Innovation is at our core. We love learning new things about agriculture and applying new thinking to old problems. We regularly conduct research and development projects on behalf of industry organisations. We are very proud of our close collaborations with a range of leading industry organisations and universities across these projects.
neXtgen Agri is focused on applying machine learning and machine vision to the Australasian sheep industry.
We have collaborated with several organisations and universities to build and analyse some of the largest agricultural data sets created for the sheep industry.
One example is a 1.4 million image data set used to train a sheep recognition classifier. Our current research involves:
Maiden ewes can represent up to 30% of the whole farm ewe flock and their reproductive performance is usually 20-30% lower than that achieved at their subsequent joining.
We are partnering with Meat and Livestock Australia (MLA) and our producer network to demonstrate the impacts of adopting best-bet management of maiden ewes on their reproductive performance and carryover effects on subsequent performance. This 5-year project will enable participating producers to confidently improve their productive performance of maiden ewes.
This work is funded by MLA through their Producer Demonstration Site (PDS) initiative. For more information or to sign up to receive project updates please click on the below link:
On behalf of The New Zealand Merino Company (NZM) we are working toward a genetic solution to footrot.
We are developing a footrot breeding value that can be used to reduce the susceptibility of sheep to this debilitating disease. This project has been ongoing since 2012 and involves the Animal Genetics and Breeding Unit (AGBU) and Sheep Genetics.
The project has required significant collaboration with fine wool breeders across New Zealand. We run the NZM Central Progeny Test as part of this work program. We are making some serious inroads into finding footrot resistant fine-wool sheep. For more information contact us, or visit NZM's Perfect Sheep website.
Within the Grazing Bytes project we are investigating the ability to assess the amount of pasture that sheep are consuming out in the paddock, in real time.
The project is using Smart Tags that have been developed by Australian Wool Innovation (AWI) to undertake this work. If successful, the results from this project will enable producers to understand what is happening out in their paddocks with a lot more accuracy and allow for more targeted nutrition and more efficient pasture utilisation.
The project is using a combination of old science and very new science in the form of machine learning. We are hoping to achieve what has been thought of by many researchers in the past as the holy grail of sheep research –accurately assessing pasture intake of grazing sheep.
This is a collaborative project between Australian Wool Innovation, neXtgen Agri, Murdoch University, Muresk Institute and Agriculture Victoria.
We undertook a review of flystrike and proposing a research strategy for future research on this important topic.
We conducted this work on behalf of Meat and Livestock Australia.
To carry out this work we brought together an impressive line-up of flystrike gurus – Professor Herman Raadsma, Professor Bill Pomroy, Dr David Scobie alongside our own Dr Mark Ferguson.
This project gave us the opportunity to not just review what has been done to date but to do some blue sky thinking on what the focus of future research efforts could be.
The ability to detect animal behaviour using sensors has started to become a reality over the last few years.
In order to be able to use this new capability, the industry needs large banks of data that can be utilised to train algorithms. Within this project we are building the world’s largest sheep behaviour data bank.
This involves over 500 hours of video of sheep grazing, walking, sitting, standing and ruminating across a range of grazing scenarios. This footage is then meticulously examined to determine the activity of each of 10 sheep in 10 second intervals.
The sheep in the study have been fitted with a range of sensors. The sensor data is combined with the sheep behaviour data and this information is used to train a machine learning model.
This project is a collaboration between Meat and Livestock Australia, Murdoch University, neXtgen Agri, Muresk Institute and the Western Australian Department of Primary Industries and Regional Development.
We partnered with Meat and Livestock Australia (MLA) and our producer network to demonstrate the role that genetics can play - augmenting nutritional and management strategies - in improving ewe reproductive performance and lamb survival.
This work was funded by MLA through their Producer Demonstration Site (PDS) initiative. For more information about the project and its results, please click the link below.
