Partnerships
The R & D Department Green Has Italia, firmly believes that interdisciplinarity and contact with the academic and scientific world, are key to achieving the goals proposed. The main research projects see the collaboration of important Italian organizations, which are briefly listed below:
Department of Life Sciences and Systems Biology, UNIVERSITY OF TURIN
Chemical characterization of high added value matrices, biochemical studies, and molecular biology, aimed at understanding bioactive molecule richness, the mechanism of action and the effectiveness of innovative prototypes.
Chemical characterization of high added value matrices, biochemical studies, and molecular biology, aimed at understanding bioactive molecule richness, the mechanism of action and the effectiveness of innovative prototypes.
Department of Agricultural and Environmental Sciences, UNIMI-UNIVERSITY OF MILAN
Molecular biology studies and activation of biochemical processes in plants subjected to abiotic type stress and treated with innovative prototypes.
Molecular biology studies and activation of biochemical processes in plants subjected to abiotic type stress and treated with innovative prototypes.
Department of Life Sciences and Systems Biology, UNIVERSITY OF TURIN
Plant-microorganism interactions: impact of microbial inoculants on root-associated microbiota in high value crops.
Plant-microorganism interactions: impact of microbial inoculants on root-associated microbiota in high value crops.
Department of Agricultural, Forestry and Food Sciences, UNITO – UNIVERSITY OF TURIN
Nutritional solution study in NGS soilless systems to reduce nitrate content on leaves.
Nutritional solution study in NGS soilless systems to reduce nitrate content on leaves.
PFC – Pharma&Food Consulting
Rheological studies of formulation stability.
Rheological studies of formulation stability.
D’Alesio&Santoro
Applied variable spectrum LED technology for applications to optimize experimental growth environments.
Applied variable spectrum LED technology for applications to optimize experimental growth environments.