How many cattle are in the world? The global live cattle population amounted to about 1.57 billion heads in 2023, up from approximately 1.51 million in 2021. Cows as livestock The domestication of cattle began as early as 10,000 to 5,000 years ago. From ancient times up to the present, cattle are bred to provide meat and dairy. Cattle are also employed as draft animals to plow the fields or transport heavy objects. Cattle hide is used for the production of leather, and dung for fuel and agricultural fertilizer. In 2022, India was home to the highest number of milk cows in the world. Cattle farming in the United States Cattle meat such as beef and veal is one of the most widely consumed types of meat across the globe, and is particularly popular in the United States. The United States is the top producer of beef and veal of any country worldwide. In 2021, beef production in the United States reached 12.6 million metric tons. Beef production appears to be following a positive trend in the United States. More than 33.07 million cattle were slaughtered both commercially and in farms annually in the United States in 2019, up from 33 million in the previous year.

Share of major livestock types (cattle, horses, sheep, goats, pigs and poultry) in total livestock population expressed in livestock units (LSU); based on Farm Structure Survey data.

Cheptels by herd size by municipality Agreste – Agricultural Censuses (1988, 2000, 2010) **** All farms (excluding collective grazing) Small farms Medium and large holdings Reference years: 1988, 2000, 2010 Livestock: Total Bovines Total Vaches Dairy cows Suckler cows Bovine animals of one year or more Bovine animals less than one year old Total Equidae Goats Nurturing sheep Dairy ewes Total Pigs Breeding sows of 50 kg or more Broilers and roosters Herd size: Together Of which 1 to 19 heads (cows, goats, nurturing sheep, pigs, sows) Of which 1 to 39 heads (total cattle, chickens) Of which 80 or more heads (cows) Of which 100 or more heads (total cattle) Of which 150 or more heads (goats, nurturing sheep) Of which 200 or more heads (dairy grapes, sows) Of which 500 or more heads (total pigs) 10000 or more heads (chickles) Livestock unit: Holdings having Corresponding livestock (heads) * * * * # The agricultural censuses, ten-year surveys, offer an instant, complete and detailed picture of a key sector of the French and European economy: agriculture (agricultural population, plant areas, including vineyards, livestock numbers, means of production, ancillary activities, etc.). It answers questions as diverse as it is varied, at all geographical levels, allowing comparisons at the finest level (canton, common) and takes into account the local specificities as well as the new challenges of agriculture, such as signs of quality, territorial farm contracts, cultivation practices, etc. It is also interested in smaller farms and the important local impact. To prepare for the future of the agricultural world: The agricultural census makes it possible to measure the impact of agricultural policies, in particular the Common Agricultural Policy (CAP), on agricultural practices and the environment. It gives political leaders, national elected officials and representatives of the profession keys to preparing future agricultural laws and regulations and international negotiations. It provides elected representatives of rural communes with valuable data for spatial management and spatial planning. The 2010 agricultural census follows the 1970, 1979, 1988 and 2000 censuses. The 2020 agricultural census will soon begin. The main data relate to: Crops and areas cultivated, Breeding and livestock, Methods of crop protection, Farm equipment, Diversification of activities (green tourism...), The marketing of products (AOC, direct sales to consumers, etc.), Employment (employee, family employment, etc.) and the level of training of the farmer, Management of the farm. There is no question about the financial results or the income of farmers. Who was identified? Investigators identified all production units meeting 3 criteria > producing agricultural products; > have an independent day-to-day management; > attain or exceed a certain threshold in area, production or number of animals. This threshold has been defined as follows: > a utilised agricultural area (UAA) of 1 hectare or more; > or a specialised crop area greater than or equal to 20 ares; > or sufficient agricultural production activity, estimated in terms of number of animals, production area or minimum production volume.

The global livestock breeding services market is experiencing robust growth, driven by increasing demand for high-yielding and disease-resistant livestock. Technological advancements in artificial insemination, embryo transfer, and genomic selection are significantly enhancing breeding efficiency and accelerating genetic improvement. The market is segmented by animal type (pigs, cattle, sheep, others) and farming type (ecological, intelligent, others), reflecting diverse breeding practices and consumer preferences. Cattle breeding currently holds the largest market share due to the high demand for beef and dairy products globally. However, the pig breeding segment is projected to exhibit substantial growth owing to the rising global population and increasing consumption of pork. The adoption of intelligent farming techniques, leveraging data analytics and automation, is a key trend transforming the sector, leading to improved herd management and optimized breeding outcomes. Geographical variations exist, with North America and Europe currently dominating the market due to advanced infrastructure and established breeding programs. However, developing economies in Asia-Pacific and regions in Africa are showing promising growth potential, fueled by expanding livestock populations and increasing investment in modern breeding technologies. Challenges include stringent regulatory frameworks surrounding animal welfare and biosecurity, as well as the high initial investment cost associated with adopting advanced breeding technologies. Despite these challenges, the long-term outlook for the livestock breeding services market remains highly positive, propelled by consistent technological innovation and rising global demand for animal protein. The forecast period (2025-2033) anticipates continued expansion, with a projected Compound Annual Growth Rate (CAGR) that factors in the aforementioned drivers and restraints. While precise figures aren't provided, a reasonable estimate for the CAGR, considering market dynamics and technological advancements, would be in the range of 5-7%. This growth will likely be uneven across different regions and animal types. For instance, regions with established agricultural infrastructure are expected to maintain a steadier growth trajectory compared to regions undergoing infrastructural development and technological adoption. Similarly, high-demand animal segments, such as cattle and pig breeding, are poised to exhibit stronger growth rates compared to others. Overall, the market is expected to witness a considerable increase in value over the forecast period, driven by the continuous demand for efficient and sustainable livestock production.

Investigating the livestock vaginal microbiota is of increasing interest due to its relationship with animal reproductive performance. Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. To address this variability, we conducted a combined analysis of publicly available 16S rRNA gene amplicon sequencing datasets to reveal the core vaginal microbiota in cattle, sheep, and pigs. The goal of this combined analysis was to identify bacterial genera that were shared despite a diverse overall sample population. A total of 2,911 vaginal samples (715 cattle, 964 sheep, and 1,232 pigs) from 29 different datasets were used in this combined analysis. Beta diversity analysis revealed structural differences of the vaginal microbiota between different animal species. Compositionally, the most abundant phyla were Bacillota, Pseudomonadota, and Bacteroidota. At the genus level, an unclassified Pasteurellaceae genus, Ureaplasma, and Streptococcus were the most abundant. Across the vaginal microbiota of individual livestock species, compositional differences were observed. The cattle and sheep vaginal microbiota contained a higher abundance of Ureaplasma and Histophilus whereas the pig vaginal microbiota contained more Fusobacterium and Parvimonas than that of the other livestock samples. Among the cattle, 120 OTUs and 82 genera were present in 70% of the vaginal samples. At the same threshold, pig samples had 40 core OTUs and 63 core genera, while the sheep samples had 22 core OTUs and 50 core genera. There were 19 overlapping core vaginal genera across the three animal species. The core vaginal OTUs were largely species-specific, although there were eight overlapping OTUs. These included Streptococcus (OTU 21), Clostridium sensu stricto 1 (OTU 18), and Corynebacterium (OTU 6), which were also some of the most abundant members of the livestock core vaginal microbiota. A better understanding of the livestock vaginal microbiota is required for future studies aimed at elucidation of the functional significance of individual microbes with respect to livestock reproductive efficiency. The core vaginal genera identified in this analysis will help guide research on mechanisms/pathways through which individual organisms enhance or impede animal reproductive efficiency.

Areas in which livestock wastes could contribute to the establishment of pond culture systems such as integrated agriculture-aquaculture farming. Livestock population was used as a surrogate for manure. Livestock populations for cattle, goats, sheep and pigs in the form of animal/km2 were obtained from U.S. Army CERL and CRSSA, Cook College, Rutgers University.

Hogs and pigs are one of the main sources of meat in the United States, and there is a thriving domestic pork market. As of March 2024, Iowa had an inventory of about 25.1 million hogs and pigs, making it the top producer of swine in the country by a large margin. In that same year, the second largest producer of hogs and pigs was Minnesota, with about nine million head. Swine Production Pigs have several advantages over other livestock. They are good at converting animal feed into meat and do not require large grazing areas. In addition, almost every part of the pig can be eaten or processed, making them an efficient source of meat. Thus, raising pigs for consumption is a good investment for small-scale farmers and factory farms alike. Pork Market in the U.S. Some of the classic staples of an American breakfast are bacon, sausage, or ham, which are all pork products. Pork is one of the most frequently consumed types of meat in the United States with the average American consuming about 51.1 pounds of pork per year as of 2020. In 2022, over 27 billion pounds of pork were produced in the United States.

This spreadsheet is the underlying data for the biodiversity indicator C9a, Animal genetic resources – effective population size of Native Breeds at Risk.

Genetic diversity is an important component of biodiversity. The UK genetic diversity indicator focuses on the diversity of Native Breeds at Risk of a number of farm animal species (cattle, sheep, goats, horses and pigs). Genetic diversity in livestock breeds is important for a number of reasons. Aside from their cultural importance, local adaptation and links to breed specific products, native or rare livestock breeds provide a resource from which to develop new breeds.

UK farm animal genetic resource is a key asset in economic, environmental, social and cultural terms. Native breeds of farm animals are often associated with traditional land management required to conserve important habitats. The indicator is also relevant to the commitments on conservation of native breeds in the UK National Action Plan on Farm Animal Genetic Resources (FAnGR).

The indicator shows the change in the average effective population sizes (Ne) for breeds of goats, pigs, horses, sheep and cattle classified by the UK Farm Animal Genetic Resources Committee as Native Breeds at Risk (NBAR). The UK Farm Animal Genetic Resource (FAnGR) Committee breed inventory was first published in 2013 with information for pigs, goats and horses, and was expanded in 2014 to include sheep and cattle; though it should be noted that there are currently no data for a number of breeds. In the 2014 inventory, all five native breeds of goats, all 11 native breeds of pigs, 15 of 20 native horse breeds, 46 of 59 native sheep breeds, and 29 of 38 native cattle breeds were classified as NBAR (for definitions of native breeds, and native breeds at risk, see Appendix 1 of the UK Country Report on Farm Animal Genetic Resources 2012). Of the native breeds classified as at risk, data for 12 native cattle breeds at risk, 24 sheep, two horses and one goat were not available in 2014, or for earlier years, and therefore effective population size could not be calculated for these breeds.

Effective population size is a calculation which takes account of the total number of animals in a population and the relative number of sires and dams (male and female parents). A low effective population size signifies a greater likelihood of in-breeding and risk of loss of genetic diversity. A larger effective population size implies a lower risk of inbreeding and higher genetic diversity.

This is one of a suite of 24 UK biodiversity indicators published by JNCC on behalf of Defra; the latest publication date was 19 January 2016 - for indicator C9a the latest data are for 2014. The supporting technical document details the methodology used to create the indicator.

Chickens led the livestock population in Africa, amounting to roughly *** billion heads in 2022. Goats and sheep followed as major livestock species in the continent, each with an approximate stock of *** million and *** million heads, respectively. That same year, Africa counted some *** million heads of cattle.

Statistics Canada conducts the Census of Agriculture every five years at the same time as the Census of Population. The most recent Census of Agriculture was on May 15, 2001.The Census of Agriculture collects and disseminates a wide range of data on the agriculture industry such as number and type of farms, farm operator characteristics, business operating arrangements, land management practices, crop areas, numbers of livestock and poultry, farm capital, operating expenses and receipts, and farm machinery and equipment. These data provide a comprehensive picture of the agriculture industry across Canada every five years at the national and provincial levels as well as at lower levels of geography. The Census of Agriculture is the cornerstone of Canada's Agriculture Statistics Program. Census of Agriculture data are an indispensable public and private sector tool for analysing important changes in the agriculture and food industries;developing, implementing and evaluating agricultural policies and programs such as farm income safety nets and environmental sustainability; and making production, marketing and investment decisions. Statistics Canada uses the data as benchmarks for its regular surveys on crops, livestock and farm finances between census years. In addition, data extracted from the unique Agriculture Population Linkage Database, which links data from both the Census of Population and Census of Agriculture databases, paint a socio-economic portrait not only of farm operators but also of their families and households. This release contains all farm data and farm operations data plus selected historical files. In 2001, a census farm was defined as an agricultural operation that produces at least one of the following products intended for sale: crops (hay, field crops, tree fruits or nuts, berries or grapes, vegetables, seed); livestock (cattle, pigs, sheep, horses, game animals, other livestock); poultry (hens, chickens, turkeys, chicks, game birds, other poultry); animal products (milk or cream, eggs, wool, furs, meat); or other agricultural products (Christmas trees, greenhouse or nursery products, mushrooms, sod, honey, maple syrup products). For 2001, a new farm type classification based on the North American Industrial Classification System (NAICS) has been added to the historical classification used in previous censuses. All tabulated data are subject to confidentiality restrictions prior to release. Due to confidentiality constraints, data for those geographic areas with very few agricultural operations are not released separately, but rather merged with a geographically adjacent area.

The global dehairing centrifuge market, valued at $854 million in 2025, is projected to experience steady growth, driven by increasing demand for efficient and hygienic meat processing across various livestock industries. The Compound Annual Growth Rate (CAGR) of 5.2% from 2025 to 2033 indicates a promising outlook, particularly fueled by the rising global population and consequently increased meat consumption. The market segmentation reveals a significant contribution from the pig and cattle segments within the application category, reflecting the substantial scale of these industries. Technological advancements leading to more compact and efficient centrifuge designs are further bolstering market expansion. While the exact contribution of each segment is unknown, a reasonable estimation based on industry trends would suggest that pigs and cattle likely represent the largest segments, followed by sheep and chickens. The geographical distribution is expected to be heavily influenced by regions with significant livestock populations and established meat processing sectors. North America and Europe are likely to hold significant market shares, with strong growth potential in rapidly developing economies within Asia-Pacific, driven by increasing industrialization and meat production. Challenges, however, might include stringent regulatory compliance and environmental concerns related to waste management. The competitive landscape showcases a mix of established players and emerging companies, indicating both opportunities for market consolidation and innovation. Companies like Rozfood, ATK Products, and Mecanova are likely to play key roles in shaping market trends through technological improvements and strategic partnerships. The forecast period of 2025-2033 presents significant opportunities for market participants to capitalize on the anticipated growth by focusing on innovative product development, catering to specific regional needs, and expanding into emerging markets. This includes focusing on sustainable and efficient technologies to meet evolving environmental concerns within the food processing industry. Future market expansion will likely depend on factors such as technological innovations, changes in consumer preferences, and the overall health of the global livestock industry.

As per Cognitive Market Research's latest published report, The Vietnam Meat and Bone Meal Market size was $235.68 Million in 2017 and it is forecasted to reach $272.50 Million by 2029.The Vietnam Meat and Bone Meal Industry's Compound Annual Growth Rate will be 1.94% from 2023 to 2030. What is Driving Vietnam Meat And Bone Meal - MBM Industry Growth?

Growing slaughtering sector

Vietnam's population has increased by roughly 1.03 percent per year over the last decade, rising from 83.1 million in 2005 to 93.4 million in 2015. The share of the urban population reached 31% in 2014, up from 27.1 percent in 2005. During this time, Vietnam's gross national income per capita climbed from $699 to $2,111, transforming it from a low-income to a lower-middle-income country.

Food demand has risen significantly in tandem with population and wealth growth, and food consumption habits have evolved. The past decade has witnessed extraordinarily high levels of increase in meat consumption (particularly pork), with growth rates exceeding those of any other country in the area. The sector's response to the growth in demand has been an intensification of slaughtering.

There are numerous slaughterhouses in Vietnam, hence the slaughtering industry is expanding. Cattle and pig slaughtering is a big business in Vietnam these days, with 42 slaughterhouses in Ho Chi Minh City alone. Currently, Vietnam has around 30 animal slaughtering and processing enterprises with a combined capacity of 500,000 tonnes per year.

The country has 15,537 pig slaughterhouses and killing slabs. In Hanoi, family-run slaughterhouses with a capacity of 1-5 pigs slaughtered per day supply an estimated 61% of pig output. Similarly, in Vietnam, over five million dogs and one million cats are ruthlessly butchered for their meat each year.

Similarly, many Vietnamese cities are proposing to establish additional slaughterhouses. The People Committee of Ho Chi Minh City intends to establish six new industrial-scale cow slaughtering operations in 2019. The Xuan Thoi Thuong and Tan Hiep FOOD PROCESSING PLANTS in the Hoc Mon district will have a capacity of 2,000 and 3,000 animals per day, respectively. Furthermore, the Vissan Joint Stock Company would open one slaughterhouse with a daily capacity of 2,500 to 4,000 animals.

These slaughterhouses generate a lot of waste. Meat and bone meal is made from slaughterhouse waste and deceased animals. Slaughterhouse wastes are animal parts that are not fit for human food, such as carcass trimmings, condemned carcasses, condemned livers, inedible offal (lungs), and bones. Animal corpses can be rendered to kill disease germs and also converted into meat and bone meal after they have died.

As a result, the growing slaughtering sector drives the growth of the Vietnam meat and bone meal market.

Restraint

Animal health issues.(Access Detailed Analysis in the Full Report Version)

Opportunity

Growing animal feed industry.(Access Detailed Analysis in the Full Report Version)

What is Meat And Bone Meal - MBM?

The rendering business produces meat and bone meal (MBM). In the diets of production animals, it is a useful source of protein and minerals, adding to the diet's protein, energy, and mineral content. Meat and bone meal are made from reclaimed animal protein, which includes byproducts such as lean meat, inedible portions, and animal carcasses from cows, pigs, and chickens.

Meat and bone meal is a foodstuff derived from animal offal. Almost 30% of an animal's life weight is consumed as offal. These are used for the feed of poultry, pet, and other animals.

Meat and bone meal contains around 45-60% protein, 33-35% ash, 8-12% fat, and 4-7% water. It is high in calcium, phosphorus, and trace minerals. Meat and bone meal are typically utilized in animal feed formulation to increase the amino acid profile of the feed.

Every year, a large number of animals are slaughtered in Vietnam, resulting in the waste products of meat and bone. This contributes to the expansion of the Vietnam meat and bone meal market. Similarly, increased pet ownership and the animal feed industry drive the Vietnam meat and bone meal market forward.

The animal grow lights market is experiencing robust growth, driven by increasing demand for efficient and sustainable livestock farming practices. The market's expansion is fueled by several key factors: the rising global population and its consequent increased demand for animal protein, the growing adoption of controlled-environment agriculture (CEA) for livestock, and the continuous technological advancements in lighting solutions leading to improved energy efficiency and light spectrum optimization for animal growth and well-being. Specific advancements like LED technology, offering precise spectral control and reduced energy consumption compared to traditional lighting, are significantly contributing to market expansion. Furthermore, the increasing awareness of the benefits of optimized light exposure on animal health, productivity, and overall welfare is driving adoption across various livestock types, from poultry and pigs to dairy cows. While initial investment costs can be a barrier for smaller farms, the long-term benefits in terms of increased yields and reduced operational costs are increasingly outweighing this factor. The market is segmented by livestock type, lighting technology, and geographical region, with significant variations in adoption rates based on technological advancement and market maturity. The competitive landscape is characterized by a mix of established players like OSRAM and Signify Holding, alongside specialized agricultural lighting companies like DeLaval and Agrilight BV. These companies are actively involved in developing innovative solutions catering to the specific needs of various livestock. The market is witnessing increasing consolidation, with larger companies acquiring smaller specialized firms to expand their product portfolios and market reach. Future growth will likely be influenced by factors such as government regulations promoting sustainable agriculture, technological breakthroughs in lighting technology (including advancements in spectral tuning and smart lighting systems), and the growing adoption of precision livestock farming techniques. Geographical expansion into developing economies with a growing livestock population will also play a crucial role in shaping the future trajectory of the animal grow lights market. While challenges like fluctuating energy prices and potential disruptions in supply chains exist, the overall market outlook remains positive, indicating substantial growth opportunities over the forecast period.

Investigating the livestock vaginal microbiota is of increasing interest due to its relationship with animal reproductive performance. Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. To address this variability, we conducted a combined analysis of publicly available 16S rRNA gene amplicon sequencing datasets to reveal the core vaginal microbiota in cattle, sheep, and pigs. The goal of this combined analysis was to identify bacterial genera that were shared despite a diverse overall sample population. A total of 2,911 vaginal samples (715 cattle, 964 sheep, and 1,232 pigs) from 29 different datasets were used in this combined analysis. Beta diversity analysis revealed structural differences of the vaginal microbiota between different animal species. Compositionally, the most abundant phyla were Bacillota, Pseudomonadota, and Bacteroidota. At the genus level, an unclassified Pasteurellaceae genus, Ureaplasma, and Streptococcus were the most abundant. Across the vaginal microbiota of individual livestock species, compositional differences were observed. The cattle and sheep vaginal microbiota contained a higher abundance of Ureaplasma and Histophilus whereas the pig vaginal microbiota contained more Fusobacterium and Parvimonas than that of the other livestock samples. Among the cattle, 120 OTUs and 82 genera were present in 70% of the vaginal samples. At the same threshold, pig samples had 40 core OTUs and 63 core genera, while the sheep samples had 22 core OTUs and 50 core genera. There were 19 overlapping core vaginal genera across the three animal species. The core vaginal OTUs were largely species-specific, although there were eight overlapping OTUs. These included Streptococcus (OTU 21), Clostridium sensu stricto 1 (OTU 18), and Corynebacterium (OTU 6), which were also some of the most abundant members of the livestock core vaginal microbiota. A better understanding of the livestock vaginal microbiota is required for future studies aimed at elucidation of the functional significance of individual microbes with respect to livestock reproductive efficiency. The core vaginal genera identified in this analysis will help guide research on mechanisms/pathways through which individual organisms enhance or impede animal reproductive efficiency.

Automatic Pig Feeders Market Outlook

The global automatic pig feeders market size was valued at approximately $2.5 billion in 2023 and is projected to reach around $5.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.5% during the forecast period. The growth factors driving this market include the increasing demand for efficient animal farming practices, technological advancements, and a rise in meat consumption globally. The need to improve feed efficiency, reduce labor costs, and ensure consistent feeding schedules is further propelling the market expansion.

One of the major growth factors in the automatic pig feeders market is the increasing adoption of automation in agriculture. With the rise in global population and the subsequent increase in demand for meat products, farmers are under pressure to enhance production efficiency. Automated pig feeders help in achieving this by reducing human intervention, thereby minimizing errors and ensuring a more consistent and efficient feeding process. This automation not only enhances productivity but also ensures the health and growth of the livestock, which is a crucial factor for farmers.

Technological advancements in animal farming equipment are also playing a significant role in the market's growth. Innovations such as IoT-enabled feeders, which allow for real-time monitoring and control, are gaining popularity. These advanced systems can track the feeding habits and health of pigs, providing valuable data that can be used to optimize feeding schedules and improve overall farm management. This technological integration is helping farmers to make more informed decisions, thereby driving the demand for automatic pig feeders.

Another important growth factor is the rising awareness about animal welfare. Consumers are increasingly concerned about the conditions in which farm animals are raised, leading to stricter regulations and standards for animal farming. Automatic pig feeders can contribute to better animal welfare by ensuring that pigs receive a consistent and balanced diet, reducing the risk of underfeeding or overfeeding. This not only improves the health and well-being of the pigs but also enhances the quality of the meat produced, which is essential for meeting consumer demands.

In parallel to the advancements in pig feeding technology, the development of Cow Automatic Feeding Equipment is gaining traction in the agricultural sector. This equipment is designed to streamline the feeding process for dairy and beef cattle, ensuring that they receive the right amount of nutrients at the right time. The integration of automation in cow feeding systems not only reduces labor costs but also enhances the precision of feed distribution, which is crucial for maintaining the health and productivity of the herd. With the growing emphasis on efficient and sustainable farming practices, Cow Automatic Feeding Equipment is becoming an essential component for modern livestock management.

From a regional perspective, Asia Pacific is expected to dominate the automatic pig feeders market during the forecast period. The region's large and growing population, coupled with an increasing demand for pork products, is driving the adoption of automated farming practices. Countries such as China and India are experiencing rapid growth in their agricultural sectors, further supporting the market expansion. North America and Europe are also significant markets, driven by technological advancements and a strong emphasis on animal welfare and sustainable farming practices.

Product Type Analysis

The automatic pig feeders market by product type can be segmented into dry feeders, wet/dry feeders, and liquid feeders. Dry feeders are currently the most widely used type due to their simplicity and cost-effectiveness. These feeders are particularly popular in small to medium-sized farms where the primary goal is to reduce labor costs and improve feeding efficiency. Dry feeders are easy to maintain and can be used with a variety of feed types, making them a versatile option for many farmers.

Wet/dry feeders are gaining traction due to their ability to provide both dry feed and water simultaneously. This type of feeder helps in reducing feed wastage and ensures that pigs have access to both feed and water at all times. Wet/dry feeders are particularly beneficial in large-scale commercial farming operations where the focus is on maximizing prod

The present study is an attempt to present the development of German livestock since the beginning of the 19th century in numbers and partly also graphically. As the objective of the investigation was to describe this development in broad terms it is based on 20 years intervals. “The information starts in 1816 because an earlier start did not seem appropriate as a consequence of the war years. The following evaluation years are 1833, 1853, 1873, 1892, 1913 and 1927. For processing the data material an appropriate demarcation of the geographical districts was of crucial importance. An appropriate unit for Prussia and Bavaria is a government district (Regierungsbezirk), for Saxony the district office (Kreishauptmannschaft), for Württemberg the district (Kreis), for Baden the federal commissioner district (Landeskommissarbezirk), for Hesse the province (Provinz) for Oldendburg the region (Landesteil) and for Alsace-Lorraine the district (Bezirk). The other regions were not subdivided. The Thuringian States have always been combined into one unit. All regions were defined after the administrative division of 1927. For Baden an earlier administrative division in 11 districts was translated into the division in four federal commissioner districts of 1927” (Ritter, a. cit., p. 5 f.).

As an Introduction to the investigation an overview over the territory size of the relevant districts will be given. This data is based on the sizes of 1927; the whole district designation is based on this year. In those tables you also find data about the population in the different districts for different years of censuses because the data of the density of livestock becomes more meaningful in combination with data about population density. For the years after the foundation of the German Empire the results of the censuses for the years of 1871, 1890, 1910 and 1925 were used. It was always possible to use numbers of population level, which are only few years away from the respective livestock census years. The population level before the foundation of the German Empire was determined through a compilation of the results of censuses of the different districts. A uniform count for all German states was first performed on December 3, 1867. For the data by the year 1833, the first of the three-year census of the Zollverein in 1834 served as a basis. Also for the numbers around 1816 appropriate data was available, partly because there was a census in Prussia in 1816.

In the description of the development of livestock horses, cattle, sheep, pigs and goats for all years of evaluation and chicken for 1912 and 1927 were taken into account. Mules and donkeys are not included due to their small importance; as well as all types of poultry besides - chickens - and bees and rabbits are not included, especially since there is no satisfactory information for the early years. Prussia started to identify spring cattle only in 1897(the first comprehensive census in the German Empire was carried out in 1900 with regard to the upcoming trade agreements; the first census for bees in the German Empire was carried out in 1873).
“We did not succeed in fining reliable data for all regions for the time around 1916 and 1833; also for the time around 1853, some gaps still remained. However, a look at the tables on the quantities of individual livestock species shows that the missing data is almost always from small regions with little importance in the overall framework.” (Ritter, a. cit., p. 4).

The basis of the representation is for all livestock species always the total number of stocks (numbers in thousands). To clearly highlight the importance of the data on the number of the different livestock species in different districts and the quantities of each livestock species per 100 inhabitants was calculated. Another part of the table describes the relations between different cattle species. “To clarify the business side of the development of the livestock sector in the last part of the study the stock of cattle of the different species is presented in relation to each of 100 cattle. Thereby a process was pursued and developed further, which for the first time was used by Th. H. Engelbrecht in his study; "The Country of the building zones except tropical countries". Besides also young cattle was recorded. In addition, the number of foals per 100 horses is given.” (Ritter, a. cit., p 10).

Data tables in HISTAT: A. Territory and population A.01 Territory in squ...

Abstract

The Annual Agricultural Sample Survey (AASS) for the year 2022/23 aimed to enhance the understanding of agricultural activities across the United Republic of Tanzania by collecting comprehensive data on various aspects of the agricultural sector. This survey is crucial for policy formulation, development planning, and service delivery, providing reliable data to monitor and evaluate national and international development frameworks.

The 2022/23 survey is particularly significant as it informs the monitoring and evaluation of key agricultural development strategies and frameworks. The collected data will contribute to the Tanzania Development Vision 2025, Zanzibar Development Vision 2020, the Five-Year Development Plan 2021/22–2025/26, the National Strategy for Growth and Reduction of Poverty (NSGRP) known as MKUKUTA, and the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) known as MKUZA. The survey data also supports the evaluation of Sustainable Development Goals (SDGs) and Comprehensive Africa Agriculture Development Programme (CAADP). Key indicators for agricultural performance and poverty monitoring are directly measured from the survey data.

The 2022/23 AASS provides a detailed descriptive analysis and related tables on the main thematic areas. These areas include household members and holder identification, field roster, seasonal plot and crop rosters (Vuli, Masika, and Dry Season), permanent crop production, crop harvest use, seed and seedling acquisition, input use and acquisition (fertilizers and pesticides), livestock inventory and changes, livestock production costs, milk and eggs production, other livestock products, aquaculture production, and labor dynamics. The 2022/23 AASS offers an extensive dataset essential for understanding the current state of agriculture in Tanzania. The insights gained will support the development of policies and interventions aimed at enhancing agricultural productivity, sustainability, and the livelihoods of farming communities. This data is indispensable for stakeholders addressing challenges in the agricultural sector and promoting sustainable agricultural development.

Statistical Disclosure Control (SDC) methods have been applied to the microdata, to protect the confidentiality of the individual data collected. Users must be aware that these anonymization or SDC methods modify the data, including suppression of some data points. This affects the aggregated values derived from the anonymized microdata, and may have other unwanted consequences, such as sampling error and bias. Additional details about the SDC methods and data access conditions are provided in the data processing and data access conditions below.

Geographic coverage

National, Mainland Tanzania and Zanzibar, Regions

Analysis unit

Households for Smallholder Farmers and Farm for Large Scale Farms

Universe

The survey covered agricultural households and large-scale farms.

Agricultural households are those that meet one or more of the following two conditions: a) Have or operate at least 25 square meters of arable land, b) Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agriculture year.

Large-scale farms are those farms with at least 20 hectares of cultivated land, or 50 herds of cattle, or 100 goats/sheep/pigs, or 1,000 chickens. In addition to this, they should fulfill all of the following four conditions: i) The greater part of the produce should go to the market, ii) Operation of farm should be continuous, iii) There should be application of machinery / implements on the farm, and iv) There should be at least one permanent employee.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used to extract the sample for the Annual Agricultural Sample Survey (AASS-2022/23) in Tanzania was derived from the 2022 Population and Housing Census (PHC-2022) Frame that lists all the Enumeration Areas (EAs/Hamlets) of the country. The AASS 2022/23 used a stratified two-stage sampling design which allows to produce reliable estimates at regional level for both Mainland Tanzania and Zanzibar.

In the first stage, the EAs (primary sampling units) were stratified into 2-3 strata within each region and then selected by using a systematic sampling procedure with probability proportional to size (PPS), where the measure of size is the number of agricultural households in the EA. Before the selection, within each stratum and domain (region), the Enumeration Areas (EAs) were ordered according to the codes of District and Council which reflect the geographical proximity, and then ordered according to the codes of Constituency, Division, Wards, and Village. An implicit stratification was also performed, ordering by Urban/Rural type at Ward level.

In the second stage, a simple random sampling selection was conducted . In hamlets with more than 200 households, twelve (12) agricultural households were drawn from the PHC 2022 list with a simple random sampling without replacement procedure in each sampled hamlet. In hamlets with 200 households or less, a listing exercise was carried out in each sampled hamlet, and twelve (12) agricultural households were selected with a simple random sampling without replacement procedure. A total of 1,352 PSUs were selected from the 2022 Population and Housing Census frame, of which 1,234 PSUs were from Mainland Tanzania and 118 from Zanzibar. A total number of 16,224 agricultural households were sampled (14,808 households from Mainland Tanzania and 1,416 from Zanzibar).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022/23 Annual Agricultural Survey used two main questionnaires consolidated into a single questionnaire within the CAPIthe CAPI System, Smallholder Farmers and Large-Scale Farms Questionnaire. Smallholder Farmers questionnaire captured information at household level while Large Scale Farms questionnaire captured information at establishment/holding level. These questionnaires were used for data collection that covered core agricultural activities (crops, livestock, and fish farming) in both short and long rainy seasons. The 2022/23 AASS questionnaire covered 23 sections which are:

1. COVER; The cover page included the title of the survey, survey year (2022/23), general instructions for both the interviewers and respondents. It sets the context for the survey and also it shows the survey covers the United Republic of Tanzania.
2. SCREENING: Included preliminary questions designed to determine if the respondent or household is eligible to participate in the survey. It checks for core criteria such as involvement in agricultural activities.
3. START INTERVIEW: The introductory section where basic details about the interview are recorded, such as the date, location, and interviewer’s information. This helped in the identification and tracking of the interview process.
4. HOUSEHOLD MEMBERS AND HOLDER IDENTIFICATION: Collected information about all household members, including age, gender, relationship to the household head, and the identification of the main agricultural holder. This section helped in understanding the demographic composition of the agriculture household.
5. FIELD ROSTER: Provided the details of the various agricultural fields operated by the agriculture household. Information includes the size, location, and identification of each field. This section provided a comprehensive overview of the land resources available to the household.
6. VULI PLOT ROSTER: Focused on plots used during the Vuli season (short rainy season). It includes details on the crops planted, plot sizes, and any specific characteristics of these plots. This helps in assessing seasonal agricultural activities.
7. VULI CROP ROSTER: Provided detailed information on the types of crops grown during the Vuli season, including quantities produced and intended use (e.g., consumption, sale, storage). This section captures the output of short rainy season farming.
8. MASIKA PLOT ROSTER: Similar to Section 4 but focuses on the Masika season (long rainy season). It collects data on plot usage, crop types, and sizes. This helps in understanding the agricultural practices during the primary growing season.
9. MASIKA CROP ROSTER: Provided detailed information on crops grown during the Masika season, including production quantities and uses. This section captures the output from the main agricultural season.
10. PERMANENT CROP PRODUCTION: Focuses on perennial or permanent crops (e.g., fruit trees, tea, coffee). It includes data on the types of permanent crops, area under cultivation, production volumes, and uses. This section tracks long-term agricultural investments.
11. CROP HARVEST USE: In this, provided the details how harvested crops are utilized within the household. Categories included consumption, sale, storage, and other uses. This section helps in understanding food security and market engagement.
12. SEED AND SEEDLINGS ACQUISITION: Collected information on how the agriculture household acquires seeds and seedlings, including sources (e.g., purchased, saved, gifted) and types (local, improved, etc). This section provided insights into input supply chains and planting decisions based on the households, or head.
13. INPUT USE AND ACQUISITION (FERTILIZERS AND PESTICIDES): It provided the details of the use and acquisition of agricultural inputs such as fertilizers and pesticides. It included information on quantities used, sources, and types of inputs. This section assessed the input dependency and agricultural practices.
14. LIVESTOCK IN STOCK AND CHANGE IN STOCK: The questionnaire

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