Projects and Research

Nanosculpted silicon membranes for shape-based biological separations

Project summary: Dairy farmers contend with a broad array of pathogens in their efforts to produce high-quality milk. For example, almost 20 different microbes are known to cause mastitis, the most common disease of dairy cattle. These infections are often treated using broad spectrum antibiotics, which raises concerns of antibiotic resistance. Isolating and identifying specific culprits from small test samples will enable farmers to incorporate more focused treatment regimens with less productivity loss for their livestock. To achieve this goal, the project proposes to develop a nanofiltration system that can be customized to isolate microbial species. While techniques exist for the separation of particles by mass or size, they lack the precision to separate by shape. The project proposes a novel method to separate particles based on shape and size, using precision nanoporous membrane filters. This platform will provide a significant step forward in the ability to isolate pathogens and enable dairy farmers to more effectively manage the health of their herds.

Interactions of fibroblast growth factor and protein metabolism during the postpartum period in lactating dairy cows and their effect on animal health

Project summary: The immediate postpartum period in lactating dairy cattle is the time when cows are most vulnerable to metabolic disorders such as ketosis and fatty liver. These disorders often predispose the animal to additional diseases and may impair reproduction. A potential marker of metabolic distress and protein imbalance is fibroblast growth factor 21 (FGF21). The goal of this project is to investigate the relationship between FGF21, protein metabolism and reproduction during the early postpartum period in dairy cows. Samples will be collected to determine if increases in FGF21 are associated with negative protein balance, which in turn may delay ovulation. This study will provide undergraduate students the opportunity to gain experience in several research techniques and lay the foundation for future studies during this critical time period. Data from this work will improve the understanding of the early postpartum period and contribute to improvements in animal health, diagnosis and interventions.

Local virtual enclosures to enforce managed grazing

Project summary: Chris Wilson rotates his grazing dairy herd by manually moving lightweight fencing, which is cumbersome. Digital solutions for confining livestock exist, involving use of GPS collars. However, these systems are costly and over-designed for the end goal, which is merely to move the cattle through a grazing area. Therefore, we propose to investigate and develop “local” means to establish and enforce a virtual, progressive grazing area. We will pursue two approaches: moving a physical fence or objects; and moving a virtual fence using short-range wireless technologies. For the “virtual” option, some technologies under consideration are ultra-high frequency RFID and Bluetooth Low Energy (BLE) tags. Using beacons or readers, the animal’s rough location will be monitored, allowing it to be directed toward “acceptable” locations as determined by the farmer.

Bringing artificial intelligence to the dairy barn

Project summary: Farms have relied on human vision to observe and interpret animal behavior. As farm sizes increase and labor changes, it is more challenging to rely on human observations. The goal of this project is to design a modular, low-cost monitoring system using sensors, computer vision and artificial intelligence to assist Wisconsin dairy farmers with the health and welfare of their herd and grow their farm business. In the full version of the system, the smart cameras and sensors will observe and detect nutritional, behavioral, health and environmental activities that can impact animal welfare and wellbeing. Next, we will translate this visual information and sensor collected data into actionable insights that enable the farmer to make data-driven decisions to improve farm operations and animal health. The idea of using an artificial intelligence system for dairy farm management is not new, but existing systems are too expensive for many farmers. The outcome of this project will provide an opportunity for farmers to employ an affordable system and grow their business.

Changing agricultural land: Understanding impacts on southern Wisconsin’s dairy farms and rural communities

Project summary: As record numbers of small and mid-sized dairy farms have closed, agricultural lands are changing hands, often being converted out of agriculture or consolidated into larger farms. This project will study the effects of land changes on southern Wisconsin dairy farms and communities and will explore the possibilities of land stewardship as a means to alleviate farmers’ struggles. In the first phase of the project, researchers will analyze existing data on the economies, populations and land sales of Grant and Dane counties. In the second phase, student and faculty researchers will interview farmers and community members to learn about their relationship to the land, how their land use has changed and the benefits and barriers of various agricultural land-use programs. In phase three, a survey will focus on differences in the towns and regions of southern Wisconsin. Study results will ultimately help dairy leaders, government agencies and nonprofit organizations make decisions about land use policy. One of the primary goals is to increase student awareness of land stewardship, strong farms, and healthy communities and build stronger connections between social science and agriculture at UW-Platteville.

Measuring the rheological properties of ice cream to predict its mouth-feel sensations

Project summary: Wisconsin ranks as a major producer of ice-cream and the majority of manufacturers have been in business for over 50 years, many are small family-owned businesses.

In order to sustain a robust economic growth, the ice-cream industry must keep strides with recent advances in science, technology and customer preference. To be at the forefront in producing nutritious products in an economically, environmentally and socially sustainable manner, the industry must innovate. Cutting across discipline lines, people with expertise in engineering and dairy sciences will come together and apply their knowledge to improve on such dairy products. This study will build understanding of the fluid mechanical characteristics of an ice-cream mix prepared by students as part of their coursework. Using a neural network model, the characteristics will be correlated with the mouth-feel sensations of the ice-cream samples. This will enable prediction of the taste sensations for various types of ice-cream mixes.

Development of milk-protein-based 3D printing biocomposites using spoiled milk and whey from dairy processing waste

Project summary: Casein and whey have been shown to have unique polymer properties for commercial applications. This project will explore the idea of converting casein in waste milk and whey from cheese byproduct to make filaments for the ever-growing 3D printing sector. Casein holds great promise as a major component in 3D printing filament. Water soluble whey can be modified to be compatible with the filament making process. Applying existing experience and knowledge in biocomposite development will help us realize the hidden potential of sustainable casein and whey in material development. Expected deliverables are milk-protein based filaments, 3D printed specimens and mechanical properties data. Achieving milestones in this project will create a new demand for milk and milk protein products and a new way to use spoiled/bacteria-contaminated milk and protein waste from processing facilities, which could potentially help farmers and communities avoid financial losses and disposal.