Browsing by Subject "Dairy farm"

Now showing 1 - 3 of 3

An expert system for planning and designing dairy farms in hot climates
(2008) Samer Mohamed, Mohamed; Jungbluth, Thomas
Planning and designing dairy farm facilities is a sophisticated work where a multitude of procedures should be carried out which requires time and efforts; moreover, making mistakes is also possible. Therefore, it is necessary to develop computer tools that have the ability to pre-process the data so as to produce value-added information, in order to accelerate analyses and to improve decision-making. Eleven simulation models were developed to plan and design several dairy farm facilities. Subsequently, an electronic spark map (decision tree) was developed for each simulation model, and then the simulation models were integrated into the relevant spark maps. Afterwards, C# language (C Sharp), which is an object-oriented programming language, was used to develop an expert system via the simulation models and the electronic spark maps. The developed expert system is able to plan and design several dairy farm facilities, e.g. housing system (corrals system), shade structure and roof material, concrete base, cooling system, milking parlor, forage storage, and manure handling system. Subsequently, it plans the farmstead layout, and it leads to implement the technologies, equipments, and machines required for performing several farm operations. Furthermore, it studies water and electricity requirements of the planned dairy farm and the available sources on site. Moreover, it calculates the capital investment and the fixed, variable, and total costs. Data of 6 dairy farms were used to carry out the expert system validation and evaluation. The differences between the actual and calculated values were determined and the standard deviations were calculated. The coefficients of variation range between 3% and 7%. The required input data are 358 thereof a multitude will be recommended by the expert system itself; consequently, it computes and displays 372 output data with the ability of saving and retrieving data. Besides, the system?s accuracy had been calculated using the actual and calculated values of the different outputs and it was found 98.6%. However, the system?s syntax includes 22106 lines. It can be concluded that the developed expert system can be used successfully for planning and designing dairy cow farms in hot climates.
Gesamtbetriebliche Analyse von Weidebetrieben und Weidesystemen in der Milchviehhaltung in unterschiedlichen Regionen Süddeutschlands
(2014) Kiefer, Lukas Robert; Bahrs, Enno
Grassland use and particularly pasture milk production is considered a highly sustainable milk production method which renders many ecosystem services for society (such as greater biodiversity, maintenance of rural cultural regions, climate protection due to higher carbon storage capacity of grassland, better animal appropriateness by regular grazing) as opposed to permanent indoor housing with its high portion of concentrate feed. Nevertheless, the share of pasture farming in overall milk production falls behind production by increasing permanent indoor housing in Germany. Therefore, it appears appropriate to analyze the necessary business environment for pasture farming with consideration of selected ecosystem services actually provided and to sketch suitable recommendations for consultation of farmers. Against this background, the research project “Business analysis and optimization of pasture-based farms and pasture systems in dairy farming in different regions of South Germany” was designed. The research project evaluated production technology, labor economics, business success, greenhouse gas emissions and specific ecosystem services of more than 80 specialized pasture milk producers through three economic years (2008/09-2010/11) and was dedicated to analysing economic and ecological competitiveness of pasture milk production at specific locations. As a result the most profitable pasture farms of the sample regarding management income and hourly rate can compete with the most profitable farms that practice permanent indoor housing; thus, they demonstrate potential economic strength of pasture farms at suitable locations. Decisive determinants of economically successful pasture management include organic farming (higher milk prices and financial compensation), high amounts of milk from forage, sufficient milk yield of the individual cow (>6,000 kg), and a great portion of pasture grass in the feed as well as high work efficiency via seasonal calving, all-day grazing and short-lawn pasture. High profitability and low greenhouse gas emissions can be achieved simultaneously through high efficiency of production. Some farms can even make “greenhouse gas avoidance gains” when production costs and proportionate emissions decrease at the same time thanks to reduced feed demand per kg milk. There is still a substantial need for research in the field of greenhouse gas balancing, particularly regarding evaluation of the manifold ecosystem services of pasture milk production. Many pasture-based farms are compensated for the above-mentioned services via the 2nd pillar of Common Agricultural Policy, but such services remain unconsidered in greenhouse gas balancing so far. It is for this reason that pasture-based farms with low productivity as well as organic farms perform poorly compared to more intensive farming with high productivity if they are measured by the established formulas of greenhouse gas balancing. Consideration of ecosystem services in the framework of greenhouse gas balancing would be possible via economic allocation of emissions between milk, meat, and subsidies of the 2nd pillar of Common Agricultural Policy, however. Based on our sample, this approach would result in an approximation of the carbon footprints per kg milk produced by extensive and intensive or organic and conventional farms, respectively. Nevertheless, a fundamental antagonism still persists between high production efficiency, which is desirable from the point of view of climate protection on the one hand and ecosystem services attainable by extensive production on the other hand. Like other milk production systems, profitable pasture milk production associated with lowest possible greenhouse gas emissions requires first of all competent training and consultation of farmers, which meets the requirements of the respective production method. Policy could improve the relevant framework conditions. Successful pasture milk producers are margin optimizers whose economic success depends above all on higher producer prices (organic milk, pasture milk), cost minimizing milk production based on pasture as the cheapest feed for many farms as well as funding of the ecosystem services which are desired by society. Farm growth and increases in milk yield are harder to achieve for pasture milk producers because consolidated areas are missing or more concentrate feed would be necessary. According to the results of the investigated sample, stronger support of the unique image of pasture milk (which does not necessarily mean monetary funding in this context) as well as increased know-how in the field of pasture milk production is desirable in order to establish or develop the numerous very positive approaches of pasture use in grassland regions that were analyzed in our investigation. The latest EU agrarian reform as well as new EAFRD regulations offer some good starting points in this regard.
Success factors of farm investments : the example of Swiss dairy farms
(2021) Kramer, Benedikt; Doluschitz, Reiner
This scientific analysis aims to identify success factors of farm investments, which are supported by interest free loans. The data basis consists of data from the Farm Accountancy Data Network (FADN) from 2003 through 2014 from Switzerland, which is matched to data from the Meliorations- und Agrarkredit-Projekt-Informations-System (MAPIS), where all supported dairy barn investments in Switzerland are registered. In addition, a Gini coefficient on the level of municipality is added, calculated from agricultural census data (AGIS). One of the main variables analysed is calculated profit. Another important variable, analysed in this work, is herd size. As a first step, the development of calculated profit and herd size change after investment are analysed by two separate fixed-effects panel regression models. The results show, that calculated profit is significantly and positively influenced by the amount of agricultural land of the farm and significantly reduced for the first three years after investment. From the fourth year onwards, no coefficients are significant anymore, which might either be caused by a divergent development of individual farms or by the diminishing number of observations. Herd size change is positive and significantly influenced by the amount of agricultural land. Also the period of quota phasing out affected herd size change positively. Dairy herds probably grew in the year before investment already and kept growing till five years after investment. Both dependent variables indicate that farms undergo an adjustment phase after investment. For the analysis of investment probability, the data sample is extended by including observations of all dairy farms and combined dairy/arable crop farms in the valley and hill region. Observations after investment are excluded. A logit regression model of the pooled data reveals that among the financial variables, only equity and farm income have a small positive and significant effect on investment probability. Social characteristics show a larger effect. The investment probability increases with age, farm household size and the presence of a partner. In order to analyse influencing factors of successful investments, investments that enable the farm to achieve the same or higher calculated profit as before, are considered successful. The year before investment is used as the basis and a Cox Proportional-Hazard-model is used to investigate those influencing factors. The model reveals that for farm having a higher calculated profit before investment, it is more difficult to restore that level after investment. Off-farm income and expenses for purchase of additional animals affect recovery of calculated profit significantly negative. The largest significant negative impact comes with more family labour. The results suggest that family labour which is likely to be freed up by productivity gains, is not reallocated to off-farm income. Additional indicators for land competition on the level of municipality are used. Agricultural income per family working unit is analysed as financial measure. This is a precursor for calculated profit and reflects financial efficiency of the input of family labor. In addition, growth of the dairy herd is analyzed. A random effects model is used for both variables. For dairy herd growth, utilized agricultural area and milk quota abolishment have a positive effect. More subsidized projects within a municipality and a higher concentration of acreage have a negative effect. For agricultural income per family working unit, utilised agricultural area, number of subsidized projects within a municipality, valley region and equity have a positive effect while milk quota abolishment has a negative effect. Off-farm income, which has been used as off-farm income per full-time working unit, showed no statistically significant effect. Neighboring effects appear to be more important for dairy herd growth than for agricultural income. Based on the derived definitions, success factors are identified. An adjustment phase is confirmed, while the productivity of family labour seems to be the most important influencing factor for recovering calculated profits of the pre-investment situation. Structural influences seem most important for herd size growth. With regard to the negative effect of off-farm labour, off-farm labour might be seen as enabling farms with off-farm labour to accept a lower level of labour productivity. In general, the social characteristics of farms seem to have a larger impact on dairy farm investments than financial variables. For investment support, the results imply not only to put emphasis on financial characteristics. In addition, the adjustment phase must be considered with investment plans. With such long lasting investments like dairy barns, strategic decisions by the farmer combined with family characteristics might be more important than financial indicators.