Time budgets, avoidance distance scores-related behaviour and milk yield of pasture-based Jersey, Friesland and crossbred cows. by Madodana Sunson Dodzi The study was conducted at the University of Fort Hare farm to determine the time budgets, the avoidance-related behaviour variables and their relationship with milk yield in three pasturebased dairy genotypes: Jersey, Friesland and crossbreed. Twenty one clinically health dairy cows aged between 52 and 55 months, in mid lactation and comprising of seven cows from each genotype were used in the study. The time spent on different activities (grazing, lying down, standing and others) at pasture was recorded using stop watches across four seasons. The behavioural responses of the three genotypes to humans were determined by recording their avoidance distance scores (AD), exit speed (ES), pen scores (PS), pen behaviour scores (PBS), plat form scores (PLS) and the occurrence of kicking (KCK) and stepping (SPG) during milking on four consecutive days in four seasons. Time spent standing was higher (P < 0.05) for Friesland compared to Jersey and crossbred during the hot-wet season. In the cool-dry season the Jersey spent more time (P < 0.05) grazing than the other breeds. The Friesland and crossbred on the other hand devoted most of their time lying down compared to Jersey in the cool- dry season (P < 0.05). There were season differences in time spent on all activities (P < 0.05). Time spent on grazing was longest in post-rainy seasonal and lowest in hot- wet season (P < 0.05). The longest lying down period was observed in the hot-dry season and lowest in hot-wet season (P < 0.05). iii Daily milk yield Varied (P < 0.05) with genotype with the Friesland and Jersey producing higher yield than the crossbred. The highest amount was produced in hot-dry and the least in hot-wet season. Milk yield was positively correlated (P < 0.05) with lying down. Standing was negatively correlated with milk yield (P < 0.05). The Friesland had the highest avoidance distance scores (P < 0.05) and the Jersey had the lowest avoidance distance scores in all seasons. There was an association (P < 0.05) between genotype and exit speed scores, pen scores and stepping behaviour scores. The Friesland exhibited the highest exit speed scores than the other breeds. The Jersey had the lowest (P < 0.05) kicking behaviour scores. There was a relationship (r = 0.64) between avoidance distance scores and exit speed. Exit speed scores were correlated with pen score(r= 0.23). Milk yield was significant related (r= 0.17) to the occurrence of kicking behaviour. The genotypes showed different levels of sensitivity to season and milk yield was influenced by breed and season. It can be concluded that time budgets vary with season and farmers need to adopt measures that buffer the effect of season on welfare of dairy cows. It can also be concluded that avoidance distance scores differs according to genotype with Jersey being more confident to humans than other two breeds. It is therefore recommended that provision of shades or cooling mechanism should be adopted to buffer the effects of hot-wet season. Improving quality of feed during the cool-dry season may be critical for Jersey cows. Finally positive handling of the dairy cows is recommended in order to improve the welfare and milk yield of pasture based dairy cows.

Orientador: Paulo de Barros Correia / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-22T09:16:24Z (GMT). No. of bitstreams: 1 Kawano_BrunoRogora_M.pdf: 3277644 bytes, checksum: 51319676ccd95ce516c2a06783c9640d (MD5) Previous issue date: 2012 / Resumo: A Indústria de Laticínios no Brasil tem buscado cada vez mais a utilização de novos métodos que possibilitem o aumento da eficiência, tanto da área técnica, quanto da área econômica, sendo que esta última acaba sendo, muitas vezes, consequência da obtenção da primeira. Este esforço no setor foi realizado no Brasil principalmente depois da maior abertura do país às empresas multinacionais ocorrida nos anos de 1990, o que fez aumentar a competitividade empresarial entre elas, sendo este fator determinante para que as indústrias de laticínios sobrevivessem a este novo cenário que se instalou. Este trabalho visa à avaliação do potencial de ganhos em eficiência energética na indústria de laticínios, que pertence ao setor de Alimentos e Bebidas. Para tal, analisou-se a aplicação de ferramentas da engenharia econômica e da otimização sendo que foi desenvolvido três Estudos de Caso. No primeiro estudo de caso, analisou-se uma análise de viabilidade técnico-econômica da substituição de motores elétricos de um laticínio, tudo isto a partir de dados reais coletados de uma grande indústria de laticínios. No segundo estudo de caso, estudou-se a otimização por meio da maximização da Margem de Contribuição (MC) de uma amostra de 6 produtos, cuja coleta de dados foi obtida de um laticínio de médio porte. No terceiro estudo de caso, utilizou-se o mesmo modelo do laticínio do segundo estudo caso, com a diferença que se analisou a maximização da margem de contribuição dos produtos em que se utilizou, na sua linha de produção, o aproveitamento de calor residual da caldeira para aquecimento de água a fim de ser utilizada nos diversos processos produtivos do laticínio. Os três casos analisados obtiveram resultados satisfatórios tanto no quesito da avaliação energética quanto na avaliação econômica / Abstract: The Dairy Industry in Brazil has sought increasingly using new methods that enable increased efficiency, both from the technical area, as the economic area, the latter of which ends up being often a result of winning the first. This effort was undertaken in the sector in Brazil especially after the opening of the country to the largest multinational corporations occurred in the 1990s, which increased business competitiveness between them, which is a determinant factor for the dairy industry to survive in this new scenario that settled. This study aims to evaluate the potential gains in energy efficiency in the dairy industry, which belongs to the Food and Beverage Industry. To this end, it was analyzed the application of tools of economic engineering and optimization that was being developed three case studies. In the first case study, it was analyzed an analysis of technical and economic feasibility of replacing electric motors of a dairy, all from real data collected from a large dairy industry. In the second case study, it was studied the optimization by maximizing the contribution margin (CM) of a sample of 6 dairy products, which data collection was obtained from a dairy midrange. In the third case study, it was used the same model for the plant in the second case study, with the difference that is considered to maximize the contribution margin of the products that we used in its production line, the use of waste heat boiler for heating water to be used in the various processes of the dairy. The three cases analyzed satisfactory results both in the question of how much energy assessment in the economic evaluation / Mestrado / Planejamento de Sistemas Energeticos / Mestre em Planejamento de Sistemas Energéticos

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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

Dairy farming in Virginia could be more profitable if price and yield risks affecting the cost and availability of feed inputs such as corngrain, corn silage, alfalfa and ryelage are reduced. Price and yield risk facing dairy farmers in Virginia can be reduced through a marketing strategy like hedging and government commodity program participation. The overall objective of this study is to evaluate how the variability of price and yields of particular feed crops affect the variability of expected returns in dairy farming. Specific objectives include: 1) to evaluate the relationship between feed production risk and the level and variability of net returns for a representative dairy farm in Virginia; 2) to evaluate the relationship between price risks of purchased feed inputs and the variability of net returns; 3) to draw implications from the results that can be used to help dairy farmers better manage feed production risk. To accomplish these objectives, the target MOTAD risk analysis technique is used. The empirical model is developed in four steps. First, the model activities such as milking and feeding of cows, heifer and calf activities, crop production, harvesting, labor, and buying and selling activities were created. Second, variable yields based on probability elicitation from dairy farmers were generated. Third, variable prices based on commodity options were generated; and fourth a target income constraint was derived. Results from the analysis indicated that the target income constraint was exceeded in every state of nature for the representative farm resulting in an efficiency frontier of a single point. Increasing the assumed debt-asset ratio and annual debt service requirement, resulted in a risk-return tradeoff with lower levels of risk (measured as mean deviation below target or MDBT) being obtained at the expense of lower levels of expected returns. At a higher debt asset-ratio, when the mean deviation below target (MDBT) was varied over a range of values, the quantity of crops harvested also varied. The average harvested acres of alfalfa and corn silage increased as the MDBT increased while the harvested acres of corn grain and ryelage decreased. Alfalfa harvest is increased because less forage in terms of ryelage is harvested and the average quantity of corn grain decreases as the MDBT increases because more com silage is grown in place of the costlier but less risky ryelage. The results show that hedging and participation in the government feed grain program could lead to effective risk reduction and increases in expected returns for the dairy farmer. Government program participation increased expected returns at all debt-asset ratios. Both government programs and hedging reduced risks at higher debt-asset ratios. Government program participation led to larger gains in expected returns as the availability of land increased. / Master of Science

Opportunity cost of postponed replacement (OC) is the income forfeited by keeping a cow for an extra day and is estimated by the income produced by an average replacement. The effect of adjusting a measure of net income, relative net income (RNI), for OC (RNIOC) by lactation was studied. After edits, the data set consisted of 2,982,001 Holstein cows. Prediction factors were developed for RNI and days of productive life (DPL) so that OC could be estimated from cows with shorter herd life opportunities. Within-herd correlations of RNI estimated from 84 month herdlife opportunity with that predicted from cows still alive at 36, 48, 60 and 72 months were .46, .59, .72 and .76, respectively and predictions reflected phenotypic trends of increased net income over time. Corresponding correlations for predicted 84 month DPL at the same ages were .28, .36, .41 and .47 and predictions conflicted with phenotypic trends of decreased herdlife over time. Total OC for cows with 84 month opportunity were raised by an average of $34 when OC was estimated specific to each lactation. The 433,116 cows with classification records and 84 month herdlife opportunity were used to estimate genetic and phenotypic (co)variances among type traits, production, and months in milk (MIM), RNI and RNIOC with a multiple trait Sire model. Production information from all cows in classified herds indicated that classified cows are not a random sample of cows in those herds. Heritability of RNIOC (.17) was higher than RNI (.12), but the genetic correlation between the traits was high (.97). Heritability of MIM was .06. Genetic correlations of MIM to the yield and linear type traits were less than -31 in absolute value. Evaluation of net merit using economic weights developed with RNIOC was more accurate than indirect prediction of MIM. Approximate reliability of a first crop AI sire evaluation for net merit is .65 compared to .42 for MIM. / Ph. D.

The inclusion of precision dairy farming technologies in dairy operations is an area of increasing research and industry direction. Machine vision based systems are suitable for the dairy environment as they do not inhibit workflow, are capable of continuous operation, and can be fully automated. The research of this dissertation developed and tested 3 machine vision based precision dairy farming technologies tailored to the latest generation of RGB+D cameras. The first system focused on testing various imaging approaches for the potential use of machine vision for automated dairy cow feed intake monitoring. The second system focused on monitoring the gradual change in body condition score (BCS) for 116 cows over a nearly 7 month period. Several proposed automated BCS systems have been previously developed by researchers, but none have monitored the gradual change in BCS for a duration of this magnitude. These gradual changes infer a great deal of beneficial and immediate information on the health condition of every individual cow being monitored. The third system focused on automated dairy cow feature detection using Haar cascade classifiers to detect anatomical features. These features included the tailhead, hips, and rear regions of the cow body. The features chosen were done so in order to aid machine vision applications in determining if and where a cow is present in an image or video frame. Once the cow has been detected, it must then be automatically identified in order to keep the system fully automated, which was also studied in a machine vision based approach in this research as a complimentary aspect to incorporate along with cow detection. Such systems have the potential to catch poor health conditions developing early on, aid in balancing the diet of the individual cow, and help farm management to better facilitate resources, monetary and otherwise, in an appropriate and efficient manner. Several different applications of this research are also discussed along with future directions for research, including the potential for additional automated precision dairy farming technologies, integrating many of these technologies into a unified system, and the use of alternative, potentially more robust machine vision cameras.