ORCID
0009-0008-2357-8565
Date of Award
2025
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Animal Biosciences
First Advisor
Jana Kraft
Second Advisor
Carol E. Adair
Abstract
Climate change is a growing concern that poses a threat to the global population and production systems alike. Cattle production systems are responsible for nearly a quarter of anthropogenic methane (CH4) emissions in the United States. Establishing non-invasive, practical tools to estimate CH4 emissions from dairy cattle is critical for developing sustainable agricultural practices that mitigate climate change. Current CH4 measurement techniques used in research are expensive and need to be revised to adapt to commercial production systems. These methods generally involve animal isolation, extensive training, and complex equipment, which limit large-scale applicability. Milk is easy to collect, and its components are known to reflect rumen methanogenesis indirectly. Thus, utilizing milk fatty acids (FA) and proteins as biomarkers to assess CH4 emissions may help the dairy industry balance productivity with environmental sustainability.The overarching goal of this thesis was to evaluate the milk FA and low-abundance protein profiles of cows producing low methane (LM) and high methane (HM) emissions and identify candidates that may serve as biomarkers for assessing CH4 emissions. Forty-eight Holstein cows were enrolled in a 48-h exploratory study. Milk samples were collected thrice daily at each milking, CH4 measurements were taken thrice daily using the Greenfeed tie-stall system, and dietary intake was recorded daily. The first objective (Chapter 2) was to compare the milk FA profiles of LM- and HM- emitting cows to identify candidate biomarkers for assessing CH4 output (g/d), CH4 yield (g/kg dry matter intake (DMI)), and CH4 intensity (g/kg energy corrected milk (ECM)). The second objective (Chapter 3) was to investigate differences in the low-abundance milk protein profiles of LM- and HM- emitting cows to identify candidate biomarkers indicative of CH4 output. Milk FA were determined via gas-liquid chromatography, and low-abundance proteins were analyzed using liquid chromatography-tandem mass spectrometry. There was no difference in production parameters (i.e., DMI, milk yield, ECM, feed efficiency) between the LM and HM groups. Significant correlations were observed between CH4 metrics and specific FA, including novel associations with 13:0-anteiso, 11-cyclohexyl-11:0, and 20:3 c5,c8,c11. Furthermore, underexplored FA such as 17:0-iso, and 20:1 c9 demonstrated high predictive performance, highlighting their potential as suitable biomarkers. Regression models incorporating FA and production parameters accurately predicted CH4 output, CH4 yield, and CH4 intensity. Proteomic analysis identified 23 low-abundance proteins differently abundant between the CH4 emission groups, with 10 exhibiting potential associations with CH4 emissions. Proteins such as polymeric immunoglobulin receptor (PIgR), peroxisome proliferator-activated receptor δ (PPARD), and laminin subunit β-1 (LAMB1) were positively correlated with CH4 output, while transcobalamin 2 (TC2) was negatively correlated. Overall, these findings demonstrate the utility of milk FA profiling as an effective method for predicting CH4 emissions in dairy cows and underscore the complexity of the milk proteome. This research provided novel insights into the relationships between CH4 emissions, milk FA, and low-abundance proteins, supporting the development of precision dairy farming through non-invasive approaches.
Language
en
Number of Pages
227 p.
Recommended Citation
Youngmark, Emily Caitlin, "From Methane To Milk: The Potential Of Milk Biomarkers For Methane Assessment" (2025). Graduate College Dissertations and Theses. 2042.
https://scholarworks.uvm.edu/graddis/2042
