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The Making of Dairy Champions: Inside the European Young Breeders School

Sunday, September 1st, 2024

Discover how the European Young Breeders School shapes future dairy leaders. Ready to unlock global opportunities in cattle breeding? Keep reading!

Summary: Are you passionate about dairy farming and eager to see the next generation thrive? For over two decades, the European Young Breeders School (EYBS) in Belgium has been shaping young talents in cattle breeding, and the 22nd edition in 2024 promises to be bigger than ever. This isn’t just a regional affair anymore; it’s a global stage where young breeders from 23 countries immerse themselves in a rich, hands-on learning experience. With a mix of theoretical lessons and practical workshops taught in four languages, the EYBS equips attendees with skills that extend beyond the farm and into the world of international agriculture. “Teamwork and communication also play a big part, and they learn something useful daily and later in life,” – Erica Rijneveld. Not to be missed, the event also fosters life-long friendships through cultural exchange, as local farming families host young breeders. Add in the thrill of competition, where participants showcase their animals and skills, and you get an unparalleled event that’s as educational as it is exhilarating! 

  • EYBS has a 20+ year legacy of developing young talents in cattle breeding.
  • The 22nd edition in 2024 will feature participants from 23 countries.
  • Comprehensive training includes both theoretical lessons and practical workshops.
  • Course content is available in four languages: French, German, English, and Dutch.
  • Emphasis on teamwork and communication prepares participants for future careers.
  • Cultural exchanges foster lifelong friendships among young breeders.
  • Competitive elements add excitement and a real-world challenge for attendees.
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Have you ever wondered where the next generation of cattle breeders will develop their skills? For almost 20 years, the European New Breeders School (EYBS) has been a leading program for developing new talent in dairy farming. This school, founded in Belgium in 1999, has grown into a worldwide center for young enthusiasts from 23 countries, providing exceptional learning possibilities in cattle breeding. With a curriculum that combines practical and theoretical instruction in many languages, the EYBS offers participants the information and hands-on experience they need to succeed in cattle breeding. Around 150 young breeders worldwide attend yearly, making it a staple event in the dairy farming industry. The EYBS not only nurtures young talent but also contributes to the advancement of the dairy farming industry. Want to learn more? Continue reading to see why the EYBS is a breeding ground for future agricultural winners.

From Regional Roots to Global Gathering: The Inspiring Journey of the European Young Breeders School

The European Young Breeders School (EYBS) was founded in 1999 to train young cattle breeders from Belgium, France, the Netherlands, and Germany. It began as a tiny regional endeavor but rapidly grew in popularity and earned a reputation for quality. Over the years, EYBS has grown into an international event with participation from all over the world. Today, young people from 23 nations, including Australia, Canada, and Italy, gather in Belgium to study and compete. This astonishing development has evolved EYBS into a cultural interaction center, receiving almost 2,000 young breeders since its founding.

A Deep Dive into Hands-On Workshops and Thrilling Competitions 

The EYBS program immerses young breeders in a five-day experience that includes three days of rigorous instruction and two days of competition.

During the first three days, participants dive into workshops and hands-on practice sessions, learning essential skills for showing and marketing cattle. Some of the critical workshops cover: 

  • Animal Preparation: Techniques in washing, bedding, clipping, and braiding cattle.
  • Marketing: Strategies for promoting and selling livestock effectively.
  • Showmanship: How to present cattle in the ring, emphasizing conformation and handling.
  • Judging: Understanding the criteria for assessing cattle quality and performance.
  • Feeding: Nutrition plans to ensure cattle maintain optimal health and appearance for shows.

Following the training period, the subsequent two days are dedicated to competition. Participants put their newfound skills to the test in: 

  • Heifer Conformation Classes: Judging the physical structure and attributes of heifers.
  • Showmanship Classes: Showcasing the handlers’ abilities to present and manage cattle in the ring.

Competitors are evaluated on their collaboration, animal preparation, and presenting abilities throughout the week. The competition concludes with honors for the best clipper/fitter, showman, and top teams.

The Magic of Cultural Exchange: 23 Countries, One Unifying Experience

Imagine young breeders from 23 different nations together in Belgium; this is the charm of the European Young Breeders School. Participants come from areas as diverse as Australia, Canada, and Italy, resulting in a melting pot of cultures and ideas. This event is more than just a training program; it’s a lively cultural interchange. Friendships formed these days might persist for years, crossing boundaries and determining future agricultural cooperation.

Language barriers? Not a problem here. The school provides French, German, English, and Dutch classes, guaranteeing that every novice breeder receives complete instruction, regardless of background. This multilingual method not only accommodates the many native languages but also encourages inclusion and mutual understanding among participants. These young people develop a global perspective via interactions, shared meals, and joint tasks, in addition to learning cattle breeding. This emphasis on inclusivity ensures that every participant feels welcomed and valued at the EYBS.

A New Era: Team USA Joins the European Young Breeders School 

While Canada has proudly sent teams since 2014, 2024 will be a historic event in the EYBS as the United States debuted. Dave Schmocker of Whitewater, Wisconsin, was instrumental in establishing the first-ever US team. Dave cites his longtime friend Erica Rijneveld as the driving force behind this endeavor. He has known Erica for over 20 years since he used to go to Europe and perform at performances with Quim Serrabassa and Erica. She had been bugging him for years to form a US team, and in March of this year, she called to inform him that she had signed them up and booked a spot. That was just the impetus they needed.

The team’s selection process includes calls to well-known dairy business officials nationwide. Schmocker assembled a selection committee that includes seasoned individuals such as John Erbsen, Aaron Eaton, Lindsay Bowen, Pat Conroy, Lynn Harbaugh, Mark and Nicky Rueth, Adam Liddle, Mike and Julie Duckett, Eddie and Mandi Bue, Chris and Jen Hill. These people have been doing it for 20 or 30 years and are still unstoppable unless you are willing to work as hard as them. About 20 young people submitted resumes, which the committee carefully ranked to select the final team members: Lauren Silveira of Chowchilla, CA; Hayden Reichard of Chambersburg, PA; Jacob Harbaugh of Marion, WI; Alli Walker of Wisconsin Dells, WI; Stella Schmocker of Whitewater, WI; and Camyrn Crothers of Pitcher, NY.

Fundraising efforts have been vital in covering school fees and plane tickets, ensuring that the young participants do not face financial hardship. On August 7th, CattleClub.com sponsored an online fundraiser, with 100% of the proceeds benefiting Team USA Youth Breeders. The auction included embryos from well-known show cows, fitting equipment, and gift certificates. Reflecting on the accomplishment, Dave said that the school costs $450 and the aircraft ticket costs around $1,000, but he wants all of these children to be able to attend for free. If enough funds are raised, the idea is to purchase some 220-powered cutters and blowers and store them there until next year. The plan is to invest in these young people while saving money for their future. Next year, they may send two squadrons! On August 28th, the team plans to go to Belgium a day early to adapt before the hectic, demanding week starts on August 29th. Dave is delighted with the international exposure and ability to develop global relationships. He expects this experience will result in new relationships, potential teammates, and future business partners. They want to visit each other in the United States and Canada, establishing solid international ties that will benefit everyone involved. Although the first year of any business may be busy, Dave radiates confidence and joy. Seeing those kids there will provide him enough personal delight to make it all worthwhile.

Success Stories: The Lasting Impact of EYBS on Young Breeders 

When young breeders come home from the European Young Breeders School (EYBS), their success stories spread across the dairy farming industry. Erica Rijneveld, a longtime tutor, has seen several young talents grow. “I’ve dealt with many passionate young breeders over the years. “The transformation they go through in just a week is unbelievable,” she says. Rijneveld underlines, “It’s incredible to see them grow not just in skills but also in confidence and teamwork.”

Take Kate Cummings, who competed in animal preparation methods and finished sixth in the 24-25-year-old handlers class at 2023 school. She recalls, “The experience was incredible.” I got insights that textbooks could never provide. The friendships and worldwide contacts I’ve acquired are invaluable.”

Felix Lemire of Canada is another outstanding performer. In 2022, he became the Champion Showman. His success sparked interest in Quebec, highlighting EYBS’s global reach. Over 2,000 students have benefitted from the school’s practical days and exciting performances.

Brad Seager of New Zealand also made news by finishing third in the July 2022-born heifer conformation class. His participation demonstrates the program’s breadth and capacity to develop champions from all around the world. When questioned about his experience, Brad said it was more than just about the competition. The training sessions were eye-opening, and the mentors were highly inspirational.

Statistics support these anecdotal results. Over 150 young breeders from 16 countries participated in 2023 alone, promoting considerable skill development and cultural interaction. Furthermore, many graduates own profitable dairy farms or become notable leaders in cow breeding circles, demonstrating the program’s lasting significance.

Longtime educator Erica Rijneveld states, “The true victory isn’t the prizes they get; it’s the lifetime love for cattle breeding that EYBS instills. “That is the true measure of our success.”

Beyond the Classroom: How EYBS Shapes Future Leaders in Dairy Farming 

The influence of the European Young Breeders School (EYBS) goes well beyond the immediate educational advantages for the young participants. EYBS successfully shapes future cow breeding leaders and innovators by instilling a love for dairy farming and giving hands-on experience. These young breeders improve their animal preparation and presentation abilities while learning essential marketing, collaboration, and cultural exchange lessons. As they return to their home countries, equipped with new information and a worldwide network, they serve as advocates for the best dairy farming methods.

Furthermore, the program’s focus on critical and honest self-assessment helps participants cultivate an attitude of ongoing growth. This mindset is essential for innovation in the dairy business, as changing problems need adaptable and forward-thinking approaches. Participating in EYBS exposes young breeders to cutting-edge methods and technology, preparing them to drive advances in cow breeding and farm management.

Another significant long-term advantage is the expansion of international collaboration. EYBS relationships often develop in global partnerships, allowing for sharing ideas and practices that may lead to industry-wide advancements. As young breeders advance into leadership positions, these linkages contribute to a more unified and creative global dairy community.

The success of previous participants demonstrates the program’s effectiveness. Many EYBS graduates have achieved substantial success in their disciplines, helping to enhance animal genetics, sustainable farming techniques, and dairy management. These success stories motivate the next generation of young breeders, resulting in a mentoring and excellence cycle that benefits the dairy business.

The European Young Breeders School is more than just a training program; it drives long-term development and innovation in the dairy sector. By developing the abilities and goals of young breeders today, we assure a better, more sustainable future for dairy farming worldwide.

The Backbone of EYBS: Uniting Forces to Cultivate Future Dairy Leaders

The Association Wallonne des Eleveurs (Elevéo and Inovéo) is instrumental in organizing and sponsoring the European Young Breeders School (EYBS). They are the primary organizers, ensuring that each edition of the school works smoothly and efficiently. This includes handling logistics, collaborating with overseas teams, and controlling the overall event organization.

Elevéo and Inovéo are not alone in their attempt. The Battice Agriculture Fair is a significant contributor, providing financial assistance and a platform for worldwide dairy farming enthusiasts. Holstein Quebec, another important partner, helps financially by organizing judges and assuring the quality of training programs.

Furthermore, additional sponsors assist with grants and gifts, helping offset costs and allowing inexperienced breeders to participate without incurring excessive expenditures. This collaborative effort demonstrates the community’s commitment to nurturing young talent in cattle breeding, ensuring that the EYBS continues to inspire and elevate future generations of the profession.

The Bottom Line

The European Young Breeders School (EYBS) in Belgium is more than an event; it’s a training ground for future dairy industry executives. From its modest regional origins to a worldwide meeting of young talents from 23 nations, the EYBS has provided a unique combination of hands-on training and exhilarating contests. Its focus on hands-on instruction in cattle preparation, marketing, and showmanship, all in a multicultural setting, develops young enthusiasts into professional, informed breeders.

What distinguishes the EYBS is its emphasis on cultural interaction and personal growth. Participants enhance their technical skills while living with local families and socializing with peers from all over the globe. They also form long-lasting friendships and create professional networks. This worldwide partnership provides the groundwork for a more connected and collaborative future in the dairy business.

Programs like the EYBS remind us of the potential that awaits the next generation. But what if every nation made equivalent investments in fostering young agricultural talent? Could we be on the verge of a worldwide dairy farming revolution spearheaded by motivated and well-trained young leaders?

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Harnessing the Power of Machine Learning to Decode Holstein Cow Behaviors

Sunday, June 30th, 2024

Explore the transformative potential of machine learning in dairy farming. Can artificial intelligence refine behavior predictions and boost efficiency in your dairy operations?

The potential of machine learning developments to transform genetic predictions using massive datasets and advanced algorithms is a reason for optimism. This transformation can significantly improve cow well-being and simplify dairy running. By rapidly processing enormous amounts of data, machine learning provides insights often lost by more conventional approaches. Incorporating artificial intelligence and machine learning into genetic prediction can lead to a more robust and productive herd, advancing animal welfare and farm profitability.

A recent Journal of Dairy Science study compared traditional genomic methods with advanced deep learning algorithms to predict milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows. This research reveals how these technologies could improve the precision of genetic prediction for cattle behavioral features.

Breaking the Mold: Traditional Genomic Methods vs. Deep Learning 

Reliable tools in dairy cow breeding have included traditional genomic prediction techniques like BLUP (Best Linear Unbiased Prediction) and its genomic equivalent, GBLUP. These techniques, which have been used for decades, estimate breeding values using genetic markers. They presume linear genetic effects, which could not fairly depict complicated gene interactions. Additionally challenging with big datasets and needing a lot of processing capability are BLUP and GBLUP.

One fresh direction is provided by deep learning. Unlike conventional techniques, algorithms like convolutional neural networks (CNN) and multiple-layer perceptron (MLP) shine at identifying intricate patterns in big datasets. Their ability to replicate nonlinear connections between genetic markers should raise forecasting accuracy. However, deep learning requires significant computing resources and knowledge, restricting its general use.

Diving Deep: Evaluating Advanced Genomic Prediction for Dairy Cow Behavior

The primary aim of this study was to evaluate how well traditional genomic prediction methods stack up against advanced deep learning algorithms in predicting milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows. With over 1.9 million daily records from nearly 4,500 genotyped cows collected by 36 automatic milking systems, our mission was to determine which methods provide the most accurate genomic predictions. We focused on four methods: Bayesian LASSO, multiple layer perceptron (MLP), convolutional neural network (CNN), and GBLUP. 

Data collection involved gathering daily records from nearly 4,500 genotyped Holstein cows using 36 automatic milking systems, also known as milking robots. This amounted to over 1.9 million records. Rigorous quality control measures were employed to ensure data integrity, resulting in a refined dataset of 57,600 SNPs. These practices were vital in excluding erroneous records and retaining high-quality genomic information for precise predictive modeling. 

Four genomic prediction methods were employed, each with unique mechanisms: 

  • Bayesian Least Absolute Shrinkage and Selection Operator (LASSO): This method uses a Bayesian framework to perform variable selection and regularization, enhancing prediction accuracy by shrinking less significant coefficients. Implemented in Python using Keras and TensorFlow, Bayesian LASSO is adept at handling high-dimensional genomic data.
  • Multiple Layer Perceptron (MLP): A type of artificial neural network, MLP consists of multiple layers designed to model complex relationships within the data. This deep learning model is executed with Keras and TensorFlow and excels at capturing nonlinear interactions among genomic markers.
  • Convolutional Neural Network (CNN): Known for detecting spatial hierarchies in data, CNN uses convolutional layers to identify and learn essential patterns. This method, also implemented with Keras and TensorFlow, processes genomic sequences to extract meaningful features influencing behavioral traits.
  • Genomic Best Linear Unbiased Prediction (GBLUP): A traditional approach in genetic evaluations, GBLUP combines genomic information with phenotypic data using a linear mixed model. Implemented with the BLUPF90+ programs, GBLUP is less computationally intensive than deep learning methods, albeit slightly less accurate in some contexts.

A Deep Dive into Predictive Accuracy: Traditional vs. Deep Learning Methods for Holstein Cow Behaviors 

Analysis of genomic prediction methods for North American Holstein cows offered intriguing insights. A comparison of traditional and deep learning methods focuses on two behavioral traits: milking refusals (MREF) and milking failures (MFAIL). Here’s the accuracy (mean square error) for each: 

  • Bayesian LASSO: 0.34 (0.08) for MREF, 0.27 (0.08) for MFAIL
  • Multiple Layer Perceptron (MLP): 0.36 (0.09) for MREF, 0.32 (0.09) for MFAIL
  • Convolutional Neural Network (CNN): 0.37 (0.08) for MREF, 0.30 (0.09) for MFAIL
  • GBLUP: 0.35 (0.09) for MREF, 0.31 (0.09) for MFAIL

Although MLP and CNN showed slightly higher accuracy than GBLUP, these methods are more computationally demanding. More research is needed to determine their feasibility in large-scale breeding programs.

Paving the Way for Future Dairy Practices: Deep Learning in Genomic Prediction 

The promise of deep learning approaches in the genetic prediction of behavioral characteristics in North American Holstein cattle is underlined in this work. Deep learning models such as the Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) showed somewhat better accuracies in estimating milking refusals (MREF) and milking failures (MFAIL) than conventional approaches such as GBLUP—this rise in forecast accuracy results in better breeding choices and more efficiency in dairy businesses.

Still, the advantages come with some problematic drawbacks. Deep learning techniques require significant computing resources and knowledge, which would only be possible for larger farms or companies. Moreover, with specific understanding, these intricate models might be more accessible for farm managers to understand and use.

Another critical concern is the pragmatic implementation of these cutting-edge techniques. Usually requiring extensive genotype data, deep learning models find it challenging to handle nongenotyped individuals, limiting their flexibility and general relevance in different dairy farming environments.

Although deep learning methods show great potential, their acceptance has to be carefully evaluated against the logistical and practical reality of dairy production. Future studies should focus on these computational and pragmatic issues to effectively include cutting-edge solutions in regular dairy operations and optimize the advantages of technology development.

Bridging the Tech Divide: Practical Steps for Implementing Genomic Prediction and Machine Learning in Dairy Farming 

Integrating genomic prediction and machine learning into dairy farm operations may initially seem daunting. Still, it can significantly enhance herd management and productivity with the right approach and resources. Here are some practical steps and tools to get you started: 

  1. Educate and Train: Begin by educating yourself and your team about the basics of genomic prediction and machine learning. University extension programs, online courses, and industry seminars can provide valuable knowledge. 
  2. Invest in Data Collection Systems: Accurate data collection is vital. Consider investing in automatic milking systems (AMS) and IoT devices that collect detailed behavioral and production data. Brands such as DairyComp, DeLaval, and Lely offer robust systems for dairy farms.
  3. Use Genomic Testing Services: Engage with genomic testing services that can provide detailed genetic profiles of your herd. Many AI companies offer DNA testing kits and genomic analysis for dairy cattle. 
  4. Leverage Software Solutions: Use software solutions to analyze the data collected and provide actionable insights. Programs such as Valacta and ICBF offer comprehensive genetic evaluation and management tools. 
  5. Collaborate with Researchers: Contact local agricultural universities or research institutions conducting genomic prediction and machine learning studies. Collaborative projects can provide access to cutting-edge technologies and the latest findings in the field. 
  6. Pilot Small Projects: Start with small-scale projects to test the effectiveness of these technologies on your farm. Monitor the outcomes closely and scale up gradually based on the results. This approach minimizes risks and helps you understand the practical aspects of implementation. 

By taking these steps, dairy farmers can begin harnessing the power of genomic prediction and machine learning, paving the way for more personalized and efficient herd management. Integrating these advanced technologies promises to transform dairy farming into a more precise and productive endeavor.

The Bottom Line

Investigating genomic prediction techniques has shown deep learning algorithms’ potential and present limits against conventional approaches. According to the research, deep learning models such as CNN and MLP are more accurate in forecasting cow behavioral features like milking refusals and failures. However, their actual use in large-scale dairy production still needs to be discovered. The intricacy and computing requirements of these cutting-edge techniques hinder their general acceptance.

Here are some key takeaways: 

  • Deep learning methods offer slightly better accuracy than traditional approaches.
  • Traditional methods like GBLUP are still valuable due to their lower computational needs and broader applicability.
  • More research is needed to see if deep learning can be practically implemented in real-world dairy breeding programs.

In summary, continued research is crucial. We can better understand their potential to revolutionize dairy breeding at scale by refining deep learning techniques and addressing their limits. 

Adopting new technologies in genomic prediction guarantees better accuracy and ensures these approaches are valuable and practical. The balance of these elements will determine the direction of dairy farming towards effective and sustained breeding campaigns. We urge industry players, academics, and dairy producers to fund more studies. Including modern technologies in dairy farming may change methods and propel the sector toward more production and efficiency.

Key Takeaways:

  • Traditional genomic prediction methods like GBLUP remain robust but show slightly lower predictive accuracy compared to deep learning approaches.
  • Deep learning methods, specifically CNNs and MLPs, demonstrate modestly higher accuracy for predicting cow behavioral traits such as milking refusals and milking failures.
  • MLP methods exhibit less reranking of top-selected individuals compared to other methods, suggesting better consistency in selection.
  • Despite their promise, deep learning techniques require significant computational resources, limiting their immediate practicality for large-scale operations.
  • Further research is essential to assess the practical application of deep learning methods in routine dairy cattle breeding programs.

Summary:

Machine learning has the potential to revolutionize genetic predictions in dairy farming by using massive datasets and advanced algorithms. A study compared traditional genomic methods with deep learning algorithms to predict milking refusals and failures in North American Holstein cows. Traditional genomic methods like BLUP and GBLUP are reliable but require significant computing resources and knowledge. Deep learning algorithms like CNN and MLP show promise in genetic prediction of behavioral characteristics in North American Holstein cattle. However, deep learning requires significant computing resources and knowledge, which would only be possible for larger farms or companies. Additionally, deep learning models struggle to handle nongenotyped individuals, limiting their flexibility and relevance in different dairy farming environments. Integrating genomic prediction and machine learning into dairy farm operations can significantly enhance herd management and productivity. Practical steps to get started include educating and training, investing in data collection systems, using genomic testing services, leveraging software solutions, collaborating with researchers, and piloting small projects. More research is needed to understand the potential of deep learning techniques to revolutionize dairy breeding at scale.

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