. The results show that differences between transgenic and non-transgenic tomatoes do exist and excellent classification can be obtained after optimizing spectral pre-treatment. The correct classifications for transgenic and non-transgenic tomatoes were both 100% using PLSDA after derivative spectral pre-treatment. The raw spectra with PLSDA model after the second derivative pre-treatment had the best satisfactory calibration and prediction abilities, with rc = 0.97964, root mean square error of calibration (RMSEC) = 0.099, rcv = 0.97963, root mean square error of cross-validation (RMSECV) = 0.0993 and a factor. The results in the present study show VIS–NIR spectroscopy together with chemometrics techniques could be used to differentiate transgenic tomato, which offers the benefit of avoiding time-consuming, costly and laborious chemical and sensory analysis.