Peach growth cycle monitoring using an electronic nose

•New device for in-loco application (orchard) for maturation phase analysis.•Comparison of the results of the methods used (KNN, SVM, RF, ELM).•Pearson's Chi-square test to remove inconsistent and redundant attributes (13–7).•Dimensionality reduction with PCA and LDA.•Improved accuracy of classifications with proposed methods. In regions with the predominance of agriculture, an inspection of the quality and fruit maturity index in the orchard is usually analyzed by the farmer’s experience, which can be subject to errors and generate a greater cost of time and money. Thus, monitoring equipment that generates a rapid and accurate response to the growth cycle of the peaches in the crop is desirable, together with a low marketing cost. For this purpose, electronic noses prove to be the most suitable equipment, since it allows online monitoring of the VOCs (Volatile Organic Compounds) generated by the crop. In this context, a prototype was developed to perform the classification of the fruit growth cycle (pre-harvest and post-harvest). Models with the 13 gas sensors made with a metal oxide semiconductor (MOS) and the reduction to 7 sensors were studied with the aid of the Pearson’s Chi-square test, for comparison. Samples with 4 growth stages were used for the training and construction of the model. The accuracy of 99.23% in the validation step and 98.08% in the sample test step using the Random Forest method with linear discriminant analysis for the reduced data set for 7 sensors shows that the device is promising for monitoring of areas with an intense emission of VOCs.