Non-Destructive Analysis of Low-Impact Grown Tomatoes

Non-destructive optical techniques, in combination with chemometric methods, have been used for rapid determination of the quality of the fruit and vegetable products. This research will focus on the application of non-destructive technologies such as VIS-NIR spectroscopy and hyperspectral images to authenticate fruit and vegetable products obtained with sustainable production techniques. Thanks to these techniques, it is possible to obtain what is called the spectral footprint or fingerprint, which is the result of several factors, including agronomic practices that influence the composition and final quality of each product.

This trial focuses on the prediction of internal quality and the discrimination of tomatoes obtained from sustainable agriculture in relation to reduced agronomic inputs. To this end, we measured the reflected radiation of tomatoes measured by a hyperspectral scanner and a spectrophotometer, which in the NIR is the result of the molecular vibrations of boundaries C-H, N-H, and O-H. The near-infrared spectra consist of the fundamental molecular absorptions, generally overlapping. After spectra acquisition, we process our data through the application of sophisticated statistical approaches like multivariate techniques for either regression or classification purposes. A prediction and a classification model is built to predict the internal quality and to discriminate tomatoes, respectively. The performance of models is being evaluated.

We expect that the results of the research will confirm the capability to predict internal quality and discriminate tomatoes obtained with low agronomic input, increasing the available tool for consumers and the authentication tools for growers.