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When analysing drivers affecting the farm performance, the presence of different technologies should be taken into account. We assume that the technology used by crop farms is not the same for all producers and therefore we use latent class model to identify technological classes at first. Class definition is based on multidimensional classification and determination of indices given by the values of individual components. The principal components analysis is applied to estimate significant and robust weights for the index components. FADN (Farm Accountancy Data Network) database, Czech crop farms data from 2005 to 2017 were used and three groups of technology classes of farms were identified with a determinant influence of the structure index and localisation. The other indices characterise sustainability, innovation, technology, diversification, and individual characteristics. Three distinct classes of crop farms were found, one major class and two minor classes. Family driven farms are usually smaller farms in terms of acreage. Highly sustainable crop farms are most likely located in lower altitudes and not in less-favoured areas. Innovative farms are also likely to be more productive. The results indicate that agricultural production farms with a more sustainable way of farming are most likely to be more productive.
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Napton, Darrell. "Farms of tomorrow: Community supported farms, farm supported communities." Journal of Rural Studies 9, no. 1 (January 1993): 103–4. http://dx.doi.org/10.1016/0743-0167(93)90015-c.
Tatarinova, M. N., M. V. Feskova, and A. S. Khusainova. "Reporting of peasant (farm) farms." Buhuchet v sel'skom hozjajstve (Accounting in Agriculture), no. 11 (November 1, 2021): 33–44. http://dx.doi.org/10.33920/sel-11-2111-03.
Intensive development of small businesses in rural areas is one of the priority directions of state policy in the field of sustainable development of the agrarian economy and rural areas. At the same time, the level of professional legal awareness and entrepreneurial thinking among farmers largely determines the effectiveness of small agricultural formations. This level depends on many factors, including the availability of knowledge of taxation issues, the ability to competently maintain accounting records, observing the requirement of rationality, the ability to navigate the regulations governing this organizational form of doing business. The article discusses the procedure for the formation and features of the presentation of reporting forms of activity of peasant (farmer) farms taking into account various factors of activity, since it is this area that underlies the construction of the entire system of accounting and analytical work.
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Ziętara, Wojciech. "PARITY INCOME AND DEVELOPMENT POSSIBILITIES OF FARMS IN POLAND." Annals of the Polish Association of Agricultural and Agribusiness Economists XXII, no. 2 (June 24, 2020): 237–45. http://dx.doi.org/10.5604/01.3001.0014.2478.
The article presents the importance of farm income, taking the farm’s ability to develop into account. It has been demonstrated that achieving farm income at a parity level is insufficient to determine the farm’s ability to develop. These requirements are also not met by labour income. What informs about a farm’s development ability is the ratio of farm income to conventional costs of own production factors: labour, land and capital in the form of the competitiveness index (Wk). Its value from 1 to 1.9 points to a competitive capacity and when it reaches 2 and more, it points to full competitiveness. Based on the data from farms covered by FADN monitoring in 2017, it was found that the farm area specialising in field crops and the cultivation of cereals, oilseeds and protein crops for seeds and being able to compete (to develop) was about 40 ha of utilised agricultural area (UAA), while in the case of fully competitive farms it was 106 ha. The size of farms specialising in vegetable and permanent (fruit-growing) crops and able to compete was 7 and 13 ha of UAA, respectively. The size of dairy farms able to compete was about 25 ha of UAA and 21 cows, while the size of fully competitive farms – 75 ha and 54 cows. The size of pig farms able to compete was about 25 ha of UAA and 26 sows, while the size of fully competitive farms – 40 ha of UAA and 37 sows. The size of “mixed” farms able to compete was 39 ha of UAA and, on average, 4 cows and 7 sows, while the size of fully competitive farms – 79 ha of UAA, 8 cows and 11 sows.
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Bastanchury-López, María Teresa, Carmen De-Pablos-Heredero, Jose Luis Montes-Botella, Santiago Martín-Romo-Romero, and Antón García. "Impact of Dynamic Capabilities on Performance in Dairy Sheep Farms in Spain." Sustainability 12, no. 8 (April 21, 2020): 3368. http://dx.doi.org/10.3390/su12083368.
This study links the dynamic capabilities (DCs) theory with performance in dairy sheep farms in Castilla La Mancha (central Spain). The approach is novel as it seeks to understand how best results can be achieved by deploying DCs in farms. The proposal is that dynamic capabilities are interrelated to each other and present a positive impact on the farm’s economic sustainability. A mixed methods approach (a combination of qualitative and quantitative methods of research) was utilized. First, 30 indicators of dynamic capabilities (8 of absorption, 11 of integration, 9 of innovation, and 2 of profits) were selected by applying Delphi’s methodology. Second, a structural equation model (SEM) was applied over a random sample of 157 dairy sheep farms to measure the relationship between DCs and the impact of each capability on farms’ final performance. The existence of positive relationships amongst absorption, integration, and innovation capabilities was evidenced. Absorption and integration capabilities exhibited positive influences on a farm’s final performance. The knowledge of the relationships amongst dynamic capabilities is a new orientation to increase farms’ viability. These findings reveal that the application of the dynamic capabilities theory can explain best farms’ economic sustainability.
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Ahiakwo, A. A., and C. B. Isirima. "FARM MACHINERY UTILIZATION AND MAINTENANCE EFFECTS ON SUSTAINABLE DEVELOPMENT OF COLLEGE FARMS." Engineering and Technology Journal 08, no. 01 (January 3, 2023): 1795–801. http://dx.doi.org/10.47191/etj/v8i1.02.
In order to expose students in tertiary institution learning agricultural science to the concept of farm mechanization, which could aid self-reliance after graduation, the federal government of Nigeria has provided farm machinery to make teaching and learning effective in this regard. The focus of this study therefore is to assess farm machinery deployment, management and maintenance effect on mechanization for sustainable development of college farms in Nigerian. The study population comprised all federal and state colleges covered by tertiary institution trust fund (tetfund). Sample of 24 colleges offering agricultural education was randomly drawn for the study. A structured questionnaire was used for data collection. Data obtained was statistically analysed using mean from a 4 point likert rating scale. Results obtained revealed that out of the 252 farm machinery available in the sampled colleges, 25 percent are tractor, 20 percent each are plough and harrow while 18percent are ridger and planter/fertilizer distributor respectively. The mean response of 2.4, 2.2 and 2.3 in disagreement to the research questions shows that there is need to improve in farm machinery utilization and maintenance as well as for teaching and learning in the colleges.
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Kowalczyk, Zbigniew, and Katarzyna Grotkiewicz. "Wear of Farm Buildings in Selected Farms." Agricultural Engineering 20, no. 2 (July 1, 2016): 109–16. http://dx.doi.org/10.1515/agriceng-2016-0032.
AbstractThe objective of the article was to compare the level and structure of wear and tear of various types of the most popular agricultural buildings in the selected agricultural farms. A comparative analysis of physical and functional wear as well as investment expenditures of the selected objects in 2010-2014 was carried out. The scope of the article covered agricultural buildings with which 90 farms in the southern Poland are equipped. These farms were varied on account of the surface area and the production nature. The detailed analysis covered: cowsheds, piggeries, garages, fruit and vegetable storages, greenhouses and barns. The average age of the majority of farm buildings as well as a considerable degree of physical wear in comparison to a lower functional wear was determined.
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ŞANDA, Mehmet Nuri. "INSPECTİON OF ATATÜRK FARMS IN TARSUS AND SİLİFKE." IEDSR Association 6, no. 11 (February 24, 2021): 206–19. http://dx.doi.org/10.46872/pj.237.
The subject of this study consisting of three section was the Piloğlu Farm in Tarsus and Şövalye and Tekir Atatürk Famrs in Silifke in Mersin city in 20. century. The first section of this study provided general information about the formation of Atatürk farms. The second section explained the formation of Piloğlu Farm in Tarsus and Şövalye and Tekir Atatürk Farms in Silifke and transferring the Orman Farm in Ankara, Piloğlu Farm in Tarsus, Karabasamak Farm and Orange Garden in Dörtyol, Şövale and Tekir farms in Silifke and Baltacı and Millet farms in Yalova to treasure in 1937 under the will of Mustafa Kemal. The third section explained the transfer of farms in Tarsus and Silifke to State Agricultural Business Institution in 1938 and the audit conducted by this institution to Piloğlu and Tekir farms in 1945-1946. During this audit, inspectors prepared reports related to the cropped area in the farm, agricultural tools, transportation vehicles, forestation work and the states of the buildings and field. These report included problems in the farms and recommendations to solve these problems.
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Aydoğan, Mehmet, Osman Uysal, Serhan Candemir, Yunus Emre Terzi, Rahmi Taşçı, Tuba Beşen, Fatma Pınar Öztürk, et al. "Türkiye’de Alabalık Yetiştiriciliği Yapan İşletmelerin Ekonomik Performanslarının Analizi." Turkish Journal of Agriculture - Food Science and Technology 8, no. 9 (September 26, 2020): 1952–64. http://dx.doi.org/10.24925/turjaf.v8i9.1952-1964.3587.
The purpose of this research is to measure the economic performance and development of rainbow trout farming in inland waters in Turkey. As a result of the research, it was determined that the farms use an average of 82% of their capacities. There was a negative relationship between the farm-scale and CUR, and as the farm scale grows, the CUR decreases. The average feed conversion rate (FCR) of the enterprises was calculated as 1.12. Fish capital (36.8%) had the largest share in active capital, and equity capital (87.2%) had the largest share in passive capital. Net profits of farms falling to one-tonne production capacity; it was calculated as 2.374 TRY in small-scale farms, 1.322 TRY in medium-scale farms and 1.896 TRY in large-scale farms. The proportional profit of farms was 1.08, 0.99, and 1.17, respectively. The average current ratio value of the examined farms was calculated as 3.67 and liquidity ratios as 3.55. As the farm's scale grows, current ratio values also increase, and large-scale farms had more cash assets than small and medium-scale farms. As a result of the research; It can be said that the trout-breeding farms in Turkey have current assets that can pay their short term debts. The average borrowing rate of farms was 0.16. In other words, 16% of the financial assets of the trout farms in Turkey were met from debts. The turnover rate of the assets of the farms was 0.79 and is below the sector average. The average rate of economic profitability of farms was calculated as 0.13. In other words, the income that farms generate from aquaculture is more than the opportunity cost.
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Müller-Rompa, S. E. K., I. Markevych, A. J. Hose, G. Loss, I. M. Wouters, J. Genuneit, C. Braun-Fahrländer, et al. "An approach to the asthma-protective farm effect by geocoding: Good farms and better farms." Pediatric Allergy and Immunology 29, no. 3 (February 7, 2018): 275–82. http://dx.doi.org/10.1111/pai.12861.
This study examines farm financial performance of Kentucky farms using Kentucky Farm Business Management data from 1998-2010. Logit models are used to estimate the likelihood of farm characteristics affecting whether financial ratios fall into critical zones or not. The results show that large farms in terms of total gross returns and total assets are less likely to experience repayment capacity problems. Total gross returns significantly affect all five financial measures. These findings will help farmers and lenders understand what factors influence farm financial performance. Profitability migration is tested to see if the migration probabilities differ across business cycles. Migration drift is also tested to determine if the Markov property of independence is violated. Results show substantial retention in return on equity (ROE) performance over time, and a tendency for trend-reversal if ROE changes occur. Results are compared to previous literature using ARMS data and Illinois FBFM.
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Xu, Qing Yun. "The competitiveness of Ontario dairy farms : a farm level analysis." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=116061.
The Canadian supply managed dairy sector is likely to face more competitive pressure from challenges through the World Trade Organization (WTO) and the changing global trade environment. Therefore, it is highly prudent for Canadian dairy producers to focus their concern on their level of competitiveness and how to improve it. This study investigated the competitiveness of Ontario dairy sector based on a sample of farm level data with a Box-Cox transformed econometric cost model. The data were gathered by the Ontario Dairy Farm Accounting Project, for the years 2005, 2006, and 2007. The impacts of output, yield per cow and several farm-specific characteristics on the average cost of milk production were examined. Results support the presence of significant size economies and yield economies within Ontario milk production. Minimum costs were achieved for farms with approximately 125 cows. The results also indicated that some farm-specific characteristics, breed and region, also had significant impacts on the cost of Ontario milk production. However, it appears that Ontario farms may find it difficult to survive if they are forced to face international competition. Even at their minimum, average costs were above an indicator international dairy price.
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BELLINGERI, ANDREA. "WHOLE FARM DECISION MAKING AND TOOLS FOR DAIRY FARMS PROFITABILITY." Doctoral thesis, Università Cattolica del Sacro Cuore, 2020. http://hdl.handle.net/10280/72496.
Nel tentativo di rispondere alle richieste della società per lo sviluppo sostenibile, i sistemi agricoli di tutto il mondo devono affrontare sfide ambientali, tecniche ed economiche. I raccolti irregolari, i prezzi fluttuanti delle materie prime e l'impatto delle attività agricole sull'ambiente sono preoccupazioni crescenti. Le tendenze demografiche effettive e i maggiori costi energetici potrebbero complicare ulteriormente lo scenario nel prossimo futuro. La ricerca sta affrontando queste sfide lavorando su sistemi di allevamento e zootecnia più sostenibili e rispettosi dell'ambiente in grado di fornire sia alti livelli di produttività che sostenibilità economica per gli agricoltori. Per ottenere un effetto, le innovazioni derivate dalla ricerca devono essere implementate a livello di azienda agricola. Tuttavia, a causa delle relazioni tra i vari elementi del bestiame nel sistema di produzione lattiero-casearia, la diversità delle aziende agricole anche in una piccola area rende complessa la piena attuazione di tali raccomandazioni. Abbiamo scoperto che pochissimi studi tentano di affrontare i tre componenti principali dei sistemi di produzione di caseifici (bestiame, terreni coltivati, mercato e materie prime) all'interno di un unico quadro di ricerca. Abbiamo quindi sviluppato un quadro collegando le caratteristiche e le esigenze del bestiame, le caratteristiche dei terreni coltivati e le opportunità di mercato per sostenere il piano di coltivazione e la gestione nutrizionale a livello aziendale al fine di massimizzare i profitti e ridurre i costi di produzione del latte.
Abbiamo scoperto che il costo reale di produzione in loco dei principali foraggi coltivati presenta un'elevata variabilità tra le aziende agricole e che una strategia decisionale dedicata al piano colturale è un modo adatto per migliorare le IOFC (reddito sul costo dell'alimentazione) a livello di azienda agricola. In trying to respond to the society demands for sustainable development, environmental, technical and economic challenges are faced by farming systems worldwide. Irregular crop yields, fluctuating commodities prices, and the impact of agricultural activities on the environment are growing concerns. Actual demographic trends and higher energy costs are likely to further complicate the scenario in the near future. Research is facing these challenges by working on more sustainable and environmental friendly cropping and livestock systems able to provide both high productivity levels and economical sustainability for farmers. To obtain an effect, innovations derived from the research, has to implemented at the farm level. However, due to the relationships between the various elements of the cropping-livestock in the dairy production system, the farms diversity even in a small area, make the fully implementation of such recommendations complex. We found that very few studies attempt to address the three main components of the dairy farm production systems (livestock, crop land, market and commodities) within a single research framework. We therefore developed a framework by connecting livestock characteristics and requirement, crop land characteristics and market opportunities to support cropping plan and nutritional management at the farm level in order to maximize profit and reducing milk costs of production.
We found that home-grown real cost of production of the main forages cultivated has a high variability among farms and that a dedicated crop plan decision making strategy is a suitable way to improve IOFC (Income Over Feed Cost) at the farm level.
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Mai, Chi Le Phuong Hartarska Valentina M. "Farm investment and off-farm income h [electronic resource] : a study of farms in Alabama /." Auburn, Ala., 2006. http://repo.lib.auburn.edu/Send%206-15-07/MAI_CHI_44.pdf.
Vaddella, Venkata Kumar. "Ammonia emissions management and modeling from storages of dairy manure." Pullman, Wash. : Washington State University, 2010. http://www.dissertations.wsu.edu/Dissertations/Spring2010/V_Vaddella_1030810.pdf.
Heenan, Deirdre Anne. "The role and contribution of farm wives on farms in Northern Ireland." Thesis, University of Ulster, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242144.
Bannon, Brian. "Engaging existing conditions with new conditions a farm equipment museum amidst an abandoned dairy farm /." This title; PDF viewer required Home page for entire collection, 2008. http://archives.udmercy.edu:8080/dspace/handle/10429/9.
Chaplin, Hannah Elizabeth. "Non-agricultural diversification of corporate farms and and farm households in Central Europe." Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.416117.
Holland, Cody. "Labor standards and efficiency estimation of farms in the Kansas Farm Management Association." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/13607.
Master of Science Department of Agricultural Economics Michael Langemeier The objectives of this thesis are to examine the labor requirements of Kansas crop and livestock enterprises and farms and the connection between labor efficiency and productivity, and other important farm characteristics including farm size and type. The derived labor requirements are compared to current KFMA labor requirements.
Enterprise summary reports and a five year whole-farm panel data set from 1,016 Kansas Farm Management Association (KFMA) farms are used in the analysis. Whole-farm labor requirements are computed with and without an adjustment for managerial and overhead cost. Individual regressions will be estimated to determine the effects that farm size, type, region and profit margin have on labor requirements.
The estimation results suggest that many of the current labor requirements still in use are accurate. However, there are enterprises with labor requirements that need updating. When the newly estimated requirements are compared to the previous KFMA requirements, 14 enterprises have lower labor requirements. Irrigated alfalfa showed the greatest decrease in labor required when compared to the previous standard, decreasing from 3.85 hrs/acre to 1.70 hrs/acre. Regression estimation results indicated that whole farm labor standards that were corrected for un-allocated overhead and managerial costs appear to be a more accurate representation of farm labor requirements.
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O'Leary, Niall. "Farmer attributes associated with farm profitability : a study of dairy farms in Great Britain." Thesis, University of Reading, 2017. http://centaur.reading.ac.uk/75745/.
How farmer attributes influence farm businesses performance and profitability is poorly understood. This thesis sets out to ascertain the farmer attributes that are associated with farm performance and profitability. For the first time from a farm management perspective, the management and job performance literature is reviewed comprehensively. A broad exploratory study focusing on farmer attitudes is reported along with a focused study on farmer personality attributes. Participants in both studies were dairy farmers in Great Britain. Linear models are presented in both studies. Just six and three variables were included in each model in the respective attitudes and personality studies. Models in both studies predict more than 40% of the variation in profitability. Cumulatively, more than half the profitability variation can be predicted by the GCA, Detail Conscientious competence, Leadership competence, temperament, attitudes and beliefs of farmers. These findings underline the major significance farm manager attributes are likely to have in driving farm profitability. The qualification ‘likely’ is used as causality has yet to be clearly established in agriculture (unlike in other sectors). The findings reported here relating to dairy farms are consistent with findings in other sectors. They thus appear to be broadly applicable and so likely to be of similar relevance to farms in sectors other than dairy. The effect sizes and the proportion of variation explained are large and may be surprising but are also similar to those found in other sectors. Strategic development and management of the highlighted farmer attributes is advised to facilitate potentially large improvements in farm profitability and financial viability. For farm management research, these may be pivotal findings offering several promising avenues for future research.
Taliaferro, Charles, and Stephen Carpenter. "Farms." In Life Science Ethics, 145–73. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8792-8_7.
Diao, Xinshen, Thomas Reardon, Adam Kennedy, Ruth S. DeFries, Jawoo Koo, Bart Minten, Hiroyuki Takeshima, and Philip Thornton. "The Future of Small Farms: Innovations for Inclusive Transformation." In Science and Innovations for Food Systems Transformation, 191–205. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-15703-5_10.
AbstractThe number of people living in rural areas of low and middle-income countries is projected to increase in the coming decades. It is in the rural areas of these countries where a large majority of the world’s extreme poor reside. The livelihoods of two to three billion rural people depend on small farms. These small farms are responsible for the production and supply of a large portion of the calories feeding low- and middle-income countries. Small farms are also preservers of crops and associated biodiversity and with the right incentives can contribute to land stewardship. Small farms are diverse, and, hence, so are their associated challenges. We categorize small farms as commercial farms, small farms in transition and subsistence-oriented farms and highlight evidence-based innovations for the sustainable transformation of each type of small farm. Broadly, small farms face high transaction costs, lack collective action, and experience coordination failure in production and marketing. Lack of market access is also a major challenge. Investments in infrastructure, including those that support access to digital technologies, can improve farmers’ access to markets and incentives as well as foster growth in the midstream segments of the value chain that provide inputs, storage, processing, and logistics to small farms. Rural Non-Farm Employment (RNFE) is increasingly the main source of income for most small farmers and provides them with a risk diversification strategy and cash, both to purchase food and for farm investments to raise productivity, expand commercial activities, and produce higher-value products. Public investments and policies that facilitate growth of the agrifood system must pay more attention to creating enabling environments for the development of RNFE and strengthening the synergy between agriculture and RNFE in rural areas.
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Pal, Imana. "Fighting malnutrition and reaching Sustainable Development Goals through school farming (during the COVID-19 pandemic)." In School Farms, 48–64. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003176558-5.
Lalli, Gurpinder Singh. "Food education and food for life." In School Farms, 11–30. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003176558-3.
Badawi, Samaa, Alshimaa A. Farag, and Gurpinder Singh Lalli. "Introduction." In School Farms, 1–8. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003176558-1.
Bakr, Ali Fouad, and Nehad Abd Gawad. "Building community resilience." In School Farms, 226–48. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003176558-18.
Moumani, Kholoud Jamal, and Amani Jamal Momani. "Working towards the garden." In School Farms, 176–88. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003176558-14.
Forgacs, Csaba. "Productivity development and regional specificities of economies of scale of specialised farms in Central and Eastern European (EU 10) agriculture (2005-2016)." In 23rd International Scientific Conference. “Economic Science for Rural Development 2022”. Latvia University of Life Sciences and Technologies. Faculty of Economics and Social Development, 2022. http://dx.doi.org/10.22616/esrd.2022.56.009.
The paper explores which farm types by specialisation direction2 (ten different types) and at what farm sizes by physical size3 (five categories) of specialised farms backed more production growth and productivity development in Central and Eastern European Countries (CEECs, EU104) over the period of 2005-2016. We compare EU10 average figures to EU27/15 averages and outline the changes by specialisation in total resource use of (i) labour (AWU), (ii) land (UAA) as well as in (iii) average farm size (UAA/specialised farms), (iv) total farm productivity (SO/farm), (v) labour productivity (SO/AWU) and (vi) area productivity (SO/UAA). We conclude that production and productivity growth of specialised farms in EU 10 differs by country, and by type and size of farming and, each CEEC has followed her own path of farm structure development in line with the country’s tradition and economic possibilities. We give regional characteristics of development in main specialisation types broken down to 5 farm size categories. We concluded the number of cereal farms increased in 6 out of 10 countries in all farm size categories and that of cattle farms went up in 5 out of EU 10 from 2005 to 2016. Farms with these two specializations have significantly extended agriculture land use and more than tripled production, but used more labor compared to basis year. SO/Farm/UAA/AWU productivity indicators of cereal farms increased quite a bit in most farm size categories in all EU 10 countries to a less extent in cattle, poultry pig and dairy farms. Growth in area productivity was led by pig, poultry, and cereal farms at E 10 level. Growth of the three productivity indicators in EU 10 are scattered quite a bit by farm types, and by countries but generally was headed by three farm size categories as 5-19.9 ha, 20-49.9 ha and 50-99.9 ha. However, the distance between EU10 and EU15 related to the level of production, land, and labour productivity still shows wide gap which needs to further narrow in the coming years.
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Moriarty, Patrick, and Tetsuya Kogaki. "Modeling of Flow Acceleration Around Wind Farms." In ASME/JSME 2007 5th Joint Fluids Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/fedsm2007-37583.
Recent measurements from operating wind farms demonstrate that the layout of the farm and interactions between turbine wakes strongly affects the overall efficiency of the wind farm. In some wind farms arranged in rectangular layouts, winds coming from the direction of the rectangular corner create a potential acceleration around the wind farm. This acceleration inherently leads to stronger local wind speeds at wind turbines downstream of the corner turbine, thereby increasing the power output of the downstream turbines. In this study, computational models are developed to predict this complex behavior seen in wind farms. The model used to examine these effects is a fully three-dimensional unsteady incompressible Navier-Stokes code, with the turbulence model turned off. Preliminary results show an optimum spacing configuration is possible. However, the results have yet to be verified at higher Reynolds number, which will be the effort of future work. Ultimately, these tools may lead to more optimal wind farm layouts.
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MATYSIK-PEJAS, Renata, Monika SZAFRAŃSKA, and Elżbieta LATO. "DETERMINANTS OF LEADING OF ORGANIC FARMS IN MAŁOPOLSKA REGION." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.033.
Poland is a country with significant potential for the development of organic farming. This is due to the possession of rural areas characterized by favorable natural and productive conditions. The advantages of Polish agriculture include relatively clean environment, low chemicals consumption, large labor resources and relatively low labor costs. The main objective of conducted research was to present factors determining the leading of organic farms in the conditions of fragmented agriculture in south Poland. The research was conducted in the Malopolska Voivodeship in 2017. Source material for analysis was primary information collected using PAPI method. In the survey participated 50 certified organic farms chosen by using purposive method of sample selection. In the area structure of surveyed organic farms dominated farms from 5.1 ha to 10 ha. The most popular direction of agricultural production on farms was the growing vegetables. Owners of organic farms as one of the main reasons for moving the farm from conventional to organic systems, considered the possibility of obtaining subsidies for one hectare of cultivation. These subsidies provide them financial support especially in the first years of operation on the market. The least important reason for transformation a farm from conventional to organic system was the factor associated with the reduction of environmental pollution as a result of the change in system of farming. As one of the advantages of running a organic farm, producers pointed the possibility of selecting disease-resistant plant and animal species and creating additional workplaces. On the other hand, as a basic disadvantage of organic farming, farmers pointed out the difficulties in finding market for the products from the farm. Most farm owners cooperate with various organizations connected with ecology. Very popular among them are also different kind of training courses, which are aimed at expanding knowledge of organic production. At the same time the educational activity of the surveyed farms is very low. Only in a few farms was conducted educational activity for children or people interested in ecology.
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ZALECKIENĖ, Jurgita. "STRUCTURAL CHANGES OF FARMER’S FARMS: CASE STUDY OF LITHUANIA." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.151.
Due to historical circumstances, the development of Lithuanian commercial farmer’s farms is slow; however, farmer’s farms are very important to the vitality of rural areas while developing agricultural commodities and goods. The purpose of this article – to analyze the structural changes in farmer’s farms and present the directions of future development. Structural changes in Lithuanian farmer’s farms during the 2005 – 2015 timeframe were analyzed while looking at the diagnostic indicators, which are the following: the number of farmer’s farms, the structure of farmer’s farms according to their size, the activity units of farmer’s farms, age of farmers, farmer’s farms sources of income. In order to study the statistical data, methods of systemization, logical analysis and generalization were applied. The analysis of the statistical data suggests that the following structural changes are taking place in Lithuanian farmer’s farms: the number of registered farmer’s farms increases and the farmers’ are getting younger. One of the most significant factors causing the structural changes in holdings – the EU financial support for the agricultural development and the changing customer demands. More and more often rural areas perform residential function and new living areas are developed. There is a predominance of the small farms (up to 10 hectares). This is mainly a result of the reform in agricultural sector at the end of 20th century. Many small agricultural holdings were established due to this reform. However, significant changes occur while choosing and/or combining the activity units of the farm: the number of farms specializing in crops increases, the number of the holdings focusing on livestock and combined farming (crops and livestock) is declining; also, farmer’s farms with diversified income or the activity units grow in number. Limited opportunities to intensify agricultural production in small farmer’s farms caused the fact that activities or income were diversified. The model of family farm remains; however, the relation between activity and the usage of family’s labour in farm activity changes.
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DuPont, Bryony L., and Jonathan Cagan. "Multi-Stage Optimization of Wind Farms With Limiting Factors." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12503.
Larger onshore wind farms are often installed in phases, with discrete smaller sub-farms being installed and becoming operational in succession until the farm as a whole is completed. An extended pattern search (EPS) algorithm that selects both local turbine position and geometry is presented that enables the installation of a complete farm in discrete stages, exploring optimality of both incremental sub-farm solutions and the completed project as a whole. The objective evaluation is the maximization of profit over the life of the farm, and the EPS uses modeling of cost based on an extensive cost analysis by the National Renewable Energy Laboratory (NREL). The EPS uses established wake modeling to calculate the power development of the farm, and allows for the consideration of multiple or overlapping wakes. A limiting factor is used to determine the size of wind farm stages: optimization stages based on the number of turbines currently available for development (representative of limitations in initial capital, which is commonly encountered in wind farm stage development). Two wind test cases are considered: a unidirectional test case with constant wind speed and a single wind direction, and a multidirectional test case, with three wind speeds and a defined probability of occurrence for each. The test case shown in the current work is employed on a 4000 km by 4000 km solution space. In addition, two different methods are performed: the first uses the optimal layout of a complete farm and then systematically “removes” turbines to create smaller sub-farms; the second uses a weighted multi-objective optimization over sequential, adjacent land that concurrently optimizes each sub-farm and the complete farm. The exploration of these resulting layouts indicates the value of full-farm optimization (in addition to optimization of the individual stages) and gives insight into how to approach optimality in sub-farm stages. The behavior exhibited in these tests cases suggests a heuristic that can be employed by wind farm developers to ensure that multi-stage wind farms perform at their peak throughout their completion.
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Košařová, Jaroslava. "ANALYZING THE EFFICIENCY AND PRODUCTIVITY OF SLOVAK FARMS SPECIALIZING IN LIVESTOCK." In NORDSCI Conference Proceedings. Saima Consult Ltd, 2021. http://dx.doi.org/10.32008/nordsci2021/b2/v4/01.
This paper aims to estimate productivity, efficiency, and especially the estimation of managerial performance among 284 farms specializing in livestock in Slovakia. Data Envelope Analysis (DEA) is used to estimate farm efficiency and related economies of scale. Taking full advantage of the panel structure, changes in farm productivity are provided by the Malmquist index and are divided into technological progress, scale effects, and managerial decision-making. Empirical results show that, on average, a 31% reduction in input use could be achieved, provided that all livestock farms operate efficiently, without further restrictions on this adjustment. In 2012 farms specialized in livestock improved their performance compared to the best farms by 17%, mainly due to improvement of the managerial efficiency by 12% and improvement of scale efficiency by 4%.
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KOZLOVA, Natalia, Aleksandr BRIUKHANOV, Eduard VASILEV, and Ekaterina SHALAVINA. "ENVIRONMENTAL ASSESSMENT OF LIVESTOCK FARMS IN RUSSIA." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.189.
The paper focuses on quantitative assessment of nitrogen flows in a livestock farm under transition to best available techniques BAT system in Russia. Comparative analysis of quantitative estimates of ammonia emissions from housing for dairy cows, fattening pigs, farrowing sows and laying hens was conducted using available literature data and information obtained through a survey of pilot livestock farms in Leningrad Region. Ammonia emission data for existing Russian enterprises were found in the range of BREF emission levels associated with BAT. The nitrogen farm-gate balance was calculated for the farm with 810 dairy cows, 2600 ha of agricultural land and milk yield of 22 kg/day. The nitrogen surplus was 48.3 kg/ha, which was below the limit values and indicated the possibility to increase the application amount of nitrogen fertilisers, however, nitrogen use efficiency of 0.21 was significantly below the European average. The viability of manure storage and spreading techniques recommended by European BREF, namely compost heaps covering and immediate incorporation of organic fertilisers after spreading, was estimated for this farm. The calculated values of total nitrogen losses are reduced by 20%; the saving of mineral fertilizers owing to higher nitrogen content in applied organic fertilisers can be 18 t / year. For the rough assessment of technologies on the initial stage of Russian reference books creation it is practicable to use the data from EU BREF on intensive rearing of pigs and poultry. When farms are assessed on the stage of integrated permits issue, it is feasible to use the measured air concentrations of hazardous substances along with the estimation of the whole-farm environmental impact by nitrogen use efficiency. For such estimates to be applied in Russia, the data needs to be collected and systematised for different categories of farms and for different climatic regions.
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Forgacs, Csaba. "In what direction is agricultural specialization headed in Central and Eastern Europe? (2005-2016)." In 21st International Scientific Conference "Economic Science for Rural Development 2020". Latvia University of Life Sciences and Technologies. Faculty of Economics and Social Development, 2020. http://dx.doi.org/10.22616/esrd.2020.53.005.
The paper deals with the main directions of specialization in Central and Eastern European Countries’ (CEECs, EU10) agriculture after the EU’s Eastward Enlargement. We analyse and compare growth and productivity advantages of specialized farm types by physical size (in hectare) in EU10 member-states to the EU10/27/15 average based on EUROSTAT data in the period of 2005-2016. We focus on exploring the main directions of specialization using such indicators as the number of specialized farms, land (Utilized Agricultural Area, UAA) and labour (Agricultural Working Unit, AWU) use on the input side, average farm size by land and labour use as well as area-, labour-, and total productivity on the output side. We conclude that the directions of specialization in farming in EU10 were based on the traditional farm production structure making the latter better able to adjust and take advantages of Common Agricultural Policy. Concerning production growth rate, the three leading specialization types of CEECs’ farms were: (i) cattle rearing and fattening, (ii) cereals, oilseed and protein crops and (iii) fruits and citrus fruits. These three specialization types of farms – in the same ranking order - also increased land (UAA) and labour (AWU) use well above the average. Specialized cereals farms and cattle rearing and fattening farms were also ranked in top three by number. Both cereals and fruits specialized farms have leading position in growth rate of land and labour use and also are in top three in growth rate of land area and total farm productivity. Cereals and fruits specialized farms also more than doubled labour productivity during the first decade after the EU’s Eastward enlargement but did not rank in the top three in this category.
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JELOČNIK, Marko, Lana NASTIĆ, and Jonel SUBIĆ. "PROCESSING OF PORK MEAT IN THE FUNCTION OF VALUE-ADDED CREATION AT THE FAMILY FARMS." In Competitiveness of Agro-Food and Environmental Economy. Editura ASE, 2022. http://dx.doi.org/10.24818/cafee/2020/9/10.
Creation of value-added at the farms could play great role in strengthening of their economic sustainability. Serbia has long tradition in pig farming. This subsector of agriculture in last few decades is facing the negative trend in production capacities (decrease in active farms and number of pigs) and it is mainly based on economically weak family farms characterized by small number of pigs. On the other hand it is obvious the strengthening of their specialization to pig farming. This line of agricultural production is specifically under the higher production risks mainly influenced by pork cycle and some market risks. Thus, the often and expressed price oscillation affects primarily the sustainability of small farms, disabling the proper planning of production and endangering their survival. Processing of pork meat at small family farms could be a good solution for income stabilization, where created value added could induce better competitiveness of the farms. The main goal of the paper is to present the economic potential of the conduction of pork meat processing at small family farms, in scenarios with or without of employment of external labour. In this context, it was used the analytical calculations based on variable costs (contribution margin). Gained results show that comparing to pig growing, organization of mentioned activity will significantly increase the farm incomes in both cases, impacting the many positive effects on farm sustainability.
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ČESONIENĖ, Laima, Daiva ŠILEIKIENĖ, and Laura EIGIRDAITĖ. "CHANGE OF ECOLOGIC FARM AREAS AND CULTIVATED CULTURES WITHIN THE TERRITORY OF LITHUANIA IN 2010–2014." In Rural Development 2015. Aleksandras Stulginskis University, 2015. http://dx.doi.org/10.15544/rd.2015.075.
Research objective is to evaluate the change of ecological farm areas and cultivated cultures within the territory of Lithuania within the period from 2010 to 2014. In 2010–2014 the data from certification institutions (databases) were used for the purpose of evaluation of change of ecological farm areas, which provide all ecological farm areas declared and certified in Lithuania within the whole reported period and agricultural plants cultivated on the areas within the set period. ArcGIS software was used for demonstration of layout of ecological farm areas within the territory of Lithuania. It was established that the major areas of ecological farms analysed within the period were located in the North-East of Lithuania, less areas in the Northern and Southern parts of middle Lithuania. During the whole period the major planted acreage of the ecological farms was taken by meadows, pastures, perennial grass; these cultures annually made almost a half of the declared planted acreage. Less declared planted acreage of the ecological farms within the research period was taken by root plants and vegetables; area planted with the cultures usually made 1 per cent from all declared planted acreage of the ecological farms. Strong correlation exists between the areas of ecological farms and pastures (r = 0.70, when p = 0.0001), complex agriculture (r = 0.76, when p = 0.0001), transition forest stage and bushes (r = 0.85, when p = 0,0001), broad-leaved forests (r = 0.84, when p = 0.0001), needle-leaved forests (r = 0.72, when p = 0.0001) and mixed forests (r = 0.84, when p = 0.0001). Weak correlation exists between ecological farm area and agricultural areas with natural plant insertions (r = 0.47, when p = 0.0001).
Reports on the topic "Farms":
1
Berns, Kent R. Farm and Weather Summary, CentralIowa Farms. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-1839.
Omotilewa, Oluwatoba, Thomas Jayne, and Milu Muyanga. The Farm Size-Productivity Relationship: Evidence From Panel Data Analysis of Small- and Medium-Scale Farms in Nigeria. APRA, Future Agricultures Consortium, September 2022. http://dx.doi.org/10.19088/apra.2022.040.
The finding that smaller farms are more productive than larger farms has long been documented. At present, evidence in the Sub-Saharan African (SSA) region has been largely limited to data from farms operating 5ha and below. Examining changes in farm size distributions and their relationship with agricultural productivity is important not only for agricultural economists and development researchers but also for evidence-based policymaking which goes beyond the current smallholder-led strategies for development in the region. This study examined the dynamics of farm operations between small-scale farms (SSFs) and medium-scale farms (MSFs) over time in different farm size categories and their relationship with agricultural productivity using farming household data spanning 0–40ha in Nigeria.
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Berns, Kent R. Farm and Weather Summary, Central Iowa Farms. Ames: Iowa State University, Digital Repository, 2005. http://dx.doi.org/10.31274/farmprogressreports-180814-1786.
Berns, Kent R. Farm and Weather Summary, Central Iowa Farms. Ames: Iowa State University, Digital Repository, 2008. http://dx.doi.org/10.31274/farmprogressreports-180814-1829.
Berns, Kent R. Farm and Weather Summary, Central Iowa Farms. Ames: Iowa State University, Digital Repository, 2009. http://dx.doi.org/10.31274/farmprogressreports-180814-1843.
Berns, Kent R. Farm and Weather Summary, Central Iowa Farms. Ames: Iowa State University, Digital Repository, 2004. http://dx.doi.org/10.31274/farmprogressreports-180814-1854.
Berns, Kent R. Farm and Weather Summary, Central Iowa Farms. Ames: Iowa State University, Digital Repository, 2007. http://dx.doi.org/10.31274/farmprogressreports-180814-1889.
Haden, David. Farm and Weather Summary Northwest Research Farms. Ames: Iowa State University, Digital Repository, 2007. http://dx.doi.org/10.31274/farmprogressreports-180814-2530.
Haden, David. Farm and Weather Summary Northwest Research Farms. Ames: Iowa State University, Digital Repository, 2005. http://dx.doi.org/10.31274/farmprogressreports-180814-2653.
Haden, David. Farm and Weather Summary Northwest Research Farms. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-2682.
