15 resultados para Dairy Production

em University of Queensland eSpace - Australia


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Objective To investigate the extent of heat load problems, caused by the combination of excessive temperature and humidity, in Holstein-Friesian cows in Australia. Also, to outline how milk production losses and consequent costs from this can be estimated and minimised. Procedures Long-term meteorological data for Australia were analysed to determine the distribution of hot conditions over space and time. Fifteen dairy production regions were identified for higher-resolution data analysis. Both the raw meteorological data and their integration into a temperature-humidity thermal index were compiled onto a computer program. This mapping software displays the distribution of climatic patterns, both Australia-wide and within the selected dairying regions. Graphical displays of the variation in historical records for 200 locations in the 15 dairying regions are also available. As a separate study, production data from research stations, on-farm trials and milk factory records were statistically analysed and correlated with the climatic indices, to estimate production losses due to hot conditions. Results Both milk yields and milk constituents declined with increases in the temperature-humidity index. The onset and rate of this decline are dependent on a number of factors, including location, level of production, adaptation, and management regime. These results have been integrated into a farm-level economic analysis for managers of dairy properties. Conclusion By considering the historical patterns of hot conditions over time and space, along with expected production losses, managers of dairy farms can now conduct an economic evaluation of investment strategies to alleviate heat loads. These strategies include the provision of sprinklers, shade structures, or combinations of these.

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The relationship between reported treatments of lameness, metabolic disorders (milk fever, ketosis), digestive disorders, and technical efficiency (TE) was investigated using neutral and non-neutral stochastic frontier analysis (SFA). TE is estimated relative to the stochastic frontier production function for a sample of 574 Danish dairy herds collected in 1997. Contrary to most published results, but in line with the expected negative impact of disorders on the average cow milk production, herds reporting higher frequencies of milk fever are less technically efficient. Unexpectedly, however, the opposite results were observed for lameness, ketosis, and digestive disorders. The non-neutral stochastic frontier indicated that the opposite results are due to the relative. high productivities of inputs. The productivity of the cows is also reflected by the direction of impact of herd management variables. Whereas efficient farms replace cows more frequently, enroll heifers in production at an earlier age, and have shorter calving intervals, they also report higher frequency of disorder treatments. The average estimated energy corrected milk loss per cow is 1036, 451 and 242 kg for low, medium and high efficient farms. The study demonstrates the benefit of the stochastic frontier production function involving the estimation of individual technical efficiencies to evaluate farm performance and investigate the source of inefficiency. (C) 2004 Elsevier B.V. All rights reserved.

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The challenge of Research, Development and Extension (R,D&E) is to apply agricultural science to serve the real needs of production systems. The ideal is to have community partnerships involving a variety of stakeholders with equal representation, and a sharing in the design of R, D&E actions. R,D&E policy in Australia is stressing the participation of industry in new projects. The Dairy Research and Development Corporation (DRDC) in Australia, and the Brazilian Agricultural Research Corporation for Dairy (Embrapa Dairy), have developed initiatives to identify priorities for R,D&E design with participation of the industry. However, weaknesses in the methods have been identified. The present study describes the results of a strategy to involve a broader range of stakeholders in the identification of regional dairy industry needs. The findings show that overall communication, finance and marketing as the three major priorities of three study regions, meaning that primary needs for the industry are not in production technologies. This is an apparent contradiction with what some stakeholders considered valuable for dairy farms, which are pasture, genetics and nutrition technologies. The results reflect the large amount of research activity into production technology, and the relative success of R,D&E. However, it is necessary to consider issues beyond production technologies before developing R,D&E projects or presenting technologies.

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The bulk of the world's goat population is found in South-East Asia and Africa, where goats are the major source of meat production. Unfortunately, lack of an organized goat meat industry and marketing structure in developing countries is primarily responsible for their poor export earnings compared to those in developed countries such as Australia and New Zealand. Goat meat is leaner than meat from other domestic red meat species as well as being comparable in terms of its nutritional constituents. Furthermore, there are few, if any, religious or cultural taboos limiting the consumption of goat meat. Development of a carcass grading system and a suitable infrastructure in developing countries are some of the key requirements needed to establish a sustainable goat meat industry in the world. With an increase in demand by consumers for low-fat red meat alternatives, the future of the goat meat industry looks promising.

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Relationships of various reproductive disorders and milk production performance of Danish dairy farms were investigated. A stochastic frontier production function was estimated using data collected in 1998 from 514 Danish dairy farms. Measures of farm-level milk production efficiency relative to this production frontier were obtained, and relationships between milk production efficiency and the incidence risk of reproductive disorders were examined. There were moderate positive relationships between milk production efficiency and retained placenta, induction of estrus, uterine infections, ovarian cysts, and induction of birth. Inclusion of reproductive management variables showed that these moderate relationships disappeared, but directions of coefficients for almost all those variables remained the same. Dystocia showed a weak negative correlation with milk production efficiency. Farms that were mainly managed by young farmers had the highest average efficiency scores. The estimated milk losses due to inefficiency averaged 1142, 488, and 256 kg of energy-corrected milk per cow, respectively, for low-, medium-, and high-efficiency herds. It is concluded that the availability of younger cows, which enabled farmers to replace cows with reproductive disorders, contributed to high cow productivity in efficient farms. Thus, a high replacement rate more than compensates for the possible negative effect of reproductive disorders. The use of frontier production and efficiency/ inefficiency functions to analyze herd data may enable dairy advisors to identify inefficient herds and to simulate the effect of alternative management procedures on the individual herd's efficiency.

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In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors ( defined as members of the dairy and associated communities), especially farm suppliers ( input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, purposive sampling, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

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The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

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Corn and soyabeans may not be available in many countries particularly those which do not have sufficient foreign currency or the capacity to grow them. This paper outlines strategies that may be important under these circumstances. Alternative feedstuffs and various feeding systems may be used to support poultry production. Alternative ingredients such as rice bran, pearl millet, cottonseed meal and grain legumes are discussed. Evidence is presented showing that amino acid requirements of layers and broilers may be too generous particularly in countries where climate, management and disease can impose production constraints. The ability of finishing broilers to perform well on very low-energy diets allows the inclusion of alternative feeds and by-products into formulations. Very low protein diets based on cereals and free amino acids can be used for layers without loss of performance. Self-selection of feedstuffs may be an important strategy in reducing feed costs of broilers and layers. The concept of matching production with available feed resources may compromise broiler growth and egg production, but in many countries this may be the most economical choice. Countries in the humid tropics usually have reduced poultry performance. The effects of high temperature and humidity are difficult to overcome. The vexed questions of the escalation in the price of fossil fuel and the outbreak of avian influenza, both seemingly without a solution, are clouds hanging over an otherwise buoyant industry.

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Signal grass pastures were oversown with four Leucaena spp. planted in hedgerows and evaluated for their agronomic productivity and ability to support steer liveweight gains. Each Leucaena sp. (L. leucocephala, L. pallida, L colli. nst. i., L. trichandra) was planted as seedlings into two I ha paddocks in rows 5 m apart, with I m spacing between trees. Cattle were rotationally grazed on the 2 replicates of each species, as well as on two I ha paddocks of a signal grass on y (Brachiaria decumbens) control, over a 243-day period at a stocking rate of 3 steers/ha. Mean presentation yield and herbage allowance of the Leucaena accessions over the grazing period were highest for L pallida (1100 kg/ha and 0.8 kg DM/kg LW, respectively), followed by L. leucocephala (700 kg/ha and 0.5 kg DM/kg LW), L. collinsii (700 kg/ha and 0.4 kg DM/kg LW) and L. trichandra (300 kg/ha and 0.2 kg DM/kg LW). Despite only moderate presentation yields and herbage allowances, steers grazing L. leucocephala and L. collinsii accessions produced the highest mean liveweight gains (LWG) of 0. and 0.56 kg/hd/d, respectively. While L. pallida produced the highest DM yields, it supported the lowest LWG of 0.36 kg/hd/d. The mean LWGs of steers grazing L. trichandra and the control (grass only) treatments were similar at 0.48 kg/ hd/d. The possible reasons for the differences in steer performance on the different Leucaena accessions are discussed.

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Milk protein production can be influenced by several factors, including environment, disease status, parity, stage of lactation, breed, genetic merit and the nutritional status of the animal (DePeters and Cant 1992). A combination of, or an interaction between, these factors can significantly affect milk protein production. Our study aims to identify the main factors affecting milk protein concentration in dairy cattle in the south-east Queensland region.