Tools for grass farmers to monitor grazing behavior and forage use in real time

Tools for grass farmers to monitor grazing behavior and forage use in real time

Summary

Our project team at Choiniere Family Farm in Highgate Vermont, studied the ability to estimate forage intake rates and assess how the value of the diet diversity can affect dairy productivity, milk quality and well-being.

The project complements an ongoing umbrella study to find out, how biodiversity affects livestock well-being, health, and productivity. Understanding the response of ruminant and environmental microbial communities to specific management practices is critical to optimizing farm productivity and product quality and enhancing ecosystem-based management of farms and agricultural landscapes.

Objectives/Performance Targets

The goal of this project was to understand how different diets affect grazing behavior and in turn, how the relationship between grazing time and diet alters rumination activity, rumen pH and health, milk composition and productivity.

At Choiniere Family Farm in Highgate VT, we tested 8 dairy cows to three different diet treatments: (1) winter feed (hay + total mixed ration TMR), (2) diverse New England cool season pastures and (3) pearl millet summer annual pasture.

Cows remained four weeks in each treatment starting with winter feed, then diverse cool season pasture (May-June), followed by pearl millet (July), subsequently by diverse (August), and pearl millet again (September), until cows went back to winter feed (October). While cows were in barn, we collected hay and TMR for quality analysis. Every week of the grazing season we sampled, forages, bacteriological swabs of udder skin, rumen fluid, feces and milk samples. We also carried out soil samples of the areas where dairy cows grazed.  Data collection was performed by Drs. Alvez, Barlow, Roman and Kraft, along with three Graduate Students and a Research Technician under their supervision.

We also collected data on lying time and lying frequency using accelerometers as a potential proxy for grazing activity and explored the availability of other grazing activity meters to estimate forage intakes grazing behavior and rumen health for pasture-based dairy cattle to demonstrate how real-time monitoring of grazing behavior and forage intakes allow farmers’ to optimize forage utilization, rumen activity, and milk composition.

The outreach part of this project will happen during Spring and Summer 2015. In mid-January, we will present preliminary results at the “19 VT Livestock and Grazing Conference”. During Summer 2015, we will host a workshop and field day at Choiniere Family Farm. On both occasions, we will summarize data in research briefs and/or factsheets. The project already has a website where general information, images and short videos are posted. The website can be accessed at: http://juanalvez.weebly.com/team.html 

Accomplishments/Milestones

Our project team was able to accomplish all of the activities planned in the timeline, except for the data analysis and the workshop. The sampling process happened until November hence, we evaluated that postponing the workshop and field day to Summer of 2015 would allow us to better communicate proper data analyses and interpretation of the findings. A summary of activities completed with the different segments of this research follows.

Dairy cows

We randomly selected eight-second and­ third lactation cows in relatively close milk production levels, with days in milk ranging from 50 to 90 days and milk fat between 2.8 and 3.6%.  Cowherd at Choiniere Family Farm is certified organic and do not receive any medicinal treatment other than nutrition.

Before the experiment began, we learned that Choiniere Farm breeds year-round. For this reason, we decided to increase the number of cows, from six to eight animals, as a way to lower risks related to illness or pregnancies that could affect statistical viability of the experiment. Towards the end of the season, four cows dropped from the experiment because they started to drop milk production due to pregnancy. Fortunately, we anticipate the results obtained from the four cows provides sufficient power to test for differences.

Rumen samples

Rumen samples were collected weekly. Initially, we planned to fistulate six cows’ however the Northeast Organic Farmers Association (NOFA) advised against the method because of the stress (and other health complications) this method could impose to cows which in turn, could result in the loss of their organic status. Instead, we used a speculum –a 16 inch metal tube that is secured by an operator in the cow’s mouth while a second operator inserts a plastic flexible transparent hose through the speculum into cow’s stomach. The second operator pumps and extracts rumen fluid.   To support rumen data, we planned to install rumination collars to measure rumination activity. However, because of schedule difficulties and high demand, the company responsible for installing these collars could only do it later in the season, which would inviabilize data collection in early season. As an alternative, we recorded events manually.

Bacteriological samples

We collected weekly samples from Quarter milk, Right hind teat end skin swab, Right inner hock skin swab, fecal material, and nasal swab for bacteriological analysis. All swab samples were transproted to the laboratory on ice and frozen at -20 C for subsequent analysis. Bacteriological culture of these samples is underway.

Milk samples

We followed cows’ performance every week across every diet. Milk samples were collected to compare fatty acid ratios to the forage fatty acid ratios. Individual milk production, milk protein and fat composition was measure from the weekly milk samples.

Grazing activity

Triaxial accelerometers (HOBO pendant G data loggers) monitored grazing behavior and were installed for a two week period covering the transition between each treatment from June to December. Thus lying behavior and activity was recorded for a week at the beginning and end of each treatment period.   These monitors record individual animal activity data for automated download to microcomputers. They are attached to the animal with leg bands to monitor lying behavior. We will evaluate the ease of use of these data and the potential application of lying time data to evaluate behavior of grazing cattle.

Forage and soil samples

In May and October we collected hay samples (diet 1) to test for quality and fatty acids. Between June and September, we carried out weekly forage species diversity, pasture biology, botanical composition, yield and quality sampling of diets (2) and (3). We collected soil samples where cows grazed. Choiniere farm has been certified organic since 2005 and it has pastures that have not been plowed for over 25 years.

Pre-grazing mass was measured just before the cows were turned out on the pasture.  Ten falling plate heights were collected from each paddock. Hand samples were collected from each plot to determine forage quality evaluation. Post-grazing mass was measured in the same manner taking 10 falling plate heights per plot.

To calibrate the falling plate, 10 to 12 samples ranging in mass from low to high were collected across the study area. At each site, the rising plate height was documented and a 0.5 m² quadrat was used to collect all the forage down to the ground surface. The material was placed in a cloth bag, then dried for 72 h, ground and weighed to determine dry matter yield; then it was sent for quality analysis.

Impacts and Contributions/Outcomes

Although we are still processing data and interpreting results, a brief article was submitted to Northeast Organic Dairy Producers Association (NODPA) in early December 2014. The article can be accessed at: (http://www.nodpa.com/research_ed_biodiversity-health_120114.shtml)

Preliminary findings will be presented at the 19 Vermont Livestock and Grazing Conference in Jan 15^th. We anticipate that around 20 to 25 attendees will participate in a workshop the follow Summer of 2015 where final results, research briefs and factsheets will be distributed.

Collaborators: