Improvement of animal level efficiency and mitigation of enteric emissions

Most recent studies have shown the potential for dietary strategies (e.g., replacement of neutral detergent fiber with starch or replacement of alfalfa silage with corn silage) to mitigate enteric emissions from dairy productions systems. Supplementation of feed additives such as seaweed, 3-nitrooxypropanol (3-NOP) and nitrate have caught the attention because of their enteric emission mitigation potentials. For instance, 3-NOP could reduce upto 40% enteric emissions depending on dose and diet composition whereas seaweed could reduce upto 67% enteric methane depending on dose, animal type (e.g., dairy or beef) and seaweed species. However, it is yet quite unknown of how these feed additives work and how they affect intake, fiber digestibility, microbial protein synthesis and whole-farm greenhouse gas emissions. Thus, the overarching goal of our research is to improve the understanding and mechanism of how diets and feed additives (e.g., seaweed, 3-NOP) affect microbial genomics, fiber digestibility, enteric methane emission and efficiency of microbial protein synthesis. 

Mitigation of greenhouse gas and ammonia emissions from manure management systems

Manure is the second significant source of greenhouse gas from the dairy production systems. Additionally, manure affects both water and air quality negatively due to nitrate leaching and ammonia emissions, respectively. Manure ammonia from dairy production systems which could possibly be the greatest concern may account for up to 50% of the total regional ammonia emissions in some regions such as Pennsylvania, USA. Nitrate leaching and nitrate contamination of drinking water is the growing concern for some regions (e.g., Wisconsin, USA). Often, ruminant diets contain excessive nitrogen and phosphorus which are excreted via manure. Thus, proper ration management could potentially reduce the nutrient excretions and reduce negative impacts on air and water quality. Therefore, the primary goal of our team is to explore animal and dietary factors that could potentially reduce the excretions of manure nutrients particularly nitrogen and phosphorus and subsequent nitrate leaching, ammonia and greenhouse gas emissions. We will explore the opportunity to collaborate with soil scientist or agronomist and waste management specialist to initiate project looking at impact of manure composition, treatment and microbial profile of manure and soil on manure greenhouse gas emissions.

Farm (system) level sustainability assessment using life cycle assessment (LCA) as a tool

Our previous research findings demonstrated that dietary mitigation strategies of enteric emission should be evaluated at the whole-farm level accounting for their impacts on upstream (e.g., feed production) and downstream emissions (e.g., manure chain emissions). Additionally, most LCA studies assume no change in soil organic carbon stock due to lack of data availability though soil carbon stock may change over time depending on vegetation type, soil management practices and soil characteristics. Thus, our research goal in this sub-field is to evaluate and compare alternative feeding management (e.g., grass vs. legume, zero grazing vs. managed grazing) and greenhouse gas mitigation strategies using integrated (holistic) life cycle assessment approach on carbon footprint (with or without accounted for soil carbon stock change), water footprint and eutrophication potential. Currently, we are also working on a pilot project that is looking for impact of incorporating multifunctionalities of dual-purpose cattle raised in extensive system on milk and beef carbon footprint. However, it is difficult and complex to allocate emissions into different cattle functionalities. Therefore, we would like to extend this project aiming to find out the best allocation methods for different functionalities of cattle. Furthermore, strong background and interest in quantitative genetics and statistics will enable us to analyze and interpret large amount of data generated by the automated and robotic systems, and data-collecting sensors aiming to improve precision livestock management.