ALIC researchers have world-leading expertise in livestock genetics, ruminant nutrition and behaviour, greenhouse gas accounting, livestock methane mitigation, meat quality, animal physiology, animal welfare, and technology development and implementation.
ALIC has a history of world-leading research undertaken by our interdisciplinary collaborative teams over the past 25 years, in fields including residual feed intake, behaviour and temperament, consequences of maternal nutrition and growth path, developmental programming, methane production and mitigation, and genetic improvement of extensive livestock. Our team of scientists, technicians, and development and advisory staff were key participants in the Beef and Sheep CRCs and have been recognised through nominations and awards, including NSW Public Service Medals and Eureka Prizes, plus regular invitations to present research at both national and international conferences and symposia.
Key research areas currently being developed at ALIC include quantitative genetics, understanding and regulation of muscle and fat biology, meat quality, feed conversion efficiency at pasture, greenhouse gas measurement and abatement, climate change risk management, objective real-time animal assessment, and decision support systems.
The R&D program is focused to sustainably increase productivity and profitability of livestock systems as one of the key programs identified in the NSW DPI Strategic Plan 2019-2023. There are key themes that allow ALIC to deliver into this strategic vision, including livestock genetics, objective live animal and carcass assessment, ruminant nutrition and behaviour, animal welfare benchmarking, precision livestock, and climate change. The projects currently being conducted by ALIC researchers under these themes are detailed below.
Selection indexes combine the BREEDPLAN estimated breeding values (EBVs) to provide an indication of the impact an animal will have on commercial profitability, and are therefore the best tool for making livestock selection and purchase decisions to change profitability. BreedObject®, the software system for developing BREEDPLAN selection indexes, was developed by NSW DPI scientists and continues to be updated, now including sophisticated handling of feed costs and methane output. The tool is an integral component of the BREEDPLAN genetic evaluation system, and is used by beef cattle breeds and breeders across Australia and internationally to assist breeders to target the most valuable trait improvement, and bull-buyers to choose bulls best suited to their production systems and target markets.
Phenotypic and genetic relationship between retail beef yield (RBY), live animal and carcass traits – Linda Cafe
This project is generating RBY phenotypes on 1000 fully pedigreed, phenotypically and genetically described cattle to use in the re-estimation of the RBY parameters in BREEDPLAN, to provide more accurate carcass RBY EBVs that better describe the modern beef cattle population. Establishing the phenotypic and genetic relationships of RBY with other live and carcass parameters will allow more reliable selection of livestock with potential improvement in efficiency for the red meat industry.
Delivering resource populations for multi-breed genomic evaluation in beef cattle – Paul Arthur
Cattle from different breeds need to be compared head-to-head in different production environments to generate data that can be used to develop multi-breed genetic evaluations and thus multi-breed EBVs. Two thousand cows representing southern Australian breeds (Angus, Charolais, Hereford, Shorthorn, Wagyu) plus Brahmans are being run across seven NSW DPI Research Stations over five years. Cows were artificially inseminated in 2019 to produce the first calves that will be used in the project. The key objective is to enable beef producers across Australia to directly compare animals from different breeds for all BREEDPLAN traits and assess their genetic merit irrespective of colour.
DeSireBull™ is a decision support tool aiming to simplify genetic information and aid producers in finding the right bull for their production needs. This tool will use BreedObject® bio-economic models in an innovative way to allow flexibility in Index selection. DeSireBull™ aims to simplify use of BREEDPLAN genetic information for commercial bull buyers, and to enhance industry’s extension and adoption efforts to increase the rate of genetic gain in beef cattle.
Objective live animal assessment integrated with BeefSpecs – Malcolm McPhee
This project aims to develop a system using 3D cameras on live cattle to assess hip height, P8 fat and muscle score, in real-time, exploiting machine learning and statistical techniques applied on 3D images. The project strives to deliver a commercial-ready portable 3D camera technology for both on-farm and vertically-integrated supply chain use. The 3D camera technology will be integrated with the BeefSpecs drafting tool across Bos taurus breeds (pure Angus, Hereford, Shorthorn and Charolais). Outputs will include an iPhone/Android BeefSpecs Calculator app integrated with radio-frequency identification (RFID) and weight of individual animals with the BeefSpecs drafting tool. This integrated system will result in on-farm practice change for improved animal productivity and profitability (e.g. more efficient use of feed due to better management decisions and selecting for higher yielding cattle).
Visible-near infrared spectroscopy (Vis-NIRS) could be used to predict animal maturity and meat quality with the benefit to remove inconsistency associated with current dentition and ossification methods. An objective measurement of quality would result in a more reliable carcass description and thus a more accurate description of the value of a carcass. Based on that premise, this project will (a) develop a validation model for prediction of animal age by scanning cattle hides using a Vis-NIRS probe; (b) investigate the potential use of a Vis-NIRS probe to determine meat tenderness and connective tissue by scanning striploin and eye round muscles; and (c) apply the Vis-NIRS concept to the sheep industry in order to predict age/maturity and meat eating quality.
Identifying ‘better doers’ – Jude Bond
Animals that are able to utilise feed more efficiently are termed ‘better doers’. These animals grow faster or fatter for example, as a result of complex interactions between genetics and intracellular metabolic processes involving many proteins. The objective of this research is to enable sheep and beef producers to cost effectively identify animals early in life that are 'better doers', using a diagnostic test to improve productivity and profitability for producers.
Improving ruminant efficiency in converting feed into food requires better understanding of nutrient-host interactions in grazing behaviour, pasture intake and rumen efficiency. NSW DPI and CSIRO are using on-animal and in-field devices that link to wireless sensor networks to generate data on location, behaviours including grazing, ruminating, drinking, resting and walking in real time, animal performance and pasture characteristics. This multi-component interdisciplinary project, that also links with UNE School of Environmental and Rural Sciences and students, aims to identify more efficient grazing cattle and develop more efficient grazing systems, through understanding grazing behaviour, pasture intake and the rumen digestive/microbiome complex, and to apply this knowledge to practical feeding, management and breeding programs.
Revising Australian feeding standards – Hutton Oddy
NSW DPI has a long-standing interest in ruminant nutrition. This extends from determining requirements for drought feeding across all classes of livestock to increasing productivity through feeding for specific production targets. Information is provided to assist producers with supplementation to opportunity feedlot, and provision of feed analysis. To continue to underpin this research, the project is reconstructing the Australian Feeding Standards to better predict animal response to nutrient inputs. This includes development of protein prediction and fat deposition in a simpler way than is currently available. Over time the project will include improved methods for estimating intake on pastures so that supplementary feeding decisions can be made with more confidence. Practical outcomes of this work to date include release in 2019 of the Drought and Supplementary Feeding Calculator and the Wagyu Feeding App. The project includes ongoing development of tools to estimate carcass characteristics (yield, marbling and MSA grade) from live animal measurements and prediction of animal growth and carcass characteristics from feed information months prior to sale.
This project is developing an animal welfare benchmarking system for the extensive beef industry, built on the concept of welfare performance as a continuum rather than a pass/fail, and will enable industry to improve practices that affect animal welfare, and to demonstrate continual improvement in welfare over time. The framework will contribute to the maintenance of the sector’s social license to operate, and provide the basis for the development of welfare assurance schemes.
Precision livestock management for extensive grazing industries – Robin Dobos
Precision livestock management aims to increase efficiency of pasture and animal management by reducing the uncertainty associated with decision making. Research studies currently being conducted are aiming to collect and evaluate high resolution sensor data, from both animals and pasture, to improve sensor design and algorithm development on both research and commercial producer sites. The project will also create benefits for the producer (real-time remote monitoring of animals and pasture leading to better decisions), the consumer (transparency), general public (objective information and reducing environmental impact), policy makers (better information to inform their decisions), technology developers (information to target products), industry providers (update information to improve advice), breeders (phenotypic identification), veterinarians (health and welfare information) and researchers (new types of information on a larger scale).
Emissions reduction pathways for NSW primary industries – Annette Cowie
NSW has a target of net zero greenhouse gas emissions by 2050. The primary industries sector has the potential to sequester carbon, offsetting emissions from other sectors. This project aims to quantify the technical potential for emissions reduction and carbon sequestration across NSW primary industries, and to identify economic and social barriers to adoption along with measures to overcome them. It will identify strategies to incorporate emissions reduction and carbon sequestration activities, while preserving profitability and enhancing resilience of production systems. The project will support NSW landholders to generate income from carbon offsets and to access markets for carbon neutral products. The project will also devise plausible scenarios for emissions reduction pathways, and recommend policies to facilitate their delivery, supporting NSW in reaching net zero greenhouse gas emissions by 2050.
Current partners are located across NSW, Australia and overseas, contributing in diverse areas of R&D for the beef and sheep industries. Our current partners include the Animal Genetics and Breeding Unit, Angus Australia, John Dee Abattoir Warwick, Local Land Services, Commonwealth Scientific and Industrial Research Organisation, Meat & Livestock Australia Donor Company, Circul8, University of New England, University of Technology Sydney, Charles Darwin University, University of Western Australia, University of Queensland, Macquarie University, Deakin University, and University of California, among others.