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Phosphorus (P) is an essential nutrient in livestock feed but can pollute waterways. In order for pig production to become less of a threat to the environment, excreta must contain as little P as possible or be efficiently used by plants. This must be achieved without decreasing the livestock performance. Phosphorus and calcium (Ca) deposition in the bones of growing pigs must be optimised without affecting the muscle gain. This requires precision feeding based on cutting-edge techniques of diet formulation throughout the animal growth phase. Modelling and data mining have become important tools in this quest. In this study, a mechanistic model taking into account the distribution of P between bone and soft tissues was compared to the established factorial models (INRA (Jondreville and Dourmad, 2005) and NRC (National Research Council, 2012)) that predict P (apparent total tract digestible, ATTD-P; or standardised total tract digestible, STTD-P) and Ca (total and STTD) requirements as a function of BW and protein deposition. The requirements for different bone mineralisation scenarios, namely, 100% and 85% of the genetic potential, were compared with these two models. Sobol indices were used to estimate the relative impact of growth-related parameters on mineral requirements at 30, 60 and 120 kg of BW. The INRA showed the highest value of ATTD-P requirement between 29 and 103 kg of BW (6%) and lower for lighter and higher BW. Similarly, the model for 85% bone mineralisation showed lower STTD-P requirement than NRC between 29 and 93 kg of BW (7%) and higher for lighter and higher BW. Contrary to other models, the Ca requirement of the proposed model is not fixed in relation to P. It increases from 95 kg of BW while the others decrease. The INRA showed the highest Ca requirements. The model Ca requirements for 100% bone mineralisation are higher than NRC from 20 to 38 kg of BW similar until 70 kg of BW and then higher again. For 85% objective, the model showed lower Ca requirements from 25 to 82 kg of BW and higher for lighter and higher BW. The potential Ca deposition in bones is the most sensitive parameter (84% to 100% of the variance) of both ATTD-P and Ca at 30, 60 and 120 kg. The second most sensitive parameter is the protein deposition, explaining 1% to 15% of the ATTD-P variance. Studies such as this one will help to usher in a new era of sustainable and eco-friendly livestock production.
While feed efficiency (FE) is a trait of great economic importance to the pig industry, the influence of the intestinal microbiome in determining FE is not well understood. The objective of this experiment was to determine the relative influence of FE and farm of birth on the pig colonic microbiome. Animals divergent in residual feed intake (RFI) were sourced from two geographically distinct locations (farms A + B) in Ireland. The 8 most efficient (low RFI (LRFI)) and 8 least efficient (high RFI, (HRFI)) pigs from farm A and 12 LRFI and 12 HRFI pigs from farm B were sacrificed. Colonic digesta was collected for microbial analysis using 16S ribosomal RNA gene sequencing and also for volatile fatty acid analysis. The α-diversity differed between the farms in this study, with pigs from farm A having greater diversity based on Shannon and InvSimpson measures compared to pigs from farm B (P < 0.05), with no difference identified in either Chao1 or observed measures of diversity (P > 0.05). In the analysis of β-diversity, pigs clustered based on farm of birth rather than RFI. Variation in the management of piglets, weight of the piglets, season of the year, sanitary status and dam dietary influence could potentially be causative factors in this large variation between farms. However, despite significant variation in the microbial profile between farms, consistent taxonomic differences were identified between RFI groups. Within the phylum Bacteroidetes, the LRFI pigs had increased abundance of BS11 (P < 0.05) and a tendency toward increased Bacteroidaceae (P < 0.10) relative to the HRFI group. At genus level, the LRFI pigs had increased abundance of Colinsella (P < 0.05), a tendency toward increased Bacteroides and CF231 (P < 0.10). At species level, Ruminococcus flavefaciens had increased abundance in the LRFI compared to the HRFI animals. In conclusion, while farm of birth has a substantial influence on microbial diversity in the pig colon, a microbial signature indicative of FE status was apparent.
Previous work led to the proposal that the precision feeding of a high-concentrate diet may represent a potential method with which to enhance feed efficiency (FE) when rearing dairy heifers. However, the physiological and metabolic mechanisms underlying this approach remain unclear. This study used metabolomics analysis to investigate the changes in plasma metabolites of heifers precision-fed diets containing a wide range of forage to concentrate ratios. Twenty-four half-sib Holstein heifers, with a similar body condition, were randomly assigned into four groups and precision fed with diets containing different proportions of concentrate (20%, 40%, 60% and 80% based on DM). After 28 days of feeding, blood samples were collected 6 h after morning feeding and gas chromatography time-of-ﬂight/MS was used to analyze the plasma samples. Parameters of oxidative status were also determined in the plasma. The FE (after being corrected for gut fill) increased linearly (P < 0.01) with increasing level of dietary concentrate. Significant changes were identified for 38 different metabolites in the plasma of heifers fed different dietary forage to concentrate ratios. The main pathways showing alterations were clustered into those relating to carbohydrate and amino acid metabolism; all of which have been previously associated with FE changes in ruminants. Heifers fed with a high-concentrate diet had higher (P < 0.01) plasma total antioxidant capacity and superoxide dismutase but lower (P ≤ 0.02) hydroxyl radical and hydrogen peroxide than heifers fed with a low-concentrate diet, which might indicate a lower plasma oxidative status in the heifers fed a high-concentrate diet. Thus, heifers fed with a high-concentrate diet had higher FE and antioxidant capacity but a lower plasma oxidative status as well as changed carbohydrate and amino acid metabolism. Our findings provide a better understanding of how forage to concentrate ratios affect FE and metabolism in the precision-fed growing heifers.
Welfare and management of calves is of increasing interest and also influences performance of these animals in later life. The aim of this study was to assess management and environmental conditions under which pre-weaned dairy calves are reared on commercial Irish dairy farms. We included 47 spring-calving, pasture-based herds in this study. Herd and animal-specific data, such as mortality rate, age and breed, were gathered from all participants via the HerdPlus® database. Information pertaining to management practices was collected by conducting an interview with the principal calf rearer, while an assessment of calf housing facilities was conducted to identify conditions calves were reared in. The environmental assessment included measurements of space allowance per calf, as well as feeding equipment hygiene. To assess calf behaviour video observations were used, while accounting for the number of calves present in a group and the space available per calf. Faecal samples were also collected to determine the presence of enteric pathogens among calves. To compare calf space allowance, group size and presence of enteric pathogens early and late in the calving season each farm was visited twice. Calf mortality was not associated with either herd size, space allowance per calf or post-colostrum feeding practices. Higher calf mortality was identified among herds which reported experiencing an on-set of calf pneumonia during weeks 8 to 10 of the calving season. This study demonstrates that factors associated with calf welfare on commercial Irish dairy farms (e.g. space allowance, mortality rate) are independent of herd size. Some management practices however, such as methods used for treating health issues can affect rates of calf mortality experienced. Calf mortality, for example, was lower in herds which treated diarrhoea cases by administering electrolytes, while continuing to offer milk. Behavioural observations indicate that smaller group sizes could promote expression of positive behaviours, potentially resulting from an overall improvement in welfare. Space allowance per calf was not associated with observed behaviour frequencies. We also identified that similar rates of calf mortality are experienced across herds of different sizes.
In mitigating greenhouse gas (GHG) emissions and reducing the carbon footprint of dairy milk, the use of generic estimates in inventory and accounting methodology at farm level largely ignores variation of on-farm GHG emissions. The present study aimed to implement results of an extant dynamic, mechanistic Tier 3 model for enteric methane (CH4) (applied in Dutch national GHG inventory) in order to capture variation in enteric CH4 emission, and in faecal N and organic matter (OM) digestibility, ultimately required to predict manure CH4 and ammonia emission. Tier 3 model predictions were translated into calculation rules that could easily be implemented in an annual nutrient cycling assessment tool including GHG emissions, which is currently used by Dutch dairy farmers. Calculations focussed on (1) enteric CH4 emission, (2) apparent faecal OM digestibility and (3) apparent faecal N digestibility. Enteric CH4 was expressed in CH4 yield indicated with the term emission factor (EF; g CH4/kg DM) for individual dietary components and feedstuffs. Factors investigated to cover predicted variation in EF value included the level of feed intake, the type of roughage fed (proportions of grass silage and maize silage) and the quality of roughage fed. A minimum number of three classes of roughage type (i.e. 0. 40% and 80% maize silage in roughage DM) appeared necessary to obtain correspondence between interpolated EF values from EF lists and Tier 3 model predictions. A linear decline in EF value with 1% per kg increase in DM intake is adopted based on model simulations. The quality of roughage was represented by the effect of maturity of harvested grass or of the whole plant maize at cutting, based on a survey of modelling as well as experimental work. Also, predictions were assembled for apparent faecal OM digestibility which could be used in national inventory and in farm accounting. Apparent faecal N digestibility (as a major determinant of predicted urinary N excretion) was predicted, to support current Dutch national ammonia emission inventory and to correct the level of N digestibility in farm accounting. Compared to generic values or values retrieved from the Dutch feeding tables, predicted OM and N digestibility and enteric CH4 are better rooted in physiological principles and better reflect observed variation under experimental conditions. The present results apply for conditions with fairly intensive grassland management in temperate regions.
Although East Africa is home to one of the most advanced dairy industries in Sub-Saharan Africa, regional annual milk production is insufficient to meet the demand. The challenge of increasing milk yields (MYs) among smallholder dairy cattle farmers (SDCFs) has received considerable attention and resulted in the introduction of various dairy management strategies (DMSs). Despite adoption of these DMSs, MYs remain low on-farm and there is a large discrepancy in the efficacy of DMSs across different farms. Therefore, the present study sought to: (1) identify on-farm DMSs employed by East African SDCFs to increase MYs and (2) summarize existing literature to quantify the expected MY changes associated with these identified DMSs. Data were collected through a comprehensive literature review and in-depth semi-structured interviews with 10 experts from the East African dairy sector. Meta-analysis of the literature review data was performed by deriving four multivariate regression models (i.e. models 1 to 4) that related DMSs to expected MYs. Each model differed in the weighting strategy used (e.g. number of observations and inverse of the standard errors) and the preferred model was selected based on the root estimated error variance and concordance correlation coefficient. Nine DMSs were identified, of which only adoption of improved cattle breeds and improved feeding (i.e. increasing diet quality and quantity) consistently and significantly (P < 0.05) increased daily MYs across the available studies. Improved breeds alongside adequate feeding explained ≤50% of the daily MYs observed in the metadata while improved feeding explained ≤30% of the daily MYs observed across the different models. Conversely, calf suckling significantly (P < 0.05) reduced MYs according to model 2. Other variables including days in milk, trial length and maximum ambient temperature (used as a proxy for heat stress) contributed significantly to decreasing MYs. These variables may explain some of the heterogeneity in MY responses to DMSs reported in the literature. Our results suggest that using improved cattle breeds alongside improved feeding is the most reliable strategy to increase MYs on-farm in East Africa. Nevertheless, these DMSs should not be considered as standalone solutions but as a pool of options that should be combined depending on the resources available to the farmer to achieve a balance between using dairy cattle genetics, proper husbandry and feeding to secure higher MYs.
Differences in how individuals cope with stressful conditions (e.g. novel/unfamiliar environment, social isolation and increases in human contact) can explain the variability in data collection from nutrient digestibility trials. We used the collared peccary (Pecari tajacu), which is under process of domestication and shows high individual behavioral distinctiveness in reactions toward humans, to test the hypothesis that behavioral differences play a role in nutrient digestibility. We assessed the individual behavioral traits of 24 adult male collared peccaries using both the ‘behavioral coding’ and the ‘subjective ratings’ approaches. For the behavioral coding assessment, we recorded the hourly frequency of behaviors potentially indicative of stress during the 30-day habituation period to the experimental housing conditions. The subjective ratings were performed based on the individuals’ reactions to three short-term challenge tests (novel environment, novel object and threat from a capture net) over a period of 56 days. During the last 26 days, the collared peccaries were fed diets either high (n = 12) or low (n = 12) in dietary fiber levels, and we determined the total tract apparent digestibility of nutrients. The individual subjective ratings showed consistency in the correlated measures of ‘relaxedness’, ‘quietness’ and ‘satisfaction’ across the three challenge tests, which were combined to produce z score ratings of one derived variable (‘calmness’). Individual frequency of BPIS/h and calmness scores were negatively correlated and both predicted the total tract digestibility of acid detergent fiber (ADF), which ranged from 0.41 to 0.79. The greater the calmness z scores (i.e. calmer individuals), the greater the total tract digestibility of ADF. In contrast, the higher the frequency of BPIS/h, the lower the total tract digestibility of ADF. Therefore, our results provide evidence that by selecting calmer collared peccaries, there will be an increase in their capacity to digest dietary fiber.
Knowing how energy intake is partitioned between maintenance, growth and egg production (EP) of birds makes it possible to structure models and recommend energy intakes based on differences in the BW, weight gain (WG) and EP on commercial quail farms. This research was a dose-response study to re-evaluate the energy partition for Japanese quails in the EP phase, based on the dilution technique to modify the retained energy (RE) of the birds. A total of 300 VICAMI® Japanese quail, housed in climatic chambers, were used from 16 weeks of age, with averages for BW of 185 g and EP of 78%, for 10 weeks. To modify the RE in the bird’s body, a qualitative dilution of dietary energy was used. Ten treatments (metabolisable energy levels) were distributed in completely randomised units, with six replicates of five quails per experimental unit. Metabolisable energy intake (MEI), egg mass (EM) and RE were expressed in kJ/kg0.67. The utilisation efficiency (kt) was estimated from the relationship between RE and MEI. The metabolisable energy for maintenance was given by RE = 0. The net energy requirement for WG was obtained from the relationship between RE in the BW as a function of the BW. The utilisation efficiency for EP (ko) was obtained from the relationship between EM and RE corrected MEI for maintenance and WG. Based on these efficiencies, the requirements for WG and EM were calculated. The energy intake by Japanese quails was partitioned according to the model: MEI = 569.8 × BW0.67 + 22 × WG + 13 × EM. The current study provides procedures and methods designed for quails as well as a simple and flexible model that can be quickly adopted by technicians and poultry companies.
There is a need to develop feeding strategies to prevent the adverse effect of concentrate feeding in high-performance horses fed energy-dense diets aiming to maintain their health and welfare. The objective of this study is to determine the effect of a VistaEQ product containing 4% live yeast Saccharomyces cerevisiae (S. cerevisiae), with activity 5 × 108 colony-forming unit/g and fed 2 g/pony per day, on faecal microbial populations when supplemented with high-starch and high-fibre diets using Illumina next generation sequencing of the V3-V4 region of the 16S ribosomal RNA gene. The four treatments were allocated to eight mature Welsh section A pony geldings enrolled in a 4-period × 8 animal crossover design. Each 19-day experimental period consisted of an 18-day adaptation phase and a single collection day, followed by a 7-day wash out period. After DNA extraction from faeces and library preparation, α-diversity and linear discriminant analysis effect size were performed using 16S metagenomics pipeline in Quantitative Insights Into Microbial Ecology (QIIME™) and Galaxy/Hutlab. Differences between the groups were considered significant when linear discriminant analysis score was >2 corresponding to P < 0.05. The present study showed that S. cerevisiae used was able to induce positive changes in the equine microbiota when supplemented to a high-fibre diet: it increased relative abundance (RA) of Lachnospiraceae and Dehalobacteriaceae family members associated with a healthy core microbiome. Yeast supplementation also increased the RA of fibrolytic bacteria (Ruminococcus) when fed with a high-fibre diet and reduced the RA of lactate producing bacteria (Streptococcus) when a high-starch diet was fed. In addition, yeast increased the RA of acetic, succinic acid producing bacterial family (Succinivibrionaceae) and butyrate producing bacterial genus (Roseburia) when fed with high-starch and high-fibre diets, respectively. VistaEQ supplementation to equine diets can be potentially used to prevent acidosis and increase fibre digestibility. It may help to meet the energy requirements of performance horses while maintaining gut health.
Fibre is essential to maintain healthy gut; however, energy demands of performance horses can be too high to be met by forages alone. Yeast may support the function of cellulolytic bacteria to digest fibre. The aim of this work was to determine the effect of an oral supplement (VistaEQ) containing 4% live yeast on the in vitro and in vivo digestibility of high-starch (HS) and high-fibre diets (HF). Eight ponies were used in a 4 × 4 Latin square design consisting of 4- × 19-day periods and four diets: HF, HF + yeast (HFY), HS and HS + yeast (HSY). In vivo apparent digestibility (AD) was estimated using total collection technique, and faecal particle size was measured using NASCO digestive analyser. Faeces from the ponies were subsequently used as an inoculum in ANKOM RF gas production system to assess fermentation kinetics in vitro. Each module contained 1 g of feed substrate DM in the following combinations: 50% grass hay and 50% alfalfa (HF_50 : 50) or concentrate (HS_50 : 50), and 75% grass hay and 25% alfalfa (HF_75 : 25) or concentrate (HS_75 : 25) with or without yeast. Yeast was able to induce more gas production from HF_75 : 25, HS_75 : 25 and HF_50 : 50 feed substrates incubated with respective faecal inoculum base. Yeast did not affect pH in vitro when the substrates were incubated in 50 : 50 ratio, while the pH was higher for HF_75 : 25 incubated with correspondent faecal inoculum compared to HS_75 : 25 and HSY_75 : 25. Yeast had no effects on ADF and CP AD of either diet. Yeast addition increased DM (HF: 0.2%, HS: 0.4%), organic matter (HF: 0.7%, HS: 1.3%), NDF (HF: 0.5%, HS: 1.5%), total detergent fibre (HF: 0.7%; HS: 0.4%) (P < 0.05) and also tended to increase hemicellulose AD (HF: 0.9%, HS: 1.2%) (P < 0.10). Faecal pH in vivo was higher for both HF diets compared to HS diet without yeast supplementation (P < 0.001, HF and HFY: 6.8; HS: 6.6, HSY: 6.7). However, no difference was observed in faecal pH when HSY was compared to both HF diets. Yeast had no effect on the size of the faecal particles (P > 0.05). Yeast increased in vitro gas production, suggesting more energy could be extracted from the feed, and the in vivo AD of some of the nutrients when HF and HS diets were fed.
Selection for prolificacy in sows has resulted in higher metabolic demands during lactation. In addition, modern sows have an increased genetic merit for leanness. Consequently, sow metabolism during lactation has changed, possibly affecting milk production and litter weight gain. The aim of this study was to investigate the effect of lactational feed intake on milk production and relations between mobilization of body tissues (adipose tissue or skeletal muscle) and milk production in modern sows with a different lactational feed intake. A total of 36 primiparous sows were used, which were either full-fed (6.5 kg/day) or restricted-fed (3.25 kg/day) during the last 2 weeks of a 24-day lactation. Restricted-fed sows had a lower milk fat percentage at weaning and a lower litter weight gain and estimated milk fat and protein production in the last week of lactation. Next, several relations between sow body condition (loss) and milk production variables were identified. Sow BW, loin muscle depth and backfat depth at parturition were positively related to milk fat production in the last week of lactation. In addition, milk fat production was related to the backfat depth loss while milk protein production was related to the loin muscle depth loss during lactation. Backfat depth and loin muscle depth at parturition were positively related to lactational backfat depth loss or muscle depth loss, respectively. Together, results suggest that sows which have more available resources during lactation, either from a higher amount of body tissues at parturition or from an increased feed intake during lactation, direct more energy toward milk production to support a higher litter weight gain. In addition, results show that the type of milk nutrients that sows produce (i.e. milk fat or milk protein) is highly related to the type of body tissues that are mobilized during lactation. Interestingly, relations between sow body condition and milk production were all independent of feed level during lactation. Sow management strategies to increase milk production and litter growth in modern sows may focus on improving sow body condition at the start of lactation or increasing feed intake during lactation.
Precision feeding using real-time models to estimate daily tailored diets can potentially increase nutrient utilization efficiency. However, to improve the estimation of amino acid requirements for growing–finishing pigs, it is necessary to accurately estimate the real-time body protein (BP) mass. The aim of this study was to predict individual BP over time in order to obtain individual daily protein content of the gain (i.e., protein deposition/daily gain, PD/DG) to be integrated into a real-time model used for precision feeding. Two databases were used in this study: one for the development of the equations for the model and the other for model evaluation. For the equations, data from 79 barrows (25 to 144 kg BW) were used to estimate the parameters for a Gompertz function and a mixed linear-quadratic regression. Individual BP predictions obtained by dual X-ray absorptiometry were regressed as a function of BW. Individual pig BP estimates were obtained by linear-quadratic regression using the MIXED procedure of SAS, considering pig measurements repeated in time. Individual Gompertz curves were obtained using the NLMIXED procedure of SAS. Both procedures generate an average or a general model, which was assessed for accuracy with the database used to generate the equations. Coefficients of concordance and determination were both 0.99, and the RMSE was 0.21 kg for the linear-quadratic regression. The Gompertz curve coefficients of concordance and determination were both 0.99, and the RMSE was 0.36 kg. In sequence, the linear-quadratic regression and Gompertz curve were evaluated in an independent data set (488 observations; 21 to 126 kg BW). The linear-quadratic regression to predict BP mass was accurate (mean absolute percentage error (MAPE) = 2.5%; bias = 0.03); the Gompertz model performed worse (MAPE = 3.9%; bias = 0.04) than the linear-quadratic regression. When using the derivative of these equations to predict PD/DG, the linear-quadratic regression was more accurate (MAPE = 4.8%, bias = 0.17%) compared to the Gompertz (MAPE = 10.6%, bias = −0.99%) mainly due to the linear decrease in PD/DG in the observed data. Further analysis using individual pig data showed that the goodness of fit of PD/DG curve depends on the individual shape of the growth curve, with either the Gompertz or the linear-quadratic regression being more accurate for specific individuals. Therefore, both approaches are provided to allow end users to select the model that best fits their needs. The proposed update of the empirical component of the original model, using either linear-quadratic regression or the Gompertz function, is able to predict BP in real-time with good accuracy.
Guanidinoacetic acid (GAA) can improve the growth performance of bulls. This study investigated the influences of GAA addition on growth, nutrient digestion, ruminal fermentation and serum metabolites in bulls. Forty-eight Angus bulls were randomly allocated to experimental treatments, that is, control, low-GAA (LGAA), medium-GAA (MGAA) and high-GAA (HGAA), with GAA supplementation at 0, 0.3, 0.6 and 0.9 g/kg DM, respectively. Bulls were fed a basal diet containing 500 g/kg DM concentrate and 500 g/kg DM roughage. The experimental period was 104 days, with 14 days for adaptation and 90 days for data collection. Bulls in the MGAA and HGAA groups had higher DM intake and average daily gain than bulls in the LGAA and control groups. The feed conversion ratio was lowest in MGAA and highest in the control. Bulls receiving 0.9 g/kg DM GAA addition had higher digestibility of DM, organic matter, NDF and ADF than bulls in other groups. The digestibility of CP was higher for HGAA than for LGAA and control. The ruminal pH was lower for MGAA, and the total volatile fatty acid concentration was greater for MGAA and HGAA than for the control. The acetate proportion and acetate-to-propionate ratio were lower for MGAA than for LGAA and control. The propionate proportion was higher for MGAA than for control. Bulls receiving GAA addition showed decreased ruminal ammonia N. Bulls in MGAA and HGAA had higher cellobiase, pectinase and protease activities and Butyrivibrio fibrisolvens, Prevotella ruminicola and Ruminobacter amylophilus populations than bulls in LGAA and control. However, the total protozoan population was lower for MGAA and HGAA than for LGAA and control. The total bacterial and Ruminococcus flavefaciens populations increased with GAA addition. The blood level of creatine was higher for HGAA, and the activity of l-arginine glycine amidine transferase was lower for MGAA and HGAA, than for control. The blood activity of guanidine acetate N-methyltransferase and the level of folate decreased in the GAA addition groups. The results indicated that dietary addition of 0.6 or 0.9 g/kg DM GAA improved growth performance, nutrient digestion and ruminal fermentation in bulls.
Phytase has long been used to decrease the inorganic phosphorus (Pi) input in poultry diet. The current study was conducted to investigate the effects of Pi supplementation on laying performance, egg quality and phosphate–calcium metabolism in Hy-Line Brown laying hens fed phytase. Layers (n = 504, 29 weeks old) were randomly assigned to seven treatments with six replicates of 12 birds. The corn–soybean meal-based diet contained 0.12% non-phytate phosphorus (nPP), 3.8% calcium, 2415 IU/kg vitamin D3 and 2000 FTU/kg phytase. Inorganic phosphorus (in the form of mono-dicalcium phosphate) was added into the basal diet to construct seven experimental diets; the final dietary nPP levels were 0.12%, 0.17%, 0.22%, 0.27%, 0.32%, 0.37% and 0.42%. The feeding trial lasted 12 weeks (hens from 29 to 40 weeks of age). Laying performance (housed laying rate, egg weight, egg mass, daily feed intake and feed conversion ratio) was weekly calculated. Egg quality (egg shape index, shell strength, shell thickness, albumen height, yolk colour and Haugh units), serum parameters (calcium, phosphorus, parathyroid hormone, calcitonin and 1,25-dihydroxyvitamin D), tibia quality (breaking strength, and calcium, phosphorus and ash contents), intestinal gene expression (type IIb sodium-dependent phosphate cotransporter, NaPi-IIb) and phosphorus excretion were determined at the end of the trial. No differences were observed on laying performance, egg quality, serum parameters and tibia quality. Hens fed 0.17% nPP had increased (P < 0.01) duodenum NaPi-IIb expression compared to all other treatments. Phosphorus excretion linearly increased with an increase in dietary nPP (phosphorus excretion = 1.7916 × nPP + 0.2157; R2 = 0.9609, P = 0.001). In conclusion, corn–soybean meal-based diets containing 0.12% nPP, 3.8% calcium, 2415 IU/kg vitamin D3 and 2000 FTU/kg phytase would meet the requirements for egg production in Hy-Line Brown laying hens (29 to 40 weeks of age).
Over the last decade, extensive research effort has been placed on developing methane mitigation strategies in ruminants. Many disciplines on animal science disciplines have been involved, including nutrition and physiology, microbiology and genetic selection. To date, few of the suggested strategies have been implemented because: (1) methane emissions currently have no direct or indirect economic value for farmers, with no financial incentive to change practices and (2) most strategies have limited, or no, long-term effects. Consequently, there is a fundamental need for research on methane mitigation strategies across disciplines. Coordinated international initiatives similar to METHAGENE could represent highly relevant coordination tool of collaboration between countries, facilitating knowledge exchange, sharing concerns and building future collaborations.
The farrowing process is one of the most energy-demanding activities for the modern hyperprolific sow. This study evaluated the effects of supply of energy on the expected date of farrowing on the farrowing kinetics and piglets’ performance during the first 24 h after birth. A total of 80 sows were used. The sows and their respective litters were considered as the experimental unit. On the expected day of farrowing, the sows were allocated to one of the following groups: sows that did not have access to feed from farrowing induction until the end of the farrowing process (CON, n = 40); sows fed 500 g of energetic supplement, which consisted of 250 g of the basal lactation diet plus 250 g of cane sugar, 18 h after farrowing induction (SUP, n = 40). The farrowing duration, farrowing assistance, birth interval, number of total born, stillborn and mummified piglets were recorded for each sow. Piglets were weighed individually at birth and 24 h later. The interval from birth to first suckle was evaluated individually for each piglet in 16 randomly selected litters (eight litters per treatment group). Blood glucose concentrations of six sows were measured shortly after expulsion of the first piglet. Farrowing duration, farrowing assistance and stillborn rate tended to be greater (P = 0.06, P = 0.09 and P = 0.07, respectively) in sows from the CON group compared to sows from the SUP group. However, there was no difference (P > 0.05) between the groups for birth interval. Colostrum intake was greater (P < 0.05) for piglets from the SUP group compared to piglets from the CON group. Additionally, BW gain of the piglets suckling the SUP group was greater (P < 0.05) than those suckling the CON group at 24 h after birth. The blood glucose concentrations during the expulsive stage of farrowing were greater (P < 0.05) in the SUP group than for sows from the CON group. In conclusion, supplying modern hyperprolific sows energy on the expected day of farrowing is a valuable nutritional intervention to improve the farrowing kinetics and piglets’ performance in early life.
Understanding existing levels of genetic variability of camel populations is capital for conservation activities. This study aims to provide information on the genetic diversity of four dromedary populations, including Guerzni, Harcha, Khouari and Marmouri. Blood samples from 227 individuals belonging to the aforementioned populations were obtained and genotyped by 16 microsatellite markers. A total of 215 alleles were observed, with the mean number of alleles per locus being 13.4 ± 6.26. All loci were polymorphic in the studied populations. The average expected heterozygosity varied from a maximum of 0.748 ± 0.122 in Guerzni population to a minimum of 0.702 ± 0.128 in Harcha population; Guerzni population showed the highest value of observed heterozygosity (0.699 ± 0.088), whereas Harcha population the lowest (0.646 ± 0.130). Mean estimates of F-statistics obtained over loci were FIS = 0.0726, FIT = 0.0876 and FST = 0.0162. The lowest genetic distance was obtained between Guerzni and Khouari (0.023), and the highest genetic distance between Harcha and Marmouri (0.251). The neighbour-joining phylogenetic tree showed two groups of populations indicating a cluster of Guerzni, Khouari and Marmouri, and a clear isolation of Harcha. The genetic distances, the factorial correspondence analysis, the analysis of genetic structure and the phylogenetic tree between populations revealed significant differences between Harcha and other populations, and a high similarity between Guerzni, Khouari and Marmouri. It is concluded from this study that the camel genetic resources studied are well diversified. However, the herd management, especially the random selection of breeding animals, can increase the level of genetic mixing between different populations, mainly among Guerzni, Khouari and Marmouri, that live in the same habitat and grazing area.
The main objective of this study was to develop a dynamic energy balance model for dairy goats to describe and quantify energy partitioning between energy used for work (milk) and that lost to the environment. Increasing worldwide concerns regarding livestock contribution to global warming underscore the importance of improving energy efficiency utilization in dairy goats by reducing energy losses in feces, urine and methane (CH4). A dynamic model of CH4 emissions from experimental energy balance data in goats is proposed and parameterized (n = 48 individual animal observations). The model includes DM intake, NDF and lipid content of the diet as explanatory variables for CH4 emissions. An additional data set (n = 122 individual animals) from eight energy balance experiments was used to evaluate the model. The model adequately (root MS prediction error, RMSPE) represented energy in milk (E-milk; RMSPE = 5.6%), heat production (HP; RMSPE = 4.3%) and CH4 emissions (E-CH4; RMSPE = 11.9%). Residual analysis indicated that most of the prediction errors were due to unexplained variations with small mean and slope bias. Some mean bias was detected for HP (1.12%) and E-CH4 (1.27%) but was around zero for E-milk (0.14%). The slope bias was zero for HP (0.01%) and close to zero for E-milk (0.10%) and E-CH4 (0.22%). Random bias was >98% for E-CH4, HP and E-milk, indicating non-systematic errors and that mechanisms in the model are properly represented. As predicted energy increased, the model tended to underpredict E-CH4 and E-milk. The model is a first step toward a mechanistic description of nutrient use by goats and is useful as a research tool for investigating energy partitioning during lactation. The model described in this study could be used as a tool for making enteric CH4 emission inventories for goats.
Poultry production is an important way of enhancing the livelihoods of rural populations, especially in low- and middle-income countries (LMICs). As poultry production in LMICs remains dominated by backyard systems with low inputs and low outputs, considerable yield gaps exist. Intensification can increase poultry productivity, production and income. This process is relatively recent in LMICs compared to high-income countries. The management practices and the constraints faced by smallholders trying to scale-up their production, in the early stages of intensification, are poorly understood and described. We thus investigated the features of the small-scale commercial chicken sector in a rural area distant from major production centres. We surveyed 111 commercial chicken farms in Kenya in 2016. We targeted farms that sell the majority of their production, owning at least 50 chickens, partly or wholly confined and provided with feeds. We developed a typology of semi-intensive farms. Farms were found mainly to raise dual-purpose chickens of local and improved breeds, in association with crops and were not specialized in any single product or market. We identified four types of semi-intensive farms that were characterized based on two groups of variables related to intensification and accessibility: (i) remote, small-scale old farms, with small flocks, growing a lot of their own feed; (ii) medium-scale, old farms with a larger flock and well located in relation to markets and (iii) large-scale recently established farms, with large flocks, (iii-a) well located and buying chicks from third-party providers and (iii-b) remotely located and hatching their own chicks. The semi-intensive farms we surveyed were highly heterogeneous in terms of size, age, accessibility, management, opportunities and challenges. Farm location affects market access and influences the opportunities available to farmers, resulting in further diversity in farm profiles. The future of these semi-intensive farms could be compromised by several factors, including the competition with large-scale intensive farmers and with importations. Our study suggests that intensification trajectories in rural areas of LMICs are potentially complex, diverse and non-linear. A better understanding of intensification trajectories should, however, be based on longitudinal data. This could, in turn, help designing interventions to support small-scale farmers.