Outline

Overview

This unit of study is designed to provide students with an advanced understanding of new and emerging livestock technologies in Australia and overseas. Examples of these technologies include (1) next-generation infrared and laser scanning to determine physiological status and whole body composition, (2) diet formulation to enhance the nutritional and eating quality of livestock food products, (3) new vaccines and other therapeutics to regulate fertility, growth and behaviour whilst enhancing welfare and wellbeing, (4) microRNA technology to influence cellular, endocrine and physiological processes, (5) new genomics and laboratory-based reproductive technologies for advanced livestock breeding, (6) technologies to monitor and control animal behaviour, (7) unmanned ground and aerial vehicles to monitor livestock and the environment, (8) sensors and advanced image-capture technology to record the attributes of soil, air and the feedbase, (9) data-fusion science to integrate, analyse and interpret collected data, and (10) modelling of livestock systems. Students will gain research and inquiry skills through research based group projects, information literacy and communication skills through on-line discussion postings, laboratory reports and presentations, and personal and intellectual autonomy through working in groups. At successful completion of the unit students will have a sound knowledge of new and emerging technologies that will shape the livestock industries in Australia and overseas. This will provide valuable grounding for students preparing for postgraduate study and other learning and career paths.

Unit details and rules

Academic unit	Life and Environmental Sciences Academic Operations
Credit points	6
Prerequisites ?	48cp of 1000-3000 level units including at least 6cp of BIOL1XXX
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Luciano Gonzalez, luciano.gonzalez@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Practical report 2 - Animal behaviour Practical report	10%	Mid-semester break Due date: 27 Sep 2021 at 23:59 Closing date: 04 Oct 2021	1000 words
Outcomes assessed:
Assignment	Start-up booklet submission Final assignment booklet	40%	STUVAC Due date: 19 Nov 2021 at 23:59 Closing date: 26 Nov 2021	3000 words
Outcomes assessed:
Assignment	Practical report 1 – Weighing systems and model data fusion Practical report	10%	Week 04 Due date: 30 Aug 2021 at 23:59 Closing date: 06 Sep 2021	1000 words
Outcomes assessed:
Assignment	Short video proposal start-up or technical booklet Video proposal	10%	Week 08 Due date: 07 Oct 2021 at 23:59 Closing date: 14 Oct 2021	5 min
Outcomes assessed:
Assignment	Practical report 3 - Environmetn + Remote sensing Practical report	10%	Week 11 Due date: 25 Oct 2021 at 23:59 Closing date: 01 Nov 2021	1000 words
Outcomes assessed:
Presentation	Assignment presentation Presentation of the final start-up or technical information booklet	10%	Week 12	3 min/group member to present + 0.5 m pe
Outcomes assessed:
Assignment	Practical report 4 - Dairy technologies Practical report	10%	Week 13 Due date: 08 Nov 2021 at 23:59 Closing date: 15 Nov 2021	1000 words
Outcomes assessed:
= group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Tutorial/Apps practical	Online class (3 hr)
Week 02	Body monitoring of animals	Online class (2.5 hr)
Week 02	Remote weighing practical	Practical (3 hr)
Week 03	Precision feeding and model-data fusion	Online class (2.5 hr)
Week 03	Model-data fusion practical	Online class (3 hr)
Week 04	Physiological monitoring of animals	Lecture (2.5 hr)
Week 04	IRT image analysis	Practical (3 hr)
Week 05	Practical beef cattle and sheep (replacing field day online)	Practical (5 hr)
Week 06	Animal behaviour 1	Lecture (2.5 hr)
Week 06	Animal behaviour 1 practical	Practical (3 hr)
Week 07	Animal behaviour 2	Online class (2.5 hr)
Week 07	Animal behaviour practical 2	Online class (3 hr)
Week 08	Precision agriculture	Lecture (2.5 hr)
Week 08	Precision ag practical	Computer laboratory (3 hr)
Week 09	Environment	Practical (3 hr)
Week 09	Environmental monitoring	Lecture (2.5 hr)
Week 10	Remote sensing	Lecture (2.5 hr)
Week 10	Remote sensing practical	Practical (3 hr)
Week 11	Technology to improve animal health and welfare	Lecture (2.5 hr)
Week 11	Welfare Data analysis	Practical (3 hr)
Week 12	On-farm automation of repetitive tasks	Lecture (2.5 hr)
Week 12	Dairy robotics practical	Practical (3 hr)
Week 13	Final presentations start-up or technical booklet	Lecture and tutorial (5 hr)

Attendance and class requirements

Attendance is expected for all lectures and practicals

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Prescribed reading will be made available in Canvas

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

LO1. describe the principles of using new technologies and approaches for precision animal management. Outline definitions, concepts and approaches around remote sensing, monitoring and automated management systems
LO2. list and explain the technologies used to monitor the physical body of animals, their uses and applications including live weight, body composition and size, and animal identification
LO3. present the concepts of using and combining new technologies into frameworks to develop new feeding systems in animal production and to manage animal nutrition using automatic control feeding systems, animal performance data and models
LO4. outline technologies to measure physiological conditions of animals including body temperature, heart rate, blood and rumen liquid composition, and electrophysiology (EEG, ECG, photoplethysmography, etc)
LO5. describe the use of new technologies to monitor animal behaviour and the role these technologies can play to improve animal conservation, productivity, sustainability and welfare
LO6. explain main principles of remote sensing for vegetation monitoring and landscape condition assessment, list and calculate relevant measures and indicators using remote sensing technologies and give examples of practical applications in animal management and landscape assessment
LO7. overview technologies to measure a range of characteristics in soil, water and the biophysical environment relevant to livestock production and wildlife including chemical composition (gases, nutrients, and pollutants), physical characteristics (moisture, water levels, temperature, conductivity, reflectance, etc.), weather forecasts, and models
LO8. present principles and concepts of precision agriculture applied to crops and pasture production, vegetation monitoring, and landscape condition assessment. Understand the different Global Navigation Satellite Systems and their applications in animal sciences
LO9. demonstrate methods used for early diagnosis and treatment of health and welfare issues of animals using new technologies with particular emphasis on the dairy industry
LO10. describe concepts and examples of machine vision and automatic video image analysis, and its application in agriculture, animal production and wildlife management
LO11. introduce technologies for the automation of repetitive tasks in the dairy industry including milking robots, herding and monitoring robots, and automated animal management. Assess the potential of technologies to save time and money, and improve animal management
LO12. define robots and describe the principles of robotics and the latest developments for applications in agriculture and animal science.
LO13. communicate in ways that are effective, appropriate and persuasive for farming and scientific audiences, and collaborate effectively.
LO14. work in groups to solve problems and contribute to class discussions.
LO15. Work individually to prepare and present a report, presentation or debate on a topic in class.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Changes are adaptations to the new COVID conditions, all online.

Additional information

Q fever requirements only for field classes if possible due to COVID

Site visit guidelines

Attendance to lectures, parcticals and field days will depend on COVID restrictions

Work, health and safety

Q-fever vaccination and completion of the Canvas module “Zoonosis Awareness” is compulsory.

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General Laboratory Safety Rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

AGRO4006: New and Emerging Tech in Animal Science

Semester 2, 2021 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect