This study aimed to develop empirical pasture dry matter (DM) yield prediction models using an unmanned aerial vehicle (UAV)-borne sensor at four flying altitudes. Three empirical models were developed using features generated from the multispectral sensor: Structure from Motion only (SfM), vegetation indices only (VI), and in combination (SfM+VI) within a machine learning modelling framework. Four flying altitudes were tested (25 m, 50 m, 75 m and 100 m) and based on independent model validation, combining features from SfM+VI outperformed the other models at all heights. However, the importance of SfM-based features changed with altitude, with limited importance at 25 m but at all higher altitudes SfM-based features were included in the top 10 features in a variable importance plot. Based on the independent validation results, data generated at 25 m flying altitude reported the best model performances with model accuracy of 328 kg DM/ha. In contrast, at 100 m flying altitude, the model reported an accuracy of 402 kg DM/ha which demonstrates the potential of scaling up this technology at farm scale. The spatial-temporal maps provide valuable information on pasture DM yield and DM accumulation of herbage mass over the time, supporting on-farm management decisions.

The accurate and timely assessment of pasture quantity and quality (i.e., nutritive characteristics) is vital for effective pasture management. Remotely sensed data can be used to predict pasture quantity and quality. This study investigated the ability of Sentinel-2 multispectral bands, convolved from proximal hyperspectral data, in predicting various pasture quality and quantity parameters. Field data (quantitative and spectral) were gathered for experimental plots representing four pasture types—perennial ryegrass monoculture and three mixtures of swards representing increasing species diversity. Spectral reflectance data at the canopy level were used to generate Sentinel-2 bands and calculate normalised difference indices with each possible band pair. The suitability of these indices for prediction of pasture parameters was assessed. Pasture quantity parameters (biomass and Leaf Area Index) had a stronger influence on overall reflectance than the quality parameters. Indices involving the 1610 nm band were optimal for acid detergent fibre, crude protein, organic matter and water-soluble carbohydrate concentration, while being less affected by biomass or LAI. The study emphasises the importance of accounting for the quantity parameters in the spectral data-based models for pasture quality predictions. These explorative findings inform the development of future pasture quantity and quality models, particularly focusing on diverse swards.

The objective of this study was to investigate whether higher lucerne (Medicago sativa; alfalfa) silage inclusion rate and longer lucerne chop length improves rumen function through increased provision of physically effective fiber, when included in a maize and lucerne silage-based total mixed ration. Diets were formulated to contain a 50:50 forage:concentrate ratio [dry matter (DM) basis] and be isonitrogenous and contain equal levels of neutral detergent fiber (320 g/kg). The forage portion of the offered diets was composed of maize and lucerne silage DM in proportions (wt/wt) of either 25:75 (high lucerne; HL) or 75:25 (low lucerne; LL). Second-cut lucerne was harvested and conserved as silage at either a long (L) or a short (S) chop length (geometric mean particle lengths of 9.0 and 14.3 mm, respectively). These variables were combined in a 2 × 2 factorial arrangement to give 4 treatments (HLL, HLS, LLL, LLS), which were fed in a 4 × 4 Latin square design study to 4 rumen-cannulated, multiparous, Holstein dairy cows in mid lactation. Effects on DM intake, chewing behavior, rumen volatile fatty acid concentration, rumen pH, rumen and fecal particle size, milk production, and milk fatty acid profile were measured. Longer chop length increased rumination times per kilogram of DM intake (+2.8 min/kg) relative to the S chop length, with HLL diets resulting in the most rumination chews. Rumen concentrations of total volatile fatty acids, acetate, and n-valerate were higher for the HLS diet than the other 3 diets, whereas rumen propionate concentration was lowest for the HLL diet. Physically effective fiber (particles >4 mm) percentage in the rumen mat was increased when L chop length was fed regardless of lucerne inclusion rate. No effect of treatment was observed for milk yield, although milk protein concentration was increased by L for the LL diet (+1.6 g/kg) and decreased by L for the HLL diet (-1.4 g/kg). Milk fat concentrations of total cis-18:1 (+3.7 g/100 g of fatty acids) and 18:3 n-3 (+0.2 g/100 g of fatty acids) were greater with HL. In conclusion, longer lucerne silage chop length increased time spent ruminating per kilogram of DM intake, but had no effect on rumen pH in the present study. Increasing dietary lucerne inclusion rate had no effects on rumination activity or rumen pH, but decreased the ratio of n-6:n-3 polyunsaturated fatty acid concentrations in milk fat.

This review considers the potential role of multispecies swards in de-risking Australian dairy systems that currently rely heavily on monocultures of perennial ryegrass and high rates of inorganic nitrogen application to be productive. Recent trends in increasing inorganic nitrogen fertiliser prices, societal pressure for increased environmental sustainability of farming practices, coupled with variable and extreme weather events have renewed interest for functionally diverse pasture mixtures. Evidence from the latest international studies either for or against the purported benefits of multispecies swards (e.g. productive, resilient, and environmentally positive) is examined. There is an ever-growing body of evidence confirming that species richness can promote high levels of productivity at low or zero rates of nitrogen fertiliser application, often with increasingly positive effects as species richness increases. However, results within and between different levels of species richness are not always consistent, suggesting that not all multispecies swards will perform alike, even at a constant level of functional diversity. A multitude of other factors is presented that interact to determine the success of one multispecies sward over another. These include soil type and fertility, species choice, functional group proportions, sward management under either grazing or cutting, fertiliser regimes, and grazing management practices. It was concluded that this complexity gives rise to a need for further research into the biological mechanisms behind multispecies mixtures to determine the factors, other than simply species richness, that will guarantee success as more farmers inevitably search for alternatives to perennial ryegrass pasture in the Australian dairy farming industry.

Perennial ryegrass (Lolium perenne L.) is a commonly grown pasture species in temperate agriculture, mainly serving as a primary energy source for dairy cows. However, its limited persistence often leads to missed production potential and early resowing, especially in countries that experience summer drought, e.g., Australia and New Zealand. Therefore, understanding the factors influencing perennial ryegrass pasture persistence is crucial for sustainable land management and climate resilience in pasture-based animal production systems. Significant gaps in knowledge exist regarding the factors influencing pasture persistence, as the number of conducted studies in this area remains limited. This study aimed to investigate the factors influencing the expression of persistence in perennial ryegrass populations using airborne and ground-based sensors. A field experiment was conducted in the southwest region of Victoria, Australia, involving ten commercial perennial ryegrass cultivar–endophyte combinations in two different populations. Persistence was evaluated using sensor-based and conventional pasture measurements over two consecutive autumns. The results revealed significant fixed effects of cultivar, endophyte, and environment and their interactions on persistence traits of perennial ryegrass. Cultivars Alto, Samson, and One50 exhibited high levels of persistence when infected with novel endophyte strains. Furthermore, prolonged environmental stresses were found to drive directional selection within pasture populations. The findings emphasise the importance of selecting appropriate cultivar–endophyte combinations and early detection of signs of poor persistence to optimise sward longevity and financial returns from pasture-based animal production systems. This study fills a knowledge gap regarding the factors influencing pasture persistence and provides valuable insights for sustainable pasture management strategies.