The dynamic North Florida dairy farm model: A user-friendly computerized tool for increasing profits while minimizing N leaching under varying climatic conditions

Victor E. Cabrera, Norman E. Breuer, Peter E. Hildebrand, David Letson

Research output: Contribution to journalArticle

20 Scopus citations


This paper describes the computer implementation of the Dynamic North Florida Dairy farm model (DyNoFlo Dairy). The DyNoFlo Dairy is a decision support system that integrates nutrient budgeting, crop, and optimization models created to assess nitrogen (N) leaching from North Florida dairy farm systems and the economic impacts resulting from reducing it under different climatic conditions. The decision support system, based on Excel® and Visual Basic® software, responds to dairy-specific environmental (climate and soils) and managerial characteristics (livestock management, waste management, crop systems management) and can be used to study the economic and ecologic sustainability of these systems. The DyNoFlo Dairy model is a dynamic adaptation of the framework "balance" of nutrients in dairy farms, commonly used in Florida. The DyNoFlo Dairy model incorporates Markov-chain probabilistic simulation of cow-flows and crop simulation for historical climatic years El Niño southern oscillation (ENSO), automated optimization of managerial options, participatory modeling, and user friendliness. This paper discusses the model components and its computer implementation in a user-friendly application. The model was parameterized for conditions found in North Florida dairy farm systems. It is intended to be a tool for producers, regulatory agencies, and extension services, and because of that, participatory and interdisciplinary work was pursued during model creation, calibration, and validation. A case study for a synthesized North Florida dairy farm using the DyNoFlo Dairy model found substantial differences in the N leaching for different ENSO phases and other managerial factors; and the possibility of decreasing N leaching up to 25% while still maintaining profitability levels.

Original languageEnglish (US)
Pages (from-to)286-308
Number of pages23
JournalComputers and Electronics in Agriculture
Issue number2
StatePublished - Nov 2005



  • Climate
  • Dairy
  • Florida
  • Leaching
  • Markov chains
  • Optimization
  • User friendly

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Forestry
  • Computer Science Applications

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