جستجوی مقالات مرتبط با کلیدواژه « تحلیل پوششی داده ها » در نشریات گروه « علوم دام »

The agricultural sector is one of the most important sectors of the Iranian economy. Lack of some important inputs such as water and environmental pollution are the main problems of this sector in increasing production. Therefore, increasing production and sustainability is one of the important goals of the country in the agricultural sector. Increasing efficiency is one of the best ways to increase production, profitability and sustainability of production in enterprises. In this study, considering the role of dairy industrial units in milk production and food security, the efficiency and ranking of resilience and efficiency criteria of dairy industrial farms in Kerman have been calculated.

Efficiency was calculated using data envelopment analysis (DEA) method and collecting 30 questionnaires from dairy industrial farms in 2020. In order to rank the criteria of resilience and efficiency, a hierarchical analysis process (AHP) was used. For this purpose, 15 paired comparison questionnaires were completed using the opinion of experts.

The results of ranking the criteria showed that the economic criteria with a weight of 0.5 are the most important for experts. The criteria of resilience with a weight of 0.205, the environmental criteria with a weight of 0.148 and the social criteria with a weight of 0.147 have the second to fourth ranks, respectively. The maximum profit among the economic sub-criteria has the highest priority in the opinion of experts. Labor expenditure among the social sub-criteria is the most important in the opinion of experts. The amount of water consumption among the environmental sub-criteria has been ranked highest by experts. Productivity is the most important sub-criteria of resilience in the opinion of experts. According to the results, maximizing profit, minimizing the cost of livestock rations and productivity are among the 11 sub-criteria considered to be the highest priority for experts. The results of efficiency calculation showed that there are no units in the range of 0 to 20. Three units were in the range of 20 to 40, 9 units in the range of 40 to 60, five units in the range of 60 to 80 and 13 units in the range of 80 to 100.

Based on the obtained results, by increasing efficiency, milk production and profitability of industrial dairy farms in Kerman can be increased. For this purpose, efficient units can be used as a model for inefficient units and increase the efficiency of units by changing management and how to use resources.

In order to optimally use the inputs, the efficiency of economic units is of great importance. The purpose of this study is to investigate the technical efficiency and economic value of some traits of production, reproduction, survival and growth of Holstein cows in Pars agro-industry. For this purpose, required information including: manpower, cattle population, feed consumption and milk production quantities were collected from Pars Livestock Unit by documentary study, observation and face-to-face interview and their efficiency was calculated based on production and economic performance. The variables used in the research include herd size in terms of head, feed and concentrate in terms of weight, manpower in terms of men per day, health in terms of number of days per day, milk production and production of manure in terms of kilograms and incomes in Rials, which include Income from milk sales, Rial value of livestock manure produced, income from sales of voluntary and forced elimination of livestock, income from sales of bulls and heifers in dairy farms were examined. Deap 2.1 software was used for performance calculations. Optimal decision was calculated numerically by a iterative method using compecon toolbox in MATLAB program. Probability of pregnancy in the first, second, third and higher lactation periods based on data analysis and using logistic regression and GenMod procedure of SAS software Obtained, the results showed that the average of technical efficiency with constant efficiency compared to the scale was 0.83; the average efficiency with variable efficiency compared to the scale was 0.86 The scale efficiency of this company was estimated to be 0.96. The amount of technical efficiency in general was 0.83, allocation efficiency was 0.87 and economic efficiency was 0.72. This unit was efficient in March in terms of types of efficiency, which means that during this month, in addition to consuming a certain amount of product produced with a minimum of inputs, the minimum costs are also considered in the composition of inputs, so the unit in this month was technically, allocative, economically and economically efficient and has a constant return on scale. Also, the highest economic value in non-optimal conditions in survival, reproductive, productive and growth traits, and also for survival rate after weaning, first calving age, milk fat and body weight of adult animals was equal to 234297.30, -41835.16, 128664.12 and 454227.93 Rials, respectively. In optimal conditions, the highest economic value for survival, reproduction, production and growth traits was related to the set of traits of production lifespan, and the calving interval, milk fatproduction and daily weight gain before weaning were estimated at 4594.88,9084.67, 1582264.09 and -1464.87 Rials, respectively. The reason for the difference in economic values of traits in optimal conditions compared to non-optimal conditions is due to the application of optimal livestock replacement strategy, so that the farmer's policy in eliminating and replacing, affect herd profit.

One surefire way to increase income and profit is to pay attention to the viability of the dairy cow and increase the efficiency of each livestock unit. The purpose of this study was to determine the efficiency and effective factors on optimal herd life in dairy cows with dynamic data envelopment analysis and planning model in Ardabil city.

The data of this study were related to 1397 time series of dairy farms in Ardebil city which were analyzed by system analysis method, economic system of dairy herd and income and cost components, and each of these components was subdivided into other sections. Then, using mathematical models, we simulated a bioeconomic model and optimized it with the help of the Matlab software Compecon toolkit. The dairy cattle were described with state variables including lactation period, milk production capacity and different gestation states. In order to design data envelopment analysis model, several inputs and outputs in the production process were studied. The main variables used in the study included, herd size by apex, feed and concentrate in kg, manpower by day, health by Frequency of milk, milk production and livestock manure production per kg and total income were determined. And Deap 2.1 software based on minimizing the amount of input per unit of product was used for performance calculations.

Optimal herd life (from first calving to elimination) was 4.55 years under optimum conditions. The results also showed that the technical efficiency with constant return to scale is 0.719 and with variable return to scale equal to 0.899 and scale efficiency was calculated to be 0.888. The overall technical efficiency value was 0.99, allocative efficiency 0.583 and economic efficiency 0.579.

The effect of heifer price, milk price and discount rate on optimum lifespan showed that with increasing heifer price, milk price decrease and discount rate increase elimination percentage decreased and optimum lifespan increased. The results of data envelopment analysis showed that in terms of variability of efficiency relative to scale, increase in herd size and health costs and decrease in forage, concentrate and labor costs, respectively, 14.18, 0.83 , 2.8% and 5% result in inefficient herds being maintained by maintaining levels. Therefore, in order to make an inefficient unit effective, changes must be made to the inputs and outputs of that unit. By specifying the differences between the inefficient and inefficient units, appropriate strategies are designed to eliminate the gap between them.

The purpose of this study was to investigate the technical efficiency of male calf fattening units in Guilan province and to determine the yield to their scale using the data envelopment analysis method. The cost and income information required was collected by completing the questionnaire using 52 units of fattening in Guilan province. The results showed that the average technical efficiency was 0.961 and 0.494 using the variable and constant returns approach to scale, respectively, which showed the efficiency of the production of fattening units. In order to evaluate the factors influencing the technical performance of the fattening units, two components of the equipment and facilities of fattening units and knowledge of fattening knowledge were used. Using the interval of standard deviation from mean (ISDM) method, scores for these two components were categorized into four groups. Then, using ANOVA and paired comparison of the groups determined by the ISDM method with the help of Tukey test, the impact of facilities and equipment privileges and fattening knowledge was studied on the technical efficiency score of fattening units. The results showed that the couples of the four groups of facilities and equipments and fattening knowledge were significantly influenced by the technical efficiency of the units.

Efficiency is a concept that determines the input and output ratios of an economic system. Data Envelopment Analysis (DEA) method is a useful tool for estimating the efficiency of a unit. The purpose of this study was estimation of economic efficiency and determining of return to scale of broiler production units in Gilan province. Therefore, the information includes the day old chick price, the cost of manpower, the cost of feed, the cost of health and treatment, the cost of fuel (gas, gasoline and electricity) of thirty commercial broiler production units in Gilan province collected and the efficiency was measured based on production and economical function. Then, the technical and allocative efficiency was estimated to calculate the economic efficiency. Based on these results, based on costs minimization, the average of technical, allocative and economic efficiency in constant returns to scale condition was 96.7, 91.8 and 88.7 percent, respectively and in variable returns to scale condition was 97.5, 94.0 and 91.6 percent, respectively. Also, the average of scale efficiency was 99.2 percent. According to results of DEA method, it is recommended the farms with capacities of 5000 to 30000 chicken, the 25 days interval among production cycles, and the proposed models should be used to increase the efficiency of commercial broiler production units in Gilan.

Performance enhancement is one of the ways to manage profitability and improve competitiveness in manufacturing units. Regarding the position of milk production under the livestock sector, despite the dispersion and difficulty of collecting the required data, in this study, data envelopment analysis was used to identify the solutions for optimal management in livestock units of Mianeh county. Data were collected through a questionnaire in a census sampling of 40 units. The results showed that from 40 units studied only nine units had less than one efficiency score and there was a possibility to provide a solution for improvement in performance according to available information for them. Of course the average efficiency of the units studied was equal to 0.945, which indicates functionally suitable for the production of milk in the studied area. According to the research findings, consumption of electricity, medicine, forage, and straw requires more attention, as well as the unit 31 was found to be the superior unit in terms of effectiveness and repetition among the units studied.

As the resources are limited, improving efficiency of sheep farming is of high importance in Iran. In the present study, the technical efficiency of Moghani sheep flocks was investigated using the method of data envelopment analysis, considering constant (CRS) or variable (VRS) returns to scale. Data of year 2015 on inputs for the amount of concentrate, forage and labor as well as outputs including the amount of meat, milk, wool and fertilizer were collected from 214 Moghani sheep flocks through interviews and questionnaires. Data analysis was performed using Deap 2.1 software. The average technical efficiencies with CRS and VRS were 0.978 and 0.977, respectively, showing high efficiency in studied flocks. With CRS and VRS, there were 14 and 25 flocks being technically efficient, respectively, and could be introduced as reference flocks to inefficient ones. The results showed that with VRS, some reduction in flock size, labor, forage, concentrate, rangelands roughages and health costs as 2.99, 2.99, 2.63, 2.79, 2.73 and 6.41 percent, respectively, would let inefficient flocks to become efficient, while maintaining the same level of previous production. The estimates of return to scale showed that most of Moghani sheep flocks had an increasing return to scale, and are able to benefit from scale-based savings and lowered cost per output unit.

As population grows and consequently the increase of application and the elevation of people`s lives, energy use has increased in poultry production industry. Regarding the importance of energy as an effective input in poultry, this research is done for efficiency analysis and index management of Broiler production in Maku Free Zone. The required data are gathered by the questionnaire and interview in 21 units of poultry during November,December and January 2015 in incubation period. Energy efficiency is calculated using Data Envelopment Analysis by constant and variable return to scale model relating to scale for 5 energy inputs including chicks, seeds,fuel, electricity, labor and 2 outputs like chicken and manure. According to the constant return to scale model it is observed that considering 21 units of poultry, 13 poultries (61.9%) had efficiency scores and 8 poultries (38.1%) had non-efficiency scores. Also according to constant return to scale model, 15 units (7.42) were efficient and 6 units (28.57%) were non-efficient. In addition the highest and the lowest fuel consumption were for gasoline (66.2%) and labors (0.07%). Poultries were the most non-efficient in fuel consumption and were the least non-efficient in chick consumption. The non-efficient use of gasoline is because of the simultaneity of incubation time and cold season, incorrect use management especially in halls and consuming gasoline as a fuel for labors` houses.

Efficiency is defined as a concept that determines the input output ratios in an economic system. Data Envelopment Analysis method is a useful tool to estimate the efficiency of a unit. The purpose of this study was to estimate technical efficiency and to determine Return to Scale of Holstein cattle farms in Guilan Province. Therefore, the information including the number of labor and dairy cows as well as the level of feed and milk production related to twenty Holstein cattle farms in Guilan province were collected in 2011 and their efficiencies estimated as based on production and economical performances. Among all the studied units, four were around 100 percent efficient while the remaining ones suffered from various degrees of inefficacy. The average technical efficiency was estimated to be 0.726, suggesting that each production input, including the number of labor, the amount of forage and concentrate, could be reduced on average by about 27.4 percent without any reduction resulting in the current level of production. Technical efficiency difference between the most efficient unit and the least one was 65.4 percent. Seventy percent of the Holstein cattle farms studied benefited from increasing returns to scale, 20 percent had constant returns to scale and 10 percent decreasing returns while. Therefore, in 70 percent of these units, given their input management as efficient, development of activity dimensions in terms of the number of labor and feed consumption could lead to even more production through an increasing return to scale.