19 research outputs found
Reducing the Environmental Impact of Animal Production
La demanda mundial de alimentos aumentará en los próximos 30 años para satisfacer las necesidades de la creciente población. Es probable que la demanda de productos de origen animal (carne, leche y huevos) aumente a un ritmo más rápido que la demanda de cereales. Hay presión para reducir los impactos ambientales de los sistemas pecuarios, en particular las emisiones de gases de efecto invernadero (GEI) y la excreción de nitrógeno y fósforo. El principal impulsor del impacto ambiental en los sistemas animales es la eficiencia de la producción, es decir, la producción de leche, carne, huevos o contaminantes por unidad de insumo. La eficiencia de producción está relacionada con el rendimiento por animal, la tasa de reproducción y la tasa de reemplazo. Una mayor eficiencia de producción significa que se necesitan menos animales por unidad de producto, de modo que las emisiones y excreciones "improductivas" asociadas con el mantenimiento y la fase de crianza se distribuyen en más unidades de producto. La nutrición puede reducir las emisiones y las excreciones por animal. Las emisiones de metano de los rumiantes están relacionadas con la cantidad de forraje digerido, por lo que aumentar las proporciones de la dieta de los concentrados y aumentar el contenido de almidón o grasa a expensas de la fibra, reducirá el metano por unidad de producto. La selección genética para bajas emisiones de metano solo debe considerarse junto con la eficiencia de la alimentación. Las excreciones de nitrógeno y fósforo están relacionadas con el contenido de nitrógeno y fósforo en la dieta, particularmente con exceso de suministros. La formulación precisa de la dieta, el uso de requisitos proteicos degradables e indestructibles del rumen en los rumiantes y los requisitos de aminoácidos digestibles en los no rumiantes, puede reducir la excreción de nitrógeno. La reducción del contenido de fósforo en las dietas y las enzimas fitasas en las dietas no rumiantes pueden reducir la excreción de fósforo. En conclusión, la principal estrategia para reducir la huella ambiental de los sistemas pecuarios debe ser reducir el desperdicio de animales reproductores mediante el sacrificio prematuro de fertilidad y enfermedades. Esto también mejorará la rentabilidad. Por lo tanto, se necesita un enfoque de todo el sistema que considere el costo ambiental de la formulación de la dieta, así como el costo económico.Global food demand will increase in the next 30 years to meet the needs of the increasing population. Demand for animal products (meat, milk and eggs) is likely to increase at a faster rate than the demand for cereals. There is pressure to reduce the environmental impacts of livestock systems, particularly greenhouse gas emissions (GHG) and excretion of nitrogen and phosphorus. The main driver of environmental impact in animal systems is production efficiency, i.e. output of milk, meat, eggs or pollutants per unit of input. Production efficiency is related to performance per animal, reproductive rate and replacement rate. Higher production efficiency means that fewer animals are needed per unit of the product so that ‘unproductive’ emissions and excretions associated with maintenance and the rearing phase are spread over more units of product. Nutrition can reduce emissions and excretions per animal. Methane emissions by ruminants are related to the quantity of forage digested, so increasing dietary proportions of concentrates, and increasing starch or fat content at the expense of fibre will reduce methane per unit of product. Genetic selection for low methane emissions should only be considered alongside feed efficiency. Nitrogen and phosphorus excretions are related to dietary nitrogen and phosphorus contents, particularly with excess supplies. Precise diet formulation, using rumen degradable and undegradable protein requirements in ruminants, and digestible amino acid requirements in non-ruminants, can reduce nitrogen excretion. Reducing phosphorus content of diets, and phytase enzymes in non-ruminant diets can reduce phosphorus excretion. In conclusion, the main strategy for reducing the environmental footprint of livestock systems must be to reduce wastage of breeding animals through premature culling for fertility and diseases. This will also improve profitability. Therefore, a whole-system approach is needed which considers the environmental cost of diet formulation as well as economic cost
Short communication: Heritability of methane production and genetic correlations with milk yield and body weight in Holstein-Friesian dairy cows
Greenhouse gases originating from the dairy sector, including methane (CH 4), contribute to global warming. A possible strategy to reduce CH 4 production is to use genetic selection. This requires genetic parameters for CH 4 production and correlations with production traits. Data were available on 184 Holstein-Friesian cows. Methane production was measured in the milking robot during milking from December 2009 to April 2010. In total 2,456 observations for CH 4 production were available. Milk yield (MY) and body weight (BW) were obtained at every milking from November 2008 to October 2010. In total 4,567 observations for milk yield and 4,570 observations for BW were available. Restricted maximum likelihood, using random regression models, was used to analyze the data. Heritability (standard error given in parentheses) for CH 4 production ranged from 0.12 (0.16) to 0.45 (0.11), and genetic correlations with MY ranged from 0.49 (0.12) to 0.54 (0.26). The positive genetic correlation between CH 4 production and milk yield indicates that care needs to be taken when genetically selecting for lower CH 4 production, to avoid a decrease in MY at the animal level. However, this study shows that CH 4 production is moderately heritable and therefore progress through genetic selection is possible
Modified approach to estimating daily methane emissions of dairy cows by measuring filtered eructations during milking
The aim of this study was to compare metrics for quantifying enteric methane (CH4) emissions from individual cows during milking using frequent spot measurements and peak analysis methods. An infrared gas analyser was used to measure the CH4 emitted by cows, and eructation peaks were identified using a Signal Processing Toolbox provided by Matlab. CH4 emissions were quantified by gas peak height, peak amplitude and average concentration, and were expressed in grams per day and CH4 yield (grams per kilogram of dry matter intake (DMI)). Peak analysis measurements of CH4 were obtained from 36 cows during 2,474 milkings, during which cows were fed a ration containing between 39 and 70 % forage. Spot measurements of CH4 were compared to a separate dataset of 196 chamber CH4 records from another group of 105 cows, which were fed a ration containing between 25 and 80 % forage. The results showed that the metrics of CH4 peak height and CH4 peak amplitude demonstrated similar positive relationships between daily CH4 emissions and DMI (both r = 0.37), and a negative relationship between CH4 yield and DMI (r = -0.43 and -0.38 respectively) as observed in the chamber measurements (r = 0.57 for daily emissions and r = -0.40 for CH4 yield). The CH4 metrics of peak height and peak amplitude were highly repeatable (ranging from 0.76 to 0.81), comparable to the high repeatability of production traits (ranging from 0.63 to 0.99) and were more repeatable than chamber CH4 measurements (0.31 for daily emissions and 0.03 for CH4 yield). This study recommends quantifying CH4 emissions from the maximum amplitude of an eructation
Effect of feeding system on enteric methane emissions from individual dairy cows on commercial farms
This study investigated the effects of feeding system on diurnal enteric methane (CH4) emissions from individual cows on commercial farms. Data were obtained from 830 cows across 12 farms, and data collated included production records, CH4 measurements (in the breath of cows using CH4 analysers at robotic milking stations for at least seven days) and diet composition. Cows received either a partial mixed ration (PMR) or a PMR with grazing. A linear mixed model was used to describe variation in CH4 emissions per individual cow and assess the effect of feeding system. Methane emissions followed a consistent diurnal pattern across both feeding systems, with emissions lowest between 05:00 and 08:59, and with a peak concentration between 17:00 and 20:59. No overall difference in emissions was found between feeding systems studied; however, differences were found in the diurnal pattern of CH4 emissions between feeding systems. The response in emissions to increasing dry matter intake was higher for cows fed PMR with grazing. This study showed that repeated spot measurements of CH4 emissions whilst cows are milked can be used to assess the effects of feeding system and potentially benchmark farms on level of emissions
Prediction of enteric methane production, yield and intensity in dairy cattle using an intercontinental database
Enteric methane (CH4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/d per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the US (US), Chile (CL), Australia (AU), and New Zealand (NZ). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6, 14.4, and 19.8% for intercontinental, EU, and US regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary NDF concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation
A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms
Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity
Where have we come with breeding for methane emissions : update from international collaborations
Where have we come with breeding for methane emissions – update from international collaborations Climate change is a growing international concern and it is well established that release of greenhouse gases (GHG) is a contributing factor. So far, within animal production, there is little or no concerted effort on long-term breeding strategies to mitigate GHG from ruminants. In recent years, several consortia have been formed to collect and combine data for genetic evaluation. Discussion areas of these consortia focus on (1) What are genetic parameters for methane (CH4) emissions, (2) What proxies can be used to assess CH4 emission, and (3) What are the prospects of breeding for lower emitting animals? The estimated genetic parameters show that enteric CH4 is a heritable trait, and that it is highly genetically correlated with DMI. So far, the most useful proxies relate to feed intake, milk mid-infrared spectral data, and fatty acid concentrations in milk. To be able to move forward with a genetic evaluation and ranking of animals for CH4 emission, international collaboration is essential to make progress in this area. Collaboration is not only in terms of sharing ideas, experiences and phenotypes, but also in terms of coming to a consensus regarding what phenotype to collect and to select for. Keywords: greenhouse gas emission, enteric methane, genetic contro
Short communication: Chemical composition, fatty acid composition, and sensory characteristics of Chanco cheese from dairy cows supplemented with soybean and hydrogenated vegetable oils
Where have we come with breeding for methane emissions : update from international collaborations
Where have we come with breeding for methane emissions – update from international collaborations Climate change is a growing international concern and it is well established that release of greenhouse gases (GHG) is a contributing factor. So far, within animal production, there is little or no concerted effort on long-term breeding strategies to mitigate GHG from ruminants. In recent years, several consortia have been formed to collect and combine data for genetic evaluation. Discussion areas of these consortia focus on (1) What are genetic parameters for methane (CH4) emissions, (2) What proxies can be used to assess CH4 emission, and (3) What are the prospects of breeding for lower emitting animals? The estimated genetic parameters show that enteric CH4 is a heritable trait, and that it is highly genetically correlated with DMI. So far, the most useful proxies relate to feed intake, milk mid-infrared spectral data, and fatty acid concentrations in milk. To be able to move forward with a genetic evaluation and ranking of animals for CH4 emission, international collaboration is essential to make progress in this area. Collaboration is not only in terms of sharing ideas, experiences and phenotypes, but also in terms of coming to a consensus regarding what phenotype to collect and to select for. Keywords: greenhouse gas emission, enteric methane, genetic contro