The global livestock identification
market is projected to reach
USD 3.6 billion by 2030 from an estimated USD 1.6 billion in 2022, at a CAGR of
10.5% from 2022 to 2030.
Major factors driving the growth of the market
include large potential to reduce economic losses and livestock mortality rates
due to accurate and efficient animal disease traceability and rapid adoption of
automation technology and IoT-enabled devices for efficient management of
livestock farms.
Driver: Increased focus of livestock farmers on
real-time identification and tracking of animals
Livestock identification is an essential aspect of
livestock farming. Earlier, cattle were identified and traced manually and
confined to farms by building physical fences. However, advanced technologies
have made real-time identification and tracking of farm animals simple and
organized processes. Advanced technology-based devices such as biometric
sensors, including non-invasive or invasive sensors, identify and trace the
health and behavior of individual animals in real-time, allowing farmers to
integrate this data for population-related analysis. The information gathered
from biometric sensors is processed and integrated using big data analytics
systems that rely on statistical algorithms to sort through large complex data
sets and provide farmers with relevant trending patterns and decision-making
tools. Real-time data gathering helps in quicker decision-making and increases
farming efficiency. The data can be used to optimize farm processes, and it
also helps maintain transparency in supply chain management. Sensor-enabled
blockchain technology affords secure and guaranteed traceability of animal
products from farm to table, a key advantage in identifying disease outbreaks
and preventing related economic losses.
Restraint: High cost of electronic identification
devices
The high cost of electronic identification devices
such as RFID tags and readers is one of the major factors impacting the
adoption of livestock identification devices by small farmers or farmers with
limited budgets. Livestock identification solutions are integrated with
high-cost technologies such as RFID, IoT modules, AI, and the cloud to improve
livestock identification and management in less time.
Farm owners who have mostly followed the traditional
identification techniques or visual identification tags find it costly to
install these high-cost devices due to their budget constraints. In unorganized
small- or mid-sized poultry farms, the deployment of various poultry automation
systems impacts poultry farmers’ profit margins because installing such systems
increases the total operating cost.
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Opportunity: Rising number of government initiatives
encouraging livestock identification technology use
Various policies are implemented by governments
across different countries for improving the business profitability and
livelihood of farmers or ranchers. Workshops are arranged by the government
authorities to educate and create awareness among the farmers regarding the
benefits of smart agricultural and digital livestock management techniques. For
instance, New Zealand conducted a workshop on the adoption of technologies for
sustainable farming in 2020. The workshop drew together participants from
agriculture and environment ministries and research institutes from the
Organisation for Economic Co-operation and Development (OECD) member countries.
The workshop formed an integral part of the OECD program of work on agriculture
and the environment under the auspices of the Joint Working Party on
Agriculture and Environment.
Challenge: Limited awareness about benefits of
livestock identification solutions among ranchers and farm owners
Although the livestock identification marketplace is
flooded with various innovative technologies, awareness among livestock farm
owners remains considerably low, which impacts the adoption of digital tools
for herd identification and management. Livestock identification solutions find
applications in almost all functional aspects of cattle, poultry, and swine
farms, such as calf management, behavior monitoring, tracking animals, and
reproduction management. However, farmers are often unable to adopt these
solutions due to budget constraints or limited herd or farm size. In addition,
these livestock identification solutions yield huge volumes of data, which is
difficult for an unprofessional resource to process and understand. Furthermore,
limited awareness and a lack of know-how pertaining to livestock technologies
among farmers is another key factor hampering the growth of the market. Thus,
livestock technologies are adopted at a lower rate by the farmers in emerging
countries due to several factors, including the high cost involved in
automating farms, lack of technical knowledge among farmers, and reluctance in
adopting new farming technologies due to limited skillset and
technology understanding.
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