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Abstract: The combination of mass spectrometry (MS) based electronic nose (eNose) with visible (VIS) and near infrared spectroscopy (NIR) was explored as an objective tool to measure sensory attributes in commercial Riesling wines grown in Australia. Calibration models were developed between instrumental data and sensory scores using partial least squares (PLS) regression with full cross validation. Good correlations (r >0.70, root mean square standard error in cross validation (RMSECV): 0.66) were found for developed and floral; intermediate (0.70> r >0.60, RMSECV: 0.84 and 0.63) for tropical and low (r<0.50, RMSECV: 0.98) for green characters measured by a sensory panel and the combination of both techniques. The results suggested that data from instrumental techniques coupled with chemometrics might be related with sensory scores measured by a trained panel. The study is considered a starting point in order to evaluate useful sources of information generated by different instrumental techniques with the objective to select combination of sensors for specific wine quality attributes. [Copyright &y& Elsevier]