Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R²) = 0.67–0.68 and a root mean square error (RMSE) between 5.43–7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59–5.44 g and 22–28%, respectively. For the FHY, R² values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between ~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs.

Body condition scoring is a valuable tool used to assess the changes in subcutaneous tissue reserves of dairy cows throughout the lactation resulting from changes to management or nutritional interventions. A subjective visual method is typically used to assign a body condition score (BCS) to a cow following a standardized scale, but this method is subject to operator bias and is labor intensive, limiting the number of animals that can be scored and frequency of measurement. An automated three-dimensional body condition scoring camera system is commercially available (DeLaval Body Condition Scoring, BCS DeLaval International AB, Tumba, Sweden), but the reliability of the BCS data for research applications is still unknown, as the system’s sensitivity to change in BCS over time within cows has yet to be investigated. The objective of this study was to evaluate the suitability of an automated body condition scoring system for dairy cows for research applications as an alternative to visual body condition scoring. Thirty-two multiparous Holstein-Friesian cows (9 ± 6.8 days in milk) were body condition scored visually by three trained staff weekly and automatically twice each day by the camera for at least 7 consecutive weeks. Measurements were performed in early lactation, when the greatest differences in BCS of a cow over the lactation are normally present, and changes in BCS occur rapidly compared with later stages, allowing for detectable changes in a short timeframe by each method. Two data sets were obtained from the automatic body condition scoring camera: (1) raw daily BCS camera values and (2) a refined data set obtained from the raw daily BCS camera data by fitting a robust smooth loess function to identify and remove outliers. Agreement, precision, and sensitivity properties of the three data sets (visual, raw, and refined camera BCS) were compared in terms of the weekly average for each cow. Sensitivity was estimated as the ratio of response to precision, providing an objective performance criterion for independent comparison of methods. The camera body condition scoring method, using raw or refined camera data, performed better on this criterion compared with the visual method. Sensitivities of the raw BCS camera method, the refined BCS camera method, and the visual BCS method for changes in weekly mean score were 3.6, 6.2, and 1.7, respectively. To detect a change in BCS of an animal, assuming a decline of about 0.2 BCS (1–8 scale) per month, as was observed on average in this experiment, it would take around 44 days with the visual method, 21 days with the raw camera method, or 12 days with the refined camera method. This represents an increased capacity of both camera methods to detect changes in BCS over time compared with the visual method, which improved further when raw camera data were refined as per our proposed method. We recommend the use of the proposed refinement of the camera’s daily BCS data for research applications.

Feeding increased volumes of milk in the preweaning phase has been shown to improve growth, morbidity and mortality rates in calves (Bos Taurus). This experiment enlisted 20 Holstein-Friesian dairy replacement calves from birth until weaning (at 10 weeks of age) and assessed the effect of feeding either 4 L (Low) or 8 L (High) of milk per calf per day on their growth, immune competence and metabolic characteristics. The responsiveness of these systems was compared through a vaccination immune challenge. Calves in the High treatment group were significantly heavier from two weeks of age and were 19 kg heavier than calves in the Low treatment group at weaning. Calves in the High treatment group also exhibited greater immune responses, with significantly higher white cell counts and neutrophil counts than calves in the Low treatment group post-vaccination. Calves in the High treatment group also had lower beta-hydroxybutyrate both pre- and post-vaccination, and higher glucose and insulin levels post-vaccination, indicating superior metabolic characteristics. Calves had ad libitum access to lucerne hay (Medicago sativa) and a commercial concentrate. Solid feed intakes were mostly the same between treatments, with differences in hay intake only detected at 7 and 8 weeks of age. Results from this experiment are indicative of a positive influence of accelerated preweaning nutrition on growth, immune response and metabolic characteristics.

Perennial ryegrass (PRG) is an important forage grown on dairy farms in temperate regions globally, including south-eastern Australia. A forage value index (FVI) providing information on the seasonal production of commercially available PRG cultivars is currently available. Despite the importance of the nutritive value of pasture in dairy farm systems, the nutritive characteristics of PRG cultivars are not currently included in the FVI as they are not routinely measured in cultivar evaluation trials. This study investigated differences between cultivar functional groups (diploid and tetraploid). It also examined differences between individual cultivars within seasons at four locations in south-eastern Australia and examined how trial location affects cultivar ranking. Samples were collected from existing cultivar evaluation trials over a 3-year period and analysed for nutritive characteristics. There were differences (p < 0.05) between diploids and tetraploids for metabolisable energy (ME) and neutral detergent fibre (NDF) in each season at each location with a few exceptions in summer and autumn. Crude protein (CP) differed between functional groups in some seasons at some sites. Spearman rank correlations within season were strong for ME between trial locations (r = 0.78–0.96), moderate to high for NDF (0.51–0.86) and variable for CP (−0.69–0.56). These findings provide guidance on methods for implementing nutritive value testing in cultivar evaluation trials and support the imminent inclusion of ME in the Australian FVI. The ranking of cultivars for ME was more consistent across trial sites compared to NDF and CP, suggesting the latter two traits, in particular CP, are more sensitive to environmental influences. Based on these results, we do not recommend the inclusion of CP as an individual trait in the Australian FVI. A significantly larger dataset and further research on the genotype by environment interactions would be needed to reconsider this. The addition of ME in the Australian FVI will lead to better cultivar choices by farmers and could lead to more targeted perennial ryegrass breeding programs.

Pasture nutritive value is economically important in south-eastern Australian dairy production systems, yet measurement of nutritive characteristics in pasture cultivar evaluation trials is not routinely undertaken, primarily due to cost. An approach aiming to reduce the total laboratory analysis costs in multi-harvest field trials by testing some entries as composite samples is provided. A field trial evaluating 31 trial entries sown in 4 replicates was used. On nine harvest occasions, samples were collected from each plot, dried, ground and analysed using near infrared spectroscopy for key nutritive characteristics (metabolisable energy (ME), crude protein (CP) and neutral detergent fibre (NDF)). Additionally, composite samples of 17 of the 31 entries from each harvest were created by combining sub-samples of material from each of four replicate plots into a single sample that was also analysed. A linear mixed model (LMM) analysis accounting for spatial and temporal variation as well as spatial and temporal correlations was conducted, comparing the full data model where all plots at all harvests were tested individually to a data model where some entries were evaluated as individual plots and others as composites. The precision and accuracy of the estimates for the two models were similar and best linear unbiased prediction (BLUP) means of the composite sampling strategy model were comparable to the full data model. It was concluded that if composite sampling is used in conjunction with testing samples from individual plots on a selection of cultivars, statistically valid inferences are possible and the total cost of determining the nutritive characteristics of perennial ryegrass cultivars in field trials can be reduced.

The frequency, duration, and intensity of heat waves in Australia are increasing. To reduce the impact of heat waves on milk production, novel management strategies are required. Altering the forage type and amount offered affect the heat load on dairy cows and offer potential strategies to ameliorate the effects of hot weather. Thirty-two multiparous, lactating Holstein–Friesian cows were assigned one of four dietary treatments: chicory high amount, chicory low amount, pasture silage high amount, or pasture silage low amount. These cows were exposed to a heat wave in controlled-environment chambers. Cows that were offered fresh chicory had similar feed intake to cows that were offered pasture silage (15.3 kg DM/d). However, cows that were offered chicory produced greater energy-corrected milk (21.9 vs. 17.2 kg/d) and had a lower maximum body temperature (39.4 vs. 39.6 °C) than cows that were offered pasture silage overall. Cows that were offered the high amount of forage had greater feed intake (16.5 vs. 14.1 kg DM/d) and energy corrected milk yield (20.0 vs. 17.9 kg/d) than cows that were offered the low amount, as intended, but with no difference in maximum body temperature (39.5 °C). We conclude that feeding chicory instead of pasture silage to dairy cows shows promise as a dietary strategy to ameliorate the effect of heat exposure, and there was no advantage in restricting feed amount.