Relevant bibliographies by topics / Dairy analysis

Academic literature on the topic 'Dairy analysis'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Dairy analysis"

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Bindu, T. Hima, Dr S. E. V. Subrahmanyam Dr.S.E.V.Subrahmanyam, and Dr M. S. Bhat Dr. M. S. Bhat. "Swot Analysis of Dairy Industry in India." International Journal of Scientific Research 3, no. 1 (June 1, 2012): 249–51. http://dx.doi.org/10.15373/22778179/jan2014/81.

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Pandian, A. Serma Saravana, M. Prabu M. Prabu, and N. Kumaravelu N. Kumaravelu. "Swot Analysis of Dairy Sector Development in Tamil Nadu." Indian Journal of Applied Research 3, no. 4 (October 1, 2011): 238–40. http://dx.doi.org/10.15373/2249555x/apr2013/80.

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Budiraharjo, Kustopo, Budi Raharjo, and Solikhin Solikhin. "ANALYSIS OF FACTORS AFFECTING THE IMPORT OF DAIRY MILK (CASE STUDY: THE IMPORT OF DAIRY MILK IN INDONESIA)." Agrisocionomics: Jurnal Sosial Ekonomi Pertanian 5, no. 1 (June 17, 2021): 27–33. http://dx.doi.org/10.14710/agrisocionomics.v5i1.7138.

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The supply of fresh dairy milk in the country (SSDN) has not been able to meet the needs of domestic dairy milk consumption so that the fulfillment of dairy milk consumption needs is also done byimporting dairy milk. This study aims to analyze the factors that influence milk imports in Indonesia.The research method uses quantitative analysis techniques, namely multiple linear regression. This research was conducted in Indonesia using secondary data from 2006-2016 obtained at the Central Statistics Agency and the Ministry of Agriculture and other literature related to research. Research variables include exchange rates, GDP per capita, milk exports, and milk production. The results showed that variables GDP per capita, milk exports, and milk production have positive influence. Meanwhile, exchange rate has negative influence for milk imports.
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Pandian, A. Serma Saravana, Dr K. N. Selvakumar Dr. K. N. Selvakumar, and Dr M. Prabu Dr. M. Prabu. "Impact of Dairy Development Programmes in India - An Economic Analysis." Indian Journal of Applied Research 3, no. 12 (October 1, 2011): 131–32. http://dx.doi.org/10.15373/2249555x/dec2013/35.

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Nasuda, Yuko, Masato Ohnuma, Michihiro Furusaka, Kaoru Hara, and Toshinori Ishida. "Nanostructure Analysis of Dairy Products." Nippon Shokuhin Kagaku Kogaku Kaishi 67, no. 6 (June 15, 2020): 186–92. http://dx.doi.org/10.3136/nskkk.67.186.

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Dahiya, Pooja, Roopsi Kaushik, and Anil Sindhu. "Physiological Analysis of Dairy Effluent." International Research Journal on Advanced Science Hub 2, Special Issue ICAET 11S (November 1, 2020): 20–29. http://dx.doi.org/10.47392/irjash.2020.228.

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Moori, Roberto Giro, Rodrigo Leme Pinto Lima, and Julio Eduardo Da Silva Menezes. "Collaborative Relationship Analysis Between Dairy." Journal of Operations and Supply Chain Management 5, no. 2 (December 22, 2012): 13. http://dx.doi.org/10.12660/joscmv5n2p13-25.

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This exploratory and descriptive study tested one application of the IMP Interaction <br />Model developed by the International Marketing and Purchasing Group (IMP Group) researchers. The <br />sample with 83 dairy farmers and 28 respondents from milk processing companies revealed, with a <br />statistical significance level of 0.05, that geographical concentration and information exchange (technical and administrative) constructs contribute for buyers and sellers collaborative relationship. This <br />result leads to conclude that logistics systems and the adoption of both process and information technologies are essential for Brazilian milk production chain competitiveness. In addition, IMP Interaction <br />Model has been proved to be efficient in showing the main constructs contribution for development <br />and maintenance of collaborative relationships between buyers and sellers.
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Zdenka, Naglova, Boberova Barbora, Horakova Tereza, and Smutka Lubos. "Statistical analysis of factors influencing the results of enterprises in dairy industry." Agricultural Economics (Zemědělská ekonomika) 63, No. 6 (June 13, 2017): 259–70. http://dx.doi.org/10.17221/353/2015-agricecon.

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The article deals with companies processing and producing dairy products and cheeses in the Czech market. The dairy industry is a crucial field among the production of food products. On March 31, 2015 the milk quotas were cancelled. The impacts of their cancelation can bring danger for the dairy business but also provide some opportunities. Therefore it is important that businesses are economically powerful and so are able to strengthen their competitive position. This article aims to analyse businesses to identify vulnerable groups of businesses and those groups whose welfare is not essentially jeopardized. Partially, the aim is to assess whether there are significant differences in economic indicators among enterprises of the dairy industry (divided according to their size, ownership and subsidy drawing). At the same time the aim is to find groups of dairy businesses from the set which are similar to each other and which differ from other groups of companies and thus set their position in the Czech market. Over all there were 35 dairy milk businesses analysed in 2013. There were statistically significant differences in some economic indicators among corporations considering drawing grants, size, ownership structure and binding to primary production. According to the cluster analysis the large companies with foreign ownership can be considered as a potential threat and may affect the position and competitiveness of other businesses. The results indicate the endangered position of Czech medium-sized businesses as well as opportunities for stabilizing small businesses which specialize closely.
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Demircan, V., T. Binici, H. Koknaroglu, and Aktas AR. "Economic analysis of different dairy farm sizes in Burdur province inTurkey." Czech Journal of Animal Science 51, No. 1 (December 5, 2011): 8–17. http://dx.doi.org/10.17221/3903-cjas.

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The purpose of this study was to analyze the economic structure of different dairy farm sizes in Burdur province in Turkey. Data were acquired by conducting a survey on 132 dairy farms selected by the stratified random sampling method. Dairy farms were divided into three groups according to their sizes and were analyzed accordingly. It was found that production cost decreased and profit increased as animal unit per farm increased. Production costs per animal unit for the first, second, and third group were 2 634.09, 2 252.01 and 1 930.52 YTL, respectively (1 USD = 1.42 YTL), whereas the net profit was &ndash;267.36, 25.95 and 405.99 YTL, respectively. When the average profit of all farms was considered, it was found that the profit was not high enough to sustain a farm household&rsquo;s living. In the study area the retail sale price of 1 kg of milk was 0.468 YTL and production cost of 1&nbsp;kg milk was 0.455 YTL. Hence it could be said that the profit margin (0.013 YTL/kg), defined as the difference between these two prices, was small. It was found that besides milk production, the cattle value appreciation increased farm income. &nbsp;
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Cho, Kwang-Hyun, Jun-Pyo Choi, Byung-Wha You, Deuk-Hwan Lee, Hong-Sik Kong, Kyung-Do Park, and Hak-Kyo Lee. "Analysis of Daily Milking Flow in Holstein Dairy Cow Using the LactoCorder." Journal of Animal Science and Technology 51, no. 4 (August 1, 2009): 265–72. http://dx.doi.org/10.5187/jast.2009.51.4.265.

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Dissertations / Theses on the topic "Dairy analysis"

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Engelmann, Josh. "Dairy price risk management analysis." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/13209.

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Master of Agribusiness
Department of Agricultural Economics
Kevin Dhuyvetter
The size of our dairy operation increased from 300 milk cows to 1,700 milk cows in 2003. Once the dairy operation increased, the dependency on milk price to support the entire operation also increased. This was due to the fact that the cropping side of the operation became more devoted to growing feed for the livestock as opposed to producing cash crops. Thus, the increase in the number of milk cows led to decreased diversity in our income potentially increasing the financial risk of the operation. The purpose of this thesis is to study different risk management tools and strategies to aid in the formulation of a risk management plan for milk sales in our operation. Risk management strategies using forward contracts, futures, put options, and cash were analyzed at different time periods and various minimum price levels. The strategies were analyzed over the last ten years (2001-2010) of available price data. Twenty-five risk management strategies were analyzed both with and without set minimum milk prices. Minimum price levels ranged from $14/cwt to $17/cwt in $1 increments. The time frame for the transaction ranged from zero to twelve months prior to production in three-month increments. Based on historical data, risk management strategies can be used to decrease the price risk faced by an operation. The risk management strategies did not affect the average price received at statistically significant levels typically considered. Different risk management opportunities are highlighted that need to be analyzed before fully implementing a risk management plan for dairy operations.
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Skolrud, Tristan Del. "A Fourier analysis of the U.S. dairy industry." Pullman, Wash. : Washington State University, 2009. http://www.dissertations.wsu.edu/Thesis/Summer2009/t_skolrud_072009.pdf.

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Thesis (M.A. in economics)--Washington State University, August 2009.
Title from PDF title page (viewed on Sept. 15, 2009). "School of Economic Sciences." Includes bibliographical references (p. 18-20).
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Gondal, K. Z. "Analysis of the lactation curve of Pakistani dairy buffaloes." Thesis, University of Newcastle Upon Tyne, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356147.

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Heiman, Travis. "Analysis of a cooperative dairy producer risk management program." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/16173.

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Master of Agribusiness
Department of Agricultural Economics
Kevin Dhuyvetter
Dairy Farmers of America (DFA) is national milk marketing cooperative. DFA’s primary focus is to market the milk of the cooperative’s 17,000 members. In addition, DFA offers its membership a number of farm services. The sole purpose of these services is to make it easier for DFA members to operate their businesses. One of the services offered provides members access to forward contracting alternatives for pricing their milk. The objective of this research is to utilize demographic and other information related to the characteristics of individual dairy producers and determine how these characteristics impact the use (or lack thereof) of risk management marketing tools. More specifically, the focus of this research is to identify what types of dairy producers are most likely to use the DFA’s forward contracting program. The logit model estimated indicated that regional and demographic differences impact the use of DFA’s forward contracting program. Members in the Mountain Area are most likely to use the program followed by members in the Central Area. Demographic differences that significantly impacted the use of forward contracting include age (older producers use forward contracts less than younger operators) and the size of operation, as measured by milk produced per year (larger operators were more likely to use forward contracting services). While the estimated logit model did identify several factors related to the use of forward contracting services, relationships are not particularly strong and the percent of producers using the services is relatively low. Thus, the model is limited in its ability for identifying key factors and thus it will be difficult for DFA to base a targeted marketing effort at certain producers. DFA would need additional information about their members to successfully target for this farm service.
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Meadows, Cheyney. "Evaluation of the effects of a contract breeding program on reproductive efficiency in Ohio dairy herds." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1117163496.

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Hess, Vincent T. "An Economic Analysis of Factors Affecting Pre-Weaned Dairy Calf Growth and Profit Optimization in Dairy Calf Operations." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4627.

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This study was an extension of a study submitted in April 2014 by Sheldon D. Holt entitled “Ambient Temperature, Calf Intakes, and Weight Gains on Preweaned Dairy Calves”. A major component in a profitable dairy operation is the raising of female calves as replacement heifers; but since no direct income is generated by calf raising alone, it is often overlooked as a potential profit area on a dairy farm. Calf management practices that ultimately impact milk productivity and reproductive performance during a heifer’s lifetime begin at birth. This study examines the effect of calf starter intake on calf growth, measuring specifically calf weight. How calf starter intake affected production costs was also examined. Other factors included in the study were seasonal change, hip height, days since birth, and weather conditions. The cost of calf starter is one of the main contributors to total production cost in raising dairy calves. Since the amount of starter intake consumed by the calves in this study was measured by Holt, a cost analysis can be performed using these data. Therefore, the first two objectives of this study are to 1) develop a model which minimizes cost of starter feed (which is a variable controlled by the dairy producer) and 2) use the model developed under objective 1) to find the breakeven point (where the cost of an input is less than or equal to the value gained from that input) and conduct sensitivity analysis with respect to this point. Although an analysis was performed on the data at the close of its collection in 2014 by S.D Holt, there are several econometric issues that were not adequately addressed before these analyses were performed. The following problems have been found in the data: functional form, multicollinearity, heteroskedasticity, and serial correlation. Any interpretation or prediction based on these data, without these issues being resolved, is not reliable. In order for interpretations and predictions based on these data to be valid, the last two objectives of this study are to 3) define in detail the econometric problems that existed in Holt’s study and 4) find and implement solutions to econometric problems that existed in that study.
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Xu, Qing Yun. "The competitiveness of Ontario dairy farms : a farm level analysis." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=116061.

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The Canadian supply managed dairy sector is likely to face more competitive pressure from challenges through the World Trade Organization (WTO) and the changing global trade environment. Therefore, it is highly prudent for Canadian dairy producers to focus their concern on their level of competitiveness and how to improve it. This study investigated the competitiveness of Ontario dairy sector based on a sample of farm level data with a Box-Cox transformed econometric cost model. The data were gathered by the Ontario Dairy Farm Accounting Project, for the years 2005, 2006, and 2007. The impacts of output, yield per cow and several farm-specific characteristics on the average cost of milk production were examined. Results support the presence of significant size economies and yield economies within Ontario milk production. Minimum costs were achieved for farms with approximately 125 cows. The results also indicated that some farm-specific characteristics, breed and region, also had significant impacts on the cost of Ontario milk production. However, it appears that Ontario farms may find it difficult to survive if they are forced to face international competition. Even at their minimum, average costs were above an indicator international dairy price.
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Stennes, Bradley Kenneth. "Bovine somatotropin and the Canadian dairy industry : an economic analysis." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/42012.

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Bovine Somatotropin (BST) is a naturally occurring hormone in dairy cows which affects milk production levels (Chalupa and Galligan, 1988). The effects of BST have been known since the 1930's but limited supply of this hormone made any large scale commercial use impossible. Recently a low cost source of BST became available through recombinant DNA technology. This low cost availability of the hormone has led to research experiments which show that recombinant BST can significantly increase a cow's ability to produce milk (Peel and Bauman, 1987; Burton et al, 1987; Soderholm et al, 1988; De Boer et al, 1988). A number of studies have examined the firm level impacts of BST on the Canadian dairy industry. This present work will build upon these earlier studies by examining the impacts of BST at the both the firm and aggregate levels for all of the dairy producing regions in Canada. To facilitate this analysis at an aggregate level a linear programming model of the Canadian dairy industry was used. This model describes the dairy sector for each province, including the production, processing, trade and marketing subsectors, and is incorporated into the Canadian Regional Agricultural Model (CRAM), (Webber et al, 1986). Several scenarios were examined representing different government policy responses with the introduction of BST to the Canadian dairy industry. These scenarios are compared to a 1986 "base case" situation of the dairy industry. The first scenario examined represents a "no policy change" situation. Provincial quota levels, producer prices, levies and subsidies all remain unchanged and BST adoption rates are assumed for each province. In order to maintain existing milk production levels with BST a 5% reduction in the national cow herd results. This lower number of animals producing the same amount of milk as in the base case results in a 5% increase in dairy producer income at the national level. In the second scenario the impact of BST on quota values is examined. As in the first scenario all dairy policy instruments remain at 1986 base levels. The decrease in marginal costs for a producer fully adopting BST is then estimated. Using a marginal cost estimate of $32 per hi, the fall in marginal cost was nearly 6% or $2.00 per hi on average for Canada. This results in an 18% increase in what these producers can pay for quota. Using lower marginal cost estimates would result in a greatre increase in this variable and smaller quota increases. In scenario 3 some of the benefits of BST adoption are passed on to consumers. This is done by allowing production levels to expand such that the difference between farm-gate price and supply price remains the same as prior to the introduction of BST. Quota values remain at their base case level. This resulted in a 2% increase in the national supply of raw milk. In the fluid milk market the supply of standard milk increased by 2% and lowfat milk production increased by approximately 3 percent. In the industrial market cheese production increased by 6%, butter production increased by 2% and skim milk powder production fell by approximately 4 percent. In the final scenario the benefits of BST adoption are passed on to the taxpayers. This is accomplished by reducing the dairy subsidy by an amount which just offsets the cost savings in each province as a result of BST adoption. This leads to a decrease in the dairy subsidy of $80 million at the national level or approximately 30% of the 1986 subsidy payment. At the firm level, given the assumptions of this study, the main impacts of BST are a fall in marginal costs of $2 per hi and an increase in quota values of 18%. While these estimates of firm level changes resulting from BST adoption are not trivial they are much less than would be expected with earlier results of milk yield increases of over 25 to 3 5% accompanied by dry matter feed increases of only 10 to 15 percent (Bauman et al, 1985; Soderholm et al, 1988) . Given the assumed Canadian adoption rates of approximately 50% the aggregate level impacts of BST are more moderate. The national herd size falls by 5% and dairy producer incomes are increased by 5% to produce at the base case 198 6 production levels.
Land and Food Systems, Faculty of
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Kamthunzi, Wellam. "Design, economic and environmental analysis of dairy waste management systems /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.

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Waak, Elisabet. "Listeria monocytogenes : farm and dairy studies /." Uppsala : Dept. of Food Hygiene, Swedish Univ. of Agricultural Sciences ([Institutionen för livsmedelshygien], Sveriges lantbruksuniv.), 2002. http://epsilon.slu.se/avh/2002/91-576-6376-9.pdf.

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Books on the topic "Dairy analysis"

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Hawksworth, John. Dairy-McKay watershed analysis. Tillamook, Or. (4610 Third St., Tillamook 97141): The Bureau, 1999.

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Nollet, Leo M. L. Handbook of dairy foods analysis. Boca Raton, FL: CRC Press, 2010.

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Toldrá, Fidel, and Leo M. L. Nollet, eds. Handbook of Dairy Foods Analysis. 2nd ed. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429342967.

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Chandler, Jack. Prince Edward Island dairy farm business analysis, 1987. Charlottetown, P.E.I: Dept. of Agriculture and Forestry and Agriculture Canada, 1988.

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Chandler, Jack. Prince Edward Island dairy farm business analysis, 1985. Charlottetown, P.E.I: Prince Edward Island . Dept. of Agriculture, 1985.

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Haidacher, Richard C. Consumer demand for dairy products: A summary analysis. [Washington, DC]: U.S. Dept. of Agriculture, Economic Research Service, 1988.

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Lowe, M. J. An analysis of Genus Management costed dairy farms 1989 - 1990. Crewe: Genus Researchand Development, 1990.

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Saarela, Maria, and Tiina Mattila-Sandholm. Functional dairy products. Boca Raton, Fla: CRC Press, 2003.

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D'Silva, Joyce. The cynical abuse: BST : a welfare analysis. Petersfield: Compassion in World Farming Trust, 1994.

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Karszes, Jason A. Dairy replacement programs: Costs & analysis, western New York, 1993. Ithaca, NY (14853-7801): Dept. of Animal Science and Agricultural, Resource, and Managerial Economics, College of Agriculture and Life Sciences, Cornell University, 1994.

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Book chapters on the topic "Dairy analysis"

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Munjanja, Basil K., and Anna T. D. Gowera. "Dairy Products." In Spectroscopic Methods in Food Analysis, 543–72. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315152769-21.

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Calvo, María V., Manuela Juárez, and Javier Fontecha. "Triacylglycerols in Dairy Foods." In Handbook of Dairy Foods Analysis, 171–93. 2nd ed. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429342967-9.

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Overton, Michael W. "Dairy Records Analysis and Evaluation of Performance." In Dairy Production Medicine, 272–302. Oxford, UK: Blackwell Publishing Ltd., 2011. http://dx.doi.org/10.1002/9780470960554.ch22.

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Hernando, I., E. Llorca, and A. Quiles. "Emerging Techniques for Microstructural Analysis." In Microstructure of Dairy Products, 67–88. Chichester, UK: John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781118964194.ch4.

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Impoco, Gaetano. "Quantitative Image Analysis in Microscopy." In Microstructure of Dairy Products, 89–125. Chichester, UK: John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781118964194.ch5.

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Frankhuizen, Rob. "NIR Analysis of Dairy Products." In Handbook of Near-Infrared Analysis, 657–83. 4th ed. Fourth edition. | Boca Raton : Taylor and Francis, 2021. |: CRC Press, 2021. http://dx.doi.org/10.1201/b22513-36.

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Giangiacomo, Roberto, and Tiziana M. P. Cattaneo. "Analysis of Dairy and Eggs." In Near-Infrared Spectroscopy in Agriculture, 559–97. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/agronmonogr44.c20.

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McGorrin, Robert J. "Flavor Analysis of Dairy Products." In ACS Symposium Series, 23–49. Washington, DC: American Chemical Society, 2007. http://dx.doi.org/10.1021/bk-2007-0971.ch002.

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Aristoy, M. Concepción, and Fidel Toldrá. "Amino Acids in Dairy Foods." In Handbook of Dairy Foods Analysis, 9–31. 2nd ed. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429342967-3.

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Islam, Saher, and Devarajan Thangadurai. "Proteomic Authentication of Dairy Products." In Handbook of Dairy Foods Analysis, 405–27. 2nd ed. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429342967-21.

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Conference papers on the topic "Dairy analysis"

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Wibowo, Ignatius Prasetya Aji, and Lukertina Lukertina. "Production and Distribution Analysis of Dairy Farming." In Proceedings of the 4th International Conference on Management, Economics and Business (ICMEB 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200205.004.

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Jingjing, Li, and Liu Sheng. "Inner Mongolia MengNiu dairy company financial analysis." In 2011 IEEE International Conference on Granular Computing (GrC-2011). IEEE, 2011. http://dx.doi.org/10.1109/grc.2011.6122626.

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Batanov, S. D., O. S. Starostina, I. A. Baranova, M. M. Shaidullina, and L. V. Kornilova. "Biological trait analysis of dairy cattle heredity." In PROCEEDINGS OF THE II INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS, SYSTEMS AND TECHNOLOGIES: (CAMSTech-II 2021). AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0092878.

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Fairbrother, P., W. O. George, and J. M. Williams. "On-Line Analysis Of Fermentation Of Dairy Waste." In Intl Conf on Fourier and Computerized Infrared Spectroscopy, edited by David G. Cameron. SPIE, 1989. http://dx.doi.org/10.1117/12.969535.

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Scott Inglis, Curt Gooch, and Michael Timmons. "Engineering Analysis of Digesting Sand-Laden Dairy Manure." In 2006 Portland, Oregon, July 9-12, 2006. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2006. http://dx.doi.org/10.13031/2013.21182.

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X Song, T Leroy, E Vranken, D Berckmans, W Maertens, and B Sonck. "Vision-based trackway analysis in dairy cow's locomotion." In 2007 Minneapolis, Minnesota, June 17-20, 2007. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2007. http://dx.doi.org/10.13031/2013.23176.

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Rizojeva-Silava, Aleksandra, Sandija Zeverte-Rivza, and Peteris Rivza. "Analysis and outlook of dairy sector in Baltic States." In 20th International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering, 2021. http://dx.doi.org/10.22616/erdev.2021.20.tf225.

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Li, Jingyi. "Operation Status Analysis and Promotion Strategy of BRIGHT DAIRY." In 2021 International Conference on Economic Development and Business Culture (ICEDBC 2021). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/aebmr.k.210712.008.

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Chudasama, Ronak, Sagar Dobariya, Komal Patel, and Hezal Lopes. "DAPS: Dairy analysis and prediction system using technical indicators." In 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS). IEEE, 2017. http://dx.doi.org/10.1109/ssps.2017.8071587.

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Junwen Wang, Yao Hu, and Jingshan Li. "Transient analysis of dairy filling and packing production lines." In 2010 American Control Conference (ACC 2010). IEEE, 2010. http://dx.doi.org/10.1109/acc.2010.5530736.

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Reports on the topic "Dairy analysis"

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Sam Alessi and Dennis Keiser. Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual. Office of Scientific and Technical Information (OSTI), October 2012. http://dx.doi.org/10.2172/1070144.

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Soethoudt, Han, Greet Blom-Zandstra, and Heike Axmann. Dairy value chain analysis in Tunisia : Business opportunities. Wageningen: Wageningen Food and Biobased Research, 2018. http://dx.doi.org/10.18174/452934.

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Ingasia Ayuya, Oscar, Dave Mwangi Ireri, Judy Kithinji, Asaah Ndambi, Catherine Kilelu, Bockline Omedo Bebe, Paul Ndung’u, and Jan van der Lee. Milk dispensing machines in Kenya’s dairy industry: trends and scenario analysis. Wageningen: Wageningen Livestock Research, 2020. http://dx.doi.org/10.18174/521451.

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Farrell, Johanna. Dairy in Ethiopia. Application of the Supply Chain Analysis for Nutrition (SCAN) Tool. Global Alliance for Improved Nutrition (GAIN), November 2021. http://dx.doi.org/10.36072/bp.7.

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Jongeneel, Roel, Huib Silvis, Co Daatselaar, and Walter van Everdingen. Background analysis for a Temporary Measure (State aid) aimed at restructuring the Dutch Dairy Sector. Wageningen: Wageningen Environmental Research, 2017. http://dx.doi.org/10.18174/413461.

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Ton, Giel, Nora Ourabah Haddad, Jos Bijman, Mohamed Sraïri, and Patience Mshenga. Organizational challenges and the institutional environment: a comparative analysis of dairy cooperatives in Kenya and Morocco. Wageningen: Wageningen University & Research, 2016. http://dx.doi.org/10.18174/399770.

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van Knegsel, Ariëtte T. M., H. Mollenhorst, Roselinde M. A. Goselink, and Yvette de Haas. Milk analysis and cow health : predicting dairy cow life span with milk sampling in early lactation. Wageningen: Wageningen Livestock Research, 2020. http://dx.doi.org/10.18174/544552.

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Mizrach, Amos, Sydney L. Spahr, Ephraim Maltz, Michael R. Murphy, Zeev Schmilovitch, Jan E. Novakofski, Uri M. Peiper, et al. Ultrasonic Body Condition Measurements for Computerized Dairy Management Systems. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568109.bard.

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The body condition (BC) score is recognized in the dairy industry as an essential tool for managing the energy reserves of the dairy cow, which is essential for sustaining optimal and efficient production over several lactations. The current use of BC scoring depends on the accuracy of subjective visual estimates, and this limits its kusefulness as a management aid in the dairy industry. A measuring tool that would frequently provide objective data on the cow's body reserves would be a major contribution to efficient dairy herd management. Ultrasonic sensors have the potential to be developed into an efficient BC measuring device, and the experimental use of such sensors for subcutaneous fat thickness (SDFT) estimates, as an indication for BC in beef cattle, supports this assumption. The purposes of this project were: 1. To compare visual BC scoring and ultrasonic fat thickness with on-line automated body weight (BW) measurements as monitors of nutritional adequacy of dairy cows at various stages of lactation. 2. To determine the effects of variation in digestive fill in early and late lactation on the accuracy of body weight measurements in lactating cows. 3. To modify an existing ultrasonic system and develop a specialized, low-cost sensor for repeatable determination of body condition scores by users with minimal training and skill. 4. To develop a standard for the assignment of body condition scores based on ultrasonic measurements of subdermal fat thickness. The procedure to execute these objectives involved: 1. Frequent measurement of BW, milk yield (MY), BC (visually scored) and subdermal fat thickness ultrasonically measured of dairy cows, and data analysis on average and individual basis. 2. Testing and selection of an appropriate special-purpose sensor, finding an optimum body location for working an ultrasonic measurement, prcessing the signals obtained, and correlating the resulting measurements with performance responses in lactating cows. Linking the ultrasonic signals to BC scores, and developing a BC scoring data acquisition system are the first steps towards fulfilling the necessary requirements for incorporating this device into an existing dairy herd management system, in order to provide the industry with a powerful managment tool. From the results obtained we could conclude that: 1. BC does not correlate with BW changes during all stages of lactation, although in general terms it does. These results were confirmed by individual cow BW and BC data obtained during the course of lactation, that were supported by individual objective ultrasonic measurement of SDFT. 2. BW changes reflect energy metabolism reliably ony after peak milk yield; early in lactation, a decrease in BW expresses mobilization of body reserves only qualitatively, and not quantitatively. 3. Gastrointestinal content increases throughout the whole period during which dry matter intake (DMI) increases. The drastic increase very early in lactation prevents the use of BW changes as a basis for quantitative estimatio of energy meatabolism; at this stage of lactation, konly a BC score or any other direct measurements willl provide a quantitative estimate of energy metabolism. 4. Ultrasonic measurements of subdermal fat thickness can be used to quantify changes that correlate with the actual condition of the cow, as assessed by performance and the traditional way of scoring. 5. To find the best site on the cow's body at which to obtain responses to BC and its changes in the course of lactation, additional sites have to be examined. From the present study, it seems that the sites between ribs 12 and 13 have the potential for this purpose. 6. The use of templates made it easier to repeat measurements at a desired site and spot. However, the convenient easy-to-handle way to standardize the measurement, described in this study, koffers scope for improvement. 7. The RF peak values of the A-mode are better indicators of the location of fat layer borders than image analysis, from the point of view of future commercial development. 8. The distances between the RF peaks of the A-mode can be automatically measured by suitable software, for future commercial development. 9. Proper analysis of daily body weight and milk yield data can provide the necessary information on body condition changes during lactation, until a direct BC measurement device is developed. 10. In any case, at least one visual BC assessment has to be done, preferably immediately after calving, for calibration purposes.
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Gutierrez, Gustavo A., P. Jeff Berger, and Mary H. Healey. Joint Genetic Analysis of Conception and Maintenance of Pregnancy in Dairy Cattle Using a Linear-Threshold Model. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-948.

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Mizrahi, Itzhak, and Bryan A. White. Uncovering rumen microbiome components shaping feed efficiency in dairy cows. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600020.bard.

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Ruminants provide human society with high quality food from non-human-edible resources, but their emissions negatively impact the environment via greenhouse gas production. The rumen and its resident microorganisms dictate both processes. The overall goal of this project was to determine whether a causal relationship exists between the rumen microbiome and the host animal's physiology, and if so, to isolate and examine the specific determinants that enable this causality. To this end, we divided the project into three specific parts: (1) determining the feed efficiency of 200 milking cows, (2) determining whether the feed- efficiency phenotype can be transferred by transplantation and (3) isolating and examining microbial consortia that can affect the feed-efficiency phenotype by their transplantation into germ-free ruminants. We finally included 1000 dairy cow metadata in our study that revealed a global core microbiome present in the rumen whose composition and abundance predicted many of the cows’ production phenotypes, including methane emission. Certain members of the core microbiome are heritable and have strong associations to cardinal rumen metabolites and fermentation products that govern the efficiency of milk production. These heritable core microbes therefore present primary targets for rumen manipulation towards sustainable and environmentally friendly agriculture. We then went beyond examining the metagenomic content, and asked whether microbes behave differently with relation to the host efficiency state. We sampled twelve animals with two extreme efficiency phenotypes, high efficiency and low efficiency where the first represents animals that maximize energy utilization from their feed whilst the later represents animals with very low utilization of the energy from their feed. Our analysis revealed differences in two host efficiency states in terms of the microbial expression profiles both with regards to protein identities and quantities. Another aim of the proposal was the cultivation of undescribed rumen microorganisms is one of the most important tasks in rumen microbiology. Our findings from phylogenetic analysis of cultured OTUs on the lower branches of the phylogenetic tree suggest that multifactorial traits govern cultivability. Interestingly, most of the cultured OTUs belonged to the rare rumen biosphere. These cultured OTUs could not be detected in the rumen microbiome, even when we surveyed it across 38 rumen microbiome samples. These findings add another unique dimension to the complexity of the rumen microbiome and suggest that a large number of different organisms can be cultured in a single cultivation effort. In the context of the grant, the establishment of ruminant germ-free facility was possible and preliminary experiments were successful, which open up the way for direct applications of the new concepts discovered here, prior to the larger scale implementation at the agricultural level.
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