Information detailing the management of livestock through grazing, land management and regulated facilities.

This statistic displays the market share of standalone software applications in livestock monitoring and management worldwide in 2016 and 2021, by delivery model market. In 2016, the on-cloud standalone delivery systems held a ** percent share of the standalone software market for livestock monitoring and management.

The livestock management app market is booming, projected to reach $4 billion by 2033. Discover key trends, leading companies (Farm4Trade, Novastock, Ranch Manager Open, etc.), and regional market share insights in this comprehensive market analysis. Learn how these apps are revolutionizing farming with AI, GPS tracking, and data-driven decision-making.

This statistic displays the market share of hardware and systems applications in livestock monitoring and management worldwide in 2016 and 2021, by technology. In 2016, sensors held a ** percent share of the hardware and systems technology segment of the livestock monitoring and management market worldwide.

The global Cattle Management Software market, valued at $1.76 billion in 2025, is projected to experience robust growth, driven by a Compound Annual Growth Rate (CAGR) of 9.81% from 2025 to 2033. This expansion is fueled by several key factors. Increasing adoption of precision livestock farming techniques, coupled with the rising demand for efficient resource management and improved animal health, are major drivers. The market is witnessing a shift towards cloud-based solutions, offering enhanced scalability, accessibility, and data analytics capabilities compared to on-premise systems. Furthermore, the growing availability of affordable internet connectivity and mobile devices in rural areas is facilitating broader market penetration, particularly among smaller farms and individual livestock owners. The integration of IoT sensors, AI, and machine learning into these software solutions is further accelerating market growth, providing farmers with real-time data-driven insights into animal health, productivity, and resource consumption, leading to optimized operations and increased profitability. Different segments within the market, including dairy and meat sectors, along with various end-users like farm owners and dairy managers, are all contributing to this overall growth. However, factors like the high initial investment costs associated with software implementation and the digital literacy gap among some farmers could potentially act as market restraints. Despite these potential restraints, the market's growth trajectory remains positive, particularly in regions like North America and Europe, which are characterized by high technological adoption rates and established agricultural practices. The Asia-Pacific region, however, presents a significant opportunity for future expansion, driven by increasing livestock populations and rising government initiatives promoting technological advancements in agriculture. The competitive landscape is dynamic, with a blend of established players like Merck & Co Inc and GEA Group AG and emerging technology providers like Chetu and smaXtec animal care GmbH, leading to continuous innovation and market evolution. The increasing focus on data-driven decision-making in the livestock industry will further propel the demand for sophisticated cattle management software solutions in the coming years. The market's diversification across sectors, software types, and end-users ensures its long-term sustainability and growth potential. Recent developments include: May 2024: AgriWebb, an AgTech software platform for the livestock industry, secured AUD 11 million (USD 7.3 million) in funding from existing investors Germin8 Ventures, Grosvenor Food & AgTech, and Telus Ventures, and new investor, Sweden-based industrial company Munters Group.July 2023: AgriEID, a livestock management software provided in Australia, released its new next-generation cattle scales and integrated software platform. This platform improved how farmers manage their herds, making professional data collection and analytics more accessible and affordable.. Key drivers for this market are: Growing Need for Cattle Management Software, Increasing Demand for Improved Efficiency and Enhance Farm Profitability. Potential restraints include: Growing Need for Cattle Management Software, Increasing Demand for Improved Efficiency and Enhance Farm Profitability. Notable trends are: The Dairy Segment is Expected to Witness Significant Growth During the Forecast Period.

In recent years, the Livestock Management System (LMS) market has been gaining significant traction as the agricultural industry seeks more efficient ways to manage animal health, nutrition, breeding, and overall productivity. These advanced systems leverage technology to provide farmers and livestock producers with

This dataset brings together cattle health records, feeding patterns, and milk yield statistics to support innovation in precision livestock farming 🐄.

With this data, you can:

🔹 Predict milk production using feeding and health indicators.

🔹 Detect early signs of diseases through anomaly detection.

🔹 Explore the relationship between nutrition, health, and productivity.

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What’s inside?

🥛 Milk yield and productivity data

🌿 Feeding habits (intake levels, nutrient composition, feed type)

💉 Health conditions, symptoms, and treatments

🌍 Management & environmental factors affecting cattle

This dataset is designed for data scientists, veterinarians, agri-tech researchers, and machine learning enthusiasts who are passionate about building solutions in animal health monitoring and smart dairy farming.

The global livestock management system market is booming, projected to reach $6 billion by 2033 with a CAGR of 10%. Driven by technological advancements and a rising demand for efficient farming, this market analysis reveals key trends, restraints, and leading companies shaping the future of livestock farming. Explore the insights and data on temperature monitoring, humidity monitoring, and security monitoring systems.

The Precision Livestock Farming (PLF) market is experiencing robust growth, driven by increasing demand for efficient and sustainable livestock production. Technological advancements in sensors, data analytics, and automation are revolutionizing farm management practices, leading to improved animal health, enhanced productivity, and reduced operational costs. The market is segmented by technology (e.g., wearable sensors, automated feeding systems, robotic milking), animal type (dairy cattle, beef cattle, swine, poultry), and application (monitoring, management, prediction). Major players like Quantified AG, Allflex, and Datamars are driving innovation and market penetration through their advanced solutions. The market's expansion is further fueled by government initiatives promoting sustainable agriculture and the growing awareness among farmers about the benefits of data-driven decision-making. A conservative estimate based on current market trends suggests a market size of approximately $2.5 billion in 2025, with a projected Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching over $8 billion by 2033. Despite significant market potential, challenges remain. High initial investment costs for technology adoption and the need for robust internet connectivity in rural areas pose significant hurdles. Data security and privacy concerns, along with the need for skilled labor to effectively utilize and interpret the data generated by PLF systems, also represent obstacles to widespread adoption. However, ongoing technological improvements, decreasing costs of sensors and analytics, and increased farmer education are expected to address these challenges, leading to continued market growth in the foreseeable future. The competitive landscape is characterized by both established players and emerging technology companies, fostering innovation and diverse solutions for various livestock farming needs. Regional variations in adoption rates are expected, influenced by factors such as agricultural practices, technological infrastructure, and government support.

Discover the booming digital livestock monitoring market! This comprehensive analysis reveals a projected $5 billion market by 2033, driven by technological advancements and a growing demand for efficient livestock management. Learn about key trends, major players like Allflex & Datamars, and regional market shares.

The effects of stocking rate on livestock performance and profitability were monitored on 12 pastures at the Central Grasslands Research Extension Center (CGREC) near Streeter, ND from 1989 through 2015. These data were produced from an investigation of how the impacts of grazing intensity on native range, in addition to an economic component, was included to determine grazing intensity effect on animal production. Cattle were raised at the CGREC or purchased at auction. Livestock cattle breeds are unknown, but can be described as either yearling open heifer, bred heifers or all steers. 1994 was the only year when the herds were mixed sexes. A table of stocking history is available with this data package as a supplemental dataset called: StockingHistory1989-2015.csv. Information on pasture acreage and the proportion of acres in various ecological range sites, as well as stocking rates, are included as supplemental datasets and are called, respectively: Pasture_and_RangeSites.csv and Revised_AUM_Cals.csv This data package supports papers reporting the response of livestock performance as ADG (average daily weight gain) and production as weight gain per unit land area to cattle grazing on northern mixed-grass prairie in south-central North Dakota that was subsequently invaded by Kentucky bluegrass (Poa pratensis L.) in 1995. Grazing traditionally occurred mid-May until mid-October in 12 pastures, each approximately 30 acres. The goal of managing grazing intensity was to leave a certain percentage of forage produced in that year OR relative to an average year on the pasture. This was achieved by adjusting stocking rate (i.e. number of individuals per area) within each pasture. When necessary as in 2015, animals were supplemented with dried distiller’s grain at .3% of body weight each day. An animal unit month was used to determine stocking rates and is defined as the forage required to sustain a 1,000 lb cow and her calf for one month. This assumes they require 26 lbs/day of forage on a dry matter basis. This forage amount was based on metabolic weight of animals in this study, including a 1200lb cow as 1.147 AUMs and a 700 lb steer or open heifer as.765 AUM. Five grazing intensities included: no grazing, light grazing (1.3 animal unit months [AUM] · ha-1 with 65% of forage left in the fall), moderate grazing (2.7 AUM · ha-1 with 50% of forage left in the fall), heavy grazing (4.4 AUM · ha-1 with 35% of forage left in fall), and extreme grazing (6.9 AUM · ha-1 with 20% of forage left in the fall). Resources in this dataset:Resource Title: Descriptions of pasture and rangelands sites. File Name: Pasture_and_RangeSites.csvResource Description: These data are supplemental to livestock production and provide descriptions of pasture and rangeland ecological sites on which cattle grazed.Resource Title: Data dictionary for descriptions of pasture and rangelands sites. File Name: Pasture_and_RangeSites_DataDict.csvResource Description: Column header definitions for descriptions of pasture and rangelands sitesResource Title: Stocking history (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: StockingHistory1989-2015.csvResource Description: These are supplemental data to describe stocking history (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota Resource Title: Data dictionary for the stocking history (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: StockingHistory1989-2015_DataDict.csvResource Description: Column headers defined for the stocking history (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota Resource Title: Stocking rates (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: AUM_Calcs_AUMperAcre.csvResource Description: Stocking rates (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota reported for each grazing treatment in acres required to provide forage, as well as a mean stocking rate calculated with AUM/acre and as the inverse of the number of acres provided.Resource Title: Data dictionary for stocking rates (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: AUM_Calcs_DataDict_AUMperAcre.csvResource Description: Column headers defined for stocking rates (1989-2015) for pastures at the Central Grasslands Research Extension Center near Streeter, North Dakota Resource Title: 27 years of livestock production data under different stocking rate levels at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: Streeter-ND_1989-2015_compiled.csvResource Description: Compiled data for 27 years of livestock production data under different stocking rate levels at the Central Grasslands Research Extension Center near Streeter, North Dakota. Multiple data dictionaries are available to supplement these data, including descriptions of ecological sites, the stocking history, and stocking rates for each grazing treatment. Resource Title: Data dictionary for 27 years of livestock production data under different stocking rate levels at the Central Grasslands Research Extension Center near Streeter, North Dakota . File Name: Streeter-ND_1989-2015_compiled_DataDict.csvResource Description: Columns headers defined for compiled 27 years of livestock production data under different stocking rate levels at the Central Grasslands Research Extension Center near Streeter, North Dakota

Namibia Compact - Community-Based Rangeland & Livestock Management

Statistical relationships between sex and livestock management factors.

Livestock Farm Management Software Market Outlook

The global market size for Livestock Farm Management Software is anticipated to grow significantly from USD 1.2 billion in 2023 to USD 3.8 billion by 2032, with a robust CAGR of 13.5% during the forecast period. The growth of this market is fueled by technological advancements in agriculture, increasing demand for livestock products, and the adoption of precision farming practices.

One of the primary growth factors for the Livestock Farm Management Software market is the technological advancement in the agricultural sector. Innovations such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics are transforming traditional farming practices. These technologies enable real-time monitoring and data collection, which help farmers make informed decisions, optimize resource utilization, and enhance productivity. The integration of these advanced technologies into farm management software solutions is significantly boosting market growth.

Another key driver for the market is the increasing demand for livestock products such as meat, dairy, and eggs. With the global population on the rise and an increasing awareness of the nutritional benefits of animal products, the demand for livestock products is expected to grow. This surge in demand necessitates efficient livestock management practices to ensure high-quality production, animal health, and sustainability. Livestock farm management software provides the tools needed to monitor and manage various aspects of livestock farming, thereby supporting the growing demand.

The adoption of precision farming practices is also contributing to the growth of the Livestock Farm Management Software market. Precision farming involves the use of advanced technologies and data-driven approaches to optimize agricultural practices. In the context of livestock farming, precision farming techniques help in monitoring animal health, managing feed, tracking breeding activities, and ensuring financial management. The implementation of precision farming practices through software solutions not only enhances farm productivity but also promotes sustainable farming practices.

Farm Accounting Software plays a crucial role in the financial management aspect of livestock farming. As farms grow and operations become more complex, the need for robust accounting solutions becomes evident. This software helps farmers manage their finances by tracking expenses, revenues, and cash flow, ensuring that they maintain a healthy financial status. With features such as budgeting, financial forecasting, and detailed reporting, farm accounting software provides the necessary tools for farmers to make informed financial decisions. The integration of this software with other farm management solutions allows for a seamless flow of information, enhancing overall farm efficiency and productivity. As the demand for transparency and accountability in farming operations increases, the adoption of farm accounting software is expected to rise significantly.

From a regional perspective, North America holds a significant share of the Livestock Farm Management Software market. The region's advanced technological infrastructure, high adoption rate of digital solutions in agriculture, and the presence of major market players contribute to its leading position. Additionally, the growing awareness about the benefits of precision farming and the increasing demand for livestock products further drive market growth in North America. Other regions such as Europe, Asia Pacific, and Latin America are also witnessing substantial growth, driven by similar factors and the increasing focus on sustainable agriculture.

Component Analysis

The Livestock Farm Management Software market is segmented by component into software and services. The software segment encompasses various types of farm management solutions that cater to different aspects of livestock farming. These solutions include herd management software, animal health monitoring software, and feed management software, among others. The software segment is expected to dominate the market due to the increasing adoption of digital solutions for efficient farm management. These software solutions help farmers in data collection, analysis, and decision-making processes, thereby enhancing overall farm productivity.

In the services segment, the market includes various support services such as in

The global livestock management chips market is experiencing robust growth, driven by increasing demand for efficient animal tracking and management solutions. The market, valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching an estimated value exceeding $4.5 billion by 2033. This growth is fueled by several key factors including the rising adoption of precision livestock farming, stringent regulations regarding animal welfare and traceability, and the increasing integration of technology in agricultural practices. Furthermore, the growing demand for enhanced data analytics and improved disease surveillance contributes to the market's expansion. Major players such as Microchip ID Systems, Pethealth Inc., and Datamars, Inc. are driving innovation through the development of advanced chip technologies, fostering competition and driving market expansion. The market segmentation is witnessing a shift towards more sophisticated technologies, such as RFID (Radio-Frequency Identification) and GPS-enabled chips, providing real-time location data and detailed health information. This trend is complemented by the increasing integration of livestock management chips with cloud-based platforms and analytics tools, enabling farmers to make data-driven decisions regarding animal health, breeding, and resource allocation. However, challenges such as high initial investment costs, concerns about data privacy and security, and the need for robust infrastructure in certain regions act as potential restraints to the market's growth. Despite these challenges, the long-term outlook for the livestock management chips market remains positive, driven by continued technological advancements and growing awareness of the benefits of efficient livestock management.

This statistic displays the market value of livestock monitoring and management worldwide from 2016, by product type. In that year, the market value of hardware and systems for the global livestock monitoring industry amounted to about **** billion U.S. dollars.

Established in 1912, the Northern Great Plains Research Laboratory (NGPRL) is a USDA Agricultural Research Service facility located in Mandan, Morton County, North Dakota. In 1916, NGPRL scientists established a long-term rangeland management research project focusing on developing the most appropriate stocking rates for rangelands in the region. The research project ran for 100 years and included pasture 62, a heavily stocked pasture, and 66, a moderately stocked pasture for the entire time. Also, in 1931, pasture 37 was converted from smooth bromegrass to crested wheatgrass, which was both lightly and moderately stocked. NGPRL's grazing season is traditionally May-October which reflects the surrounding region. Animals may be put on slightly later or pulled earlier due to extreme weather conditions or events (e.g. drought, blizzard). The legacy livestock production data from these pastures include 100 years (1916-2016) of livestock production data from pastures 62 and 66 and 84 years (1932-2016) from pasture 37. Pasture 37 was fertilized annually in spring with 40 pounds nitrogen urea [46-0-0] per acre until 2010 and after that it was fertilized intermittently. Grazing treatments on these pastures were applied with stocking rates calculated in 1916 based on 600 lb. animal. Stocking rates were adjusted when pasture sizes were decreased, and this information is included in the data dictionary for the stocking rate and AUM data table. Please note data is missing from 1984 and 1985 from all the pastures. Johnson Thatcher Sarvis established the experiment in 1915 and managed it until 1940. The experiment was continued by George Rogler from 1940 to 1952, Russell Lorenz and George Rogler from 1953 to 1973, Russell Lorenz from 1974 to 1979, Lenat Hofmann from 1980 to 1992, and James Karns from 1993 to 2002. Numerous technicians and part-time students were also involved in the day-to-day management and conduct of the experiment. We would like to recognize these scientists and support staff for their extraordinary foresight and determination in skillfully managing and continuing this experiment into the twenty-first century. Thanks also to Holly Johnson at the Northern Great Plains Research Laboratory for organizing, cataloging, and annotating the publications from the long-term experiment. Resources in this dataset:Resource Title: Legacy Livestock Production . File Name: LegacyProduction.csvResource Description: In 1916 long-term rangeland management research was established to meet the needs of farmers and ranchers in the region. These are the legacy livestock production data from those research pastures, which included pastures: 62, a heavily grazed pasture; 66, a lightly grazed pasture; and 37, a pasture planted with crested wheatgrass and subsequently fertilized was both moderately and lightly grazed. NGPRL's grazing season is traditionally April-October. Resource Title: Data Dictionary Defining Attributes of Legacy Production Data. File Name: DataDictionaryLegacyProduction.csvResource Title: Calendar Dates for Legacy Livestock Production Data. File Name: CalendarDates.csvResource Description: Animals may be put on slightly later or pulled earlier due to extreme weather conditions or events (e.g. drought, blizzard). Resource Title: Data Dictionary for Calendar Dates for Legacy Livestock Production Data. File Name: DataDictionaryCalendarDates.csvResource Title: Animal Unit Months and Stocking Rates for Legacy Livestock Production Data. File Name: AUM_StockingRates.csvResource Description: Pastures 62 and 66 have over one hundred years of data (1916-2016). Pasture 37 was cultivated out of brome-grass in 1931 to plant crested wheatgrass and thus has eighty-four years of data. Pasture 37 was fertilized annually in spring with 40 pounds nitrogen urea [46-0-0] per acre, per year. Grazing treatments on these pastures were applied with stocking rates calculated in 1916 based on 600 lb. animal. Stocking rates were adjusted when pasture sizes were decreased, and this information is included in the data dictionary for the stocking rate and AUM data table. Resource Title: Data Dictionary for Animal Unit Months and Stocking Rates for Legacy Livestock Production Data. File Name: DataDictionaryAUM_StockingRates.csv

Discover the booming Ranch Management System market! This comprehensive analysis reveals key trends, drivers, and restraints shaping this $1.5B+ industry, including insights on leading companies, regional growth, and future forecasts through 2033. Explore the potential of precision agriculture and data-driven livestock management.

The global livestock management chips market is experiencing robust growth, driven by increasing demand for efficient animal tracking and management solutions. The market's expansion is fueled by several factors, including the rising global population and the consequent surge in demand for meat and dairy products. This necessitates optimized livestock farming practices to ensure efficient resource utilization and enhanced productivity. Technological advancements in chip technology, offering improved durability, longer battery life, and enhanced data transmission capabilities, further contribute to market growth. Furthermore, government initiatives promoting animal welfare and traceability are creating a favorable regulatory environment, encouraging the adoption of livestock management chips. The market is segmented based on animal type (cattle, swine, poultry, etc.), chip technology (RFID, microchip, etc.), and geographic location. While precise market sizing requires further data, considering a global market for animal identification and tracking already exceeding several billion dollars, a reasonable estimate for the livestock management chip segment, encompassing a subset of the broader market, would be in the low billions, exhibiting a healthy CAGR (Compound Annual Growth Rate). Key players like Microchip ID Systems, Pethealth Inc., and Datamars, Inc. are actively shaping the market through continuous innovation and strategic partnerships. Challenges faced by the market include the relatively high initial investment costs associated with implementing chip-based livestock management systems, particularly for smaller farms. Concerns regarding data security and privacy related to animal tracking also pose a restraint to widespread adoption. However, the long-term benefits, including improved disease control, enhanced breeding programs, and reduced livestock losses, are steadily overcoming these barriers. The future trajectory of the market is poised for continued expansion, driven by technological improvements, increasing awareness of the benefits, and supportive government policies. Focus on developing cost-effective solutions and addressing data security concerns will be critical for sustaining this growth.