CHEMICAL ENGINEERING TRANSACTIONS VOL. 45, 2015 A publication of The Italian Association of Chemical Engineering www.aidic.it/cet Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Sharifah Rafidah Wan Alwi, Jun Yow Yong, Xia Liu Copyright © 2015, AIDIC Servizi S.r.l., ISBN 978-88-95608-36-5; ISSN 2283-9216 DOI: 10.3303/CET1545145 Please cite this article as: Schimith C.D., Scavarda A., Bittencourt S., Santos M.B., Vaccaro G.L.R., Gabbi A., Weise A.D., 2015, The system dynamics use for measurement of the results of technological applications for genetic improvement in milk supply chain, Chemical Engineering Transactions, 45, 865-870 DOI:10.3303/CET1545145 865 The System Dynamics Use for Measurement of the Results of Technological Applications for Genetic Improvement in Milk Supply Chain Cristiano D. Schimith a , Annibal Scavarda* ,b , Sandro Bittencourt a , Marindia B. Santos c , Guilherme L. R. Vaccaro a , Adriana Gabbi c , Andreas D. Weise c a University of the Sinos Valley, São Leopoldo 93022-000, Brazil b Federal University of the State of Rio de Janeiro, Rio de Janeiro 22290-240, Brazil c Federal University of Santa Maria, Santa Maria 97105-900, Brazil annibal.scavarda@unirio.br The Brazilian economy is based on natural resources, classified as an exporter of commodities, with an emphasis on milk production in the last decade, represented by the ranking of having the second largest dairy herd in the world. In this scenario, this paper aims to use the system dynamics to simulate scenarios and to measure financial results related to production that milk supply chain gets by using genetic improvement technology. Methodology initially discusses qualitative aspects, identifying members, links, and attributes of supply chain management researched, which allowed to describe the systemic structure and to identify the variables used to design scenarios with and without the use of genetic technologies. The model was tested in a real situation, in a country state that has adopted these technologies. The final result of the study showed that, in the scenario of use of genetic improvement technologies, the variables production (liters), revenues and net income increased by 45 % and 53 %, comparing with non-use scenario. The model showed to be effective to simulate the deployment of genetics in dairy herd. 1. Introduction Brazil, an exporter of commodities (Bianconi et al., 2013), has its economy based on natural resources. With the second largest dairy herd in the world, it produces more than 29 Mm 3 of milk, with global representation in the growth of dairy exports (Picinin, 2013). The author also states that this number may be even more representative in 2020, reaching 38.2 Mm 3 . According to Instituto Brasileiro de Geografia e Estatística. (IBGE, 2009), the annual growth rate is higher than the growth rate of the Brazilian population, which also indicates an increase in consumption of dairy products. According to Petrus et al. (2009), in Brazil often the quality of the raw material is low, but with genetic improvement raw material could be better. The increase in national milk production implies additional income and employment, improving the well- being of rural families (Delatoura et al., 2014). Subsistence farming increases the economic development in rural communities. The state of Rio Grande do Sul has the second largest Brazilian milk production, behind only the Southeast region (IBGE, 2009). The climate, similar to the European, influences on productivity (Picinin, 2013). Taking advantage of this increased production, dairy companies are diversifying their products, increasing their market share. To increase production the partnerships between milk producers and the beneficiary industries promote the sector of economic growth (EMBRAPA, 2013). In this scenario and taking advantage of future research suggestions by Pettersson and Segerstedt (2013), who suggested a genetic gain analysis in the production chain, and Su and Lei (2008), who considered that economic returns evaluations should be done in productive chain, this research aims to study one of the milk production chain links, the first link, known as “producti on.” In this way, we used system dynamics to develop a tool that enables small farmers who use livestock for milk production to simulate scenarios on the use of genetic improvement through in vitro production.