Factors Driving Sow Breeding Operations to Become Large
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This study examines the influences of economic and non-economic variables on the size of U.S. sow breeding operations using a probit model. Data from a national survey of U.S. hog operations identifying two different size categories were used in this study. Findings indicate that factors such as operations located in Delta States, climate controlled facilities, specialized operation, breeding practices, and risk attitudes toward investments influence decisions to establish breeding operations with 500 or more sows. Producers located in Iowa were more likely to choose breeding operations with 499 or less sows.Keywords:
Pig breeding
Probit
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Breeding record is an important way to implement standardized sheep raising, trace major sheep raising epidemic information and ensure the quality and safety of products for sheep-raising households or farms. Based on 849 questionnaires from 17 cities of Shandong Province, the paper firstly used the binary discrete model of Logit to analyze the factors influencing the establishing behavior of breeding records of sheep-raising households or farms and then used the ISM model to explain the relationship and hierarchy of each influencing factor. The result showed that seven factors including the education level of the deciders, farming scale, fixed number of farming years, degree of specialization, support of the government, whether to join the industrialization organization and the recognition of the breeding records have a significant impact on the establishing behavior of breeding records of the sheep-raising households or farms. Among them, the support of the government and the recognition of breeding records are the surface direct factors, degree of specialization and whether to join the industrialization organization are the middle indirect factors, the education level of the deciders, the farming scale and the fixed number of farming years are deep source factors.
Industrialisation
Agribusiness
Raising (metalworking)
Binary logit model
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Despite large efforts to generate and extend management innovations for rangeland operators, little is known about the degree to which practices are used. We determined what influenced use of 26 management practices among 340 permittees using data from a mailed survey. Five, co-dominant socioeconomic groups of permittees were identified by cluster analysis: Operators, 2 types of traditional Ranchers, and 2 types of Hobbyists. The main concern across groups was losing access to public land, and coping strategies overall included passivity (64%), intensification of private-land use (27%), and enterprise diversification (5%). Across all groups the 4 highest use rates uniformly occurred for livestock cross-breeding (92%), livestock supplementation (80%), planting improved forages on private land (76%), and interaction with extension personnel (73%). The 4 lowest rates (3 to 12%) occurred for use of futures markets, range-trend monitoring on private land, estrus synchronization, and short-duration grazing (SDG). Groups varied in use of feed and financial consultants, prescribed fire on private land, forward contracting, and controlled grazing systems other than SDG, with Large-Scale Operators tending to use these the most. Larger operation size and higher level of formal education and income for managers were positively associated with using more practices. Hobbyists tended to use practices the least. Practices which were less complex, clearly linked to animal production, potentially more cost-effective, and had greater compatibility with operational goals were favored. Socioeconomic groups and coping strategies have utility for better targeting research and extension. Understanding why some seemingly beneficial practices are rarely used requires improved communication with rangeland operators.
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The changing farm population challenges Cooperative Extension to adjust programming objectives to meet the changing needs of their clientele. In New England, a mail survey identical to a survey conducted 5 years ago is used to assess production practices, technologies, and future concerns of Vermont dairy farmers. The survey findings are then compared to the earlier survey to identify trends in farm size, technologies, and operator characteristics. While New England dairy farms are making a major shift in technology and size, the dairy industry is witnessing the disappearance of small farms and a fastening pace in the growth of herds with more than 400 cows. In this environment, there is a tremendous need for Cooperative Extension to identify changing production trends and the uses of technology on regional dairy farms for future programming needs. With fewer resources and yet greater pressure to meet clientele educational needs, the survey presents the opportunity to identify producer concerns and direct future programming needs. We have seen the average size of Vermont dairy farms has grown from 39 in 1970 to 90 in 1997 to 115 in 2002. the comparison of current practices to 1997 also indicates that average production has increased to by more than 2000 pounds of milk per cow. While farms are getting bigger, there are more farms using milking parlors and automatic takeoffs on larger farms. However the median size herd is only 70 cows, up from only 60 cows 5 years ago, indicating that a few larger dairy farms greater than 500 cows significantly affects the average size. One of the biggest changes seen in the state's dairy industry has been the practice of grazing. Ten years ago grazing had been promoted as a viable alternative production that was linked to lower production costs and higher profitability. In Vermont, grazing received focused attention from many farmers who desired to link Vermont's grass forage advantage with greater profitability. However, the 2002 mail survey indicated farmers relying on grazing has decreased by nearly 20%, and herd size of farms using grazing has increased by 12 cows to 55 cows per farm. The characteristics of farm operators have also shifted as the age of the respondents has decreased while educational level has increased. In other demographics, we have seen the number of farms using corporative business structure increased from 5 to 15%. Dairy farmers identified real estate taxes and environmental regulations as the factors most threatening to their survival. The results from the survey provide a picture of the dairy farming needs, however to better group farmers to identify concerns and focus programming needs, factor analysis is used to group farmers by a set of characteristics set the farmers apart from others. Factor analysis is a statistical procedure that ranks correlation among a set of key characteristics that are not readily identifiable through ordinary statistical procedures. For example, factor analysis has been used previously to identify graziers vs. non-graziers, farmers more likely to adopt certain technologies, and those more likely to expand their herds in the future. These statistics will assist Vermont Cooperative Extension to direct programming needs at groups that are most concerned about certain issues, most likely to expand, or to direct at farmers most concerned about an issue such as estate planning. This recent survey provides a rare opportunity to analyze extension clientele. The use of cluster analysis will provide Extension leadership greater knowledge of the state's dairy farmer population and enable the formation of more effective and directive programming.
Dairy Farming
Milking
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As horticulture production increases over time, growers are expected to improve efficiency, adopt appropriate technologies, improve working conditions and workers' safety, and enhance markets. Mechanization decisions are made to maximize production under a least-cost combination of inputs including mechanization. The objective of this paper is to determine the socioeconomic factors influencing the level of mechanization among nurseries and greenhouses. The results will provide more profound insights into the empirical relationships between the level of mechanization and the economic and technical characteristics of nurseries or greenhouses. Results will also describe the influences of owners or operators' characteristics on mechanizations decisions. The level of mechanization shows the extent by which nurseries or greenhouses have currently mechanized each of the significant workers' tasks involved in the production of horticulture products. A regression equation was estimated using the socioeconomic database collected from a survey of 215 randomly selected wholesale nurseries and greenhouses in eight Southern states. The regression results explained 69% of the variation in the level of mechanization among participating nurseries or greenhouses. Younger owners or operators tend to approve of higher mechanization in horticulture operations. Significant differences in the levels of mechanization were observed among owners or operators with different levels of formal educational attainment. Workers' tasks in greenhouse-only operations tend to be more mechanized than nursery-only operations. Workers' tasks in operations with higher annual gross sales were more mechanized than smaller operations. The shortage of permanent or part-time workers would encourage owners or operators to shift to more mechanized horticulture production activities. Corporate-run horticulture organizations provided more mechanization options for their workers than the other business operations.
Mechanization
Economic shortage
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This study examines the influences of economic and non-economic variables on the size of U.S. sow breeding operations using a probit model. Data from a national survey of U.S. hog operations identifying two different size categories were used in this study. Findings indicate that factors such as operations located in Delta States, climate controlled facilities, specialized operation, breeding practices, and risk attitudes toward investments influence decisions to establish breeding operations with 500 or more sows. Producers located in Iowa were more likely to choose breeding operations with 499 or less sows.
Pig breeding
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Citations (1)
This article utilizes a farmer survey to analyze the relationships between farm business structure and the importance farmers place on risk management practices. The strongest relationships occur between farm size and risk management, while rating differences across age of operator, tenure, and use of debt are less pronounced.
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Exotic dairy goats have increasingly become important in alleviating poverty and combating hunger and malnutrition in Kenya. Such goats were introduced in the eastern Kenyan highlands through a group-based approach about a decade ago by FARM-Africa. It is only through this approach that interested households could access imported Toggenburg bucks and other related services. However, the approach resulted in farmers incurring different magnitudes of transaction costs. This study thus assesses the magnitudes and determinants of transactions costs in a group-based breeding approach. Data was generated using 165 randomly selected farmers from the project area. Main findings were that wealth level of households and participation in credit schemes affected adoption positively and negatively respectively. The study showed that the adoption of the dairy goats was not a costless process, and those who could not afford to meet the transactions costs are likely to be left out.
Kenya
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Based on the survey data of 217 pig farmers from six districts in Beijing,this study uses logistic binary discrete model to analyze how farmers' behavior of quality control influence the quality of pigs. The results show that it has a remarkable influence on archival records of farms through co-op mode,professionalization degree and perceiving of income increase by breeding quality-safe pigs; it has obvious effects on implementation by farms during withdrawal period by choices of sales contract and co-op mode, cognitive difficulties of security technology,cognitive level of animal remedy and additives; and it also has evident impact on breeding scale,education level and government regulation with an all-in and allout method of production in the farm. With the purpose of improving the pork safety,it's suggested that government strengthen its policies and measures by stimulating farms to control the quality of pigs.
Pig breeding
Binary logit model
Professionalization
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A study was conducted in the four counties the maize- wheat-teapotato and sugarcane-based farming system in North western Kenya to explore the variability among household characteristics and farm productivity. The aim of this work was to establish homogenous groups of crop-livestock mixed farming systems of Kenya. A two step approach was adopted for the study. The first was a rapid rural appraisal followed by a formal survey aimed at establishing farm types to facilitate detailed analysis of synergistic crop-livestock interaction systems. A random sample of 423 farmers was interviewed using a semi structured questionnaire. Descriptive and multinomial techniques were used in the analysis. Two classifications were utilized, the first step was establishing the criteria for classification and the second based on resource accessibility by farmers. The criteria used were the proportions of various crop and livestock enterprises and resource endowment. The process came up with eight farm types based mainly on the farm enterprise orientation, farm size, land productivity, cattle breeding, and farm by-products. Based on the formal survey three farm types were identified as intensive, semi intensive and extensive systems. The resource groups in all the counties were identified by: crop-livestock management, soil fertility management, food security and farm and off-farm income as important indicators of variability. However, all households were net food buyers, implying food insecurity. In addition, off-farm activities and off farm income were important livelihood survival strategies. Development planners and policy makers need to develop unique interventions targeting each specific group, since blanket policies are not appropriate in such a situation. Options such as optimizing livestock numbers to match available feed resources and improving feed availability through breeding and adoption of dual-purpose crop varieties with better digestibility coefficient, improving the cost-effectiveness of existing nutrition technologies (e.g. crop-by-products’), and bringing more land under fodder crops need to be explored. Since the farm sizes within the region had continued to decline, limiting the availability of on-farm livestock feed, there is need for policy instruments that can discourage land fragmentation
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Establishment of pig-breeding record is fundamental to enforce the source supervision of pork production and construct the tracing mechanism of pork quality safety. Based on the result of 327 questionnaires, Logit Binary Choice Model is used in this paper to quantitatively analyze the factors influencing the willingness of pigbreeding farms and farmers to establish breeding record. It shows that six factors, which are education level, specialized level, participation in pig-breeding cooperative organization, recognition of breeding record, government’s propaganda and supervision, have significant and positive impact on the willingness of pigbreeding farms and farmers to build breeding record. Key words: Pig-breeding farm and farmer; Breeding record; Logit model; Influence factors
Binary logit model
Pig breeding
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