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      Examining the production amount of milk and dairy products using network analysis in Turkey

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          Abstract

          Abstract Among the sub-branches of the livestock industry in Turkey, milk and dairy product sector is one of the most active production areas. It is essential to examine the supply structure of the milk and dairy product sector and reveal the relations between the production amounts of the products to understand the overall structure of the sector. We determined the pattern network structures based on the amount of raw cow milk entering the industry and the production amounts of six products between 2010/01 and 2020/09. In addition, we studied the product-based development of the sector. The findings obtained from the network analysis of the production amounts of milk and dairy products indicated a relationship between the products and their interactions with each other. The amount of raw milk entering the production process was located in the center and displayed a positive relationship with all products it interacted with. The amount of raw cow milk entering the production process and the amount of cow cheese produced affected other products included in the network. In addition, among the products produced, the production amounts of ayran and yogurt exhibited the highest correlation coefficient with a moderate positive correlation value (0.609). The resulting social network graph provides important clues about the general production understanding of Turkey’s dairy sector and consumer preferences in the market.

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          Collective dynamics of 'small-world' networks.

          Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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            Graph drawing by force-directed placement

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              A faster algorithm for betweenness centrality*

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                Author and article information

                Journal
                cta
                Food Science and Technology
                Food Sci. Technol
                Sociedade Brasileira de Ciência e Tecnologia de Alimentos (Campinas, SP, Brazil )
                0101-2061
                1678-457X
                2022
                : 42
                : e125821
                Affiliations
                [01] Burdur orgnameMehmet Akif Ersoy University orgdiv1Faculty of Veterinary Medicine orgdiv2Department of Animal Health Economics and Management Turkey
                [03] Kastamonu orgnameKastamonu University orgdiv1Faculty of Veterinary Medicine orgdiv2Department of Animal Health Economics and Management Turkey
                [04] Konya orgnameSelçuk University orgdiv1Faculty of Veterinary Medicine orgdiv2Department of Animal Health Economics and Management Turkey
                [05] Konya orgnameSelçuk University orgdiv1Faculty of Veterinary Medicine orgdiv2Department of Biostatistics Turkey
                [02] Elazıg orgnameFırat University orgdiv1Faculty of Veterinary Medicine orgdiv2Department of Animal Health Economics and Management Turkey
                [06] İzmir orgnameİzmir Katip Çelebi University orgdiv1Faculty of Medicine orgdiv2Department of Biostatistics Turkey
                Article
                S0101-20612022000100945 S0101-2061(22)04200000945
                10.1590/fst.125821
                527f4dde-75fa-4856-bd62-071e356af8e5

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 28 November 2021
                : 17 January 2022
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 53, Pages: 0
                Product

                SciELO Brazil

                Categories
                Original Article

                raw milk,dairy products,dairy industry,network analysis,Turkey

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