An assessment of dairy farm structure and characteristics of dairy production systems in Serbia

In order to have a more precise description of dairy farm structure and characteristics of dairy production systems, as well as to assess possibilities for improving production and farming conditions in which milk production is organized, a survey based research was directed at a select group of farms across the Serbia. 1180 questionnaires have been mailed to farmers whose farms are registered for either cattle or mixed production. Questionnaire was divided into 6 sections: general information of the farm, agricultural and structural information, zootechnical information, sanitary and veterinarian information, information about education and extension, and information on the perspectives of future farming. About 59% of analyzed farms have size up to 20 ha, with average size of about 10 ha. On the other hand, about 55% farms raises up to 15 cows and heifers with average of 6 heads per farm, while 3% of farms have more than 200 cows and heifers. Over 86% of surveyed farmers intend to expand existing farm production, mainly by increasing the number of animals, stricter selection and improvement of the conditions for feeding, housing, care and milking. About 75% of farmers have expressed a positive expectation from future membership of Serbia in EU, although these expectations are not clearly defined.

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The Topic of the Ideal Dairy Farm Can Inspire How to Assess Knowledge about Dairy Production Processes: A Case Study with Students and Their Contributions

Processes ◽

10.3390/pr9081357 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1357

Author(s):

Marek Gaworski ◽

Chloé de Cacheleu ◽

Clémentine Inghels ◽

Lucie Leurs ◽

Camille Mazarguil ◽

...

Keyword(s):

Milk Production ◽

Dairy Farm ◽

Learning System ◽

Dairy Production ◽

Full Time ◽

Farm Production ◽

Animal Pain ◽

Production Processes ◽

Distance Learning System ◽

The Ideal

The dairy farm and on-farm production processes are the subject of numerous evaluations. These are not only evaluations of the economic efficiency of milk production. Opinions expressed by various social groups are also an important contribution to improving the approach to milk production on the farm. As a result of such opinions, a vision of an ideal dairy farm may be formed. The aim of the study was to develop the thematic area of an ideal dairy farm in the opinion of two groups of students who were learning remotely (in the distance learning system) due to the Covid-19 pandemic. The first group consisted of six Erasmus+ students. The second group consisted of 70 full-time Polish students. As part of their homework, the students answered three questions about the ideal dairy farm. Students had 4 weeks to do their homework. Erasmus+ students’ homework was used to propose a ranking method for assessing the answers to three questions by the students themselves. Homework of Polish students was used to analyze the frequency of using certain keywords. Polish students, in their homework on the ideal dairy farm, mainly used the basic concepts related to dairy production. Unfortunately, a very small number of students used terms that represent a responsible approach to dairy production, including ethical aspects, freedom, sustainability, animal pain, antibiotics, and organic milk production. In conclusion, it was indicated that the curriculum should be structured in such a way as to raise students’ awareness of dairy production and its current challenges.

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Use of Markov Processes in Predicting Dairy Farm Size Distribution Changes

Journal of the Northeastern Agricultural Economics Council ◽

10.1017/s0163548400004738 ◽

1979 ◽

Vol 8 (2) ◽

pp. 59-72

Author(s):

John W. Wysong ◽

Mahmood Y. Seyala

Keyword(s):

Dairy Farm ◽

Farm Size ◽

Primary Data ◽

The Past ◽

Farm Production ◽

The Future ◽

Short Run ◽

Long Term Trends ◽

Average Size

During the past several decades, a number of research publications have used Markov chain processes to predict changes in number of farm firms, the average size of farms and labor resource productivity in farm production (Conneman, Harris and Wilson, Judge and Swanson, Kottke, Seyala, Willett and Saupe, Wysong and Seyala). The Markov method assumes that the pattern of change exhibited in the past will continue into the future. This method provides information on historical changes by frequency distribution categories as well as for the whole cohort, and allows for projection of these changes into the future. Previous studies have used mainly short-run periods of up to 5 years as the primary data base. This study has considered the use of longer-run base periods of 10 to 20 years combined with periodic updating of sample data in projecting long-term trends in numbers and sizes of dairy farms and revising such projections through time.

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The changing nature of dairy production in Victoria, Australia: are we ready to handle the planning and development of large, intensive dairy operations?

Animal Production Science ◽

10.1071/an18476 ◽

2020 ◽

Vol 60 (4) ◽

pp. 473

Author(s):

Y. J. Williams ◽

S. McDonald ◽

S. J. Chaplin

Keyword(s):

Animal Welfare ◽

Land Use Planning ◽

Large Scale ◽

Production Systems ◽

Dairy Farm ◽

Dairy Production ◽

State Planning ◽

Codes Of Practice ◽

Environmental Requirements ◽

Farm Category

Around the world, dairy production continues to intensify, with farmers increasing stocking rates, feeding more supplements, and transitioning into fully housed systems. Dairy production in Victoria is no exception and farmers are starting a move towards intensive (i.e. permanently housed) dairy operations. Challenges associated with these transformations have included difficulties, or failure, to obtain planning approval and public concern around the effect of intensive developments on environmental degradation, animal welfare and industry image. We examined current land-use planning provisions, environmental requirements, animal-welfare regulations, industry guidelines and codes of practice for their applicability and suitability to the implementation of intensive dairy-production operations, particularly large-scale ones, in Victoria, Australia. Our aim was to clearly identify factors that have the potential to hinder the growth and expansion of existing dairy-production systems into intensive operations, and the establishment of new intensive dairy enterprises. The majority of legislation examined posed no obstacles to the development of large-scale intensive dairy operations. New definitions for intensive livestock production and the inclusion of an intensive dairy-farm category in the State planning provisions will reduce current confusion across and within planning departments. A standard methodology to determine separation distances is required and a code for intensive dairy farming would greatly assist with the planning-approval process. Many advisory publications fall short when applied to intensive dairy operations as they are currently written for pasture-based farms with limited infrastructure for regularly feeding or housing large herds of >700 cows.

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Data-driven decision support tools in dairy herd health

Improving dairy herd health Improving - Burleigh Dodds Series in Agricultural Science ◽

10.19103/as.2020.0086.19 ◽

2021 ◽

pp. 101-118

Author(s):

Victor E. Cabrera ◽

Keyword(s):

Decision Support ◽

Production Systems ◽

Dairy Farm ◽

Dairy Herd ◽

Big Data Analysis ◽

Data Driven ◽

Decision Support Tools ◽

Herd Health ◽

Farm Production ◽

Support Tools

This chapter describes the development process of data-driven decision support tools for dairy herd management with an emphasis on real-time continuous data integration and its applications on dairy herd health. It includes concepts on big data analysis, expert systems, and artificial intelligence towards more sustainable dairy farm production systems.

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Assessing and reducing the environmental impact of dairy production systems in the northern US in a changing climate

Agricultural Systems ◽

10.1016/j.agsy.2021.103170 ◽

2021 ◽

Vol 192 ◽

pp. 103170

Author(s):

Karin Veltman ◽

C. Alan Rotz ◽

Larry Chase ◽

Joyce Cooper ◽

Chris E. Forest ◽

...

Keyword(s):

Environmental Impact ◽

Production Systems ◽

Dairy Production ◽

Changing Climate

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Understanding the dairy production systems in rural settlements in the Brazilian semi-arid region: characterization, typology, and holistic perception

Tropical Animal Health and Production ◽

10.1007/s11250-021-02840-x ◽

2021 ◽

Vol 53 (4) ◽

Author(s):

Maria Samires Martins Castro ◽

Delano de Sousa Oliveira ◽

Raquel Oliveira dos Santos Fontenelle ◽

Ana Paula Araújo do Nascimento ◽

Robson Mateus Freitas Silveira ◽

...

Keyword(s):

Arid Region ◽

Production Systems ◽

Dairy Production ◽

Rural Settlements ◽

Holistic Perception ◽

Semi Arid Region ◽

Semi Arid

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Use of information and communication technologies in small-scale dairy production systems in central Mexico

Experimental Agriculture ◽

10.1017/s0014479720000319 ◽

2020 ◽

Vol 56 (5) ◽

pp. 767-779

Author(s):

Juan de Dios García-Villegas ◽

Anastacio García-Martínez ◽

Carlos Manuel Arriaga-Jordán ◽

Monica Elizama Ruiz-Torres ◽

Adolfo Armando Rayas-Amor ◽

...

Keyword(s):

Cluster Analysis ◽

Production Systems ◽

Communication Technologies ◽

Small Scale ◽

Central Mexico ◽

Dairy Production ◽

Dairy Farmers ◽

Use Of Technology ◽

Group 2 ◽

Small Scale Dairy

AbstractThe objective of the study was to characterize small-scale dairy production systems to identify the technological preferences according to the farmer and farm characteristics and to analyze the importance and role of the information communication technologies (ICTs) in the dissemination of information related to management and livestock activities. To collect the data, a survey was applied to 170 small-scale dairy farmers from central Mexico. To characterize the farms, a factor analysis (FA) and cluster analysis (CA) were performed. To compare and identify differences between groups, a Kruskal–Wallis test was conducted. Four factors that explain 70.93% of the accumulated variance were identified; these factors explain the use of technology, production characteristics, social connections, and use of ICTs. The cluster analysis identified four groups. Group 1 was integrated by farmers with more experience and the largest farms. Group 2 had higher studies and use of ICTs. Group 3 was formed by young farmers but had a low use of technology. Group 4 contained older farmers with a low use of technology. The young farmers with higher studies have begun to incorporate ICTs into their daily activities on the farm, as observed in Group 2. Smartphones were the most used and were considered important by the farmers of the four groups, since they enable interaction with other farmers and the dissemination of topics of interest related with the farm. In conclusion, four group of farmers were differentiated; therefore, different extension approaches should be implemented to take into account the preferences and the technologies considered most important for each group. The ICTs are emerging technologies among small-scale dairy farmers to communicate information related to livestock management, mainly by young farmers with studies of secondary, as observed in Group 2.

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Soil carbon dynamics in Brazilian atlantic forest converted into pasture‐based dairy production systems

Agronomy Journal ◽

10.1002/agj2.20578 ◽

2020 ◽

Author(s):

Patricia Perondi Anchão Oliveira ◽

Paulo Henrique Mazza Rodrigues ◽

Maria Fernanda Ferreira Menegucci Praes ◽

André Faria Pedroso ◽

Bia Anchão Oliveira ◽

...

Keyword(s):

Soil Carbon ◽

Atlantic Forest ◽

Production Systems ◽

Carbon Dynamics ◽

Dairy Production ◽

Brazilian Atlantic Forest ◽

Soil Carbon Dynamics

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The Italian Wine Sector: Evolution, Structure, Competitiveness and Future Challenges of an Enduring Leader

Italian Economic Journal ◽

10.1007/s40797-021-00144-5 ◽

2021 ◽

Author(s):

Eugenio Pomarici ◽

Alessandro Corsi ◽

Simonetta Mazzarino ◽

Roberta Sardone

Keyword(s):

Economies Of Scale ◽

Production Systems ◽

International Markets ◽

Structural Features ◽

Italian Wine ◽

Diamond Model ◽

Future Challenges ◽

Wine Sector ◽

European Policies ◽

Average Size

AbstractThe Italian wine supply chain has performed well in recent decades both in terms of profitability and success on the domestic and international markets. This is despite the fact that it is fragmented in terms of products, prices and consumption context, and, in particular, despite the fact that it is characterised by an organisation that hinders the full exploitation of economies of scale. This paradox has not been investigated in literature. We propose several elements in support of the hypothesis that the Italian wine sector’s success is linked to favourable elements of the Porter Diamond Model (5 out of 6) but also to the “district” nature of a large part of the sector. The presence of numerous networks, some of which are formal and others informal, gives most Italian local production systems specialising in grapes and wine the characteristics of industrial districts, due to the local social capital that is stratified there. These networks include operators such as Cooperatives and Consorzi di Tutela, upstream and downstream industries and services, tourism, research and educational bodies. Such networks can overcome the weakness represented by the low concentration and small average size of the operators. To support this hypothesis, we analyse the historical evolution of the sector and its drivers, the structural features of the different phases of the wine chain (grape growing, winemaking, bottling and distribution), the market relationships within the chain and the national and European policies favouring the sector. This analysis also underlines the differences between the Italian sector and its competitors from the Old and New World.

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