ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Modeling complex problems with system dynamics: applications in animal agriculture1
| Autor: | Michael E. Van Amburgh, Andre Rozemberg Peixoto Simões, Paul Andrew LaPierre, Charles F. Nicholson |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Rumen
Systems Analysis Computer science Process (engineering) Supply chain Complex system Models Biological 03 medical and health sciences Genetics Animals Productivity Featured Collection 030304 developmental biology 0303 health sciences Scale (chemistry) Data Science 0402 animal and dairy science 04 agricultural and veterinary sciences General Medicine Replicate 040201 dairy & animal science System dynamics Dairying Risk analysis (engineering) Food systems Animal Nutritional Physiological Phenomena Cattle Female Animal Science and Zoology Brazil Food Science |
| Zdroj: | Journal of Animal Science. 97:1903-1920 |
| ISSN: | 1525-3163 0021-8812 |
| DOI: | 10.1093/jas/skz105 |
| Popis: | Many problematic outcomes in agricultural and food systems have important dynamic dimensions and arise due to underlying system structure. Thus, understanding the linkages between system structure and dynamic behavior often is important for the design and implementation of interventions to achieve sustained improvements. System dynamics (SD) modeling represents system structure using stock-flow-feedback structures expressed as systems of differential equations solved by numerical integration methods. System dynamics methods also encompass a broader methodological approach that emphasizes model structural development and data inputs to replicate one of a limited number of problematic behavioral modes, anticipates dynamic complexity, and focuses on feedback processes arising from endogenous system elements. This paper highlights the process of SD modeling using 2 examples from animal agriculture at different scales. A dynamic version of the Cornell Net Carbohydrate and Protein System (CNCPS) that represents outcomes for an individual dairy cow is formulated as an SD model illustrates the benefits of the SD approach in modeling rumen fill and animal performance. At a very different scale, an SD model of the Brazilian dairy supply chain (farms, processing, and consumers) illustrates the country-level impacts of efforts to improve cow productivity and how impacts differ if productivity improvement occurs on small farms rather than large farms. The paper concludes with recommendations about how to increase awareness and training in SD methods to enhance their appropriate use in research and instruction. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|