We collect synthetic training data for the anomaly detector by observing the simulated response of the gas sensor array in the fruit ripening room under normal conditions. Precisely, we sample CO 2 , C 2 H 4 , and H 2 O partial pressures p from the probability distribution in Fig. An instance of a training data set is shown in Fig. , as sensor response vectors scattered in sensor array response space. Note the responses of the two QCM-ZIF sensors are strongly correlated owing to their high selectivity to water (see Fig. ).