173 resultados para Animal feeding


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Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific. © 2015 Macmillan Publishers Limited.

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The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.

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Objective To identify measures that most closely relate to hydration in healthy Brahman-cross neonatal calves that experience milk deprivation. Methods In a dry tropical environment, eight neonatal Brahman-cross calves were prevented from suckling for 2–3 days during which measurements were performed twice daily. Results Mean body water, as estimated by the mean urea space, was 74 ± 3% of body weight at full hydration. The mean decrease in hydration was 7.3 ± 1.1% per day. The rate of decrease was more than three-fold higher during the day than at night. At an ambient temperature of 39°C, the decrease in hydration averaged 1.1% hourly. Measures that were most useful in predicting the degree of hydration in both simple and multiple-regression prediction models were body weight, hindleg length, girth, ambient and oral temperatures, eyelid tenting, alertness score and plasma sodium. These parameters are different to those recommended for assessing calves with diarrhoea. Single-measure predictions had a standard error of at least 5%, which reduced to 3–4% if multiple measures were used. Conclusion We conclude that simple assessment of non-suckling Brahman-cross neonatal calves can estimate the severity of dehydration, but the estimates are imprecise. Dehydration in healthy neonatal calves that do not have access to milk can exceed 20% (>15% weight loss) in 1–3 days under tropical conditions and at this point some are unable to recover without clinical intervention.

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Exposure to hot environments affects milk yield (MY) and milk composition of pasture and feed-pad fed dairy cows in subtropical regions. This study was undertaken during summer to compare MY and physiology of cows exposed to six heat-load management treatments. Seventy-eight Holstein-Friesian cows were blocked by season of calving, parity, milk yield, BW, and milk protein (%) and milk fat (%) measured in 2 weeks prior to the start of the study. Within blocks, cows were randomly allocated to one of the following treatments: open-sided iron roofed day pen adjacent to dairy (CID) + sprinklers (SP); CID only; non-shaded pen adjacent to dairy + SP (NSD + SP); open-sided shade cloth roofed day pen adjacent to dairy (SCD); NSD + sprinkler (sprinkler on for 45 min at 1100 h if mean respiration rate >80 breaths per minute (NSD + WSP)); open-sided shade cloth roofed structure over feed bunk in paddock + 1 km walk to and from the dairy (SCP + WLK). Sprinklers for CID + SP and NSD + SP cycled 2 min on, 12 min off when ambient temperature >26°C. The highest milk yields were in the CID + SP and CID treatments (23.9 L cow−1 day−1), intermediate for NSD + SP, SCD and SCP + WLK (22.4 L cow−1 day−1), and lowest for NSD + WSP (21.3 L cow−1 day−1) (P < 0.05). The highest (P < 0.05) feed intakes occurred in the CID + SP and CID treatments while intake was lowest (P < 0.05) for NSD + WSP and SCP + WLK. Weather data were collected on site at 10-min intervals, and from these, THI was calculated. Nonlinear regression modelling of MY × THI and heat-load management treatment demonstrated that cows in CID + SP showed no decline in MY out to a THI break point value of 83.2, whereas the pooled MY of the other treatments declined when THI >80.7. A combination of iron roof shade plus water sprinkling throughout the day provided the most effective control of heat load.