A Dynamic Tool to Describe Lamb Growth and Its Use as a Decision Support System

A dynamic model has been developed to simulate aspects of feedlot lamb growth and body composition, including energy and protein requirements, growth rate, composition of gain, and body mass. Model inputs include initial body mass (kg), standard final mass (kg), age (days), and dietary energy concentration (Mcal·kg-1). The model was assessed as a decision support tool using a dataset of 564 individual measures of final body mass and diet energy. The simulations provide graphical and numerical descriptions of nutrient requirements, composition of gain, and estimates of animal performance over time. The model is accurate and precise, with a root mean squared error of 7.79% of the observed final body mass and a coefficient of determination of 0.89 when simulating the same variable. The model can be used as a reliable decision support tool to estimate final body mass and the days on feed required to reach a certain final mass with precision and accuracy. Moreover, the dynamic model can also serve as a learning tool to illustrate practical principles of animal nutrition, nutrient requirement relationships, and body composition changes. This model holds the potential to enhance livestock management practices and assist producers in making informed decisions about feedlot lamb production.

Effects of offering free-choice hay for the first 5 days postpartum on productivity, serum inflammatory markers, gut permeability, and colon gene expression in fresh dairy cows

The objective of the present study was to evaluate the effects of offering free-choice hay to cows during the first 5 d immediately after calving on feed intake, milk yield, plasma metabolites, serum inflammatory markers, rumination, gut permeability, and colon gene expression. It was hypothesized that cows offered free-choice hay would have lower gut permeability, lower inflammation, and higher milk production, compared with cows not offered hay. Thirty-two multiparous cows were fed a closeup total mixed ration (TMR; 21.5% starch, 32.1% forage neutral detergent fiber [NDF] on a dry matter basis) until calving. In the postpartum period, all cows were fed a fresh cow TMR (26.8% starch and 23.4% forage NDF) from calving until 21 DIM, and were assigned randomly to receive 1 of 2 treatments as follows: (1) free-choice timothy hay (61.6% NDF; 9.6% crude protein), offered outside of the TMR in a separate manger, for the first 5 d postpartum (FCH; n = 20), or 2) no free-choice hay (NH; n = 12). The FCH cows tended to have lower serum haptoglobin concentration on d 3, compared with NH (0.95 vs. 1.52 mg/mL). Within the FCH group, cows with greater hay intake had a smaller increase in serum amyloid A from d 1 to 3 after calving (r = 0.37), and tended to have a smaller increase in serum haptoglobin concentration (r = 0.36). Cows in the FCH group had a lower ratio of starch intake (kg) to forage NDF intake (kg) on d 1 and 2, compared with NH (0.91 vs. 1.14 ± 0.03), and cows that had a lower starch:forage NDF ratio tended to have a smaller increase in serum haptoglobin concentration from d 1 to 3 after calving (r = 0.32). Cows in the FCH group had lower TMR dry matter intake (DMI; 15.0 vs. 17.1 ± 0.93 kg/d) and lower total DMI (TMR + hay DMI; 15.9 vs. 17.1 ± 0.87 kg/d), from d 1 to 5 when free-choice hay was offered, compared with NH. However, the hay treatment did not affect plasma energy metabolite concentration, gut permeability, colon gene expression, milk yield, rumination time, or change in body weight or body condition score. Overall, these findings suggest that offering free-choice hay for the first 5 d after calving may reduce serum inflammatory marker concentration, but milk yield may not increase, due to lower intake.

Peripartum factors associated with variation in voluntary postpartum hay intake in dairy cows

The objective of this research was to assess variation in postpartum hay intake when offered alongside total mixed ration (TMR) as free choice, and identify factors related to the hay intake. Twenty multiparous cows were fed a closeup TMR (21.5% starch, 39.1% neutral detergent fiber [NDF] on a dry matter [DM] basis). After calving, cows were offered free choice timothy hay (61.6% NDF, 9.6% crude protein) in addition to a fresh cow TMR (26.8% starch, 33.0% NDF) for the first 5 d postpartum. Cows were fed individually with separate mangers for TMR and hay, each offered ad libitum. Prepartum DM intake (DMI) was recorded, and baseline blood samples were collected after calving, but before the first postpartum feeding. Free choice hay intake ranged from 0 to 4.7 kg/d (DM basis) or 0 to 55.2% (% of total DMI). Cows that consumed more hay (% of total DMI) from d 1 through 5 postpartum had lower DMI 2 d before calving (r = -0.63), and greater baseline concentrations of plasma β-hydroxybutyrate (r = 0.60) and serum haptoglobin (r = 0.68). Additionally, hay intake (% of total DMI) from d 1 through 5 postpartum tended to be positively related to baseline plasma fatty acid concentration (r = 0.41). These findings suggest that cows with lower intake before calving and cows with greater ketone production and inflammation at calving may consume more hay, when offered separate from TMR.

Modifying the National Research Council weight gain model to estimate daily gain for stockers grazing bermudagrass in the southern United States

The energy requirements, feed intake, and performance of grazing animals vary daily due to changes in weather conditions, forage nutritive values, and plant and animal maturity throughout the grazing season. Hence, realistic simulations of daily animal performance can be made only by the models that can address these changes. Given the dearth of simple, user-friendly models of this kind, especially for pastures, we developed a daily gain model for large-frame stockers grazing bermudagrass sCynodon dactylon (L.) Pers.], a widely used warm-season perennial grass in the southern United States. For model development, we first assembled some of the classic works in forage-beef modeling in the last 50 yr into the National Research Council (NRC) weight gain model. Then, we tested it using the average daily gain (ADG) data obtained from several locations in the southern United States. The evaluation results showed that the performance of the NRC model was poor as it consistently underpredicted ADG throughout the grazing season. To improve the predictive accuracy of the NRC model to make it perform under bermudagrass grazing conditions, we made an adjustment to the model by adding the daily departures of the modeled values from the data trendline. Subsequently, we tested the revised model against an independent set of ADG data obtained from eight research locations in the region involving about 4,800 animals, using 30 yr (1991-2020) of daily weather data. The values of the various measures of fit used, namely the Willmott index of 0.92, the modeling efficiency of 0.75, the R2 of 0.76, the root mean square error of 0.13 kg d-1, and the prediction error relative to the mean observed data of 24%, demonstrated that the revised model mimicked the pattern of observed ADG data satisfactorily. Unlike the original model, the revised model predicted more closely the ADG value throughout the grazing season. The revised model may be useful to accurately reflect the impacts of daily weather conditions, forage nutritive values, seasonality, and plant and animal maturity on animal performance.

Animal Design Through Functional Dietary Diversity for Future Productive Landscapes

Pastoral livestock production systems are facing considerable societal pressure to reduce environmental impact, enhance animal welfare, and promote product integrity, while maintaining or increasing system profitability. Design theory is the conscious tailoring of a system for a specific or set of purposes. Then, animals—as biological systems nested in grazing environments—can be designed in order to achieve multi-faceted goals. We argue that phytochemical rich diets through dietary taxonomical diversity can be used as a design tool for both current animal product integrity and to develop future multipurpose animals. Through conscious choice, animals offered a diverse array of plants tailor a diet, which better meets their individual requirements for nutrients, pharmaceuticals, and prophylactics. Phytochemical rich diets with diverse arrangements of plant secondary compounds also reduce environmental impacts of grazing animals by manipulating the use of C and N, thereby reducing methane production and excretion of N. Subsequently functional dietary diversity (FDD), as opposed to dietary monotony, offers better nourishment, health benefits and hedonic value (positive reward increasing “liking” of feed), as well as the opportunity for individualism; and thereby eudaimonic well-being. Moreover, phytochemical rich diets with diverse arrangements of plant secondary compounds may translate in animal products with similar richness, enhancing consumer human health and well-being. Functional dietary diversity also allows us to design future animals. Dietary exposure begins in utero, continues through mothers' milk, and carries on in early-life experiences, influencing dietary preferences later in life. More specifically, in utero exposure to specific flavors cause epigenetic changes that alter morphological and physiological mechanisms that influence future “wanting,” “liking” and learning of particular foods and foodscapes. In this context, we argue that in utero and early life exposure to designed flavors of future multifunctional foodscapes allow us to graze future ruminants with enhanced multiple ecosystem services. Collectively, the strategic use of FDD allows us to “create” animals and their products for immediate and future food, health, and wealth. Finally, implementing design theory provides a link between our thoughtscape (i.e., the use of FDD as design) to future landscapes, which provides a beneficial foodscape to the animals, an subsequently to us.

The assessment of supplementation requirements of grazing ruminants using nutrition models

This paper was aimed to summarize known concepts needed to comprehend the intricate interface between the ruminant animal and the pasture when predicting animal performance, acknowledge current efforts in the mathematical modeling domain of grazing ruminants, and highlight current thinking and technologies that can guide the development of advanced mathematical modeling tools for grazing ruminants. The scientific knowledge of factors that affect intake of ruminants is broad and rich, and decision-support tools (DST) for modeling energy expenditure and feed intake of grazing animals abound in the literature but the adequate predictability of forage intake is still lacking, remaining a major challenge that has been deceiving at times. Despite the mathematical advancements in translating experimental research of grazing ruminants into DST, numerous shortages have been identified in current models designed to predict intake of forages by grazing ruminants. Many of which are mechanistic models that rely heavily on preceding mathematical constructions that were developed to predict energy and nutrient requirements and feed intake of confined animals. The data collection of grazing (forage selection, grazing behavior, pasture growth/regrowth, pasture quality) and animal (nutrient digestion and absorption, volatile fatty acids production and profile, energy requirement) components remains a critical bottleneck for adequate modeling of forage intake by ruminants. An unresolved question that has impeded DST is how to assess the quantity and quality, ideally simultaneously, of pasture forages given that ruminant animals can be selective. The inadequate assessment of quantity and quality has been a hindrance in assessing energy expenditure of grazing animals for physical activities such as walking, grazing, and forage selection of grazing animals. The advancement of sensors might provide some insights that will likely enhance our understanding and assist in determining key variables that control forage intake and animal activity. Sensors might provide additional insights to improve the quantification of individual animal variation as the sensor data are collected on each subject over time. As a group of scientists, however, despite many obstacles in animal and forage science research, we have thrived, and progress has been made. The scientific community may need to change the angle of which the problem has been attacked, and focus more on holistic approaches.

Digestion and nitrogen excretion by Holstein-Friesian cows fed grasses with lucerne or lucerne and plantain

Forages and forage mixtures with greater tolerance of dry conditions than perennial ryegrass (Lolium perenne L.) are desirable for dairy farming in New Zealand, and a low urinary nitrogen (N) excretion is desirable to lessen pollution of waterways and ground water, and nitrous oxide emissions. Measurements were undertaken with late-lactation Holstein-Friesian cows (5/treatment) fed tall fescue (Festuca arundinacea Schreb.) with a substantial incursion of weed grasses, as either a sole diet (Grass), or with lucerne (Medicago sativa L.) or lucerne and plantain (Plantago lancelota L.), in metabolism stalls. Approximate ratios (DM basis) of Grass with lucerne (GL) were 55:45, and Grass with lucerne and plantain (GLP) were 55:25:20. Measurements included intakes, production, digestion, rumen function, and urinary excretion, including the circadian patterns of metabolite excretion with a focus on nitrogenous aspects. The DM intakes (kg/day) of cows fed Grass, GL and GLP were 14.9, 12.7 and 15.0 (P = 0.006), and DM digestibility (%) was 58.0, 59.8 and 61.9 (P = 0.006), respectively. Milk yields (kg/day) were Grass, 9.0; GL, 8.7 and GLP, 11.7 (P = 0.003) but composition was not affected by diet. Rumen digesta weight was greatest in cows fed Grass, averaging 23.4% of liveweight after morning feeding. The microbial growth (g/kg organic matter digested) was 16.8 in cows fed Grass and ~24.0 in the other diets. Dietary crude protein concentrations (g/100 g DM) were Grass, 15.4, GL, 20.1 and GLP, 18.3 and urinary N excretion (g/day) was lowest with the Grass diet but urinary N concentration was lowest from cows fed GLP. Daily creatinine excretion was unaffected by diet but there was a 2-fold range in excretion rates within 24 h and values from cows fed fresh forages are lower than published values from cows fed dry diets. Results showed that supplementation of poor quality pasture with lucerne or lucerne with plantain had minor effects on digestibility, and measurements of urinary N suggest a need for caution when predicting urinary N excretion from spot urine sampling in grazing trials.

Grazing management: setting the table, designing the menu and influencing the diner

Pastoral livestock-production systems are under increasing environmental, social and consumer pressures to reduce environmental impacts and to enhance biodiversity and animal welfare. At the same time, farmers face the challenge of managing grazing, which is intimately linked with profitability. Recent advances in understanding grazing patterns and nutritional ecology may help alleviate such pressures. For instance, by managing grazing to (1) manipulate links between ingestive–digestive decisions and temporal patterns of nutrient excretion, (2) provide phytochemically diverse diets at appropriate temporal (the menu) and spatial (the table) scales and (3) influence the behaviour of animals (the diners) on the basis of their specific ‘personalities’ and needs, to overcome or enhance animal differences, thereby enhancing their and farm productivity and welfare, as well as our health. Under pastoral systems, synergies between animals’ and farmers’ grazing decisions have the potential to offer greater benefits to the animal, the environment and the farm than does simple and parsimonious grazing management based on a single component of the system. In the present review, we look at grazing and its management through an alternate lens, drawing ideas and hypotheses to stimulate thinking, dialogue and discussions that we anticipate will evolve into innovative research programs and grazing strategies. To do so, we combined experimental and observational studies from a wide range of disciplines with simulation-modelling exercises. We envisage a more holistic approach to manage grazing based on recent advances in the understanding of the nutritional ecology of grazing animals, and propose management practices that may enable pastoral livestock-production systems to evolve continually as complex creative systems.

Behavioral Timing without Clockwork: Photoperiod-Dependent Trade-Off between Predation Hazard and Energy Balance in an Arctic Ungulate

Occurrence of 24-h rhythms in species apparently lacking functional molecular clockwork indicates that strong circadian mechanisms are not essential prerequisites of robust timing, and that rhythmical patterns may arise instead as passive responses to periodically changing environmental stimuli. Thus, in a new synthesis of grazing in a ruminant (MINDY), crepuscular peaks of activity emerge from interactions between internal and external stimuli that influence motivation to feed, and the influence of the light/dark cycle is mediated through the effect of low nocturnal levels of food intake on gastric function. Drawing on risk allocation theory, we hypothesized that the timing of behavior in ruminants is influenced by the independent effects of light on motivation to feed and perceived risk of predation. We predicted that the antithetical relationship between these 2 drivers would vary with photoperiod, resulting in a systematic shift in the phase of activity relative to the solar cycle across the year. This prediction was formalized in a model in which phase of activity emerges from a photoperiod-dependent trade-off between food and safety. We tested this model using data on the temporal pattern of activity in reindeer/caribou Rangifer tarandus free-living at natural mountain pasture in sub-Arctic Norway. The resulting nonlinear relationship between the phasing of crepuscular activity and photoperiod, consistent with the model, suggests a mechanism for behavioral timing that is independent of the core circadian system. We anticipate that such timing depends on integration of metabolic feedback from the digestive system and the activity of the glucocorticoid axis which modulates the behavioral responses of the animal to environmental hazard. The hypothalamus is the obvious neural substrate to achieve this integration.

Managing the herbage utilisation and intake by cattle grazing rangelands

Rangelands throughout the world provide clean water, fix solar energy in plants, sequester carbon, and offer recreational opportunities, with other ecosystem goods and services, including food from wild and domestic herbivores. Grazing rangelands with cattle requires constant management to balance the economic sustainability of the farm with other ecological services that rangelands provide. The challenges in management arise from the diversity of the rangeland forage resources at extremely large spatial and temporal scales. To be able to predict the performance of cattle grazing in extensive rangeland environments, estimating herbage intake is paramount because it quantifies energy intake and performance. Nutrient demand is the major driver of herbage intake, and characteristics of the sward and terrain of the landscape dictate how this demand is met. System models that integrate changes in weather patterns and herbage over long periods of time will allow farmers and scientist to monitor changes in herbage mass and utilisation. Dynamic models that include herbage growth components sensitive to weather patterns and animal demands are needed to predict how long-term changes in beef herd management will affect performance and range condition. Vegetation indexes captured across biomes with satellites can accurately quantify the dynamics of aboveground net primary production and changes in nutritional value with confidence. The computer software, PCRANCH, is a program for simulating cow–calf herd dynamics over long periods of time. The models within the PCRANCH software can simulate herbage growth and animal utilisation at large spatial and temporal scales needed for rangeland management and allow ranchers to evaluate the impacts of management on other ecological services. Knowing the long-term impact of management changes on swards enable ranchers to anticipate the ecological and economic benefits of improvements or demonstrate a protection of current ecological services.

The catastrophe of meal eating

Optimisation of feed intake is a major aim of pasture and range management for ruminants and understanding what influences feeding behaviour may play an important role in satisfying this aim. An obstacle to such understanding is the fact that feeding is a two-state variable (eating or not eating, albeit with changes in rate of eating during meals), whereas the likely influencing factors are mostly continuous variables. These include gut-fill, concentrations and rates of utilisation of nutrients and metabolites, and changes in nutrient demand due to growth, reproduction and environment, both climatic and social. Catastrophe theory deals mathematically with situations in which an outcome is discontinuous (e.g. eating or not eating) and influencing variables (‘control’ variables in terms of catastrophe theory) are continuously variable (e.g. physiological and environmental factors affecting feeding). We discuss models of feeding and develop an approach in which the Type 2 catastrophe, illustrated by the bifurcation or cusp diagram, is adapted to use negative feedbacks and capacity to handle food and nutrients as the two controlling factors. Ease of prehension, as expressed by rate of eating, is modelled, as are pauses within, as well as between, meals. Quantification has not yet been attempted and the approach is presented to stimulate new thinking about the modelling and prediction of feeding behaviour and meal dynamics.

Synthesis: foraging decisions link plants, herbivores and human beings

Herbivores make decisions about where to forage and what combinations and sequences of foods to eat, integrating influences that span generations, with choices manifest daily within a lifetime. These influences begin in utero and early in life; they emerge daily from interactions among internal needs and contexts unique to biophysical and social environments; and they link the cells of plants with the palates of herbivores and humans. This synthesis summarises papers in the special issue of Animal Production Science that explore emerging understanding of these dynamics, and suggests implications for future research that can help people manage livestock for the benefit of landscapes and people by addressing (1) how primary and secondary compounds in plants interact physiologically with cells and organs in animals to influence food selection, (2) temporal and spatial patterns of foraging behaviours that emerge from these interactions in the form of meal dynamics across landscapes, (3) ways humans can manage foraging behaviours and the dynamics of meals for ecological, economic and social benefits, and (4) models of foraging behaviour that integrate the aforementioned influences.