96 resultados para Compounded Cattle Feed (CCF)


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Various food and feed samples including groundnut seed, maize, sorghum, soyabean cake, groundnut cake, cotton cake, poultry feed, buffalo milk, cow milk and milk powders were collected from farmers' fields, farmer's stores, oil millers storage, traders' storage, retail shops and supermarkets. More than 2000 samples were analysed by ELISA and most of the commodities, with the exception of sorghum seed, contained high levels of aflatoxin. Groundnut cake was one of the major cattle feed ingredients in the peri-urban area of Hyderabad (Andhra Pradesh, India) and >75% of the samples contained >100 µg/kg aflatoxin, leading to a high level of aflatoxin M1, in milk samples. Strategies to reduce aflatoxin levels (especially in groundnut) by management interventions at preharvest, harvest and storage, are discussed.

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The present study investigated whether consuming dairy products naturally enriched in cis-9, trans-11 (c9,t11) conjugated linoleic acid (CLA) by modification of cattle feed increases the concentration of this isomer in plasma and cellular lipids in healthy men. The study had a double-blind cross-over design. Subjects aged 34-60 years consumed dairy products available from food retailers for 1 week and then either control (0.17 g c9,t11 CLA/d; 0.31 g trans-vaccenic acid (tVA)/d) or CLA-enriched (1.43 g c9,t11 CLA/d; 4.71 g tVA/d) dairy products for 6 weeks. After 7 weeks washout, this was repeated with the alternate products. c9,t11 CLA concentration in plasma lipids was lower after consuming the control products, which may reflect the two-fold greater c9,t11 CLA content of the commercial products. Consuming the CLA-enriched dairy products increased the c9,t11 CLA concentration in plasma phosphatidylcholine (PC) (38 %; P=0.035), triacylglycerol (TAG) (22 %; P < 0.0001) and cholesteryl esters (205 %; P < 0.0001), and in peripheral blood mononuclear cells (PBMC) (238 %; P < 0.0001), while tVA concentration was greater in plasma PC (65 %; P=0.035), TAG (98 %; P=0.001) and PBMC (84 %; P=0.004). Overall, the present study shows that consumption of naturally enriched dairy products in amounts similar to habitual intakes of these foods increased the c9,t11 CLA content of plasma and cellular lipids.

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The present study investigated whether consuming dairy products naturally enriched in cis-9, trans-11 (c9,t11) conjugated linoleic acid (CLA) by modification of cattle feed increases the concentration of this isomer in plasma and cellular lipids in healthy men. The study had a double-blind cross-over design. Subjects aged 34-60 years consumed dairy products available from food retailers for 1 week and then either control (0.17 g c9,t11 CLA/d; 0.31 g trans-vaccenic acid (tVA)/d) or CLA-enriched (1.43 g c9,t11 CLA/d; 4.71 g tVA/d) dairy products for 6 weeks. After 7 weeks washout, this was repeated with the alternate products. c9,t11 CLA concentration in plasma lipids was lower after consuming the control products, which may reflect the two-fold greater c9,t11 CLA content of the commercial products. Consuming the CLA-enriched dairy products increased the c9,t11 CLA concentration in plasma phosphatidylcholine (PC) (38 %; P=0.035), triacylglycerol (TAG) (22 %; P < 0.0001) and cholesteryl esters (205 %; P < 0.0001), and in peripheral blood mononuclear cells (PBMC) (238 %; P < 0.0001), while tVA concentration was greater in plasma PC (65 %; P=0.035), TAG (98 %; P=0.001) and PBMC (84 %; P=0.004). Overall, the present study shows that consumption of naturally enriched dairy products in amounts similar to habitual intakes of these foods increased the c9,t11 CLA content of plasma and cellular lipids.

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The Green Feed (GF) system (C-Lock Inc., Rapid City, USA) is used to estimate total daily methane emissions of individual cattle using short-term measurements obtained over several days. Our objective was to compare measurements of methane emission by growing cattle obtained using the GF system with measurements using respiration chambers (RC)or sulphur hexafluoride tracer (SF6). It was hypothesised that estimates of methane emission for individual animals and treatments would be similar for GF compared to RC or SF6 techniques. In experiment 1, maize or grass silage-based diets were fed to four growing Holstein heifers, whilst for experiment 2, four different heifers were fed four haylage treatments. Both experiments were a 4 × 4 Latin square design with 33 day periods. Green Feed measurements of methane emission were obtained over 7 days (days 22–28) and com-pared to subsequent RC measurements over 4 days (days 29–33). For experiment 3, 12growing heifers rotationally grazed three swards for 26 days, with simultaneous GF and SF6 measurements over two 4 day measurement periods (days 15–19 and days 22–26).Overall methane emissions (g/day and g/kg dry matter intake [DMI]) measured using GF in experiments 1 (198 and 26.6, respectively) and 2 (208 and 27.8, respectively) were similar to averages obtained using RC (218 and 28.3, respectively for experiment 1; and 209 and 27.7, respectively, for experiment 2); but there was poor concordance between the two methods (0.1043 for experiments 1 and 2 combined). Overall, methane emissions measured using SF6 were higher (P<0.001) than GF during grazing (186 vs. 164 g/day), but there was significant (P<0.01) concordance between the two methods (0.6017). There were fewer methane measurements by GF under grazing conditions in experiment 3 (1.60/day) com-pared to indoor measurements in experiments 1 (2.11/day) and 2 (2.34/day). Significant treatment effects on methane emission measured using RC and SF6 were not evident for GF measurements, and the ranking for treatments and individual animals differed using the GF system. We conclude that under our conditions of use the GF system was unable to detectsignificant treatment and individual animal differences in methane emissions that were identified using both RC and SF6techniques, in part due to limited numbers and timing ofmeasurements obtained. Our data suggest that successful use of the GF system is reliant on the number and timing of measurements obtained relative to diurnal patterns of methane emission.

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The objective of the study was to determine if there were adverse effects on animal health and performance when a range of ruminant animals species were fed at least 10 times the maximum permitted European Union (EU) selenium (Se) dietary inclusion rate (0.568 mg Se/kg DM) in the form of selenium enriched yeast (SY) derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060. In a series of studies, dairy cows, beef cattle, calves and lambs were offered either a control diet which contained no Se supplement or a treatment diet which contained the same basal feed ingredients plus a SY supplement which increased total dietary Se from 0.15 to 6.25, 0.20 to 6.74, 0.15 to 5.86 and 0.14 to 6.63 mg Se/kg DM, respectively. The inclusion of the SY supplement (P < 0.001) increased whole blood Se concentrations, reaching maximum mean values of 716, 1,505, 1,377, and 724 ng Se/mL for dairy cattle, beef cattle, calves and lambs, respectively. Selenomethionine accounted for 10% of total whole blood Se in control animals whereas the proportion in SY animals ranged between 40 and 75%. Glutathione peroxidase (EC 1.11.1.9) activity was higher (P < 0.05) in SY animals when compared with controls. A range of other biochemical and hematological parameters were assessed, but few differences of biological significance were established between treatments groups. There were no differences between treatment groups within each species with regard to animal physical performance or overall animal health. It was concluded that there were no adverse effects on animal health, performance and voluntary feed intake to the administration of at least ten times the EU maximum, or approximately twenty times the US FDA permitted concentration of dietary Se in the form of SY derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060.

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Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

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Maize silage-based diets with three dietary crude protein (CP) supplements were offered to 96 finishing cattle of contrasting breed (Holstein Friesian (HF) v. Simmental x HF (SHF)) and gender (bull v. steer) housed in two types of feeding system (group fed v. individually fed). The three protein supplements differed either in CP or protein degradability (degradable (LUDP) v. rumen undegradable (HUDP)) and provided CP concentrations of 142 (Con), 175 (LUDP) and 179 (HUDP) g/kg dry matter (DM) respectively, with ratios of degradable to undegradable of 3.0, 1.4 and 0.9:1 for diets Con, LOP and HUDP respectively. DM intakes were marginally higher (P = 0. 102) for LOP when compared with Con and HOP Rates of daily live-weight gain (DLWG) were higher (P = 0.005) in LUDP and HOP when compared with Con. HF had higher DM intakes than SHF although this did not result in any improvement in HF DLWG. Bulls had significantly better DM intakes, DLWG and feed conversion efficiency than steers. Conformation scores were better in SHF than HF (P < 0.001) and fat scores lower in bulls than steers (p < 0.001). There was a number of first order interactions established between dietary treatment, breed, gender and housing system with respect to rates of gain and carcass fat scores.

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In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 2481 on N partition, and a new model of P partition. The second objective was to construct a decision support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original simulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 6791 to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which production and environmental objectives are antagonistic, and it may help to explain and understand the complex mechanisms involved at the ruminal and metabolic levels. A part of the integrated model outputs were the forms of N and P in excreta and methane, which can be used as indices of environmental pollution. (C) 2004 Elsevier B.V All rights reserved.

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A study was carried out on 92 smallholder farms in Kwale district in Coast Province of Kenya to estimate the milk yield. The effect of concentrate feed supplementation on milk yield was also evaluated. Data were collected during a one-year observational longitudinal study. Analysis was done for 371 observations following 63 calving events. The mean annual milk offtake was estimated at 2021 kg/cow. Forty-nine (77.8%) of the lactating cows were supplemented with concentrate feeds at varying rates of 0.5-3.0 kg/cow per day. Supplementary feeding of lactating cows led to a significantly higher mean daily milk yield compared to non-supplemented cows throughout the year (p<0.05). The mean annual milk offtake from supplemented cows (2195 kg/cow) was 18.6% more than offtake from non-supplemented cows, a difference that was statistically significant (p<0.05). Therefore, supplementary feeding of commercial feed concentrates was a rational management practice. It was also concluded that milk production from smallholder dairy cows in the coastal lowlands of Kenya was comparable to that from similar production systems but lower than national targets.

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Effects of transition from late gestation to early lactation on plasma concentrations of glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide 1-(7-36) amide (GLP-1), and cholecystokinin (CCK) have not been reported in cattle. The objective of the present study was to measure plasma concentrations of GLP-1, GIP, CCK, insulin, glucose, and nonesterified fatty acids in blood plasma obtained from the coccygeal vein of 32 Holstein cows at an average of 11 d before, and 5, 12, and 19 d after calving. Feed dry matter intake (DMI) averaged 14.4, 17.7, and 19.9 kg/d on d 5, 12, and 19 of lactation, respectively, as milk yield increased (30.6, 36.6, and 39.7 kg/d, respectively). Plasma concentrations of insulin and glucose were lower postpartum than prepartum, but did not differ among samples collected after calving. In contrast, plasma concentration of gut peptides increased linearly after calving, perhaps as a consequence of increased feed intake and nutrient absorption; however, the increases in plasma concentrations of GIP and GLP-1 as lactation progressed were not associated with increased DMI per se, and likely reflect the endocrine and metabolic adaptations of lactogenesis. In contrast, increased concentration of CCK was related both to increasing days in milk and DMI. By 19 d postpartum, concentrations of GLP-1, GIP, and CCK increased by 2.3-, 1.8-, and 2.8-fold, respectively, compared with values at 11 d before calving. Although these peptides have direct and indirect effects that reduce appetite and DMI in other species (including increased insulin secretion), these may be glucose- or insulin-dependent functions, and insulin and glucose concentrations were reduced in early lactation.

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The effects of specific nutrients on secretion and plasma concentrations of gut peptides (glucagon-like peptide-1((7-36)) amide (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), and cholecystokinin-8 (CCK)) differ across species, but are not reported for cattle. Our objective was to determine acute (hours) and chronic (1 week) effects of increased abomasal supply of protein, carbohydrate, or fat to the small intestine on dry matter intake (DMI) and plasma concentrations of GLP-1, GIP, CCK, and insulin. Four mid-lactation Holstein cows were used in a 4 x 4 Latin square design experiment. Treatments were 7-day abomasal infusions of water, soybean oil (500 g/d), corn starch (1100 g/d), or casein (800 g/d). Jugular vein plasma was obtained over 7 h at the end of the first and last day of infusions. Oil infusion decreased DMI on day 7, but total metabolizable energy (ME) supply (diet plus infusate) did not differ from water infusion. Casein and starch infusion had no effect on feed DMI; thus, ME supply increased. Decreased DMI on day 7 of oil infusion was accompanied by increased plasma GLP-1 concentration, but decreased plasma CCK concentration. Increased plasma GIP concentration was associated with increased ME supply on day 7 of casein and starch infusion. Casein infusion tended to increase plasma CCK concentration on both days of sampling, and increased plasma GLP-1 and insulin concentration on day 1 of infusion. The present data indicate a sustained elevation of plasma concentration of GLP-1, but not CCK, may contribute to the reduced DMI observed in dairy cows provided supplemental fat. (C) 2008 Elsevier Inc. All rights reserved.

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Milk solids yield in modern dairy cows has increased linearly over the last 50 years, stressing the need for maximal dietary energy intake to allow genetic potential for milk energy yield to be realized with minimal negative effects on health and reproduction. Feeding supplemental starch is a common approach for increasing the energy density of the ration and supplying carbon for meeting the substantial glucose requirement of the higher yielding cow. In this regard, it is a long held belief that feeding starch in forms that increase digestion in the small intestine and glucose absorption will benefit the cow in terms of energetic efficiency and production response, but data supporting this dogma are equivocal. This review will consider the impact of supplemental starch and site of starch digestion on metabolic and production responses of lactating dairy cows, including effects on feed intake, milk yield and composition, nutrient partitioning, the capacity of the small intestine for starch digestion, and nutrient absorption and metabolism by the splanchnic tissues (the portal-drained viscera and liver). Whilst there appears to be considerable capacity for starch digestion and glucose absorption in the lactating dairy cow, numerous strategic studies implementing postruminal starch or glucose infusions have observed increases in milk yield, but decreased milk fat concentration such that there is little effect on milk energy yield, even in early lactation. Measurements of energy balance confirm that the majority of the supplemental energy arising from postruminal starch digestion is used with high efficiency to support body adipose and protein retention, even in early lactation. These responses may be mediated by changes in insulin status, and be beneficial to the cow in terms of reproductive success and well-being. However, shifting starch digestion from the rumen impacts the nitrogen economy of the cow as well by shifting the microbial protein gained from starch digestion from potentially absorbable protein to endogenous faecal loss.

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The efficiency of energy utilisation in cattle is a determinant of the profitability of milk and beef production, as well as their environmental impact. At an animal level, meat and milk production by ruminants is less efficient than pig and poultry production, in part due to lower digestibility of forages compared with grains. However, when compared on the basis of human-edible inputs, the ruminant has a clear efficiency advantage. There has been recent interest in feed conversion efficiency (FCE) in dairy cattle and residual feed intake, an indicator of FCE, in beef cattle. Variation between animals in FCE may have genetic components, allowing selection for animals with greater efficiency and reduced environmental impact. A major source of variation in FCE is feed digestibility, and thus approaches that improve digestibility should improve FCE if rumen function is not disrupted. Methane represents a substantial loss of digestible energy from rations. Major determinants of methane emission are the amount of feed consumed and the proportions of forage and concentrates fed. In addition, feeding fat has long been known to reduce methane emission. A myriad of other supplements and additives are currently being investigated as mitigators of methane emission, but in many cases compounds effective in sheep are ineffective in lactating dairy cows. Ultimately, the adoption of ‘best practice’ in diet formulation and management may be the most effective option for reducing methane. In assessing the efficiency of energy use for milk and meat production by cattle, and their environmental impact, it is imperative that comparisons be made at a systems level, and that the wider social and economic implications of mitigation policy are considered.

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Various studies have indicated a relationship between enteric methane (CH4) production and milk fatty acid (FA) profiles of dairy cattle. However, the number of studies investigating such a relationship is limited and the direct relationships reported are mainly obtained by variation in CH4 production and milk FA concentration induced by dietary lipid supplements. The aim of this study was to perform a meta-analysis to quantify relationships between CH4 yield (per unit of feed and unit of milk) and milk FA profile in dairy cattle and to develop equations to predict CH4 yield based on milk FA profile of cows fed a wide variety of diets. Data from 8 experiments encompassing 30 different dietary treatments and 146 observations were included. Yield of CH4 measured in these experiments was 21.5 ± 2.46 g/kg of dry matter intake (DMI) and 13.9 ± 2.30 g/ kg of fat- and protein-corrected milk (FPCM). Correlation coefficients were chosen as effect size of the relationship between CH4 yield and individual milk FA concentration (g/100 g of FA). Average true correlation coefficients were estimated by a random-effects model. Milk FA concentrations of C6:0, C8:0, C10:0, C16:0, and C16:0-iso were significantly or tended to be positively related to CH4 yield per unit of feed. Concentrations of trans-6+7+8+9 C18:1, trans-10+11 C18:1, cis- 11 C18:1, cis-12 C18:1, cis-13 C18:1, trans-16+cis-14 C18:1, and cis-9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of feed. Milk FA concentrations of C10:0, C12:0, C14:0-iso, C14:0, cis-9 C14:1, C15:0, and C16:0 were significantly or tended to be positively related to CH4 yield per unit of milk. Concentrations of C4:0, C18:0, trans-10+11 C18:1, cis-9 C18:1, cis-11 C18:1, and cis- 9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of milk. Mixed model multiple regression and a stepwise selection procedure of milk FA based on the Bayesian information criterion to predict CH4 yield with milk FA as input (g/100 g of FA) resulted in the following prediction equations: CH4 (g/kg of DMI) = 23.39 + 9.74 × C16:0- iso – 1.06 × trans-10+11 C18:1 – 1.75 × cis-9,12 C18:2 (R2 = 0.54), and CH4 (g/kg of FPCM) = 21.13 – 1.38 × C4:0 + 8.53 × C16:0-iso – 0.22 × cis-9 C18:1 – 0.59 × trans-10+11 C18:1 (R2 = 0.47). This indicated that milk FA profile has a moderate potential for predicting CH4 yield per unit of feed and a slightly lower potential for predicting CH4 yield per unit of milk. Key words: methane , milk fatty acid profile , metaanalysis , dairy cattle

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