Modeling and Simulation for Decision Support in Precision Livestock Farming

Niloofar, Parisa; Lazarova-Molnar, Sanja; Francis, Deena P.; Vulpe, Alexandru; Suciu, George; Bălănescu, Mihaela

doi:10.1109/wsc48552.2020.9383975

Cited by 5 publications

(7 citation statements)

References 55 publications

(31 reference statements)

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“…Enhanced animal welfare directly impacts outcomes in livestock production, such as meat, milk, and eggs, as healthy animals yield higher quality and quantity of products. Additionally, optimizing animal welfare contributes to reducing emissions intensity in the production of livestock products, benefiting both farmers' incomes and environmental sustainability [15,40]. Nutrition is a fundamental aspect of animal welfare, evaluated through the Five Domains Model, which emphasizes the importance of providing animals with appropriate feed and water [36,41].…”

Section: Decision Support Tools In Livestock Feed Formulationmentioning

confidence: 99%

Animal Feed Formulation—Connecting Technologies to Build a Resilient and Sustainable System

Akintan,

Gebremedhin,

Uyeh

2024

Animals

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The unprecedented challenges presented by the increase in global population have placed substantial demands on the livestock industry for human nutrition, necessitating heightened animal productivity and leading to an increased demand for natural resources to produce animal feed. Feed producers are leading the charge, consistently refining formulations to adapt to the evolving needs of livestock, driven in part by the cost of over 50% associated with feed production. This paper critically analyses the pressing issues within feed formulation, addressing the requirement for environmentally sustainable practices amidst the challenges of climate change. The exploration extends to how advanced decision support tools can enhance formulation techniques and profitability and contribute to environmental sustainability. Through an in-depth review of current feed formulation technologies, encompassing their applications and limitations, this study aims to enhance the existing knowledge base. Additionally, we examined future trends, highlighting the essential role of connecting technologies to establish a resilient and sustainable system. The emphasis is on the potential of formulation techniques to positively impact the environment and enhance the overall quality and performance of the animals. This paper provides actionable insights to improve animal production by examining feed formulation models and decision support tools. The anticipated outcome is a more informed and sustainable decision-making process, addressing the multifaceted challenges confronted by the livestock industry and making contributions to global efforts in climate change mitigation and environmental stewardship in animal production agriculture.

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Section: Decision Support Tools In Livestock Feed Formulationmentioning

confidence: 99%

Animal Feed Formulation—Connecting Technologies to Build a Resilient and Sustainable System

Akintan,

Gebremedhin,

Uyeh

2024

Animals

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“…A wide variety of flexible models for simulation of weather (Maher and Earnshaw, 2022), crop growth (e.g., Berre et al, 2015), and livestock growth (Teleken et al, 2017;Niloofar et al, Frontiers in Environmental Science frontiersin.org 2020) have been developed and validation procedures have been established. In general, these growth models can determine the inputs and yields per unit (typically of land area) for a given biological organism and set of production practices.…”

Section: Simulation-based Random Outcomesmentioning

confidence: 99%

Agricultural resource and risk management with multiperiod stochastics: A case of the mixed crop-livestock production system in the drylands of Jordan

Boussios

Preckel²,

Yigezu³

et al. 2022

Front. Environ. Sci.

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Generally, agricultural production involves several challenges. In the drylands, it is further complicated by weather-related risks and resource degradation. In this paper, we present a case study of the mixed crop-livestock production system in Jordan. To better capture the nature of response farming in the drylands, we develop a methodology for using crop simulation models to directly generate data for optimizing production practices of an integrated crop-livestock producing household in a dynamic stochastic context. The approach optimizes producer’s adaptations to random events, such as weather, which are realized throughout the planning horizon. To ensure the sustainability of the optimized production decisions, long-term valuations of end of horizon soil attributes are included in the objective function. This approach endogenizes the tradeoff between short-and long-run productivity. Model results show that due to the limited natural resource endowments and financial liquidity constraints of the typical farm households in the study area, we find these households have limited options. To optimally respond to weather conditions during the production season, better manage risk, and achieve improvements in soil attributes, a typical household would need larger farm size, larger flock, and better financial liquidity than it currently commands. Like all such models, the farm household model used in this paper is not suitable for drawing policy implications. Therefore, targeted analysis using appropriate sectoral or economy-wide models will be needed in the future to identify and test the efficacy of different policy and institutional interventions including land consolidation, establishment of producer and marketing cooperatives, access to financial services including agricultural credit, and crop insurance in expanding the resource base of farmers—thereby positioning them for higher earnings, ensuring soil conservation, and enhancing the sustainability of the production system.

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“…To achieve our objectives, we propose finding answers to the following research questions: (1) What are the types of studies and approaches used in simulating beef production systems? And (2) what are the strategies used to simulate the growth of an animal?…”

Section: Introductionmentioning

confidence: 99%

“…To make informed decisions, we need to understand how the system works and the potential impacts of intervention to the production process. Simulation models, which provide the framework and tools to describe and understand the system [ 2 ], could be useful to evaluate the impacts of any decisions and hence help guide appropriate actions needed to improve the production.…”

Section: Introductionmentioning

confidence: 99%

Simulation Approaches Used for Management and Decision Making in the Beef Production Sector: A Systematic Review

Awasthi,

Morshed,

Williams

et al. 2024

Animals

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Simulation models are used in various areas of agriculture to better understand the system and assist in decision making. In the beef production sector, a variety of simulation research focusing on various dimensions of the system is available. However, an overview of the available research is lacking. Therefore, a systematic review was conducted to provide an overview of simulation studies of beef production and create an understanding of the simulation approaches used. Scopus, Web of Science, and ProQuest Central research databases were used to search the relevant articles, with the last search conducted in June 2023. Studies that developed or used simulation strategies and used beef cattle as a primary focus of the study were included. The 105 studies included in this review were examined thoroughly to record the authors, year of publication, country of study, type of study, focus area of the study, simulated scenarios, validation methods, and software programs used. There has been growing research interest in simulating beef production systems worldwide, with most studies conducted in North America and Europe. Among these studies, the majority (84.76%, n = 89) are biophysical or bioeconomic study types and use deterministic approaches (n = 42). Additionally, most studies have a whole-farm scope (38.09%, n = 40) and focus on productivity (51.43%, n = 54). Since only less than half of the studies mentioned the validation techniques and software programs used, there is a need to improve the availability of this information to ensure that the models are adopted effectively in decision making.

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Modeling and Simulation for Decision Support in Precision Livestock Farming

Cited by 5 publications

References 55 publications

Animal Feed Formulation—Connecting Technologies to Build a Resilient and Sustainable System

Animal Feed Formulation—Connecting Technologies to Build a Resilient and Sustainable System

Agricultural resource and risk management with multiperiod stochastics: A case of the mixed crop-livestock production system in the drylands of Jordan

Simulation Approaches Used for Management and Decision Making in the Beef Production Sector: A Systematic Review

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