جستجوی مقالات مرتبط با کلیدواژه "dairy farms" در نشریات گروه "کشاورزی"

The growth of livestock production and the development of livestock farms increases the production of by-products, including livestock waste, which leads to destructive environmental effects. Paying attention to waste management methods has a beneficial effect in reducing the amount of environmental effects. The present study was performed by practical data collection from 4 farms with different methods of waste disposal. The tables and recommendations of the Intergovernmental Panel on Climate Change (IPCC) were used to estimate emissions levels. The obtained data were processed with Simapro software to calculate the environmental indicators of disposal methods. Based on the results, in the management method of waste collection in lagoon, the final environmental index was the lowest as 0.706 per ton of waste. In the depot method for dry mass and using part of it as animal bed, the obtained index was the highest with 1.379. Among the environmental effects and indicators, the effect of the global warming group in all farms was greater than the effect of other groups. Despite the high production of methane in the storage method in the lagoon, due to the production of nitrous oxide gas in the drying method and especially the use of dry waste in the animal bed, these methods had a greater effect of global warming. By managing waste through anaerobic digestion and methane collection, environmental effects can be reduced and energy benefits can be used.

This study was carried out in order to investigate the management and efficiency of dairy farms units and milk production function, in 121 units of dairy farm in Lorestan province at the year 2017. The Required data was collected with field survey and face to face interview method. Data of production function were estimated using corrected ordinary least squares (COLS) Method by Cobb Douglas functions. Also, technical efficiency was estimated by deterministic parametric frontier (DPF). In terms of dairy farms units cost, feed costs accounted for 65.5 %, labor costs 16.16 %, health care and insemination 9.9 %, and 9.1% other costs (including the cost of losses, location and maintenance of dry cows). The average technical, allocative, economic efficiency of the units were 64.3, 52.4 and 44.3% respectively, that showed the significant potential of these units in increasing their productivity. Based on this results farms were not desirable condition in terms of economic efficiency, similar with allocation efficiency in contrast to the technical efficiency. The results showed that dairy cattle units were not efficient 75.7 percent economically in Lorestan province and failed to optimally and effectively minimizing inputs cost. Milk production function results showed that consumption of alfalfa, corn silage, concentrates, artificial insemination number a positive and very significant effect (P<0.05)  and number of workers, hygiene and health costs also fuel and electricity consumption had a positive and significant effect on milk yield (P<0.05). The results of milk production function showed that the importance of increasing each unit of the concentrate (0.352) in increasing milk production was more than other inputs. Generally, the majority of dairy farms due to lack of observance of economic principles in the management of inputs had a low allocation and economic efficiency. Finally, according to the obtained results, it is necessary to implement the guaranteed milk price and maintain the relative stability of forage and concentrate prices in increasing milk production of dairy farms units in Lorestan province.

The purpose of this study was determination of technical efficiency for Sirjan dairy farms using fuzzy data envelopment analysis approach. The underlying assumption of this method unlike conventional data envelopment analysis approach is that input and output data have imprecise. Since activities of agricultural and animal husbandry is done under environmental uncertainty conditions there is uncertainty about inputs and outputs. Therefore employing fuzzy data envelopment analysis is preferred into conventional data envelopment analysis. Necessary information for this study was collected through filling questionnaires for the years 2017 from 32 units of dairy farms in Sirjan. The result showed that the average technical for dairy farms was 81 percent. It has undulate from at least 36% up most 100%. In the other words, can increase amount of efficiency without changing the level of technology and better use of current technology. Also the gap between the best and the worst producer was 64% that can be improved by increasing technical and managerial knowledge, more promotion and new sciences and techniques among the dairy farms of the region.

Over the last decades, productivity growth analysis in agriculture has attracted attention of the economic researchers as well as policy makers in both developed and developing countries. Improving productivity is the best and effective way to achieve economic growth due to scarcity of production resources. Productivity management involves understanding the components and analyzing its changes in the development process. Improving total factor productivity (TFP) is seen as necessary for producers to remain competitive and profitable, particularly in markets where they face declining terms of trade. Without changes scale, TFP can be increasing in several ways, such as increasing output from the same level of inputs, constant the same level of output with a lower level of inputs, or changing the mix of inputs and or outputs. The objective of this research was measuring and decomposing productivity and profitability change. This paper estimated TFP changes and decomposed these changes into technical change, technical efficiency change, and scale and mix efficiency change in industrial dairy farms by using Hicks-Moorsteen TFP indexes. This index was chosen among other indexes, because it is an index that bases on distance functions and data envelopment analysis (DEA) methodology for estimating distances is convenient. Secondly, it is closely related to the Malmquist index, which has been used for some time as the index number of choice in the productivity decomposition literature. For the purposes of comparison, this paper developed data envelopment analysis (DEA) methodology for computing and decomposing Hicks-Moorsteen index. Input and output quantity and price data were included for labor, capital, animal feed, fuel, and milk using records from the results of a sample survey of industrial dairy farms in the provinces of Iran during 1990-2013. The results indicate that the TT effect (the growth in output prices relative to the growth in input prices) on profitability has been moderated by compensating changes in total factor productivity (TFP). The TT was improved 86 percent from 1990 to 1996 and during this period a simultaneous reduction in total factor productivity (TFP) by 15 percent was observed. In other words, industrial dairy farms productivity has been responsive to changes in the industrial dairy farms TT. The TFP survey also indicated that the index was initially decreased and then increased, and despite the fluctuations over the period of 1990-2013, the average has increased by 15% compared with the base year of 1990. Productivity efficiency (TFPE) has been decreased from 1990 to 2013, and decreased from 0.521 in 1990 to 0.248 in 2013. In other words, the gap between the existing TFP and the maximum TFP has increased over the study period. Analyzing TFP change in the 1990s indicates that important components of TFP change have been changed in ROSE and in the second half of the study period, the main component industrial dairy farms TFP change is technical change. These findings support the view that research and development expenditure has led to expansions in the production possibilities set, that dairy farms adopt new technologies quickly and make relatively few mistakes in the production process, and that they rationally adjust the scale and scope of their operations in response to changes in prices and other production incentives. The results demonstrate that industrial dairy farms have high technology, scale, and output mix-efficient throughout the study period, but input mix efficiency has been steadily decreasing over the study period and that reaches less than 40 per cent in 2013. In general, the development and promotion of technological symbols such as improved cows, artificial insemination, and embryo transfer, as well as increased production scale through the implementation of incentive policies and support of large manufacturing units can be considered to improve the productivity of production factors. Moreover, province level variations in scale and mix efficiency suggest that there exists a scope for improving productivity by taking a differential approach to the efficient use of agricultural resources and to increase scale and mix efficiency in production of the industrial dairy farms. Being able to identify the components of TFP change is critically important for public policy-making. Policies that can lead to these outcomes include reductions in the levels of output price support, removal of input subsidies, increases in tax rates and any other policies that cause deteriorations in the agricultural TT. These policies can have the effect on increasing productivity.

Dairy cows are very sensitive to heat stress caused by climate change, and this directly affects the efficiency and profitability of these farms. Despite the importance of this issue, economic studies that analyze the relationship between the efficiency of dairy farms and climate change are very limited. Therefore, the purpose of this study was to evaluate the effect of climate change on the cost productivity of dairy farms. The information of 16 main production provinces in 1990, 1993, 2000, 2007, 2013 and 2016 was used and the stochastic frontier cost function was estimated by considering THI index. The result indicates that the average cost efficiency of dairy farms is about 0.70 and its highest and lowest values are 0.78 and 0.50 for east Azerbaijan and Esfahan provinces respectively. Also, the changes in the THI index have a negative and significant effect on cost efficiencies in the studied provinces. Therefore, it is not necessary to consider genetic selection for raising milk production in the breeding policy, but also its adaptation to climate conditions.

In recent years, due to increasing attention to environmental problems, undesirable outputs incorporated in production functions with desirable outputs in researches; this is done by output distance function.
The objective of this research is estimating the shadow price of pollutants produced in dairy farms.
In this study, output distance function estimated for dairy farms in Sarab, which 51 samples were selected among all farms (109 farms) using random sampling; then shadow prices of pollutants (Nitrogen and Phosphorus) calculated.
Average shadow prices of Nitrogen and Phosphorus calculated 30 and -6.5 million of Rls per ton of Nitrogen and Phosphorus, respectively. Results show that it is possible to increase farmer’s revenue by disposing one ton of nitrogen. Negative shadow price for Phosphorus shows that disposing each ton of Phosphorus from production process is equivalent to ignorance of 6.5 million Rls of revenue.
It is suggesting that in order to maximize production and minimize pollution, achieve a desirable nutrition and balanced diet by observing technical and economic principles of optimal input combination and dietary nutrition.

Based on studies, there is a need to determination of blood parameters of dairy cows especially during the transitional period to assess the physiological status of cows and following that to assess nutritional status of them and in case of diet imbalance and possible deficiency in the farm, diet is balanced and reducing the quality and quantity of milk production can be prevented, also it may cause increase of reproductive efficiency. Therefore, the aim of this study was to evaluate the nutritional status of fresh cows through blood metabolites and providing suitable strategy to improve the nutrition of this group of dairy cattle.
seven dairy farms which are members Union of Agricultural Cooperatives livestock industry in Isfahan random from each of the 7 postpartum cows were selected and sampled. Sampling was conducted in July 2013. Samples for measurement of cholesterol, albumin, urea nitrogen, total protein, glucose, BHBA, NEFA, calcium and sodium blood were sent to the laboratory. Data was then analyzed based on randomized completely design. Duncan’s analysis used for comparison means of dairy farms, as well as, each of the metabolites through t test were compared with the normal range.
The results showed that the blood sugar level of dairy cows in some of dairy farms was lower than normal value(50 mg dL-1) in summer(P generally, it can be concluded that there was sodium deficiency during early lactation in the most of farms. The lower level of albumin, glucose, sodium and calcium in some of case than the normal levels can be key factors in increasing of open days in the most of dairy farms.

In the developed world، particularly in developing countries، livestock is the most important agricultural sub-sector. Livestock of primary and secondary industries has an especial place in the national economybecause of their greatvalue of products، creating job opportunities، providing health products for consumers، increasing export income of the economy throughaccessing global markets of livestock products and finally their undeniable role in acquiring food security. The demand for milk in Iran increased due to an increase in population and the amount of milk production was also increased. The great share of increased produced milk goes to the industrial dairy farms. One of the major methods to increase the amount of milk production continually is to make its production efficient and improve economic conditions. The current study attempts to determine the efficiency and ranking of industrial dairy farms in Saqqez and Divandarreh cities using super-efficiency model.

The statistical populations of the study are all active industrial dairy farms of Saqqez and Divandarreh cities which are about 19 farms. The required data for calculating the efficiency were gathered by surveying and completing questionnaires for the year 2013. In this study first، for each farm Data Envelopment Analysis (DEA) method and GAMS software package were used to estimate super efficiency. Super efficiency is a form of modified DEA model in which each farm can get an efficiency greater than one. Then in order to make sure about being unbiased the obtained super-efficiency scores، the modified model of Banker and Gifford، was re-estimated and the conventional efficiency scores of farms were compared by normalizing and removing some of the scores of outlier farm based on pre-selected screens. The model has suggested conditions for which some of the estimates for dairy farms might have been contaminated with error. As a t result، it has been ranked as an efficient farm.

The statistical description of the farms studied showed that، the highest and lowest amount of produced milk from one dairy were in the range of 845 and 250 kg per month. The super efficiency estimation showed that the mean of farms''super efficiency based on the assumption of variable return to scale for input-oriented is 1. 01. About 58 per cent of the studied dairy cattle farms were inefficient and the Super-efficiency of about 42 per cent of total farms got scores under the average. The amount of λ_k^* for all farms except for farms 3 and 5 has become 0. Furthermore، these two farms in primitive super efficiency model have become infeasible. Therefore، they have been considered as reference farms. The results of super-efficiency method and efficiency conventional DEA method were compared together and inefficient farms got the similar efficiency and super-efficiency scores، and efficient farms whose super-efficiency score had been equaled or more than 1، stand over frontier production function in the conventional model. To determine the sensitivity of results to removing the outliers، three different levels (1)

The aims of the present study was to evaluate the level of aflatoxin B1 (AFB1) in feedstuffs (corn silage, corn, dried alfalfa, cottonseed meal, cottonseed, soybean meal, canola meal, barley, wheat bran, concentrate, sugar beet pulp and wheat straw) that collected from dairy herds in Khorasan Razavi Province that classified according to milk yield in very high (>10000 Kg/day), high (5000-10000 Kg/day), intermediate (2000-5000 Kg/day) and low (<2000 Kg/day) milk production. Sampling was performed during cold (early December to late January) and warm (early June to late July) seasons. Feed samples were placed in sterile packages and were maintained until test at -18 °C. Aflatoxin B1 levels were measured using ELISA. Results showed significant differences between the amount of aflatoxin B1 in cottonseed meal, canola meal, wheat bran, sugar beet pulp and wheat straw among all dairy herd classes (P<0.05). The contents of aflatoxin B1 in all feedstuffs during the cold seasons were higher than those of warm seasons. Results also showed that aflatoxin B1 level in %21.87 of the total diet samples were higher than the maximum tolerance limit (50 ng/g).

Objective of this study was to estimate different kinds of efficiency in dairy farms of Fars province, using data envelopment analysis (DEA) approach.The data applied to study was obtained through completing 100 questioners among a randomly selected sample of dairy farms. The results showed that Scale and technical efficiency of the sample were 0.85 and 0.6 on average, respectively. Scale efficiency was obtained for 22 heads farms indicating a higher profitability as compared to other sizes of farm. As well as efficiency of scale is most dairy ascending.