Environmental performance comparison among a vis/NIR benchtop device, a cost-effective vis/NIR portable device, and wet-chem analyses for the assessment of grape (Vitis vinifera L.) quality parameters

Grape quality composition at harvest is one of the most important factors that determine the future quality of the wine. By measuring grape quality parameters, it’s possible to determine the optimum harvest timing, ensuring the production of high-quality wines. These parameters are usually obtained through traditional analytical methods, the wet-chem analyses, which require samples to be sent to geographically distant laboratories and waiting a long time before achieving results. All these procedures imply the use of chemicals. As a solution to destructiveness and slowness problems, optical methods can be suitable alternatives to monitor the technological maturation of grapes. The aim of the work is to evaluate and compare the environmental impact of three different types of analyses carried out to evaluate technological parameters (total soluble solids content, pH, and total acidity) using three different approaches: the wet-chem method, an optical method using a benchtop vis/NIR device, and a second optical method using an innovative and cost-effective vis/NIR prototype. The Life Cycle Assessment (LCA) methodology was used to identify the most sustainable solution and propose actions to reduce the impact along the wine supply chain in a "from-cradle-to-grave" approach. The functional unit was identified by the execution of the analyses necessary to obtain the three technological parameters. Results demonstrate how, first, the wet-chem analyses should be carried out in triplicate to obtain technological parameters, while for the vis/NIR benchtop and the innovative prototype, the three quality parameters can be obtained with only one single analysis. Moreover, the optical analysis carried out with the cost-effective prototype results in a solution with a lower impact and is 3.2 times more sustainable than the wet-chem analysis. If an innovative optical prototype can be identified as the best solution, its performance may not be so reliable in obtaining precise and trustworthy results. For this reason, a performance factor was included, and results have been normalized; nevertheless, results confirmed what was obtained in the previous scenario. In conclusion, the study demonstrates how innovations in agriculture and the development of smart optical solutions could provide advantages both in monitoring the quality of agri-food products in an industry 4.0 approach and in proposing green solutions.