Applications

Social and economic impacts of the Project are related to the potential reduction of agricultural inputs with increased sustainability of the production and reduced impact for the environment, ensuring high-quality crop to the consumer and reducing the food losses. The added information on crop history and the marketing strategies will allow to sustain and diffuse the use of LIP, creating a virtuous mechanism which will positively affect further farmers and consumers choices. Moreover, continuous quality monitoring is valuable to enable longer time of transportation, exploiting special environmental conditions (temperature, humidity, modified or controller atmosphere) while checking the state of products, thus reducing food losses. Timely detection of quality changes makes it possible to reuse products through recycling processes and to reduce waste. Smart shelves can continuously check products and improve their management. Smart refrigerators can extend this check at consumers’ home to further prevent losses. Objective non-destructive and contactless quality evaluation can make objective and consistent the quality levels in the expanding online markets of fresh products.

Regarding the scientific impact, the WP1 will provide detailed evidences, supported by scientific data, of the effects of different growing techniques/systems on crop performance and sustainability of production processes in Mediterranean greenhouse conditions. Moreover, a wide range of management strategies, corresponding to different levels of availability of smart tools and competences, will be tested to provide further insight into the effectiveness of new tools. In particular, the project will provide updated data on the water/fertilizers use efficiency related to the case studies analyzed, with reference to the species, the different growing techniques, and the use of smart tools to support decisions. We also expect from the project the definition of cultivation protocols for the two studied species with clear relations between the cultivation management strategies and the impacts on the product measurable quality and the sustainability of the production process. ND methods will enable to discriminate product obtained with LIP on the base of spectral changes induced, providing useful information on produce quality for the consumer, and at the same time, for the farmers. This will be possible without the need for specific expertise and time-consuming laboratory analysis, but by simple locating a fruit close to a sensor. Moreover, ND prediction models for the internal quality of rocket and tomato will be provided. The study about ND and contactless CVS based techniques will provide further insights about the color correction process needed to obtain calibrated color images and about the correlation between measurable color characteristics and the quality parameters of interest. The project will identify the relevant colors for correcting the visual appearance of the product: this will provide proper guidelines about the colors to be used to design the graphical elements of the packaging (to avoid the placement of color-chart in the scene) and will develop and tune correction models that will focus on correcting especially the colors that are really present in the product at hand. The combination of these results is expected to enable a reliable and robust quality prediction and discrimination that would be applicable flexibly and extensively from harvest to transportation, during the shelf-life up to the refrigerator of consumers. The possibility to bring quality prediction and discrimination at smartphone level will be also studied. The study will also identify the colors characteristics that are more reliable and informative about the quality and will develop and verify statistical and machine learning methods that best model their functional correlation with the parameters of interest for each considered product.

Finally, the results of WP3 will allow identifying the impact on producer income coming from LIP practices and ND technologies. Measuring consumer preferences will depict the impact of technology on potential marketing and certification strategies. In case the premium price consumers are willing to pay is significantly high, there is room for the technological transfer and the scale-up of those LIP practices and ND based certification. Consumer segmentation is going to identify the market niche of consumers that recognize quality throughout the impact of LIP. Investors and producers, therefore, could better target their communication strategies in order to promote their differentiated production based on ND methods certification. Impacts of start-ups and new business are thus expected to be positive as well. The possibility to have high acceptance of information on consumers determines future perspectives for the idea of quality assurance in the fresh produce sector.