Content area

Abstract

The advancement of precision technologies has revolutionized livestock farming, particularly in the dairy sector, where sensor-based systems offer new opportunities for real-time monitoring and improved herd management. Over the past few decades, the adoption of sensor technologies in dairy farms has steadily increased, driven by the growing need for actionable insights that enhance animal health, productivity, and welfare. These technologies, often integrated with management software, enable the early detection of diseases, evaluation of physiological parameters, and monitoring of behavioral patterns, ultimately supporting timely decision-making on the farm. Despite the availability of a wide range of sensors in the commercial market, their successful implementation largely depends on the generation of meaningful data that can be directly translated into effective management actions. While many studies have focused on postpartum health disorders, there is a growing interest in expanding the application of sensors across different physiological stages of the dairy cow, including the dry period and transition phase, to help inform management decisions during the lactation cycle. Understanding how behavioral patterns such as rumination, activity, lying, and standing behavior respond to changes in management and physiological status is crucial for enhancing cow comfort, reducing health issues, and improving productivity outcomes, and longevity of dairy cows. The objective of this dissertation is to explore how sensor technologies can be applied across various stages of the production cycle, particularly around the dry-off and transition periods, and how they can be leveraged to promote animal welfare and optimize performance. Through a series of experimental studies, this dissertation investigates the behavioral and physiological responses of dairy cows to different dry-off strategies, as well as the implications of behaviors dynamics in the postpartum period. The first experimental chapter examines how milk production in the week preceding dry-off influences activity and rumination behavior during the initial 30 days of the dry period. The second and third experimental chapters assess the use of acidogenic boluses around dry-off, evaluating their impact on cow comfort, behavior, and metabolic responses. Finally, the fourth experimental chapter explores the role of rumination recovery in the first week postpartum in modifying the association between hyperketonemia and subsequent performance. Together, these studies contribute to a deeper understanding of how sensor data can support more informed and effective management practices during critical periods of the lactation cycle.

Details

1010268
Business indexing term
Title
From Dry-Off to Fresh: Using Herd Monitor Technology to Understand Behavior, Welfare, and Performance in Dairy Cows
Number of pages
179
Publication year
2025
Degree date
2025
School code
0130
Source
DAI-B 87/2(E), Dissertation Abstracts International
ISBN
9798291502990
University/institution
University of Minnesota
Department
Animal Sciences
University location
United States -- Minnesota
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
32169789
ProQuest document ID
3241072357
Document URL
https://www.proquest.com/dissertations-theses/dry-off-fresh-using-herd-monitor-technology/docview/3241072357/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic