Forages and Pastures Symposium I
Designing Research for Beef Cattle Production in Extensive Environments – Dr. Timothy DelCurto, Montana State University
The Forages and Pastures Symposium I on Friday, July 16th, began with Dr. DelCurto discussing the ongoing challenges of designing research for beef cattle production in extensive environments. Previous study designs trying to get enough observations for statistical inference required cattle to be brought in from the rangeland each day, sorted, fed, and then let back out. This design was limited though with the number of treatments and replicates that could be performed, everything was based on pen averages rather than learning about individual animal variation, and it required a lot of work and labor that ultimately disrupted natural grazing patterns of these animals. Advancements in technology has made it possible to apply treatments, such as supplementation studies, to individual animals on these extensive environments allowing us to reduce our disruption of the landscapes and interfering with the animal’s normal behaviors. Using individual animal identification, electronic feeders, GPS collars, activity monitors has created more opportunities for researchers to evaluate the grazing behavior of these animals more accurately on extensive landscapes, monitor individual animal intake, learn about optimal use of rangelands and optimal nutrient delivery systems, and discover the influence of supplement intake and cow age on grazing behavior and rangeland use patterns. While there are still many challenges beef cattle research in extensive rangeland environments face such as working with large data sets and having to use multiple regression techniques, there are a ton of research opportunities and questions that can be answered with the advancing technology.
Opportunities and Challenges of Conducting Grazing Experiments in Pasturelands – Dr. Joao Vendramini, University of Florida
Dr. Vendramini continued by analyzing the challenges and opportunities of conducting grazing experiments in pasturelands. He started out by stressing the importance of standardizing forage and grazing terminology used in research. There have been publications defining the recommended nomenclature over the years and this needs to be a continuous process that researchers work on to ensure uniformity across studies to ultimately get information across more efficiently and successfully. There are other challenges within grazing experiments in pasturelands as well such as the intrinsic variability of measurements on the pastureland that limits the ability of researchers to find differences among treatments and the large number of resources and labor needed which may lead to decreasing the size of experimental units that will potentially exacerbate the already existing limitations of detecting differences among treatments. Overall, it is important to understand and acknowledge the limitations and decide what procedures would be acceptable and unacceptable. Grazing systems are great providers of ecosystem services, which is a major focus currently, leading to more opportunities to expand the knowledge on multifunctionality of grazing research projects and fostering collaboration with colleagues.
Have New Feeding Technologies Revolutionized the Way We Design Grazing Experiments? – Dr. Stacey Gunter, USDA
Dr. Gunter began his discussion by explaining how technological advancements have enabled us to look at individual animals by facilitating autonomous collection of intake, feeding behavior, and body weight data, both for pen based and pasture based systems. These individual feeding systems are not new, but previous technology caused experiments to be very laborious when trying to train and acclimate animals, having to gather them at each feeding, and sort them into individual stalls, overall disrupting the normal grazing activities of these animals. Newer, more automated systems such as SmartFeed Pro, GreenFeed, GrowSafe, and Insentech reduce labor and seem to have less disruption of grazing behavior but rely on the animal’s willingness to use the system and their true ability to access it in the face of more dominant animals. The use of these technologies seems to cause some confusion, conflict, and discontent when discussing experimental units in experimental design and analysis. The subtle or not so subtle differences in systems will have large implications on how they can be used in experimental designs, and it will be critical for the researchers to make sure their audience ultimately understands why they made the choices they did in regard to their experimental design. While these newer technologies have advantages such as calves having 24/7 access to supplement and the ability to measure many interesting data paints, there are still disadvantages to be aware of and hopefully improve upon such as only a few animals can access at a time, there may be a displacement rate, and potential influences of herd mentality.
Statistical Analysis of Grazing Research – Dr. W. Brandon Smith, Tarleton State University
Dr. Smith opened his presentation by stating that technology has improved how we do what we do, but no matter how we use the technology and perform research, ultimately, we still have to perform an analysis. The collection of data on multiple scales causes questions to arise about the correct assignment of the experimental unit and brings about other intricacies such as ensuring we account for spatial and temporal effects of the environment when analyzing the data. Dr. Smith’s main question then was how can we obtain the maximum information from experimental data? He then discussed how grazing experiments were originally handled and ran through some examples of statistical analysis to show the differences between the use of traditional approaches and modified approaches of a completely randomized design versus a randomized complete block design. Overall, analysis is not cut and dry and different parts of data have different ways to be analyzed. Dr. Smith stressed that statistics is a tool, but the key to statistics is knowing how to use it and accounting for the correct error term to maximize the information provided from the experiment. He concluded with saying that grazing research is a battle of mindset, once the design is developed and data are collated, the statistics are there and will become straightforward, but it comes down to our mindset and understanding what to account for in the analysis itself.