Performing Department
(N/A)
Non Technical Summary
With the global population expected to reach 9.7 billion by 2050, the demand for animal-based protein like meat and milk is increasing. This growth poses a challenge: how can farmers produce more food without harming the environment? Livestock, especially cattle, produce a significant amount of greenhouse gases (GHGs), mainly through methane emissions from their digestive systems. This methane not only can harm the planet but also represents a loss of about 10% of the energy cows get from their food. Additionally, livestock can pollute water and release other harmful gases through manure management. Despite efforts, current strategies to reduce these emissions have shown limited success without affecting the animals' health and productivity. We propose that a better understanding of the microbes living in cows' stomachs (rumen microbiome) and how they interact with the cows' genetics and diet could be the key to solving this problem. Our main goal is to uncover how the rumen microbiome affects methane production in dairy cows and how diet changes can influence these emissions. We will focus on cows with different genetic potentials for methane production to investigate if diet can make a difference in their emission levels. We also aim to understand the trade-offs involved in reducing methane emissions and their impact on other greenhouse gases produced from cow manure. Finally, we will use our findings to develop educational programs aimed at promoting environmentally friendly practices among farmers and the broader community.By the end of this research, the goal is to have a clearer picture of how the cow's microbiome influences methane emissions. This knowledge could lead to the development of targeted feeding strategies and breeding strategies that contribute to lower methane emissions in cattle, making livestock farming more sustainable. We also anticipate that our findings will guide the development of more effective ways to manage cow manure, reducing its environmental impact. Ultimately, this work will provide a foundation for future research and innovation in sustainable livestock production, guiding the development of more holistic and effective approaches to reduce the environmental impact of dairy farming.
Animal Health Component
0%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
0%
Goals / Objectives
This project aims to advance the productivity and sustainability of ruminant livestock systems by creating effective management strategies for dairy farmers. These strategies will improve the conversion of feed into valuable products for the animals and reduce greenhouse gas (GHG) emissions from enteric fermentation and manure. The project will leverage existing resources at the University of Wisconsin-Madison to monitor methane emissions from individual animals and identify dairy cows with high- and low-methane emission phenotypes, providing unparalleled opportunities to understand the underlying mechanisms driving methane production in cattle. The overarching hypothesis is that differences in rumen microbiome function, specifically the diversity and abundance of methanogens, are associated with variations in methane emissions in dairy cattle and influenced by the host genome. The main goal is to unravel the ecological processes associated with methane production by dairy cows and manure fermentation and determine if changes in diet can influence emission traits in cattle with different genomic potentials for methane production. To accomplish this, we propose the following specific objectives:1) Understand microbial contributions to methane emissions: We will characterize the active microbial communities in the rumen of dairy cows with varying methane emission levels using metatranscriptomic analysis and determine if methane production in rumen and manure is associated with variation in methanogenic activity.2) Determine the impact of diet on methane emissions: We will investigate how dietary changes, specifically starch-rich versus fiber-rich diets, affect methane production in dairy cows with different genomic potentials for methane production.3) Evaluate greenhouse gas (GHG) emissions from manure management: We will assess the GHG emissions from storing and applying manure produced by dairy cows with distinct methane emission traits, providing insights into how diet influences these emissions and the abundance of methanogens.4) Develop an extension program to promote enhanced environmental health awareness: We will create an extension program with diverse materials to raise awareness and promote practices that reduce GHG emissions from livestock production among farmers, industry partners, and the wider community.
Project Methods
For aim 1, rumen and fecal samples will be collected from different cohorts of lactating cows housed at two study sites in Wisconsin (Emmons Blaine Arlington Dairy Research Center and Marshfield Agricultural Research Station). This will represent the largest sampling effort to date to identify cows with distinct traits of enteric emission (~1,000 animals). Methane emission measurements will be collected for six weeks using the GreenFeed system during voluntary visits of the animals. At the end of the experiment, the methane data will be used to calculate different metrics and rank the animals as high or low-methane emitters. Rumen and fecal samples will then be collected from these animals and RNA will be extracted from rumen contents and sequenced to investigate the composition of the microbiota associated with each cattle phenotype. Sequencing reads will be filtered to remove traces of host RNA and ribosomal rRNA. Differential abundance (at both phylum and genus levels) and differential gene expression analysis will be conducted using DESeq2, and correlations between microbial gene expression and methane emission profile will be calculated using Spearman's rank correlation. Barcoded amplicons of the archaeal 16S rRNA gene will be generated and sequenced on an Illumina MiSeq, and taxonomic classification will be assigned using appropriate databases. Alpha and beta diversity analyses will be performed to compare community membership and structure using PCoA plots and statistical tests like PERMANOVA and ANOSIM.In aim 2, experiments will be conducted with sixty-four multiparous Holstein cows housed at the UW-Madison Blaine Dairy and fed different experimental diets containing distinct levels of starch and forage. Individual milk yield, milk components, dry matter intake, feeding behavior, body weights, body condition score, and methane and carbon dioxide emissions will be measured. Data collected will be used to rank cows based on methane emissions as described for Aim 1 and statistical analyses will be performed to evaluate the effects of dietary changes on animal performance, rumen microbiome composition, and methane emissions. An experiment will be conducted to determine if the dietary changes result in a re-ranking of cows. This will provide novel and relevant information regarding the interactions between animal traits, microbiome composition and diet. Treatment means will be determined using least squares means and data will be analyzed according to the study design using mixed models. Significant treatment by week interaction effects will be partitioned to examine the effects of treatment within a week.In aim 3, manure and urine will be collected from dairy cows ranked as high and low methane emitters, stored in barrels, and measured for greenhouse gas (GHG) emissions and ammonia using a gas analyzer. Manure samples will be applied to different soil types in laboratory incubations, and GHG emissions will be measured using gas chromatography. Little is known about the association between enteric emissions of dairy cows with different genomic potential for methane production and the emissions of GHG from the manure of these animals. Results from this objective can also help producers make informed decisions on how to manage the manure at the farm level to reduce GHG emissions. Statistical analyses will be performed to analyze the effects of manure type, soil type, and soil conditions on GHG emissions using three-way ANOVA and Spearman's rank correlation.Finally, aim 4 will focus on the development of extension materials based on the research findings to promote enhanced environmental health awareness among farmers, industry partners, and the broader community. Dissemination of results will occur through an established webinar series organized by the UW-Madison Division of Extension. The impact of the extension program will be evaluated through surveys, feedback forms, and monitoring the adoption of recommended practices by the target audience. In addition, the findings will inform the development of sustainable management practices for reducing the environmental footprint of dairy farming.