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 Environmentally Integrated Dairy Management Research: Madison, WI
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ARS Home Midwest Area Madison, Wisconsin U.S. Dairy Forage Research Center Environmentally Integrated Dairy Management Research Research





- Burch, Tucker
- Young, Eric
- Jaramillo, David
- 2021
- 2020
- 2019
- 2018
- 2017
- Publications
- Food Animal Production (101)
- Soil and Air (212)
- Sustainable Agricultural Systems Research (216)

Research Project: **Location:
                            Environmentally Integrated Dairy Management Research** Project Number: 5090-12630-005-000-D
                        
                        Project Type: In-House Appropriated Start Date: Jul 13, 2016
                        
                        End Date: Jul 12, 2021 **Objective:**
                        
                        Objective 1: Develop land and manure management practices to improve crop and forage productivity, quality, and nutrient use efficiency; and reduce pathogens and losses of nutrients.
Sub-objective 1.A.  Conduct multi-scale experiments to investigate biochemical and physical processes controlling snowmelt, snowmelt infiltration and runoff, and nutrient losses from soil and manure.
Sub-objective 1.B. Evaluate nutrient cycling, nitrous oxide and ammonia emissions, and nutrient and pathogen runoff losses with conventional and improved liquid dairy manure management practices for alfalfa production and in a silage corn-rye cover crop system.
Sub-objective 1.C. Determine manure/crop management effects on N, P, and pathogens in runoff from dairy cropping systems.
Sub-objective 1.D. Evaluate effects of alternative manure application methods on alfalfa-grass yield, quality, and silage fermentation characteristics.
Sub-objective 1.E. Determine potential of fall-grown oat to capture nutrients from summer manure or fertilizer applications and produce a late-fall, energy-dense forage crop. Determine potential of spring wheat and barley for fall-forage yield, quality, and nutrient capture from mid-summer manure or fertilizer applications. Evaluate oat mixtures with wheat, triticale or cereal rye (1 planting) for total fall and spring forage yield (2 harvests), as well as nutrient capture.
Objective 2. Develop, improve, calibrate, and validate model routines for nutrient management to assess environmental impacts, nutrient use efficiency, and economics at the farm scale.
Objective 3: Characterize soil biodiversity and manure pathogen dynamics and interactions.
Sub-objective 3.A. Conduct laboratory microcosm experiments to manipulate soil biodiversity and measure die-off rates of dairy manure-borne pathogens.
Sub-objective 3.B. Conduct field studies relating agricultural cultivation practices to soil biodiversity and die-off rates of manure-related pathogens.
Objective 4. Reduce nutrient losses from replacement dairy heifer production through management strategies that target nutrient use efficiency and growth performance.
Sub-objective 4.A. Improve understanding of heifer development and growth, especially effects of genomic testing for residual feed intake (RFI) on nutrient-use efficiency and growth.
Sub-objective 4.B. Determine effect of common management strategies (pen stocking rate, limit feeding, ionophores, diet composition, etc.) on nutrient-use efficiency and growth performance of heifers. **Approach:**
                        
                        Improved management of dairy farms requires successfully managing its nutrient flows, both to maximize nutrient use by animals and crops to optimize profit, and to minimize nutrient loss to the environment. We will investigate most aspects of nutrient cycling throughout the dairy-farm system with a variety of methods and at different scales, including replicated field plots, field-scale paired watersheds, feeding trials with replicated pens of heifers, and computer modeling. We will also examine pathogen transport and viability at different points in the dairy farm system. Some experiments will investigate only one or two nutrient or pathogen pathways, while others will be more comprehensive, including, for example, surface runoff, gaseous emission, and plant removal. Computer modeling will investigate the whole-farm system. Our research team also has a longer-term goal, which is to integrate information across experiments to more completely describe, quantify, model, and manage the entire dairy-farm for improved efficiency and sustainability. Achieving this goal will help ensure the existence of profitable, environmentally acceptable dairy farming for coming decades.


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