Pasture-based Production Systems Research Articles

How the Inclusion of Pigeon Pea in Beef Cattle Diets Affects CH4 Intensity: An In Vitro Fermentation Assessment

Tropical pastures intercropped with legumes have been gaining prominence for increasing the efficiency of livestock production systems when compared to pasture monocultures. Here, our objective was to understand the fermentation processes that tropical grass and legumes underwent when included in ruminant diets, which have previously been found to optimize animal performance while reducing the intensity of enteric CH4 emissions. For this purpose, three areas containing pigeon pea (Cajanus cajan) and Urochloa spp. were sampled. Samples were dried, grounded, chemically analyzed, and included in five proportions (0%, 25%, 50%, 75%, and 100%) of pigeon pea in the diet. The diets were then analyzed using an in vitro fermentation technique. Statistical analysis was performed using SAS statistical software, considering bottles as replicates, and our results suggest that a 25% inclusion of pigeon pea is optimal for balancing CH4 mitigation and fermentation efficiency, highlighting the importance of more studies with this legume due to its benefits, especially as a supplement during drought periods that impact the production and quality of tropical pastures. It is important to consider that pigeon pea’s secondary compounds may have positively modulated the fermentation process and reduced CH4 emissions. However, excessive legume inclusion can negatively affect digestibility and animal health, impairing animal performance and the sustainability of pasture-based production systems.

Economic viability of milk production in seasonal pasture-based production system in temperate region of India

Economic viability of milk production in seasonal pasture-based production system in temperate region of India

A narrative review of factors affecting the welfare of dairy cows in larger Australasian pasture-based production systems

On the basis of current growth trajectories, pasture-based dairies of the future are likely to be bigger, have higher stocking rates and feed more concentrate to cows. This review uses the five-domains framework to consider risks to the welfare of dairy cows in these larger intensified pasture-based production systems. The factors considered in this review can be broadly categorised as (1) emerging welfare risks that can be managed, (2) emerging welfare risks that require research to be managed, or (3) persisting and/or exacerbated welfare risks. First, large herds could be subject to welfare risks associated with more stock per labour unit, longer milking times and longer distances walked to and from the dairy. To counter this, the time that cows in large herds spend off pasture can be reduced by splitting the herd into several more manageable groups, and animal-monitoring technologies can help identify health challenges with a reduced stockperson to animal ratio. Cow body condition and productivity can be maintained at high stocking rates by improving pasture production and feeding a higher proportion of concentrate. The risk of ruminal acidosis may then be reduced by appropriate transition feeding regimes and rumen buffers. Second, ensuring social stability and reducing competition may become difficult as herd sizes increase and feeding becomes more intensive. The resulting variability in feed intake, increased agonistic behaviour and social stress present emerging risks to cow welfare. Research is needed to better understand the social behaviour of cows in large intensive pasture-based herds, and how the design of the pre-milking area, the feeding pad and pasture feeding regimes (i.e. quantity and timing of pasture allocation) can improve accessibility for more vulnerable animals. Finally, intensive pasture-based dairies of the future will continue to face welfare challenges relating to lameness, mastitis and cull-cow management, whereas risks due to environmental exposure may be exacerbated by the removal of shelterbelts to facilitate irrigation. These require continued efforts in research (e.g. ways of incorporating shelter into intensive grazing systems), development (e.g. pathway to market for aged beef) and extension (e.g. improved record keeping and benchmarking of lameness and mastitis).

Forage accumulation and nutritive value in extensive, intensive, and integrated pasture-based beef cattle production systems

Context A challenge for the livestock sector is to improve the production and nutritive value of forage grasses through sustainable management strategies. Aims This study evaluated the impact of management on the productive and nutritive value of five pasture-based production systems: irrigated pasture with 600 kg nitrogen (N) ha−1 (IP600); rainfed pasture with 400 kg N ha−1 (RP400); rainfed pasture with 200 kg N ha−1 (RP200); silvopastoral with 200 kg N ha−1 (SP200); and degraded pasture without N fertilisation (DP0). Methods During two experimental years, samples were collected pre- and post-grazing to determine forage and nutritional parameters. Land-saving effects and efficiencies of N fertilisation and water use were calculated. Key results For C4 grasses, forage mass accumulation was greater for IP600 and RP400. IP600 also presented the greatest leaf area index and crude protein concentration, whereas DP0 presented the lowest values of both. For C3 grasses in the IP600 treatment, greater forage mass accumulation and leaf area index were found in winter than in autumn; all nutritional characteristics were not affected by season of the year. For land-saving effect, and N- and water-use efficiencies, IP600, RP400 and RP200 presented higher values than DP0 and SP200. Conclusions More intensified systems with proper management allowed better productive and nutritional characteristics than degraded pasture or silvopasture, especially during seasons with greater precipitation or when irrigated. Implications Intensification practices make better use of natural resources (water and land) and agricultural inputs (N fertiliser) to ameliorate the effects of seasonality and improve quality and productivity of tropical grasses in pasture-based livestock production systems.

Muscle biopsy long-chain omega-3 polyunsaturated fatty acid compositions, IMF and FMP in Australian pasture-based Bowen Genetics Forest Pastoral Angus, Hereford, and Wagyu Beef Cattle

BackgroundWe investigated breed and gender variations in the compositions of long-chain (≥ C20) omega-3 polyunsaturated fatty acids (LC omega-3 PUFA), fat melting point (FMP) and intramuscular fat (IMF) contents in biopsy samples of the M. longissimus dorsi muscle of grazing beef cattle. The hypothesis that biopsy compositions of health-beneficial LC omega-3 PUFA, FMP and IMF in a pasture-based production system will vary with breed, was tested. Muscle biopsies were taken from 127 yearling pasture-based Angus, Hereford, and Wagyu heifers and young bulls exclusive to the Australian Bowen Genetics Forest Pastoral breeding stud averaging 12 ± 2.43 months of age and under the same management routine.ResultsBreed had a significant influence on IMF, FMP, and the compositions of oleic acid, α-linolenic acid (ALA), eicosapentaenoic (EPA), docosahexaenoic (DHA), docosapentaenoic (DPA), and total EPA + DHA + DPA in the M. longissimus dorsi muscle biopsies (P ≤ 0.03). The Wagyu breed had the highest (11.1%) and Hereford the lowest (5.9%) IMF (P = 0.03). The reverse trend was observed in FMP values where the Hereford breed had the highest (55 °C), Angus intermediate (46.5 °C), and Wagyu the lowest (33 °C) FMP. The Wagyu and Angus breeds had similar oleic fatty acid (18:1n-9) content, while the Hereford breed had the lowest (P < 0.01). The highest ALA, DPA, total EPA + DHA, total EPA + DHA + DPA and total ALA + EPA + DHA + DPA contents were detected in the Wagyu breed (P ≤ 0.03). The Hereford had similar EPA and DPA contents to the Angus (P ≥ 0.46). Total EPA + DHA + DPA contents in Wagyu, Angus, and Hereford were 28.8, 21.5, and 22.1 mg/100g tissue (P = 0.01), respectively. Sex was an important source of variation that influenced LC omega-3 PUFA composition, FMP and IMF, where yearling heifers had higher IMF (11.9% vs 5.3%), lower FMP (33°C vs 37°C), and higher LC omega-3 PUFA than bulls.ConclusionAll the results taken together indicate that the Wagyu breed at 28.8 mg/100g tissue, was the closest to meeting the Australia and New Zealand recommended source level threshold of 30 mg/100g tissue of health-beneficial ≥ C20 omega-3 FA content. Since gender was a significant determinant of LC omega-3 PUFA composition, IMF content and FMP, it should be factored into enhancement strategies of healthy meat eating quality traits in grazing cattle. These findings also suggest that the Bowen Genetics Forest Pastoral beef cattle studs are important sources of LC omega-3 PUFA that can be used to cover the deficit in these health claimable fatty acids in Western diets.

Estimating milk production and energy-use efficiency of pasture-grazed Holstein and Jersey cows using mathematical models

The efficiency of feed use for milk production is critical for sustainable and profitable pasture-based dairy systems. The aim of this study was to estimate milk production and energy-use efficiencies of pasture-grazed Holstein and Jersey cows. Lactation records of 122 Holstein and 99 Jersey cows varying from parities 1 to 6 that were managed under similar feeding and environmental conditions were collected from 2005 to 2014. Feed intake and nutrient requirements of the cows were calculated using the National Research Council and the Cornell Net Carbohydrate and Protein System equations. Holsteins had a higher milk yield/kg dry matter intake (1.36±0.01 vs. 1.27±0.01 kg), whereas Jerseys had higher efficiencies in milk fat (52.4±0.3 vs. 58.4±0.4 g), milk protein (42.7±0.3 vs. 45.1±0.3 g), and energy-corrected milk (1.30±0.01 vs. 1.36±0.01 kg) per kg dry matter intake. Jersey cows also had a higher dry matter intake/kg body weight (3.13±0.02 vs. 3.51±0.02%). During transition and early lactation stages, Holstein and Jersey cows were in negative energy balance for 102.4±2.3 vs. 74.2±2.3 days, with the lowest energy reserves (-53.9 MJ vs. -39.7 MJ) reached at 22.3±0.9 vs. 24.6±0.9 days post-calving, respectively. Compared to Holsteins, Jersey cows used proportionally less net energy intake to produce 100 g milk fat (13.7±0.10 vs. 12.5±0.10), 100 g milk protein (16.7±0.14 vs.16.2±0.15) and a 1-kg energy-corrected milk (5.52±0.04 vs. 5.35±0.04), making them a better breed for pasture-based dairy systems as they possess more production and feed-use efficiency traits, which are desirable in pasture-based production systems.

How valuable are the ecosystem services of local animal breeds? The case of Kalaritiko sheep in Greece

The loss of local sheep breeds (LSB) and Animal Genetic Resources in general threatens the nutrition and livelihood security of the present and future generations. Market forces and new production patterns are the main factors that have led to the underestimation of the Total Economic Value (TEV) (i.e. the aggregated use and non-use values) of LSB and, consequently, to their substitution by high-yielding imported ones. The objective of this study is to estimate the TEV of the Kalaritiko sheep (KaS) using the Ecosystem Services (ES) framework. For this purpose, a choice experiment was implemented analyzing the societal preferences of Attica Region dwellers regarding the most important ES stemming from the traditional, pasture-based production system (PPs) of KaS. Our results show that important use and non-use values are relevant to KaS PPs. The findings of this study call for the establishment of an incentive mechanism, where reformed agri-environmental policies can work synergistically with new marketing strategies, contributing to the valorization and protection of KaS and so its traditional PPs.

Study of the Feasibility of Proposed Measures to Assess Animal Welfare for Zebu Beef Farms within Pasture-Based Systems under Tropical Conditions

Pasture-based production systems are predominant in major beef-producing countries; however, these systems lack validated protocols to assess animal welfare under commercial conditions. The objective of this study was to test the feasibility of the proposed measures and methodology for the evaluation of animal welfare in fattening cattle under pasture conditions. The initial methodology was developed with the participation of producers, professionals, the general public, and the Colombian health authority, through workshops with a participatory approach and collaborative knowledge management. The study was carried out in 24 pasture-based commercial Zebu cattle farms in the middle Magdalena region of Colombia. Visits were made with an average duration of 2.5 h, which included the evaluation of 788 fattening cattle. The methodology evaluated animal-based, resource-based, and management-based indicators through a questionnaire-guided interview to evaluate cattle handling and health, animal-based measurements, and documentation management. A protocol validation process was carried out by selecting indicators that remained unchanged, adjusting those that were feasible to implement, and removing inadequate indicators. The application of the methodology demonstrated that there are feasible measures to include in the evaluation protocols of pasture-based fattening systems. Likewise, the active participation of producers is crucial to achieving a greater commitment to the implementation of this methodology for the assessment of animal welfare in cattle under pasture conditions.

2 Satellite-Based Decision Support Tools to Assist Grazing Cattle Production

Abstract Grasslands cover approximately 40.5% of the surface of the earth and 80% of agriculturally productive land. After forests, grasslands are the primary carbon sink source and the most used feed source for livestock production. Regularly monitoring grasslands assures efficient management and sustainability of pasture-based production systems. Conventional ground-based methods to monitor grassland production and management rely on field measurements, which are time-consuming and usually restricted to small-scale assessment. Using satellite information allows for large-scale monitoring of grasslands and capturing the spatial variability of the land surface with high temporal resolution. Various methods for grassland monitoring based on satellite data can be applied, such as classifications, correlations/regression analyses, and time series analyses. Depending on the purpose of the application, these methods are sometimes combined to derive grassland management and production information. The ability of satellite-based data to quantify vegetation characteristics depends on the type of sensor and instrumentation features, such as spectral, radiometric, spatial, and temporal resolution, polarization, and angularity. The models to estimate grassland biomass based on remote sensing have been chiefly focused on optical systems. The spectral reflectance of raw bands and vegetation indices were used as proxies to investigate spatial and temporal patterns of grassland production. Optical (multispectral or hyperspectral) sensors are passive and require sunlight, so they depend highly on the weather (cloud) and light conditions. Thus, there has been increasing interest in active sensors, such as Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LIDAR) sensors, which are not constrained due to clouds but are more complex. Using satellite data in combination with field measurements has commonly yielded regression models (e.g., linear, power, logarithmic, multiple linear) for estimating grassland biomass or biophysical characteristics (e.g., chlorophyll, leaf area index) of different types of grasslands. The exponential evolution of digital computers has pushed forward machine learning-based regression methods to estimate biomass. Random forest, support vector machines, and artificial neural networks are the most used algorithms. The possibility of accurate mapping and monitoring of biomass and nutritional attributes of grasslands based on satellite provides essential insights into the decision support system for pasture management. A better understanding of the nitrogen status of pastures, forage biomass, and its nutritive value is instrumental in livestock and forage management. Timely prediction of these variables can help improve decision-making by grazing land managers on, for instance, the adjustment of stocking rate or adequate supplementation to match the needs of animals toward more sustainable production. Future use of satellite-based grazing models in tandem with ruminant nutrition models will enable to development of decision-support tools to assist with many aspects of livestock production in diverse environmental conditions and accounting for temporal variability. (FAPESP #2020/14367-7)

A three-year comparison of once-a-day and twice-a-day milking in seasonal-calving pasture-based systems

Globally, the majority of dairy cows are milked twice a day (TAD); however, in pasture-based production systems, such as in Ireland, the idea of milking once a day (OAD) is being considered for reasons such as improved work-life balance. The immediate effects within a lactation, as well as the multilactation consequences of OAD, compared with TAD milking, require understanding. The objective of this randomized experiment was to compare OAD and TAD milking, over a 3-yr period, by examining the differences in milk production and composition, body weight (BW), body condition score (BCS), dry matter intake (DMI), udder characteristics, locomotion score, and milking time. Over the 3-yr period, 83 cows were enrolled in the experiment; 32, 44, and 48 cows in yr 1, 2, and 3 of the experiment, respectively. Each year, 23% of the herds were primiparous animals, while the remainder were second lactation or greater in parity. All cows were milked in the morning at 0700 h; only cows milked TAD were milked a second time each day at 1600 h. Cows rotationally grazed pastures for the duration of the lactating period and were housed during the nonlactating period. Milking cows OAD reduced cumulative milk yield by 26%, and milk solids yield (kg of fat + kg of protein) by 21%, across the 3 yr of the experiment when compared with cows milked TAD which produced 4,126 and 365 kg/cow, respectively. A contributory factor to the reduced production was a shorter lactation length (9.7 d) of the cows milked OAD compared with TAD (294 d). Milk fat percent of cows milked TAD was similar for all 3 yr of the study (5.05%), whereas milk fat percent of the cows milked OAD increased year on year, with each year being greater than the previous year (5.02%, 5.32%, and 5.70% for yr 1, 2, and 3; respectively). Milk protein percent was greater (+0.19%) for cows milked OAD compared with TAD which was 3.78%. Compared with cows milked TAD, total DMI for cows milked OAD was 22% less at the start of lactation (<167 d), but as the lactation progressed (>167 d) we observed no difference in DMI between treatments. Similar to the literature, milking cows OAD significantly increased average somatic cell score, both during (+16%) and at the end of lactation (+19%), compared with milking cows TAD which were 4.69 and 4.79, respectively. We detected positive aspects associated with OAD milking such as greater BW, BCS, and fertility performance. Milking OAD reduced both milking time per cow per day (reductions ranged from 34% in the first 4 mo of lactation to 43% during mo 5-9 of lactation) and milking time per liter of milk (-3.5 s/L) throughout lactation, leading to less labor inputs on-farm which can have positive implications for farmer work-life balance. The significant time saving and potential savings in costs (e.g., electricity) need to be considered in conjunction with the milk production reduction when considering OAD milking for the entire lactation.

A Multi-Variable Sentinel-2 Random Forest Machine Learning Model Approach to Predicting Perennial Ryegrass Biomass in Commercial Dairy Farms in Southeast Australia

One of the most valuable and nutritionally essential agricultural commodities worldwide is milk. The European Union and New Zealand are the second- and third-largest exporting regions of milk products and rely heavily on pasture-based production systems. They are comparable to the Australian systems investigated in this study. With projections of herd decline, increased milk yield must be obtained from a combination of animal genetics and feed efficiencies. Accurate pasture biomass estimation across all seasons will improve feed efficiency and increase the productivity of dairy farms; however, the existing time-consuming and manual methods of pasture measurement limit improvements to utilisation. In this study, Sentinel-2 (S2) band and spectral index (SI) information were coupled with the broad season and management-derived datasets using a Random Forest (RF) machine learning (ML) framework to develop a perennial ryegrass (PRG) biomass prediction model accurate to +/−500 kg DM/ha, and that could predict pasture yield above 3000 kg DM/ha. Measurements of PRG biomass were taken from 11 working dairy farms across southeastern Australia over 2019–2021. Of the 68 possible variables investigated, multiple simulations identified 12 S2 bands and 9 SI, management and season as the most important variables, where Short-Wave Infrared (SWIR) bands were the most influential in predicting pasture biomass above 4000 kg DM/ha. Conditional Latin Hypercube Sampling (cLHS) was used to split the dataset into 80% and 20% for model calibration and internal validation in addition to an entirely independent validation dataset. The combined internal model validation showed R2 = 0.90, LCCC = 0.72, RMSE = 439.49 kg DM/ha, NRMSE = 15.08, and the combined independent validation had R2 = 0.88, LCCC = 0.68, RMSE = 457.05 kg DM/ha, NRMSE = 19.83. The key findings of this study indicated that the data obtained from the S2 bands and SI were appropriate for making accurate estimations of PRG biomass. Furthermore, including SWIR bands significantly improved the model. Finally, by utilising an RF ML model, a single ‘global’ model can automate PRG biomass prediction with high accuracy across extensive regions of all seasons and types of farm management.

A new insight about the selection and intake of forage by ewes and lambs in different production systems on pasture

Keeping lambs with their dams and providing concentrate supplement for weaned lambs are two strategies used in lamb meat production systems on pasture that may affect the way that lambs explore, select, and ingest the forage while grazing. Thus, this study aimed to evaluate the selection and intake of forage by ewes and lambs using the continuous bite monitoring method in two pasture-based production systems: non-weaned and non-supplemented lambs (NW); and weaned lambs supplemented with concentrate (WS). Continuous bite monitoring is based on a bite-coding grid that allows the estimation of bite mass, intake rate, selection of plant species and plant parts by grazing animals. Two experiments were carried out during September–November of two subsequent years on a mixed pasture of black oat (Avena strigosa Schreb.) and annual ryegrass (Lolium multiflorum Lam.) established over a perennial Tifton 85 (Cynodon spp.) pasture. On the second year, a third treatment including only the dams of weaned lambs – dry ewes – was also evaluated. In the WS system, lambs were supplemented with concentrate feed at 2% of body weight (BW)/day on a dry matter (DM) basis. Both experiments lasted 46 days, and a continuous stocking management with the forage allowance maintained at 16% BW in DM/day for all treatments. There was a high degree of variability on botanical and morphological composition of forage that was ingested by lambs and ewes, with ranges of 3–14 and 8–11 bite categories for NW lambs and ewes, respectively; 12–15 bite categories for WS lambs, and 8 bite categories for dry ewes. There was similarity between the forage ingested by lambs and ewes in the NW system, except for inflorescences of black oat and annual ryegrass, that were ingested in greater proportions by ewes. WS lambs ingested the most diverse forage diet, which appeared to explore the superior strata of pasture (above 10–15 cm of height) more frequently, and grazed inflorescences and senescent material in higher proportions than NW lambs. Dry ewes showed higher intake of Paspalum spp., Kikuyu grass and other voluntary species and weeds compared to NW ewes. These results suggest that the production system affects the way that lambs explore the pasture and compose their forage diet, with WS lambs ingesting the most diverse diet. The increased intake of inflorescence and, eventually, voluntary species and weeds may be a strategy used by lactating and dry ewes to extend the vegetative stage of high-quality forage species and reduce the population of low-quality plant species on pasture.

Taste of green: Consumer liking of pasture-raised beef hamburgers as affected by information on the production system

This paper aims to understand the link between the appreciation of sustainable food and taste. By taking the example of pasture-raised beef, we analyze the role of relevant information and the perception of taste by consumers. The latter is particularly crucial for its long-term acceptance. The objective of this study was, first, to assess consumers' sensory liking for hamburgers prepared with pasture-raised beef patties in a real-life setting and, second, the effect on the sensory evaluation by adding comprehensive information about the production system. A total of 507 German consumers participated in a home test. Using a between-subjects design, consumers were randomly assigned into four groups. While the same meat was used, three groups tested the burgers under informed condition. The first informed group received truthful information about the pasture-based production system. The second informed group received information flyers about organic husbandry and the third informed group about conventional husbandry. The fourth group received no information (i.e., blind condition), serving as a control group. Overall, consumers evaluated pasture-raised beef burgers in terms of sensory liking positively. Providing additional information about the extrinsic quality of the product affected sensory perception. Labeling beef burger patties as “pasture-raised” and “organic” positively affected hedonic ratings, whereas labeling beef burger patties as “conventional” tended to have a negative effect. Consequently, information on beef production system practices seems to transmit consumers’ perceptions of quality and hence may be an important cue to strengthen more sustainable production systems.

Relationships between body weight, body condition score at breeding and reproductive and progeny performance in Kiko meat goats over two breeding cycles

Body condition scores (BCS) and/or body weights (BWT) are often used as visual or tactile management tools to evaluate and improve reproductive competency in pasture-managed small ruminant animals. This study was designed to evaluate relationships between BCS, BWT and reproductive traits (number born alive and weaned, litter size, birth and weaning weights) in 16 purebred Kiko, 11 purebred Boer and 7 Kiko x Boer crossbred meat goat dams that were semi-intensively managed and bred to both Boer and Kiko bucks. BWT was recorded using a scale and palpable BCS scale of 1 to 5 (1= emaciated to 5= obese) and was subjectively determined at breeding, parturition and weaning. Pearson correlation coefficient (r) analysis was used to determine the relationships between residual values of reproductive and progeny performance and BWT or BCS. Pre-partum BCS and weaning BCS had a correlation of r=0.09. A moderate correlation was observed between BWT at breeding and the number born alive (r=0.36) suggesting that pre-partum BWT is the key body conformation measurement linked to the reproductive performance of dams both at birth and weaning. Both at breeding and at weaning BCS were negatively correlated with litter size (r= -0.11) and birth weight (r=-0.32) and weakly correlated with the number born alive (r=0.06). Also, negative correlations were obtained between BCS at weaning and kid weaning weight (r=-0.58) and number weaned (r=-0.26). Although BCS had no significant (P≥0.05) effect on kg kids born per dam, birth weight of kids, and kids weaning weights, it is evident that a BCS score of 3 at the mating time could optimize reproductive performance. The results of this project established the important roles that pre-breeding BWT and/or BCS have on reproductive performance (kidding rate) in meat goat herds. We recommend their evaluation as a useful management tool for distinguishing differences in the pre-partum nutritional needs of meat goat herds, especially in the pasture-based production system. Int. J. Agril. Res. Innov. Tech. 12(2): 64-73, December 2022

Quantification of relative stock units for horses to permit correct application within pasture-based production systems

Context Overseer® is the primary software tool used to estimate farm-level nutrient cycle and management for regulatory purposes in New Zealand. The model compares feed demand among different livestock by using ‘revised stock units’ (RSUs, the annual energy requirement of a mature ewe to raise a single lamb to weaning; 6000 MJ metabolisable energy). The RSUs for several common equine stock classes are not yet available, while those currently available within the model are based on the linear scaling of feed demand to liveweight, which does not consider allometric scaling of metabolism to liveweight or the differences in digestive physiology and nutrient metabolism between ruminants and monogastric hindgut fermenters (horses). Aim To compare the current RSU values used in Overseer® for different equine stock classes, with the equineRSU values calculated using equine-specific models. Methods Weighted average estimates of the bodyweight for the different equine livestock classes were calculated from the published literature. These weighted average estimates of bodyweight were used to estimate the energy requirements on the basis of data published by National Research Council. The resulting dry-matter intake and N intake from the equineRSU values and the current RSU values in use within Overseer® were modelled using published data on diet composition, crude protein content and the digestibility of the different feeds offered. Results The current RSUs in Overseer were 2.5–6.8 units higher than the equineRSU values obtained from the equine-specific models. This overestimation in feed demand resulted in N-intake estimates at an animal level being 52–108% higher than values derived using the equine-specific estimates. Conclusion The use of RSUs based on linear scaling of feed demand from ruminants on the basis of liveweight overestimates feed demand and N intake in horses. If horses are to be included within nutrient management models, feed demand must be based on published equine data for energy requirements to avoid over-inflation of N excretion. The equineRSUs calculated in this study reduce the risk of over-inflation of N intake and excretion, and subsequently the N leaching estimations. Implication Failure to accurately model feed demand of horses within nutrient management software would unfairly compromise stocking density and horse management on large commercial breeding farms. The implication for these errors on economic impact and restricted livestock number is greatest for the Thoroughbred breeding industry due to the scale of the operations.

Genetic selection of Nellore cattle raised in tropical areas: Economic indexes and breeding decisions risks

Different selection indexes (Index I [Optimal], Index II [Maternal], and Index III [Terminal]) were evaluated in a full-cycle, pasture-based production system of Nellore cattle. The economic selection indexes consisted of combinations of the traits: body weight at 120 (W120), 210 (W210), 365 (W365), and 450 days (W450) of age; age at first calving (AFC); calving interval (CI); scrotal circumference at 365 (SC365) and 450 (SC450) days of age; ribeye area (REA); subcutaneous fat thickness (FAT); stayability (STAY); and accumulated productivity (ACP). Bootstrap analyses were performed to assess the distribution of the response to the optimal index by changes in the economic value of traits and the impact caused by each economic trait. The implementation of the optimal index and the adjustment of the expected return for uncertainty in the prediction of breeding values were carried out with 67 sires. The most genetic-economic important traits were W450, AFC, ACP, and REA. Index I showed the greatest economic response to selection (R$ 938.95/generation), followed by Indexes II (R$ 811.84) and III (R$ 476.26). Economic response variations of Index I ranged from R$ 100.71 to R$ 1747.43. The highest contributions and range of economic response were observed in ACP, followed by W450, and CI. Sires ranking changed ± 4.0 positions with adjustment for risk in Index I, indicating changes in breeding decisions when selecting sires. All indexes presented great efficiency and can be adapted to similar production scenarios that expect a similar overall gain. Adjustment for risk in the selection index should be considered for optimal breeding decisions.

86 Effects of Hurricane-Related Prenatal Stress on Postnatal Growth and Development of Steers and Heifers in a Limited Resource Beef cow-Calf System

Abstract Cost effective growth in beef calves is necessary for productivity of limited-resource pasture-based cow-calf operations. However, pasture-based production systems are often plagued by environmental stressors such as droughts, high ambient temperatures and adverse weather events that might impede calf growth and development. Our study evaluated the effects of prenatal stressors such as hurricanes on postnatal calf growth and development. Crossbred beef calves born from the same lineage in two different years were compared: Group 1, dams experienced effects of a category 5 hurricane in their late gestation. Group 2, dams experienced no adverse environmental effects their late gestation. Body weights and condition scores were collected at weaning, yearling age, 14 -15 months age and, and 20 months of age. Blood samples were collected periodically to evaluate metabolite and hormone profiles. Data were evaluated by mixed procedures of SAS, and significance determined at P&amp;lt; 0.05. Calf body weights during the juvenile periods were less (P&amp;lt; 0.05) in both steers and heifers born to dams that experienced hurricane-related stress during late gestation compared with their normal contemporaries. However, this weight difference was not evident during adult stages. Further, although blood cortisol was not different in yearling heifers, glucose and progesterone concentrations were decreased (P&amp;lt; 0.05; P&amp;lt; 0.01, respectively) in Group 1 heifers compared with the control group. In adult steers, serum cortisol differed (P&amp;lt; 0.001) between groups (965±38 vs 1282±40.5, pg/mL for Groups 1 and 2 respectively). Indeed, Group 1 steers exhibited decreased serum cortisol concentrations at both summer and fall periods when ambient temperatures were expected to present varied stressful challenges to the animals. Thus, detrimental effects of a natural disaster such as a hurricane may impede postnatal growth and development of heifers and steers as seen in this project. Further investigation is on this phenomenon is warranted. Funded by NIFA CBG # 2021-38821-34599.

The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems

The excretion of nitrogen (N) in faeces and urine from beef cattle contributes to atmospheric pollution through greenhouse gas and ammonia emissions and eutrophication of land and aquatic habitats through excessive N deposition and nitrate leaching to groundwater. As N excretion by beef cattle is rarely measured directly, it is important to accurately predict losses by utilising a combined knowledge of diet and production parameters so that the effect of dietary changes on the potential environmental impact of beef production systems can be estimated. This study aimed to identify differences between IPCC and more detailed country-specific models in the prediction of N excretion and N losses at a system level and determine how the choice of model influences the interpretation of differences in diet at the system scale. The data used in this study were derived from a farm-scale experimental system consisting of three individual grazing farms, each with a different sward type: a permanent pasture, a high sugar ryegrass monoculture, and a high sugar ryegrass with white clover (~30% groundcover). Data were analysed using a mixed linear model (residual maximum likelihood analysis). The IPCC methods demonstrated significantly lower estimates of N excretion than country-specific models for the first housing period and significantly greater losses for the grazing and second housing periods. The country-specific models enabled prediction of N partitioning to urine and faeces, which is important for estimation of subsequent N losses through the production system, although the models differed in their estimates. Overall, predicted N losses were greater using the IPCC approaches compared to using more detailed country-specific approaches. The outcomes of the present study have highlighted that different models can have a substantial impact on the predicted N outputs and subsequent losses to the environment for pasture-based beef finishing systems, and the importance, therefore, of using appropriate models and parameters.

Seed-Borne Erwinia persicina Affects the Growth and Physiology of Alfalfa (Medicago sativa L.).

Seed-borne Erwinia persicina can be transmitted globally via alfalfa (Medicago sativa L.) seed trade, but there is limited information about the impact of this plant-pathogenic bacterium on alfalfa plants. In this study, strain Cp2, isolated from alfalfa seeds, was confirmed by whole-genome sequencing to belong to E. persicina. Subsequently, the effects of Cp2 on alfalfa growth and physiology were evaluated by constructing a rhizosphere infection model. Strain Cp2 had a strong inhibitory effect on the elongation and growth of alfalfa roots, which was very unfavorable to these perennial plants. Furthermore, an increased number of leaf spots and yellowing symptoms were observed in plants of the Cp2 group from day 10 to day 21 and the strain Cp2 was re-isolated from these leaves. Correlation between growth and photosynthetic parameters was analyzed and the significant decreases in fresh weight and root and plant lengths in the Cp2 group were related to the marked reduction of chlorophyll b, carotenoid, transpiration rate, and stomatal conductance of leaves (r > 0.75). In addition, nine physiological indicators of root, stem, and leaf were measured in the plants 21 days after treatment with Cp2. The physiological response of root and leaf to Cp2 treatment was stronger than that of stem. The physiological indicators with the greatest response to Cp2 infection were further explored through principal component analysis, and superoxide dismutase, peroxidase, ascorbate peroxidase, and soluble protein showed the greatest changes in roots, stems, and leaves (P < 0.001). Among tissues, the commonality was the change of soluble protein. Therefore, soluble protein is speculated to be a physiological marker during alfalfa–E. persicina interactions. These findings indicate that once E. persicina spreads from alfalfa seeds to the rhizosphere, it can invade alfalfa roots and cause disease. This study demonstrates that this plant pathogenic bacterium may be a potential threat to new environment when they spread via seed trade and these “dangerous hitchhikers” warrant further attention, especially in the study of bacterial diseases in pasture-based production systems.

Evaluating Alternatives to Locomotion Scoring for Detecting Lameness in Pasture-Based Dairy Cattle in New Zealand: In-Parlour Scoring.

Simple SummaryLameness in dairy cows is a significant challenge globally. Early detection accompanied by effective treatment can reduce the number of cows that are lame and the impact of lameness. Currently, locomotion scoring by observing the gait posture of cows is the most widely used method of detecting lame cows. However, its use is limited, especially in pasture-based production systems like in New Zealand. One possible alternative to locomotion scoring is observing and recording cows for indicators of lameness while cows are being milked. We recorded the presence of four indicators (shifting weight, abnormal weight distribution, swollen heel or hock joint, and overgrown hoof) on two dairy farms in New Zealand. Two or more indicators were more useful predictors of higher locomotion scores (lameness). However, more results on more farms are needed before the in-parlour scoring procedure can be recommended as an alternative to locomotion scoring in pasture-based dairy cattle.Earlier detection followed by efficient treatment can reduce the impact of lameness. Currently, locomotion scoring (LS) is the most widely used method of early detection but has significant limitations in pasture-based cattle and is not commonly used routinely in New Zealand. Scoring in the milking parlour may be more achievable, so this study compared an in-parlour scoring (IPS) technique with LS in pasture-based dairy cows. For nine months on two dairy farms, whole herd LS (4-point 0–3 scale) was followed 24 h later by IPS, with cows being milked. Observed for shifting weight, abnormal weight distribution, swollen heel or hock joint, and overgrown hoof. Every third cow was scored. Sensitivity and specificity of individual IPS indicators and one or more, two or more or three positive indicators for detecting cows with locomotion scores ≥ 2 were calculated. Using a threshold of two or more positive indicators were optimal (sensitivity > 92% and specificity > 98%). Utilising the IPS indicators, a decision tree machine learning procedure classified cows with locomotion score class ≥2 with a true positive rate of 75% and a false positive rate of 0.2%. IPS has the potential to be an alternative to LS on pasture-based dairy farms.