MANAGEMENT SYSTEMS TO IMPROVE THE ECONOMIC AND ENVIRONMENTAL SUSTAINABILITY OF DAIRY ENTERPRISES.

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1016355
• Multistate No.: NC-_old2042
• Project Start Date: Oct 1, 2018
• Project End Date: Dec 31, 2019
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIV OF WISCONSIN
21 N PARK ST STE 6401
MADISON,WI 53715-1218

Performing Department
Biological Systems Engineering

Non Technical Summary
The specific aim of this multidisciplinary, multistate, and integrated project is to promote more economically and sustainable dairy farm production systems. Heat stress of dairy cows is an ever-increasing menace to dairy production because of global warming and the increasing internal heat production of high yielding cow. Heat stressed cows produce less milk, and they are susceptible to diseases, and have impaired fertility, all of which have a large economic toll. Dairy producers need desperately heat abatement technologies and management strategies that are economically feasible. It is not known what the optimal ventilation technologies and management strategies are for specific types of dairy farms. Farmers are making multi-million dollar investments on heat abatement technologies without knowing their effectiveness. It is imperative to provide science-based information to assist dairy farmers in making the best decisions that optimize cow comfort at the least cost investment. We propose to help in this area by studying the most promising cooling technologies on modern commercial dairy farms by using state-of-the-art fluid dynamics knowledge together with innovative measurements, which will be related to cow behavior and performance, and then incorporated into a dynamic, interactive economic model that can predict the best economic outcomes according to farm specific conditions. Our ultimate goal, beyond the time-scope of the specific project, is to develop a decision support system tool that aids farmers in the decision-making of investment in cooling abatement technologies.

Animal Health Component

100%

Research Effort Categories

Basic

0%

Applied

100%

Developmental

0%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
402	3499	2020	60%
307	3499	3100	40%

Knowledge Area
307 - Animal Management Systems; 402 - Engineering Systems and Equipment;

Subject Of Investigation
3499 - Dairy cattle, general/other;

Field Of Science
2020 - Engineering; 3100 - Management;

Keywords

dairy housing

heat stress

computational fluid dynamics

economic analysis

Goals / Objectives
Evaluate whole farm system components and integrate information and technology to improve efficiency, profitability, environmental sustainability and social responsibility.

Project Methods
With little consensus among designers currently working in the industry, the primary objective of this proposal is to evaluate the state of the heat abatement technology in its current form in the Wisconsin dairy industry and to do so by bringing to bear expertise in the fields of CFD, cow behavior and economic modeling. The use of modeling will save producers and builders from repeating design mistakes as it will allow us to ask questions that would be difficult or impossible to answer if an actual facility had to be built to answer them.Our long-term goal is to establish a design standard for large-scale barns and provide customizable decision support tools for improved economic decision-making. Our approach will include the following specific steps: (i) work with current building designers to identify current design trends in an effort to develop optimally designed mechanically ventilated and hybrid (mechanically and naturally ventilated) barns, (ii) visit typical mechanically ventilated barns to perform animal and ventilation measurements in order to determine those design characteristics that are preferred by cows and those which are not, (ii) create a design platform to facilitate CFD models, one based on design trends and actual observations, (iv) determine the actual costs associated with the construction, maintenance and running a ventilation system that can create optimal ventilation models at the least cost, and (v) conduct a comprehensive economic analysis.Specific goals: The specific goals are to prioritize 4 design traits for mechanical ventilation systems:1). A way to provide fast moving air in the cow's resting space (>7 km/hr or 4.5 mph).2). A system that works optimally across all 4 seasons - providing adequate air changes per hour during the winter to prevent pneumonia and sufficient cooling in the summer to prevent heat stress.3). A flexible design (hybrid) to allow for switching between natural and mechanical ventilation between seasons.4.) An analysis of the economic factors important to the design and maintenance of the system to provide optimal performance at least cost according to farm specific conditions.Therefore, the proposed tasks are to (i) develop a dynamic, cow-level, stochastic, dairy herd simulation model capable of quantifying the economic, environmental, and health impacts of various housing facilities, heat abatement technologies and management strategies, and (ii) achieve the extension goal, supported by developed modelling, using lessons learned during the project's CFD research phase and via our connection with the dairy industry and dairy producers; that is, we intend to disseminate all project findings and promote housing facilities and management strategies that can achieve better farm-specific heat abatement.Significant questions, yet to be answered, have arisen regarding actual airflow patterns, temperature gradients and cow environmental preferences within mechanically ventilated barns. In addition, CFD work requires boundary conditions, and the outcomes of the computational simulations must be validated in comparison with the experimentally measured data. Therefore, we propose to study 2 mechanically ventilated cow barns in order to evaluate cow behavior and inform our models using real time data collected from barns that are currently operational. We will choose one barn laid out in typical cross-vent design and one in typical tunnel-vent design. The herds will be selected based on referrals to the Dairyland Initiative program.Based on the 3D model facilities created, a series of virtual dairy facilities will be built for computational simulations. These facilities should consist of walls with measured seasonal boundary conditions. The CFD model's boundary conditions included walls with appropriate emissivity and the inlet and outlet air speed, temperature, evaporative cooling, and relative humidity conditions. Both radiation and convection within the animals' hair layer will be developed in the animal occupied zone (AOZ) model, and evaporation and sweating may also be considered. The airflow will be considered turbulent, and the flow patterns will be found by using the realizable k-ε turbulence model.We propose to assess and evaluate every economic factor associated with the design, construction and operation of a modern dairy housing and cooling system. We will also project these economic factors across time and with respect to the uncertain conditions of weather, prices, and, importantly, the impacts that the studied cooling systems may have on such dairy-farm performances as animal productivity and well-being. Cabrera's team will first develop a next-event daily dynamic stochastic Monte Carlo simulation model of a dairy herd's dynamics (cow-flow, herd structure) with emphasis on cow-specific heat impacts. The model will be capable of using actual cow-level characteristics and follow each individual cow (and her possible replacements), through all possible stochastic events for a determined period of time (e.g., five years) to assess the economic, environmental (i.e., water and energy usage), and health impacts of various heat abatement management strategies.Specifically, individual cows will be simulated as if living through stochastic events within reproductive cycles. A dataset of cows in a herd and their current characteristics (i.e., lactation number, number of days postpartum, reproductive status, milk production, etc.) will be loaded from actual farm records. Then, for each cow, possible events in the future will be stochastically scheduled. All of these factors will affect and be affected by the conditions of heat stress that will be communicated by the CFD model.The focus will be on the heat stress exposure, tolerance, and impact and its alleviation that can be achieved by abatement technologies and management strategies. The spatial-temporal stochastic component will be a novel component for this livestock model. In addition to simulating the bio-physiological stochastic characteristics of a cow existing in a determined time period, it will be important to simulate, stochastically, the location and corporal position of the cow within the facilities. We have evidence indicating that the cooling abatement is greatly variable within a facility according to the technology used, and, therefore, the heat stress impact on a particular cow will depend, among other factors, on her location and corporal position. Also, the heat stress a cow suffers can have both immediate impacts (e.g., decrease in productivity) and more long-term effects (e.g., delayed calving interval); consequently, the model must identify each cow and follow her through successive lactations according to the cow exposure and tolerance to heat stress.The goal of the economic model is to inform dairy farm managers of the investment-benefit of heat abatement technologies and strategies according to farm specific conditions. The model will be developed to receive farm and cow specific information (e.g., herd reproductive performance or cow genetic potential) and based on these project the farm specific impact of different heat stress scenarios. The economic model will be used to perform virtual applied research on which heat stress abatement management technologies are more promising. Ultimately, the economic model will become the core baseline of future development of a decision support tool for use and application in dairy farms.

Progress 10/01/18 to 12/31/19

Outputs
Target Audience:The target audiences are researchers, consultants, practitioners, and dairy producers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?This project is effectively used as a series of topics in senior capstone design projects with one-on-one work and collaborative group tasks in conjunction with (1) design of modern dairy barns, (ii) utilization of state-of-the-art computational tools (CFD), and (iii) development and integration of Internet Technologies such as Internet of Things (IoT) and real-time monitoring of microenvironments. Additionally, our team presented a number of papers at international conferences, and the significant advances have been published in renowned refereed journals. How have the results been disseminated to communities of interest?These new findings and design recommendations have been made available to dairy producers in written form and on the Dairyland Initiative web pages by means of an outreach vehicle, which now has over 3,000 registered users worldwide (http://thedairylandinitiative.vetmed.wisc.edu). What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? This project developed computational fluid dynamics (CFD) models that can provide clear pictures of how newly designed dairy housing barns will perform in a real-life setting. What is more, these state-of-the-art modeling tools can accomplish their task much more cheaply and quickly than could the trial-and-error method because they enable engineers to evaluate a proposed ventilation system before it is installed. To validate the models' reliability, the researchers, working in collaboration with a group of commercial dairy farmers, conducted a series of coordinated computational and experimental studies. Considering the advances in CFD models and the capabilities they make available, we can now further develop a Machine Learning based CFD simulator that nonprofessional users would be able to afford and operate. Additionally, the team developed a minimally invasive method that involves using implantable biosensors with radio-frequency identification (RFID) capabilities. We successfully tested in regard to its ability to continuously measure the subdermal temperature of a dairy cow, and the outcomes could be effectively used to assess the CFD outcomes to mitigate heat stress of dairy cows. This study's findings will serve as the step toward any future research and development that may take place in the field of precision agriculture, especially research that considers even smaller and more practical electronics. We have accomplished the following three areas. (1) Evaluation of Optimal Airflow and Baffle Locations in Large-scale Mechanically-Ventilated Dairy Houses using CFD Baffles are often installed in mechanically cross-ventilated barns to combat heat stress by enhancing the cooling effect produced by the barn's design. How effectively these baffles operate during warm weather often depends on where each baffle is located and at what angle it is set. Currently, their location and orientation are determined primarily according to the personal experience of the contractor in charge of installing the barn's ventilation system. This study seeks to quantify the extent to which the location and orientation may affect the efficiency of the installed baffles. Computational fluid dynamics was used to create a three-dimensional model of a typical low-profile, cross-ventilated dairy barn. Differences were evaluated using both heat transfer and heat stress index (the Equivalent Temperature Index for Cattle - EITC). The results obtained from the tested scenarios indicated that installing the baffles in the animal occupied zone (AOZ) could indeed increase the air velocity (from less than 0.5 m s-1 to around 3 m s-1 once baffles were in place), and could also greatly increase (by 21.1% to 50.9%) the amount of heat removed, while reducing the EITC by ~6 oC. In comparisons between the most commonly used scenario (in which baffles were installed vertically in the middle of the resting area), and the other with-baffle-scenarios, the rate at which heat was removed from the cows varied by -3.0% to 2.6%, with the maximum difference being 172.4W. However, the commonly used scenario produced no significant improvement. The results obtained provide a more reliable reference for agricultural engineers, consultants, and dairy producers engaged in designing large-scale dairy barns. (2) Understanding Microenvironments within Tunnel-ventilated Dairy Cow Freestall Facilities using CFD The objective of this study was to determine the correlation between ventilation rates occurring in a barn designed to house dairy cows and the microenvironments that develop within the cow pens. To do this, a CFD model of a tunnel-ventilated template barn was developed in accordance with the latest barn and ventilation design recommendations. For validation, the tunnel template model was benchmarked by comparing the outcome of a corresponding CFD model with microenvironment data collected experimentally in an actual tunnel-ventilated barn. The groups of cows inside the barn were modelled as an animal occupied zone through a porous-media with their presence characterized according to their animal densities: no-density (empty pen), low-density, and high-density. To distinguish between designs, the resting area with velocity magnitudes below 1 m s-1 was compared to the total resting area, and their ratio was defined as the "critical resting area." Increasing the barn's ventilation rate produces diminishing returns; 40 air changes per hour is the ventilation rate when airspeed could be augmented by local components, such as circulation fans placed over the stalls. Because approximately 20 % of an average farmstead's electricity is used to power its ventilation system, this finding should present an opportunity to reduce energy costs associated with ventilation while still meeting the cows' physiological needs. (3) Implantable Biosensor and Wearable Scanners to Monitor Dairy Cattle Heat Stress in Real-Time In conjunction with CFD modeling, the team also developed a method to integrate information technology to monitor heat stress. That is, a minimally invasive method that involves using implantable biosensors with radio-frequency identification (RFID) capabilities was tested in regard to its ability to continuously measure the ear base subdermal temperature of a dairy cow. An increase in subdermal temperature, reflective of vasodilation, could, we surmised, potentially detect the level of heat stress. This could provide a better way to control dairy-barn cooling systems, which are commonly controlled solely on the basis of either air temperature or some other such non-ideal environmental parameter. Concurrent with the development of new technologies, the Long-Range (LoRa) wireless communication protocol and a concept known as the "Internet of Things" (IoT) were utilized to extract temperature data from the base of a cow's ear every 30 seconds (real-time). To test the method, an implant temperature sensor was injected, at the base of the ear, into three Holstein cows, and each was equipped with a wearable RFID scanner (mounted on an existing collar) for five days during a summer season in Wisconsin. The primarily objective was to determine the efficacy of using implantable biosensors and wireless communication to monitor the heat-stress levels experienced by these dairy cows, in real-time, over the five days. Overall, the recorded subdermal temperature data obtained from implantable biosensors closely corresponded to the changes that occurred in core (vaginal) body temperature, and the developed wireless communication nodes successfully measured and monitored the temperature readings in real-time. Each cow showed different heat stress responses despite the fact that all three were in virtually the same location and subject to the same temperature-humidity index (THI) throughout the study. The study also found that the temperature readings achieved by the implantable biosensor began to more closely match in value the corresponding core body temperature (CBT) readings as THI increased. Furthermore, the CBT of a cow could be reasonably predicted, by applying a machine-learning (ML) algorithm on measured subdermal-temperature and THI data. The present study also found that the dairy cows tested displayed no obvious adverse effects that could have resulted from the biosensor implanted at the base of the ear. This study's findings serve as the first step towards any future research and development that may take place in the field of precision agriculture, especially research that considers even smaller and more practical electronics.

Publications

• Type: Journal Articles Status: Published Year Published: 2019 Citation: Zhou B, Xiaoshuai Wang, Mario R Mondaca, Li Rong, Christopher Y Choi (2019) Assessment of optimal airflow baffle locations and angles in mechanically-ventilated dairy houses using computational fluid dynamics, Computers and Electronics in Agriculture, 165, 1-11.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Mondaca MR, CY Choi, NB Cook (2019) Understanding microenvironments within tunnel-ventilated dairy cow freestall facilities: Examination using computational fluid dynamics and experimental validation, Biosystems Engineering 183, 70-84.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Bo Zhou, Seunghyeon Jung, Xiaoshuai Wang, Mario Mondaca, 2019, Effects of Baffles on Airflow Patterns, Heat and Mass Transfer in Mechanically-ventilated Dairy Housing using Computational Fluid Dynamics. 2019 ASABE Annual International Meeting, Boston, MA.
• Type: Conference Papers and Presentations Status: Submitted Year Published: 2020 Citation: Seunghyeon Jung, Eka Sutandar, Hanwook Chung, Christopher Y. Choi, 2020 Assessment of Airflow Patterns, Heat and Mass Transfer at Cow-Level in Mechanically-ventilated Dairy Housing using Computational Fluid Dynamics, ASABE Annual International Meeting, Omaha, NE.
• Type: Journal Articles Status: Under Review Year Published: 2020 Citation: Hanwook Chung, Jingjie Li, Younghyun Kim, Jennifer M.C. Van Os, Sabrina H. Brounts, Christopher Y. Choi, 2020, USING IMPLANTABLE BIOSENSOR AND WEARABLE SCANNERS TO MONITOR DAIRY CATTLE HEAT STRESS IN REAL-TIME, Computers and Electronics in Agriculture.