121 exploitations des bassins laitiers de la Mitidja et d’Annaba ont fait l’objet d’une enquête pour recueillir les informations relatives à leur structure, à l’utilisation des terres, à la main d’œuvre et à la gestion économique de l’exploitation. Une typologie des exploitations a permis d’identifier huit types d’élevages qui diffèrent par les effectifs humains et bovins, et les pratiques agricoles.La durabilité de ces exploitations a été évaluée à l’aide de 37 indicateurs décrivant les échelles agro-environnementale, socio-territoriale et économique. Cinq groupes d’exploitations ont été identifiés selon leurs scores de durabilité. Les exploitations de la région d’Annaba ont des scores de durabilité totale et agro-environnementale supérieurs à celles de la Mitidja.Cette étude montre l’influence du système de production sur les paramètres concourant à l’estimation de la durabilité des exploitations, en particulier la gestion des ressources fourragères et la diversification des cultures. Les objectifs économiques prennent le pas sur la composante sociale.L’étude de la dynamique des exploitations a permis d’analyser les évolutions passées à travers une comparaison avec l’état actuel de ces élevages ainsi que les évolutions prévisibles à partir de recommandations proposées à l’éleveur. Cette démarche a permis de soulever les atouts et les faiblesses de ces systèmes d’élevage, d’élaborer une méthode utilisable par les décideurs ainsi que par les acteurs du secteur agricole à différents niveaux de décision, leur permettant d’élaborer des stratégies dans une perspective de développement durable / 121 dairy farms of the Mitidja and Annaba basins were the subject of an investigation to collect information on their structure, the land use, and the economic management. A typology of the exploitations made it possible to identify eight types of farming systems differing by manpower, herd size, cultures and practices. The sustainability of these farms was evaluated using 37 indicators describing the agro-environmental, socio-territorial and economic scales. Five groups of systems were identified according to their sustainability scores. The farms of the area of Annaba have higher scores for total and agro-environmental sustainability than those of Mitidja. This study shows the influence of the production system on the parameters contributing to estimate the dairy farms sustainability, particularly with regard to the stock fodder management and the diversification of the cultures. The economic objectives are more important than the social component (formation, social link, isolation). The dynamics of the exploitations were studied by the way of the passed evolutions compared to their actual position as well as to their foreseeable evolutions from recommendations suggested to the stockbreeder. This study showed the assets and the weaknesses of these systems and provides a method usable by the decision makers as well as by the actors of the agricultural sector at various levels of decision, allowing them to elaborate strategies in a perspective of sustainable development

The efficiency of utilization of dietary nitrogen can be monitored using milk urea nitrogen (MUN). Overfeeding or underfeeding of protein can be identified through the observation of deviations from target MUN concentrations. This will assist in lowering feed costs of dairy farms, and improving nutrition management of herds. Higher efficiency of utilization of dietary nitrogen might result in a reduction in environmental pollution. Non-genetic factors affecting variation in MUN were herd-test-day (HTD), lactation stage and year of calving. The contribution of HTD was the highest, ranging from 58.56% to 63.18% in parity 1 to 3. Lactation stage had the second largest contribution to the MUN variation. Differences in least squares means for MUN in various years of calving were observed. The heritability estimate for MUN was 0.09±0.01 in the first parity, and remained constant at 0.11±0.01 in the second and third parity. Heritability estimates for milk, fat and protein yield ranged from 0.40±0.01 to 0.43±0.01, 0.21±0.01 to 0.26±0.01, and 0.32±0.01 to 0.38±0.01, respectively. These estimates were within acceptable ranges for South African Holstein cattle. Genetic correlations between MUN and milk production traits were low and positive, ranging from 0.01±0.003 to 0.10±0.004 across parities. Phenotypic correlations ranged from 0.02±0.11 to 0.16±0.07, being generally higher than the genetic correlations. The positive associations between MUN and milk production traits are undesirable as the dairy cows would be less efficient in utilizing dietary protein and may result in increased environmental pollution. The genetic trend for MUN was 0.44, 0.007 and 0.049 mg/dl in the first, second and third parity, respectively. Results of the current study indicate that MUN has potential as a management tool in South African Holstein dairy herds. It might be a good indicator of the efficiency of dietary protein utilization of dairy herds, and has practical advantage as it is currently collected by the national dairy herd recording and improvement scheme. / Dissertation (MSc Agric)--University of Pretoria, 2013. / gm2014 / Animal and Wildlife Sciences / unrestricted

Dairy farmers in Virginia are confronted with the problem of continually re-organizing and adjusting their farming operations in an effort to maintain or improve their competitive position. Increasing competition in dairying within the state, as well as potential competition developing in areas outside of the state, makes it essential that dairymen operate efficiently. In particular, they must give careful consideration to various ways of reducing their production costs. Feed costs make up 50 to 60 percent of the total cost of producing milk. Consequently, the feeding program on any dairy farm greatly affects the cost of producing milk and, ultimately, the net return to the farmer. This study had four objectives: (1) to determine the available resources and their restrictions on the farms included in this study; (2) to determine an optimum forage and grain production system and forage to grain feeding ratio for three levels of milk production per cow with milk sales at the blend price not to exceed the present total base sales; (3) to determine which of the three levels of milk production is the most profitable at the present blend price of $5.73 per 100 pounds; (4) to study the effect of changes in the price of milk on the relative profitability of the three levels of production per cow and the forage-to-grain feeding ratios when the amount of profitable milk production is less than the present base. / Master of Science

M.S.

Ao longo dos últimos anos tem se observado no mundo uma expansão do setor leiteiro. Parte dessa expansão se deve a novas tecnologias que foram adotadas nas últimas décadas, mas também ocorreu por causa da queda, ou da anulação de barreiras comerciais. Contudo, notou-se também uma queda no número de fazendas leiteiras. Sendo o leite uma commodity os preços seguem as oscilações de mercado - oferta e demanda - e nenhum dos agentes possui poder para influenciar nos preços de compra e venda dessa mercadoria. Como os boletins do CEPEA mostram, os preços no ano passado têm-se mantido abaixo da média histórica, referente à última década, mas os termos de troca com relação a quantidade de litros de leite para se comprar insumos e defensivos se mantêm em patamares estáveis com tendência de alta. Tendo em vista esse problema, surge a necessidade de buscar compreender melhor como funciona o sistema de produção do setor leiteiro. Este trabalho satisfatoriamente conseguiu detectar através das fronteiras estocásticas de produção simples - leite como único produto de saída - e multi-output - leite e outros produtos animais existentes nas fazendas - além da regressão quantílica para análise de quantis variados da produção de leite, quais os insumos utilizados pelos produtores que oferecem melhores retornos para sua produção bem como analisar fatores de eficiência (BATTESE, COELLI; 1995; CHIDMI; SOLÍS; CABRERA, 2011). Os resultados apresentados apontam para a necessidade de se levar em consideração a inter-relação entre os insumos considerados - função de produção translog - e identificaram os insumos referentes ao capital - quantidade de vacas ordenhadas e gastos com máquinas e equipamentos - e ao trabalho - gastos com salários - como principais insumos da atividade pecuária. Os gastos com medicamentos animais, com energia elétrica e a área disponível para a atividade pecuária se mostraram contraproducentes indicando mau uso ou uso excessivo desses fatores, além de ressaltar a importância do capital na pecuária. Em geral, para quase todos os modelos testados, a produção leiteira apresentou retornos constantes à escala e nível de eficiência em torno de 88% em média para as fronteiras estocásticas e 90% para as estimativas feitas com regressão quantílica. Entre os fatores de eficiência identificados estão a capacidade de armazenamento de silos e tanques de refrigeração para o leite e a margem bruta líquida obtida com a atividade. Os fatores de ineficiência identificados são a prática de queimadas e o percentual de mulheres na administração das unidades produtivas. Com relação aos variados modelos estimados percebeu-se, em suma, a necessidade de se intensificar a produção pecuária e de melhorar a infraestrutura das fazendas. / Over the past few years it has been observed in the world an expansion of the dairy industry. Part of this expansion is due to new technologies that have been adopted in recent decades, but also because of the fall, or the annulment of trade barriers. However, it has also been noted a drop in the number of dairy farms. Being a commodity, milk prices follow the market oscillations - supply and demand - and none of the agents has enough power to influence buying and selling prices of this commodity. As the CEPEA bulletins show, prices last year have remained below the historical average for the last decade, but the terms of trade regarding the amount of liters of milk to buy inputs and pesticides at levels remain stable with uptrend. In view of this problem, there is the need to get a better understanding of how the dairy sector production system works. This work satisfactorily managed to detect, through the single-output stochastic production frontier method - value of milk production as output - and multi-output - value of milk and other existing animal products at the farms - besides quantile regression analysis for multiple production quantiles, which inputs used by farmers offer the best outcome for their production as well as analyzing efficiency factors (BATTESE; COELLI, 1995; CHIDMI; SOLÍS; CABRERA, 2011). The estimated results pointed to the need of considering the interrelation of considered inputs - translog production function - and identified the capital related inputs - quantity of milked cows and expenditure on machinery and equipment - and work related inputs - expenditure on wages - as main production inputs. Expenditure on animal drugs and on electricity and the area available for livestock activity proved counterproductive indicating misuse or overuse of these factors, in addition to emphasizing the importance of capital in livestock. In general, for most of the tested models, dairy production showed constant returns to scale and an average efficiency level of 88% for stochastic frontier models and 90% for estimates done using quantile regression. Among the identified efficiency factors are the storage capacity of silos and cooling tanks for milk and the net gross margin with activity. The identified inefficiency factors are the practice of burning and the percentage of women in the management of production units. With regard to various models estimated it was realized, in short, the need to intensify livestock production and to improve the infrastructure of the farms.

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