The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Christopher A. Wolf - One of the best experts on this subject based on the ideXlab platform.
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2011 Michigan Upper Peninsula Dairy Farm Business Analysis Summary
2012Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 14 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
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2010 Michigan Upper Peninsula Dairy Business Analysis Summary
2011Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 16 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
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2009 Michigan Upper Peninsula Dairy Business Analysis Summary
2010Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 18 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. Average values are reported in the summary tables and discussion that follows but readers should note that considerable variation exists in most measures.
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2008 Michigan Upper Peninsula Dairy Farm Business Analysis Summary
2009Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 23 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
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2007 Michigan Upper Peninsula Dairy Farm Business Analysis Summary
2008Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 24 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion.
Eric Wittenberg - One of the best experts on this subject based on the ideXlab platform.
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2002 MICHIGAN SWINE (FARROW TO FINISH) BUSINESS ANALYSIS SUMMARY
2020Co-Authors: Gerald D. Schwab, Eric WittenbergAbstract:This report summarizes the financial and production Records of 7 Michigan swine Farms, farrow to finish. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from one or a combination of fat hogs, feeder pigs and cull breeding hogs sales. The Records came from Michigan State University's TelFarm/MicroTel project, the Farm Credit Service system, or by AgriSolutions in Michigan. The values were pooled into averages for reporting purposes. Farm Records were included if a Farm financial summary was completed on 2002 data including beginning and ending balance sheets, plus income and expenses. The data were checked to verify that cash discrepancy was less than 10% of gross cash inflow and that debt discrepancy was less than $1,000. While considerable variation in the data exists, average values are reported in the summary tables below.
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2011 Michigan Upper Peninsula Dairy Farm Business Analysis Summary
2012Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 14 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
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2010 Michigan Upper Peninsula Dairy Business Analysis Summary
2011Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 16 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
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2009 Michigan Upper Peninsula Dairy Business Analysis Summary
2010Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 18 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. Average values are reported in the summary tables and discussion that follows but readers should note that considerable variation exists in most measures.
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2008 Michigan Upper Peninsula Dairy Farm Business Analysis Summary
2009Co-Authors: Eric Wittenberg, Christopher A. WolfAbstract:This report summarizes the financial and production Records of 23 dairy Farms across the Upper Peninsula (UP) of Michigan. To be included, the Farms must have produced at least 50 percent of gross cash Farm income from milk and dairy animal sales. The Records came from Michigan State University’s TelFarm project and Farm Credit Service system in Michigan. Farm Records checked for accuracy. While considerable variation in the data exists, average values are reported in the summary tables and discussion that follows.
Komminist Weldemariam - One of the best experts on this subject based on the ideXlab platform.
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AGWS: Blockchain-enabled Small-scale Farm Digitization
2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020Co-Authors: Nelson Bore, Andrew Kinai, Peninah Waweru, Isaac Wambugu, Juliet Mutahi, Everlyne Kemunto, Reginald Bryant, Komminist WeldemariamAbstract:Farm Records hold the static, temporal, and longitudinal details of the Farms. For small-scale Farming, the ability to accurately capture these Records plays a critical role in formalizing and digitizing the agriculture industry. A trusted exchange of these Records could unlock critical insights to different stakeholders across the value chain. Recently, there has been increasing attention on digitizing small scale Farming with the goal of increasing Farm-level transparency and visibility, access to credit, etc. using these Farm Records. However, most solutions proposed so far have the shortcoming of providing granular and trusted small-scale Farm digitization. To address these challenges, we present a system, called AG-Wallet System(AGWS), which leverages blockchain to formalize the interactions and data flow in small-scale Farming ecosystem. Utilizing instrumentation of Farm tractors, we demonstrate the ability to utilize Farm activities to create trusted electronic field Records (EFR). Using AGWS, we processed over one hundred thousand small-scale Farm-level activity events for which we also performed automated Farm boundary detection of several Farms.
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ADW: Blockchain-enabled Small-scale Farm Digitization.
arXiv: Distributed Parallel and Cluster Computing, 2020Co-Authors: Nelson Bore, Andrew Kinai, Peninah Waweru, Isaac Wambugu, Juliet Mutahi, Everlyne Kemunto, Reginald E. Bryant, Komminist WeldemariamAbstract:Farm Records hold the static, temporal, and longitudinal details of the Farms. For small-scale Farming, the ability to accurately capture these Records plays a critical role in formalizing and digitizing the agriculture industry. Reliable exchange of these record through a trusted platform could unlock critical and valuable insights to different stakeholders across the value chain in agriculture eco-system. Lately, there has been increasing attention on digitization of small scale Farming with the objective of providing Farm-level transparency, accountability, visibility, access to Farm loans, etc. using these Farm Records. However, most solutions proposed so far have the shortcoming of providing detailed, reliable and trusted small-scale Farm digitization information in real time. To address these challenges, we present a system, called Agribusiness Digital Wallet (ADW), which leverages blockchain to formalize the interactions and enable seamless data flow in small-scale Farming ecosystem. Utilizing instrumentation of Farm tractors, we demonstrate the ability to utilize Farm activities to create trusted electronic field Records (EFR) with automated valuable insights. Using ADW, we processed several thousands of small-scale Farm-level activity events for which we also performed automated Farm boundary detection of a number of Farms in different geographies.
O. Aloquili - One of the best experts on this subject based on the ideXlab platform.
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Evaluating the impact of electrical grid connection on the wind turbine performance for Hofa wind Farm scheme in Jordan
Energy Conversion and Management, 2008Co-Authors: M. H. Abderrazzaq, O. AloquiliAbstract:The growth of wind energy is attributed to the development of turbine size and the increase in number of units in each wind Farm. The current modern design of large wind turbines (WT) is directed towards producing efficient, sensitive and reliable units. To achieve this goal, modern turbines are equipped with several devices which are operated with highly advanced electronic circuits. Sensing instruments, measuring devices and control processes of major systems and subsystems are based on various types of electronic apparatus and boards. These boards are very sensitive to the voltage variations caused by abnormal conditions in both the turbine itself and the electric grid to which the wind Farm is connected. This paper evaluates wind Farm Records and proposes a number of methods to overcome such obstacles associated with the design of large wind turbines. Several cases of grid abnormality such as sudden feeder interruption due to the short circuit, network disconnection, voltage variation and circuit breaker opening affecting wind turbines operation and availability are classified and presented. The weight of such impact is determined for each type of disturbances associated with electronic problems in the wind turbine. Wind turbine performance at Hofa wind Farm scheme in Jordan is taken as a case study. © 2008 Elsevier Ltd. All rights reserved.
Liam Brunt - One of the best experts on this subject based on the ideXlab platform.
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Farm Production in England 1700–1914. By Michael E. Turner, John V. Beckett, and Bethanie Afton. Oxford: Oxford University Press, 2001. Pp. xii, 295. £45.00.
The Journal of Economic History, 2003Co-Authors: Liam BruntAbstract:Michael Turner, John Beckett, and Bethanie Afton have assembled a data set based on a large number of English Farm Records (in the form of account books, wage/labor books, and memoranda books). Some of the fruits of this effort appeared previously in Turner, Beckett, and Afton's Agricultural Rent in England, 1690–1914 (Cambridge: Cambridge University Press, 1997). This new book employs a subset of 979 of these Farm Records to cast new light on some important aspects of English Farm production in the period 1700 to 1914. In addition to the introduction and conclusion, the book comprises five substantive chapters. Chapter 2 discusses the Records as a source; chapter 3 considers some aspects of Farming practice (notably cropping patterns and fertilizer use); chapter 4 presents new estimates of wheat yields; chapter 5 presents new estimates of barley and oat yields; and chapter 6 presents new evidence on livestock weights. The most important findings of the book are that the overall growth in wheat, barley, and oat yields was much lower than is commonly thought, and that the main period of yield growth occurred between the 1820s and 1850s. The authors argue on this basis that the Agricultural Revolution can be fixed firmly in the period 1800 to 1850. The great strength of the book is that the data on which it is based are almost entirely new. For that reason, it is a very welcome contribution to our stock of knowledge, and both the authors and their funding body (the Leverhulme Foundation) are to be congratulated.
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Farm Production in England 1700 1914. By Michael E. Turner, John V. Beckett, and Bethanie Afton. Oxford: Oxford University Press, 2001. Pp. xii, 295. 45.00
The Journal of Economic History, 2003Co-Authors: Liam BruntAbstract:Michael Turner, John Beckett, and Bethanie Afton have assembled a data set based on a large number of English Farm Records (in the form of account books, wage/labor books, and memoranda books). Some of the fruits of this effort appeared previously in Turner, Beckett, and Afton's Agricultural Rent in England, 1690–1914 (Cambridge: Cambridge University Press, 1997). This new book employs a subset of 979 of these Farm Records to cast new light on some important aspects of English Farm production in the period 1700 to 1914. In addition to the introduction and conclusion, the book comprises five substantive chapters. Chapter 2 discusses the Records as a source; chapter 3 considers some aspects of Farming practice (notably cropping patterns and fertilizer use); chapter 4 presents new estimates of wheat yields; chapter 5 presents new estimates of barley and oat yields; and chapter 6 presents new evidence on livestock weights. The most important findings of the book are that the overall growth in wheat, barley, and oat yields was much lower than is commonly thought, and that the main period of yield growth occurred between the 1820s and 1850s. The authors argue on this basis that the Agricultural Revolution can be fixed firmly in the period 1800 to 1850. The great strength of the book is that the data on which it is based are almost entirely new. For that reason, it is a very welcome contribution to our stock of knowledge, and both the authors and their funding body (the Leverhulme Foundation) are to be congratulated.
