The evolution of human society generates a number of problems such as: population growth, food and limited resources, climate change. As a result, the need to increase agro-industrial production and its quality increases. These issues need to be analyzed and addressed through a cross-disciplinary approach to problem families. Based on the data resulting from the research in the biology laboratory of USM, a data model is elaborated. It is an integrated collection of concepts needed to describe the data, the relationships between them and the existing constraints on the data of the analyzed system. The implementation of this model is done by creating a graph database using the Neo4j DBMS . The initial objective of this database is to obtain the necessary knowledge on the influence of certain compounds on the development of plants and their degree of influence. Graphs are created to answer important questions in the field. The data model has the following components: nodes, labels, relationships, and properties: • Nodes and associated labels: Proteins, N2, P2, Root length, weight 100 grains, P2O5, S1 , S2 , S3 , Control, Prep1 , Prep2 . • Identifying connections (relationships) between entities: Contains, Measures, Weighs. The implementation of the data model in the Neo4j DBMS is done through the Cypher language. Example of realization of entities: Varieties (S1) and Compounds (P1). create (S1: Varieties {variety: 'S1'}), (Prep1: Compound {prep: 'Prep1'}) An instruction is made to create the relationship " Untreated " between nodes of variety " S1 " and " Control (m) ": match (s1: Variety), (m: Treatment) where id (s1) = 2 and id (m) = 1 create (s1) - [rel: Untreated] -> (m) return s1, m