72472 - Ruminant Production

Learning outcomes

At the end of the course, students will have acquired fundamental knowledge of meat and milk production systems.

In particular, students will be able to:

• understand the main stages of meat and milk production systems and identify the factors affecting production efficiency as well as the quantity and quality of animal products;
• critically compare different livestock production systems in terms of their economic profitability and the sustainability of animal production;
• access, interpret, and use information on productive traits and the genetic merit of breeding animals to support informed management and breeding decisions.

Course contents

Module 1 – Ruminant Production Systems

• Evolution of ruminant livestock production.
• Cattle, sheep, and goat production systems.
• Intensive, extensive, and organic farming systems.
• Organization and management of livestock farms.
• Technical and productive performance indicators.

Module 2 – Management of Ruminants at Different Production Stages

• Replacement stock management.
• Dairy cow management.
• Beef cattle management.
• Sheep and goat management.
• Animal welfare across different production categories.
• Key productive performance indicators.

Module 3 – Feeding and Nutritional Management

(Key concepts are assumed to have been acquired in the course "Animal Nutrition".)

• Feeding management.
• Forages and grazing systems.
• Nutritional management at different physiological and productive stages.
• Precision feeding.
• Feed efficiency.

Module 4 – Review of Reproduction and Genetic Improvement Applied to Ruminant Production

(The fundamental concepts covered in this module are assumed to have been acquired in the course "Animal Breeding and Genetics".)

• Reproductive management.
• Artificial insemination.
• Genetic selection.
• Genomics.
• Pedigree and breeding record management.

Module 5 – Ruminant Production Supply Chains

• Milk production.
• Meat production.
• Product quality.
• Certification schemes, animal welfare, and quality assurance within livestock supply chains.
• Innovation in ruminant production chains.

Module 6 – Introduction to Innovation and Sustainability in Ruminant Farming

• Precision Livestock Farming.
• Sensor technologies for livestock monitoring.
• Introduction to sustainability in ruminant production systems.

Readings/Bibliography

The teaching materials consist of the two recommended textbooks, together with the lecture materials presented during class and made available to students through the University's VIRTUALE online learning platform.

Two textbooks are recommended:

1. General principles of ruminant production

Sandrucci A., Trevisi E. Produzioni animali. EDISES Università, Naples, 2022.

Students are recommended to consult the following concise chapters (each approximately 12 pages or less):

• Chapter 4: Selection and genetic improvement of dairy cattle
• Chapter 5: Physiology of lactation
• Chapter 10: Rearing of dairy calves and replacement heifers
• Chapter 15: Environmental sustainability of milk production
• Chapter 17: Sheep production
• Chapter 18: Goat production
• Chapter 22: Selection and genetic improvement of beef cattle
• Chapter 23: Growth and development of beef cattle
• Chapter 24: Veal calf production
• Chapter 25: Intensive beef cattle production
• Chapter 27: Transport and slaughter of cattle
• Chapter 28: Carcass classification and beef quality
• Chapter 30: Environmental sustainability of beef production

2. Ruminant nutrition

Ronchi B., Savoini G., Trabalza-Marinucci M. Manuale di nutrizione dei ruminanti da latte. EDISES Università, Naples, 2019.

Students are recommended to consult the following chapters:

Chapter 5 – Feeding programmes for productive animals

• Dairy cattle: Sections 5.1–5.2
• Sheep: Sections 5.8–5.10
• Goats: Section 5.11

Chapter 6 – Feeding programmes for growing and breeding animals

Chapter 9 – Nutrition and environmental impact

Teaching methods

The course will be taught in Italian through a combination of the following teaching and learning activities:

• Lectures: lectures will provide the fundamental knowledge, principles, and theoretical background related to the topics covered in the course.
• Seminars: seminars delivered by the course instructor and guest speakers will include presentations and interactive discussions, encouraging critical reflection on specific topics and scientific approaches.
• Discussion- and research-based learning: students will actively participate in guided discussions and research-oriented activities, developing skills in scientific reasoning, critical thinking, and the interpretation of scientific evidence.

Assessment methods

Student learning will be assessed through a final oral examination in Italian.

During the oral examination, students will be assessed on both their theoretical knowledge and their ability to apply it to the topics covered during the course. The evaluation will take into account the overall level of preparation, the ability to critically analyse and establish connections among the different course topics, as well as the appropriate use of technical and discipline-specific terminology. The examination will consist of at least four questions, covering the entire course syllabus.

The first question will focus on a topic chosen by the student. Students may support their presentation with PowerPoint slides, allowing them to demonstrate their ability to synthesize information and communicate scientific concepts effectively.

To pass the examination, students must obtain a minimum mark of 18/30.

The final grade will be awarded according to the following criteria:

• 30–30 cum laude: comprehensive and in-depth knowledge of the course topics, excellent critical thinking and ability to integrate concepts across different subject areas, and full command of the appropriate scientific and technical terminology.
• 27–29: thorough knowledge of the course topics, good analytical and critical thinking skills, and appropriate use of discipline-specific terminology.
• 23–26: adequate technical preparation, satisfactory analytical skills, although not particularly in-depth, and clear communication using appropriate language.
• 18–22: sufficient knowledge of the fundamental course topics, basic analytical skills, and communication that is formally acceptable.

Insufficient preparation, inappropriate use of technical terminology, or an inability to demonstrate familiarity with the course topics and teaching materials will result in failure to pass the examination.

Use of Artificial Intelligence during the examination: the use of Artificial Intelligence (AI) tools during the oral examination is strictly prohibited. Any use of AI constitutes a violation of academic integrity.

The oral examination lasts at least 25 minutes.

Students with Specific Learning Disorders (SLDs) or temporary or permanent disabilities may take the examination using concept maps and/or other approved accommodations, in accordance with current legislation and University regulations. Students are encouraged to contact the University's Office for Students with Disabilities and Specific Learning Disorders well in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/en ). The Office will propose appropriate accommodations, which must be submitted to the course instructor for approval at least 15 days before the examination. The instructor will assess their suitability in relation to the intended learning outcomes of the course.

The dates, times, and venues of the examination sessions are published on the AlmaEsami platform. If necessary, students may also contact the course instructor to arrange an additional examination date when appropriate.

Teaching tools

The course will make use of the following teaching materials and learning resources:

• lecture slides and additional teaching materials prepared by the professor;
• original research articles and review papers from the scientific literature;
• seminars delivered by guest speakers and external experts;
• guided discussions and interactive classroom activities;
• student presentations and seminars.

The use of Artificial Intelligence (AI) is permitted to support students in studying the course materials and enhancing their understanding of the topics covered.

Regular attendance is strongly recommended, as it promotes a deeper understanding of the course content and encourages active participation in classroom discussions and learning activities.

Office hours

See the website of Martina Zappaterra