Modelling phosphorus intake, digestion, retention and excretion in growing and finishing pigs: model description

Prediction models for phosphorus excretion of pigs

OBJECTIVE

The present study aimed to measure fecal and urinary phosphorus (P) excretion from pigs and to develop prediction models for P excretion of pigs.

METHODS

A total of 96 values for P excretions were obtained from pigs of 15 to 93 kg body weight (BW) fed 12 diets in four experiments and were used to develop the prediction models. All experimental diets contained exogenous phytase at 500 phytase units per kg. Body weight of pigs and dietary P concentrations were used as independent variables in the prediction models.

RESULTS

The BW, feed intake, and P intake were positively correlated with total (fecal plus urinary) P excretions (r = 0.80, 0.91, and 0.94, respectively; p<0.001). The models for estimating P excretion were: fecal P excretion (g/d) = -0.654-0.000618×BW2+0.273×BW ×dietary P concentration (R2 = 0.83; p<0.001); urinary P excretion (g/d) = 0.045+ 0.00781×BW×dietary P concentration (R2 = 0.15; p<0.001); total P excretion (g/d) = -0.598-0.000613×BW2+0.280×BW×dietary P concentration (R2 = 0.86; p<0.001) where the BW of pigs and dietary P concentration are expressed as kg and % (as-fed basis), respectively. Based on the developed prediction models, the estimated annual fecal, urinary, and total P excretion for a market pig was 1.24, 0.09, and 1.33 kg/yr, respectively.

CONCLUSION

The P excretions in market pigs can be estimated using BW of pigs and dietary P concentration. In the present model, a market pig excretes 1.24 kg of fecal P and 0.09 kg of urinary P per year.

Review: When worlds collide - poultry modeling in the 'Big Data' era

Within poultry production systems, models have provided vital decision support, opportunity analysis, and performance optimization capabilities to nutritionists and producers for decades. In recent years, due to the advancement of digital and sensor technologies, 'Big Data' streams have emerged, optimally positioned to be analyzed by machine-learning (ML) modeling approaches, with strengths in forecasting and prediction. This review explores the evolution of empirical and mechanistic models in poultry production systems, and how these models may interact with new digital tools and technologies. This review will also examine the emergence of ML and Big Data in the poultry production sector, and the emergence of precision feeding and automation of poultry production systems. There are several promising directions for the field, including: (1) application of Big Data analytics (e.g., sensor-based technologies, precision feeding systems) and ML methodologies (e.g., unsupervised and supervised learning algorithms) to feed more precisely to production targets given a 'known' individual animal, and (2) combination and hybridization of data-driven and mechanistic modeling approaches to bridge decision support with improved forecasting capabilities.

Chemical body composition and bone growth of young pigs as affected by deficiency, adequate and excess of dietary phosphorus supply

Objective of the experiment was to study the effect of deficiency, adequate and excess dietary phosphorus supply on growth performance, retention and utilisation of phosphorus, length, mass and geometry measurements of the femur shaft, content of protein, ash, phosphorus in viscera, edible (meat and fat) and inedible (bones and skin) parts of the body in pigs ageing from 33 to 110 days. It was found that compared to animals fed according to phosphorus requirement the deficiency and excess of dietary phosphorus did not influenced o total feed intake (mean 120.6 kg) and feed conversion (mean 1.9 kg/kg gain). However phosphorus deficiency lowered total gain of the body mass (P=0.0072), diminished weight of the inedible part of the carcass (P=0.0229), decreased the content of body protein (P=0.0171), ash (P=0.0001), and phosphorus (P=0.0001). Whereas, over-supply of dietary phosphorus did not cause any change of these component. Utilisation of the total phosphorus was diminished (P=0.0001) in pigs fed diet with both excess (by 16.26%) and deficiency (by 12.28%) of the phosphorus, but excess had much lower negative impact than its’ deficiency. When available form of this element was considered over-supply still reduced (P=0.0001) its utilisation the most (by 26.58%) but deficiency made utilisation the best (7.77%). Both dietary deficiency and over-supply of the phosphorus diminished (P=0.0001) femur mass (by 25 and 11 g, respectively). Thus negative impact of phosphorus deficiency was much stronger. Moreover, phosphorus deficiency diminished (P=0.0015) bone length (by 0.5 cm), however, excess did not change this feature. Response of animals to a decrease bone mass and length due disturbances in phosphorus supply (both deficiency and excess) was the increase the vertical external diameter of the femur shaft.

Tracking gastrointestinal nematode risk on cattle farms through pasture contamination mapping

Gastrointestinal nematode (GIN) parasites in grazing cattle are a major cause of production loss and their control is increasingly difficult due to anthelmintic resistance and climate change. Rotational grazing can support control and decrease reliance on chemical intervention, but is often complex due to the need to track grazing periods and infection levels, and the effect of weather on larval availability. In this paper, a simulation model was developed to predict the availability of infective larvae of the bovine GIN, Ostertagia ostertagi, at the level of individual pastures. The model was applied within a complex rotational grazing system and successfully reproduced observed variation in larval density between fields and over time. Four groups of cattle in their second grazing season (n = 44) were followed throughout the temperate grazing season with regular assessment of GIN faecal egg counts, which were dominated by O. ostertagi, animal weight and recording of field rotations. Each group of cattle was rotationally grazed on six group-specific fields throughout the 2019 grazing season. Maps and calendars were produced to illustrate the change in pasture infectivity (density of L3 on herbage) across the 24 separate grazing fields. Simulations predicted differences in pasture contamination levels in relation to the timing of grazing and the return period. A proportion of L3 was predicted to persist on herbage over winter, declining to similar intensities across fields before the start of the following grazing season, irrespective of contamination levels in the previous year. Model predictions showed good agreement with pasture larval counts. The model also simulated differences in seasonal pasture infectivity under rotational grazing in systems that differed in temperature and rainfall profiles. Further application could support individual farm decisions on evasive grazing and refugia management, and improved regional evaluation of optimal grazing strategies for parasite control. The integration of weather and livestock movement is inherent to the model, and facilitates consideration of climate change adaptation through improved disease control.

A Novel Estimation of Unobserved Pig Growth Traits for the Purposes of Precision Feeding Methods

Recent technological advances make it possible to deliver feeding strategies that can be tailored to the needs of individual pigs in order to optimise the allocation of nutrient resources and contribute toward reducing excess nutrient excretion. However, these efforts are currently hampered by the challenges associated with: (1) estimation of unobserved traits from the available data on bodyweight and feed consumption; and (2) characterisation of the distributions and correlations of these unobserved traits to generate accurate estimates of individual level variation among pigs. Here, alternative quantitative approaches to these challenges, based on the principles of inverse modelling and separately inferring individual level distributions within a Bayesian context were developed and incorporated in a proposed precision feeding modelling framework. The objectives were to: (i) determine the average and distribution of individual traits characterising growth potential and body composition in an empirical population of growing-finishing barrows and gilts; (ii) simulate the growth and excretion of nitrogen and phosphorus of the average pig offered either a commercial two-phase feeding plan, or a precision feeding plan with daily adjustments; and (iii) simulate the growth and excretion of nitrogen and phosphorus across the pig population under two scenarios: a two-phase feeding plan formulated to meet the nutrient requirements of the average pig or a precision feeding plan with daily adjustments for each and every animal in the population. The distributions of mature bodyweight and ratio of lipid to protein weights at maturity had median (IQR) values of 203 (47.8) kg and 2.23 (0.814) kg/kg, respectively; these estimates were obtained without any prior assumptions concerning correlations between the traits. Overall, it was found that a proposed precision feeding strategy could result in considerable reductions in excretion of nitrogen and phosphorus (average pig: 8.07 and 9.17% reduction, respectively; heterogenous pig population: 22.5 and 22.9% reduction, respectively) during the growing-finishing period from 35 to 120 kg bodyweight. This precision feeding modelling framework is anticipated to be a starting point toward more accurate estimation of individual level nutrient requirements, with the general aim of improving the economic and environmental sustainability of future pig production systems.

How do pigs deal with dietary phosphorus deficiency?

Feeding strategies for growing monogastric livestock (particularly pigs) must focus on maximising animal performance, while attempting to reduce environmental P load. Achieving these goals requires a comprehensive understanding of how different P feeding strategies affect animal responses and an ability to predict P retention. Although along with Ca, P is the most researched macromineral in pig nutrition, knowledge gaps still exist in relation to: (1) the effects of P feed content on feed intake (FI); (2) the impact of P intake on body composition; (3) the distribution of absorbed P to pools within the body. Here, we address these knowledge gaps by gathering empirical evidence on the effects of P-deficient feeds and by developing a predictive, mechanistic model of P utilisation and retention incorporating this evidence. Based on our statistical analyses of published literature data, we found: (1) no change in FI response in pigs given lower P feed contents; (2) the body ash–protein relationship to be dependent upon feed composition, with the isometric relationship only holding for pigs given balanced feeds and (3) the priority to be given towards P retention in soft tissue over P retention in bones. Subsequent results of the mechanistic model of P retention indicated that a potential reduction in P feeding recommendations could be possible without compromising average daily gain; however, such a reduction would impact P deposition in bones. Our study enhances our current knowledge of P utilisation and by extension excretion and could contribute towards developing more accurate P feeding guidelines.

Quantifying the consequences of nutritional strategies aimed at decreasing phosphorus excretion from pig populations: a modeling approach

There is a global imperative to reduce phosphorous (P) excretion from pig systems. In this study, a previously validated deterministic model was modified to be stochastic, in order to investigate the consequences of different management strategies on P excretion by a group of growing pigs. The model predicts P digestion, retention and excretion from feed composition and growth parameters that describe a specified pig phenotype. Stochasticity was achieved by introducing random variation in the latter. The strategies investigated were: (1) changing feed composition frequently in order to match more closely pig digestible P (digP) requirements to feed composition (phase feeding) and (2) grouping pigs into light and heavy groups and feeding each group according to the requirements of their group average BW (sorting). Phase feeding reduced P excretion as the number of feeding phases increased. The effect was most pronounced as feeding phases increased from 1 to 2, with a 7.5% decrease achieved; the increase in phases from 2 to 3 was associated with a further 2.0% reduction. Similarly, the effect was more pronounced when the feed targeted the population requirements for digP at the average BW of the first third, rather than the average requirements at the mid-point BW of each feeding sequence plan. Increasing the number of feeding phases increased the percentage of pigs that met their digP requirements during the early stages of growth and reduced the percentage of pigs that were supplied <85% of their digP requirements at any stage of their growth; the latter may have welfare implications. Sorting of pigs reduced P excretion to a lesser extent; the reduction was greater as the percentage of pigs in the light group increased from 10% to 30% (from 1.5% to 3.0% reduction, respectively). This resulted from an increase in the P excreted by the light group, accompanied by a decrease in the P excreted by the remaining pigs. Sorting increased the percentage of light pigs that met their dig P requirements, but only slightly decreased the percentage of heavy pigs that met these requirements at any point of their growth. Exactly the converse was the case as far as the percentage of pigs that were supplied <85% of their digP requirements were concerned. The developed model is flexible and can be used to investigate the effectiveness of other management strategies in reducing P excretion from groups of pigs, including precision livestock feeding.

Environmental impact of using specialty feed ingredients in swine and poultry production: A life cycle assessment

Livestock production has a variety of environmental impacts such as greenhouse gas emissions, water pollution, acidification, and primary energy consumption. The demand for livestock products is expected to grow substantially, creating even more environmental pressure. The use of specialty feed ingredients (SFI) such as supplemented AA and phytase can reduce nutrient input into the system without compromising productivity and consequently can reduce emissions. The global change impact of using SFI in pig and broiler production systems in Europe and North and South America was studied. A life cycle assessment according to international standards (ISO 14040/44) analyzed contributions from producing SFI and animals to global change. Three different alternatives were analyzed. In addition, partial sensitivity analysis was conducted using 5 scenarios for each region for both production systems. Specialty feed ingredient supplementation in pig and broiler diets reduced greenhouse gas emissions (cradle to farm gate) by 56% and 54% in Europe, 17% and 15% in North America, and 33% and 19% in South America, respectively, compared to an unsupplemented diet. A total of 136 Mt CO equivalent (CO eq) was saved in 2012, rising to 146 Mt CO eq in 2050 on the basis of United Nations population projections. Considerable benefits of supplementation with SFI were apparent in European and South American diets when direct land use change was considered because of the reduced demand for soybean meal. The eutrophication potential of unsupplemented diets was reduced by up to 35% in pig and 49% in broiler production systems compared to supplemented alternatives. The acidification potential of supplemented strategies was reduced by up to 30% in pig and 79% in broiler production systems. The primary energy demand was similar in all alternatives, and this could be an area where the SFI industry can improve. Overall, SFI supplementation substantially reduced the global warming, eutrophication, and acidification potentials in all regions studied.

Towards a methodology to formulate sustainable diets for livestock: accounting for environmental impact in diet formulation

The objective of this study was to develop a novel methodology that enables pig diets to be formulated explicitly for environmental impact objectives using a Life Cycle Assessment (LCA) approach. To achieve this, the following methodological issues had to be addressed: (1) account for environmental impacts caused by both ingredient choice and nutrient excretion, (2) formulate diets for multiple environmental impact objectives and (3) allow flexibility to identify the optimal nutritional composition for each environmental impact objective. An LCA model based on Canadian pig farms was integrated into a diet formulation tool to compare the use of different ingredients in Eastern and Western Canada. By allowing the feed energy content to vary, it was possible to identify the optimum energy density for different environmental impact objectives, while accounting for the expected effect of energy density on feed intake. A least-cost diet was compared with diets formulated to minimise the following objectives: non-renewable resource use, acidification potential, eutrophication potential, global warming potential and a combined environmental impact score (using these four categories). The resulting environmental impacts were compared using parallel Monte Carlo simulations to account for shared uncertainty. When optimising diets to minimise a single environmental impact category, reductions in the said category were observed in all cases. However, this was at the expense of increasing the impact in other categories and higher dietary costs. The methodology can identify nutritional strategies to minimise environmental impacts, such as increasing the nutritional density of the diets, compared with the least-cost formulation.

Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems

The objective of the study was to develop a life cycle assessment (LCA) for pig farming systems that would account for uncertainty and variability in input data and allow systematic environmental impact comparisons between production systems. The environmental impacts of commercial pig production for 2 regions in Canada (Eastern and Western) were compared using a cradle-to-farm gate LCA. These systems had important contrasting characteristics such as typical feed ingredients used, herd performance, and expected emission factors from manure management. The study used detailed production data supplied by the industry and incorporated uncertainty/variation in all major aspects of the system including life cycle inventory data for feed ingredients, animal performance, energy inputs, and emission factors. The impacts were defined using 5 metrics-global warming potential, acidification potential, eutrophication potential (EP), abiotic resource use, and nonrenewable energy use-and were expressed per kilogram carcass weight at farm gate. Eutrophication potential was further separated into marine EP (MEP) and freshwater EP (FEP). Uncertainties in the model inputs were separated into 2 types: uncertainty in the data used to describe the system (α uncertainties) and uncertainty in impact calculations or background data that affects all systems equally (β uncertainties). The impacts of pig production in the 2 regions were systematically compared based on the differences in the systems (α uncertainties). The method of ascribing uncertainty influenced the outcomes. In eastern systems, EP, MEP, and FEP were lower (P < 0.05) when assuming that all uncertainty in the emission factors for leaching from manure application was β. This was mainly due to increased EP resulting from field emissions for typical ingredients in western diets. When uncertainty in these emission factors was assumed to be α, only FEP was lower in eastern systems (P < 0.05). The environmental impacts for the other impact categories were not significantly different between the 2 systems, despite their aforementioned differences. In conclusion, a probabilistic approach was used to develop an LCA that systematically dealt with uncertainty in the data when comparing multiple environmental impacts measures in pig farming systems for the first time. The method was used to identify differences between Canadian pig production systems but can also be applied for comparisons between other agricultural systems that include inherent variation.

The consequences of introducing stochasticity in nutrient utilisation models: the case of phosphorus utilisation by pigs

Simulation models of nutrient utilisation ignore that variation in pig system components can influence the predicted mean and variance of the performance of a group of pigs. The objective of this study was to develop a methodology to investigate how variation in feed composition would (a) affect the outputs of a nutrient utilisation model and (b) interact with variation that arises from the traits of individual pigs. We used a P intake and utilisation model to address these characteristics. Introduction of stochasticity gave rise to a number of methodological challenges--for example, how to generate variation in both feed composition and pigs and account for correlations between ingredients when modelling variation associated with feed mixing efficiency. Introducing variation in feed composition and pig phenotype resulted in moderate decreases in mean digested, retained and excreted P predicted for a population of pigs and an increase in their associated CV. A lower percentage of pigs in the population were predicted to meet their requirements during the feeding period considered, by comparison with the no-variation scenario. Variation in feed ingredient composition contributed more to performance variation than variation due to mixing efficiency. When variations in both feed composition and pig traits were considered, it was the former rather than the latter that had the dominant influence on variability in pig performance. The developed framework emphasises the consequences of random variability on the predictions of nutrient utilisation models. Such consequences will have a significant impact on decisions about management strategies such as feeding that are subject to variation.