Effect of glucose infusion on glucose and insulin metabolism in early- and mid-lactation ewes and goats fed diets differing in starch and highly digestible fiber concentration.

This study aimed to test possible metabolic differences between ewes and goats in response to an intravenous glucose infusion. Thirty-six animals, 18 mature Sarda dairy ewes and 18 mature Saanen goats (from 15 to 150 ± 11 d in milk [DIM], mean ± SD; body weight: 49.8 ± 6.8 kg for ewes, 60.6 ± 7.3 kg for goats) were compared simultaneously. In early lactation, both species received the same high-starch diet (HS: 20.4% starch, 35.4% neutral detergent fiber [NDF], on dry matter [DM] basis), whereas from 92 ± 11 DIM both species were randomly allocated to 2 dietary treatments: HS (20.0% starch, 36.7% NDF, on DM basis) and low-starch (LS: 7.8% starch, 48.8% NDF, on DM basis) diets. At 50 and 150 ± 11 DIM, ewes and goats were challenged with an intravenous glucose tolerance test and peripheral concentrations of glucose and insulin were determined 15 min before and 5, 10, 15, 30, 45, 90, and 180 min after glucose infusion. In early lactation, baseline plasma glucose and insulin concentrations tended to be higher in ewes than in goats (glucose: 55.8 vs. 42.9 ± 7.3 mg/dL; insulin: 0.13 vs. 0.05 ± 0.04 µg/L). After glucose infusion, glucose and insulin concentrations were higher in ewes than in goats (278.6 vs. 247.6 ± 13.1 mg/dL; 0.82 vs. 0.46 ± 0.12 µg/L). In mid-lactation, the dietary treatment (HS vs. LS) did not affect glucose and insulin metabolism. Baseline plasma glucose was numerically highest in ewes, while baseline insulin was higher in ewes than in goats (0.39 vs. 0.12 ± 0.099 µg/L). After glucose infusion, glucose concentration did not differ between ewes and goats, while insulin concentration was highest in ewes. Compared with goats, ewes showed in both periods a higher peak insulin, insulin increment, linear insulin area under the curve, insulin resistance index, and lower insulin sensitivity indices. In conclusion, despite the limitations associated with the use of intravenous glucose tolerance test to assess glucose regulation mechanisms, this study indicated large species differences in both early and mid-lactation and a more evident anabolic status in the ewes compared with the goats.

Does the timing of pasture allocation affect rumen and plasma metabolites and ghrelin, insulin and cortisol profile in dairy ewes?

A study was undertaken to assess the impact of the timing of grazing on rumen and plasma metabolites and some metabolic hormones in lactating dairy sheep allocated to an Italian ryegrass (Lolium multiflorum Lam) pasture in spring for 4 h/d. Twenty-four mid lactation Sarda ewes stratified for milk yield, body weight, and body condition score, were divided into four homogeneous groups randomly allocated to the treatments (2 replicate groups per treatment). Treatments were morning (AM, from 08:00 to 12:00) and afternoon pasture allocation (PM, from 15:30 to 19:30). Samples of rumen liquor (day 39) and blood plasma (days 17 and 34 of the experimental period) were collected before and after the grazing sessions. Moreover, on days 11 and 35, grazing time was assessed by direct observation and herbage intake measured by the double weighing procedure. Grazing time was longer in PM than AM ewes (P < 0.001) but herbage intake was undifferentiated between groups. The intake of water-soluble carbohydrates at pasture was higher in PM than AM ewes (P < 0.05). The post-grazing propionic and butyric acid concentration, as measured on day 39, were higher in PM than AM ewes (P < 0.05). The basal level of glucose on day 34 and insulin (on both sampling days) were higher in PM than AM (P < 0.05). The opposite trend was detected for non-esterified fatty acids (P < 0.05, day 34) and urea (both days). Pasture allocation in the afternoon rather than in the morning decreased plasma concentration of ghrelin (P < 0.001) and cortisol (P < 0.001), with a smoothed trend on day 34 in the latter variable. To conclude, postponing the pasture allocation to afternoon increased the intake of WSC, favoring a glucogenic pattern of rumen fermentation and a rise of glucose and insulin levels in blood, although these effects were not consistent across the whole experimental period. Moreover, the afternoon grazing decreased the level of cortisol and ghrelin, suggesting a higher satiation-relaxing effect.

Cardoon Meal as Alternative Protein Source to Soybean Meal for Limousine Bulls Fattening Period: Effects on Growth Performances and Meat Quality Traits.

Soybean meal is the most important protein source in beef cattle feeding. The research of alternative protein sources to replace soy use, avoiding negative effects on in vivo performance and on the product's quality, is an important issue. In this context, cardoon represents a non-OGM resilient crop that can be cultivated in marginal lands for extracting its seed oil (utilized for biodiesel and biodegradable bioplastic production) and whose and the residual meal from its seed oil (utilized for biodiesel and biodegradable bioplastic production) could be a suitable by-product for animal feeding, due to its fairly high protein content. The aim of this study was to evaluate the feasibility of using cardoon meal as an innovative protein source during the Limousine bulls' fattening period. Thirty-two bulls were divided into two groups and fed with a diet containing soybean meal (SG) or partially replacing soybean meal with cardoon meal as a protein source (CG), respectively. The feeding trial lasted about 11 months. Growth performances and meat physical-chemical traits were evaluated. No statistical differences in feed efficiency, average daily gain, or in the main meat quality indicators, as well as in fatty acid profiles were found among the groups. Therefore, cardoon meal could be considered as an alternative to soybean meal in fattening Limousine bulls in order to enhance the sustainability of the farming system.

Pre- and Post-Slaughter Methodologies to Estimate Body Fat Reserves in Lactating Saanen Goats.

This work aimed to compare pre- and post-slaughter methodologies to estimate body fat reserves in dairy goats. Twenty-six lactating Saanen goats ranging from 43.6 to 69.4 kg of body weight (BW) and from 1.84 to 2.96 of body condition score (BCS; 0-5 range) were used. Fifteen pre-slaughter and four post-slaughter measurement values were used to estimate the weight of fat in the omental (OM), mesenteric (MES), perirenal (PR), organ (ORG), carcass (CARC), and non-carcass components (NC) and total (TOT, calculated as the sum of CARC and NC) depots in goats. The pre-slaughter measurements were withers height; rump height; rump length; pelvis width; chest depth; shoulder width; heart girth; body length; sternum height; BW; BCS assessed in the lumbar (BCSl) and sternal (BCSs) regions; and fat thickness measured by ultrasound in the lumbar (FTUSl), sternal (FTUSs), and perirenal (FTUSpr) regions. The post-slaughter measurements were hot carcass weight (HCW), empty body weight (EBW), and fat thickness measured by digital caliper in the lumbar (FTDCl) and sternal (FTDCs) regions. Linear and multiple regressions were fit to data collected. BW, BCS (from lumbar and sternal regions), all somatic measurements, and fat thickness measured by ultrasound in the lumbar and sternal regions were not adequate to estimate the weight of total fat in lactating Saanen goats (R2 ≤ 0.55). The best pre-slaughter and post-slaughter estimators of OM, MES, PR, ORG, NC, and TOT fat were FTUSpr and EBW, respectively. Among pre- and post-slaughter measurements, BCSl (R2 = 0.63) and HCW (R2 = 0.82) provided the most accurate predictions of CARC fat, respectively. Multiple regression using the pre-slaughter variables FTUSpr, BW, and BCSl yielded estimates of TOT fat with an R2 = 0.92 (RSD = 1.14 kg). On the other hand, TOT fat predicted using the post-slaughter variables HCW and FTDCs had an R2 = 0.83 (RSD = 1.41 kg). These results confirm that fat reserves can be predicted in lactating Saanen goats with high precision using multiple regression equations combining in vivo measurements.

Dietary Starch Concentration Affects Dairy Sheep and Goat Performances Differently during Mid-Lactation.

Evolution of milk production, body reserves and blood metabolites and their relationships with dietary carbohydrates were compared in 30 Sarda dairy ewes and 26 Saanen dairy goats in mid-lactation. From 92 to 152 ± 11 days in milk (DIM), each species was allocated to two dietary treatments: high-starch (HS: 20.0% starch, on DM basis) and low-starch (LS: 7.8% starch, on DM basis) diets. In mid-lactating goats, the HS diet increased fat-corrected milk yield (FCM (3.5%); 2.65 vs. 2.53 kg/d; p = 0.019) and daily milk net energy (NEL; p = 0.025), compared to the LS diet. The body condition score (BCS) was not affected. In mid-lactating ewes, the LS diet increased FCM (6.5%) (1.47 vs. 1.36 kg/d; p = 0.008), and NEL (p = 0.008), compared to the HS diet. In addition, BCS was greater in HS than in LS ewes (3.53 vs. 3.38; p = 0.008). Goats had a higher growth hormone (GH) and lower insulin concentration than ewes (GH: 2.62 vs. 1.37 ng/mL; p = 0.04; insulin: 0.14 vs. 0.38 µg/L; p < 0.001 in goats and ewes, respectively). In conclusion, in mid-lactation, the two species responded differently to dietary carbohydrates, probably due to differences in the concentration of GH and insulin. The HS diet favored milk yield in goats and body reserve accumulation in ewes. In ewes, the partial replacement of starch with highly digestible fiber increased energy partitioning in favor of milk production.

Sheep and Goats Respond Differently to Feeding Strategies Directed to Improve the Fatty Acid Profile of Milk Fat.

This bibliographic review presents and discusses the nutritional strategies able to increase the concentration of beneficial fatty acids (FA) in sheep and goat milk, and dairy products, with a particular focus on the polyunsaturated FA (PUFA), and highlights differences between the two species. In fact, by adopting appropriate feeding strategies, it is possible to markedly vary the concentration of fat in milk and improve its FA composition. These strategies are based mostly on the utilization of herbage rich in PUFA, or on the inclusion of vegetable, marine, or essential oils in the diet of lactating animals. Sheep respond more effectively than goats to the utilization of fresh herbage and to nutritional approaches that improve the milk concentration of c9,t11-conjugated linoleic acid (c9,t11-CLA) and α-linolenic acid. Dietary polyphenols can influence milk FA profile, reducing or inhibiting the activity and growth of some strains of rumen microbes involved in the biohydrogenation of PUFA. Although the effectiveness of plant secondary compounds in improving milk FA composition is still controversial, an overall positive effect has been observed on the concentration of PUFA and RA, without marked differences between sheep and goats. On the other hand, the positive effect of dietary polyphenols on the oxidative stability of milk fat appears to be more consistent.

Milk Urea Concentration in Dairy Sheep: Accounting for Dietary Energy Concentration.

In dairy sheep milk urea concentration (MUC) is highly and positively correlated with dietary crude protein (CP) content and, to a lesser extent, with protein intake. However, the effect of dietary energy and carbohydrate sources on MUC of lactating ewes is not clear. Thus, the objective of this study was to assess the effects of diets differing in energy concentration and carbohydrate sources on MUC values in lactating dairy ewes. Two experiments were conducted (experiment 1, E1, and experiment 2, E2) on Sarda ewes in mid and late lactation kept in metabolic cages for 23 d. In both experiments, homogeneous groups of five ewes were submitted to four (in E1) or three (in E2) dietary treatments, consisting of pelleted diets ranging from low energy (high-fiber diets: 1.2-1.4 Mcal of net energy for lactation (NEL)) to high energy (high-starch diets: 1.7-1.9 Mcal of NEL) contents, but with a similar CP concentration (18.4% dry matter (DM), on average). Each diet had a different main ingredient as follows: corn flakes, barley meal, beet pulp, or corn cobs in E1 and corn meal, dehydrated alfalfa, or soybean hulls in E2. Regression analysis using treatment means from both experiments showed that the best predictor of MUC (mg/100 mL) was the dietary NEL (Mcal/kg DM, MUC = 127.6 - 51.2 × NEL, R2 = 0.85, root of the mean squared error (rmse) = 4.36, p < 0.001) followed by the ratio CP/NEL (g/Mcal, MUC = -14.9 + 0.5 × CP/ NEL, R2 = 0.83, rmse = 4.63, p < 0.001). A meta-regression of an extended database on stall-fed dairy ewes, including the E1 and E2 experimental data (n = 44), confirmed the predictive value of the CP/ NEL ratio, which resulted as the best single predictor of MUC (MUC = -13.7 + 0.5 × CP/NEL, R2 = 0.93, rmse = 3.30, p < 0.001), followed by dietary CP concentration (MUC = -20.7 + 3.7 × CP, R2 = 0.82, rmse = 4.89, p < 0.001). This research highlights that dietary energy content plays a pivotal role in modulating the relationship between MUC and dietary CP concentration in dairy sheep.

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.

Testicular development in male lambs prenatally exposed to a high-starch diet.

Maternal nutrition during critical gestation periods impacts on offspring in later life; effects of high-starch maternal diet on testicular development in lambs were addressed. Dairy ewes were fed diets providing either 27% (Starch, S) or 11% (Fiber, F) of starch from mating to lambing (∼147 days; S147, F147) or for the last 75 days of gestation (S75, F75). Testes of single male lambs were measured and then sampled for histological and gene expression analyses at selected ages. Testicular dimensions and weight were similar among groups, but the total area of seminiferous tubules increased with age and tended to be higher (p = 0.057) in lambs from starch- than fiber-fed ewes. Sertoli and germ cells number increased with age, but was not influenced by maternal diet. Transcript abundances of androgen receptor (AR), insulin-like growth factor 1 (IGF1), and hydroxysteroid (17-beta) dehydrogenase 3 (HSD17B3) was similar between S147 and F147 lambs (p > 0.1). Abundance of luteinizing hormone/choriogonadotropin receptor (LHCGR) and steroidogenic acute regulatory protein (STAR) was higher in young vs older lambs, whereas insulin-like growth factor 2 (IGF2) levels increased with age. The expression of vascular endothelial growth factor A (VEGFA), Anti-Müllerian hormone (AMH), IGF1, follicle stimulating hormone receptor (FSHR), and insulin-like growth factor 2 receptor (IGF2R) was not influenced by maternal diet or lamb age (p > 0.1). In conclusion, a high-starch maternal diet did not influence gene expression, but may have affected testicular structure in infant offspring, as seen by an increase in the total area of seminiferous tubules.

A generalized compartmental model to estimate the fibre mass in the ruminoreticulum: 1. Estimating parameters of digestion.

Parameters related to the microbial digestion of nutrients in the ruminoreticulum have been estimated by fitting mathematical models to degradation profiles generated from kinetic studies. In the present paper, we propose a generalized compartmental model of digestion (GCMD) based on implicit theoretical concepts and the gamma probability density function to estimate fibre digestion parameters. The proposed model is consistent to a broader compartmental model presented in a companion paper that integrates aspects of fibre digestion and passage. Different versions of the GCMD were generated by increasing the integer order of time dependency of the gamma function. These versions were fitted to 192 published fibre degradation profiles that were obtained using an in vitro fermentation technique. The quality of fit was evaluated based on the frequency of minimum sum of squares of errors (SSE), the number of runs of signs of residuals, and its likelihood probability calculated according to the Akaike's Information Criterion. The likelihood of the proposed model was also compared to a discrete lag time model (DLT), which is commonly used to interpret fibre degradation profiles. The GCMD had superior quality of fit compared to the DLT and was considered more likely in describing 68.75% of the profiles evaluated. Only 9.38% of the degradation profiles that were fitted to the DLT model had a lower SSE. Even though the degradation profiles studied were generated by incubating feed samples up to 96h, the true asymptotic limit of fibre degradation can only be achieved by long-term fermentations. This fact leads to questioning the uniformity of the potentially digestible fibre fraction and a further approach based on GCMD-type model was used to account for its heterogeneous nature.

A generalized compartmental model to estimate the fibre mass in the ruminoreticulum: 2. Integrating digestion and passage.

Models used to predict digestibility and fill of the dietary insoluble fibre (NDF) treat the ruminoreticular particulate mass as a single pool. The underlying assumption is that escape of particles follows first-order kinetics. In this paper, we proposed and evaluated a model of two ruminoreticular sequential NDF pools. The first pool is formed by buoyant particles (raft pool) and the second one by fluid dispersed particles (escapable pool) ventrally to the raft. The transference of particles between these two pools results from several processes that reduce particles buoyancy, assuming the gamma distribution. The exit of escapable pool particles from the ruminoreticulum is exponentially distributed. These concepts were evaluated by comparing ruminoreticular NDF masses as 43 and 27 means from cattle and sheep, respectively, to the same predicted variable using single- and two-pools models. Predictions of the single-pool model were based on lignin turnover and the turnover associated to the descending phase of the elimination of Yb-labelled forage particles in the faeces of sheep. Predictions of the two-pool model were obtained by estimating fractional passage rates associated to the ascending and descending phases of the same Yb excretion profiles in sheep faeces. All turnovers were scaled to the power 0.25 of body mass for interspecies comparisons. Predictions based on lignin turnover (single pool) and the two-pool model presented similar trends, accuracies and precisions. The single-pool approach based solely on the descending phase of the marker yielded biased estimates of the ruminoreticular NDF mass.