Spotty liver disease (SLD) causes substantial egg production losses and chicken mortality; therefore, it is a disease that concerns Australian egg farmers. Over the last few decades, much research has been conducted to determine the etiologic agents of SLD and to develop potential therapeutics; however, SLD still remains a major issue for the chicken industries globally and remained without the elucidation of potentially multiple pathogens involved. To help fill this gap, this study was aimed at understanding the viral diversity of bile samples from which the SLD-causing bacterium, Campylobacter hepaticus, has been isolated and characterised. The collected samples were processed and sequenced using high-throughput next-generation sequencing. Remarkably, this study found 15 galliform chaphamaparvoviruses (GaChPVs), of which 14 are novel under the genus Chaphamaparvovirus. Among them, nine were complete genomes that showed between 41.7% and 78.3% genome-wide pairwise similarities to one another. Subsequent phylogenetic analysis using the NS1 gene exhibited a multiple incursion of chaphamaparvovirus lineages, including a novel lineage of unknown ancestral history in free-range laying chickens in Australia. This is the first evidence of circulating many parvoviruses in chickens in Australia, which has increased our knowledge of the pathogen diversity that may have an association with SLD in chickens.

Context Heat stress is an increasing concern for the Australian dairy industry.Aims This study aimed to evaluate the effect of temperature–humidity index (THI) on rumination time (RT), milk yield and quality, and milking frequency in a pasture-based voluntary-movement automatic milking system (AMS).Methods Data were collected from the University of Melbourne Dookie College AMS farm for 3years (June 2016 to March 2019). Daily RT was collected through the transponder collar (Qwes-HR, Lely). Climatic data (maximum ambient temperature and relative humidity) were obtained from the Dookie Meteorological station to calculate daily maximum THI (THImax).Key results Daily milk yield increased with a rising THImax to 65, then declined after THImax 65. Milking frequency was highest at THImax 90, followed by a steady decline afterwards. Rumination time was maximum at mid-range THImax and declined for high and low values.Conclusions The findings of this study clearly indicated that under pasture-based voluntary-movement AMS, high THI resulted in a drop in the milk yield, milking frequency and RT.Implications With the provision of automation of data collection from AMS, further study with mathematical modelling describing the daily patterns and thresholds in conjunction with the different heat stress levels can be useful for assessing animal welfare and to mitigate heat stress and seek alternative management strategies. Context Heat stress is an increasing concern for the Australian dairy industry.Aims This study aimed to evaluate the effect of temperature–humidity index (THI) on rumination time (RT), milk yield and quality, and milking frequency in a pasture-based voluntary-movement automatic milking system (AMS).Methods Data were collected from the University of Melbourne Dookie College AMS farm for 3years (June 2016 to March 2019). Daily RT was collected through the transponder collar (Qwes-HR, Lely). Climatic data (maximum ambient temperature and relative humidity) were obtained from the Dookie Meteorological station to calculate daily maximum THI (THImax).Key results Daily milk yield increased with a rising THImax to 65, then declined after THImax 65. Milking frequency was highest at THImax 90, followed by a steady decline afterwards. Rumination time was maximum at mid-range THImax and declined for high and low values.Conclusions The findings of this study clearly indicated that under pasture-based voluntary-movement AMS, high THI resulted in a drop in the milk yield, milking frequency and RT.Implications With the provision of automation of data collection from AMS, further study with mathematical modelling describing the daily patterns and thresholds in conjunction with the different heat stress levels can be useful for assessing animal welfare and to mitigate heat stress and seek alternative management strategies.

This study aimed to identify suitable predictors of nitrogen (N) use efficiency (NUE; milk N/N intake) for cows that differed in breeds and were fed with ryegrass pasture, using existing data from the scientific literature. Data from 16 studies were used to develop models based on the relationships between NUE and dietary and animal-based factors. Data from a further 10 studies were used for model validation. Milk urea N (MUN) and dietary water-soluble carbohydrate-to-crudeprotein ratio (WSC/CP) were the best and most practical animal- and diet-based proxies to predict NUE. The results indicate that it might be necessary to adopt separate models for different breeds when using WSC/CP to predict NUE but not when using MUN.

Viral diseases pose significant threats to aquaculture industries worldwide, including the Australian fish and prawn farming sectors, which contribute over AUD 1.6 billion annually to the national economy. The Australian aquaculture industry relies heavily on wild-caught broodstock for seedstock production, introducing substantial and unprecedented biosecurity risks. This systematic review consolidates current knowledge on the viral pathogens affecting key Australian fish and prawn species, their economic impacts, and the biosecurity measures implemented for mitigation. Notably, viral outbreaks have led to losses exceeding AUD 100 million in some sectors, highlighting the urgent need for improved management. Existing biosecurity strategies, including surveillance systems, molecular diagnostics, and pathogen exclusion protocols, are critically assessed for their effectiveness. Emerging approaches such as genetic resistance breeding, advanced vaccination technologies, and integrated risk management frameworks are also explored. Key knowledge gaps, particularly in the context of emerging viral pathogens and their ecological interactions under changing environmental conditions, are identified as priority areas for future research. This review emphasises the necessity of adopting a multidisciplinary approach to enhance the resilience of Australian aquaculture, advocating for stronger biosecurity frameworks and innovative technologies to mitigate the escalating risks posed by viral diseases.

Context: While several studies have documented the consistency of milking order and its association with milk yield in herds with conventional milking systems, there is limited data available on herds in the automatic milking systems (AMS) where cows move to the dairy voluntarily to be milked. Aims: The present study was conducted to examine the consistency of milking order in AMS and its association with milk yield and cow characteristics. Methods: The study was performed at The University of Melbourne Dookie Dairy in northern Victoria, Australia. The milking herd had up to 158 Holstein–Friesian cows in a pasture-based AMS with a three-way grazing system. The study utilised the individual-cow milking times, parity number, days in milk and data on daily production (milk yield in kilograms, fat and protein percentages and liveweight) from August 2017 till April 2018. Monthly milking order was determined for each milking session by ranking individual cows on the basis of their recorded time of milking. Key results: A consistent milking order was observed with the order of cows at the beginning (percentile rank position 0–33) and end of the milking order (percentile rank position 68–100) being less variable than cows in the middle positions. Milking orders from any two consecutive months were highly correlated (P < 0.01). Energy-corrected milk yield was negatively associated with the milking position (5 of 9 months) and days in milk (8 of 9 months), but positively associated with parity number and liveweight (5 of 9 months). The cow factors such as energy-corrected milk yield, liveweight, parity and days in milk were poor predictors of milking order. This suggests that other factors such as health and social dominance might be of importance. Conclusions: This observational study indicated that cows at the beginning of the milking order have a higher milk yield than do cows at the end of the milking order in pasture-based automatic milking systems. Implications: Grazing-management strategies that allow cows at the end of the milking order to access fresh pasture are worthy of further investigation.

Roughage constitutes a fundamental component of dairy cow diets; it promotes rumen health and supports optimal animal productivity. This study applied an ANKOM gas production system to assess the in vitro fermentation characteristics of seven widely used dairy roughages (barley hay, corn silage, lucerne hay, oaten hay, ryegrass hay, timothy hay and wheaten hay) classified into relatively high and low nutritive value groups. Roughage samples representing high and low nutritive values were selected based on the upper and lower quartiles of the feed quality database. The results showed that high‐nutritive value oaten hay exhibited higher dry matter (DM) digestibility (0.50 vs. 0.24–0.43 g/g DM, p < 0.05), total gas production (87.5 vs. 15.3–81.0 mL/g DM) and total volatile fatty acid (63.2 vs. 39.3–62.5 mM) than other roughages. High‐nutritive value barley hay and oaten hay both exhibited higher methane production (7.58 and 7.77 mL/g DM, respectively) compared to other roughages (0.44–4.76 mL/g DM). Similarly, high‐nutritive value barley hay (40.23 mg/100 mL) and lucerne hay (40.76 mg/100 mL) exhibited higher ammonia nitrogen (12.16–31.99 mg/mL) than other roughages. High‐nutritive value oaten and barley hay promoted superior fermentation performance but also led to greater methane emissions, while barley and lucerne hay increased nitrogen release. These results underscore the need to balance productivity with environmental impacts when selecting roughages for dairy systems.