Smart Agriculture Market Size, Share, Statistics and Industry Growth Analysis Report by Offering (Hardware, Software, Services), Agriculture Type, Farm Size (Large, Medium, Small), Application (Precision Farming, Livestock Monitoring) and Region ( America, Europe, Asia Pacific, Row) - Global Forecast to 2028
Report Code: SE 4043 Mar, 2023, by marketsandmarkets.com
Updated on : September 18, 2024
Smart Agriculture Market Size & Growth
[371 Pages Report] The global smart agriculture market size is projected to reach USD 25.4 billion by 2028 from an estimated USD 16.2 billion in 2023, at a CAGR of 9.4% from 2023 to 2028.
The market growth of the smart agriculture industry can be attributed to the increasing global population creating pressure on food supply system and surging use of modern technologies in agriculture.
Smart Agriculture Market Forecast to 2028
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Smart Agriculture Market Ecosystem
Market Dynamics
Driver: Rising adoption of IoT, ROVs, and AI in aquaculture farming
The global aquaculture industry has witnessed tremendous advancements in aquaculture tools, techniques, and technologies in recent years. The growing inclination of the worldwide population toward consuming a protein-rich diet is consequently increasing the adoption of cutting-edge technologies, such as the Internet of Things (IoT), machine learning, Remotely Operated Vehicles (ROVs), artificial intelligence (AI), automatic feeders, and acoustic telemetry tracking systems, by aquaculture farm owners. The use of these technologies in aquaculture farming helps increase aquaculture production; enhance production efficiency; minimize wastage of resources; and improve accuracy, precision, and repeatability in farming operations while providing high profitability to farm owners.
Restraint: Fragmented agriculture industry
Agriculture is a decentralized industry, with the presence of many large, medium, and small-sized farms that operate independently. This fragmentation makes implementing a standardized machine-to-machine (M2M) solution difficult, as each farm operates differently and may have different requirements. Land fragmentation leads to an improper allocation of input and resources, which further leads to high costs. Implementing smart agricultural technologies in fragmented lands wastes time, money, and resources as managing, supervising, and collecting data from scattered lands is difficult. This also makes it difficult for farmers to attain economies of scale for M2M solutions.
Opportunity: Rising adoption of livestock monitoring solutions in emerging countries
Currently, the adoption of livestock monitoring technology in emerging countries like Brazil and Mexico is slow, primarily due to the high installation cost and low awareness among farmers. However, the growing demand for milk and dairy products, rise in per capita income of farmers, and increasing herd size and livestock farming in these countries, are expected to fuel the demand for livestock monitoring technologies, such as milking robots and feeding robots, in the coming years. The below figure portrays the number of milking robots installed worldwide and expected to be installed in the future.
Challenge: Livestock farming increasing environmental concerns and global warming
Livestock farming contributes 14–15% of the man-made greenhouse-gas emissions that are warming the planet. Animal manure can disrupt the nitrogen cycle or contaminate waterways. Livestock farming has a vast environmental footprint and a negative impact on climate. It also contributes to land and water degradation, biodiversity loss, acid rain, coral reef degeneration, and deforestation. The livestock sector already uses around 10% of global agricultural land and 8% of the total available freshwater. It is also largely responsible for deforestation and biodiversity loss and contributes 15% of global CO2 emissions.
Smart Agriculture Market Segmentation
Services segment is expected to grow at highest CAGR during forecast period
The services segment is expected to grow at the highest CAGR during the forecast period. The growing deployment and installation of precision feeding systems, field and livestock monitoring systems, and robotic systems in farms have led to a surge in demand for specialized services for smart agriculture. In addition, the growing need to train farm laborers to use advanced hardware solutions, increase the shelf-life of smart agriculture hardware, and deploy these solutions in small, medium-sized, and large farms are driving the growth of maintenance and support as well as connectivity and assisted professional services.
Precision aquaculture segment is projected to witness growth at highest CAGR during forecast period
The precision aquaculture segment is projected to witness growth at the highest CAGR during the forecast period. The growth can be attributed to the rising investments in technological research and product innovation, the surging adoption of advanced technologies such as IoT, ROVs, and AI for the real-time monitoring of aquaculture farms, the rising demand for protein-rich aqua food, and increasing support by worldwide governments for infrastructure development in aquaculture.
Smart Agriculture Industry Regional Analysis
Asia Pacific is expected to register highest growth in smart agriculture market share during forecast period
The smart agriculture industry in Asia Pacific is expected to grow at the highest CAGR during the forecast period. The increasing adoption of variable rate technology and smart irrigation controllers, along with AI-based farm analytics services, are some of the major factors propelling the growth of the market in this region. The rising demand for automation of livestock farms and aquaculture farms in this region is further expected to boost the growth of the smart agriculture market in Asia Pacific. In addition, the increasing livestock population and the growing demand for meat products in Asian countries, including China, Australia, India, and Japan, contribute to regional market growth. For instance, the cattle population in China and India increased by 3% and 0.4%, respectively, to reach 98 and 307 million heads in 2022, compared to 95 and 306 million heads in 2021.
Smart Agriculture Market Statistics by Region
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Top Smart Agriculture Companies - Key Market Players
The smart agriculture companies players have implemented various types of organic as well as inorganic growth strategies, such as new product launches, contracts, agreements, alliances, collaborations, joint ventures, partnerships, expansions, investments, and acquisitions to strengthen their offerings in the market.
Some of the key players in the smart agriculture companies are
- Deere & Company (US),
- Trimble Deere & Company (US),
- Trimble Inc. (US),
- AGCO Corporation (US),
- Topcon Positioning Systems (US),
- DeLaval (Sweden),
- AKVA Group (Norway),
- Allflex Livestock Intelligence (US),
- Innovasea Systems Inc. (US),
- Afimilk Ltd. (Israel),
- Heliospectra AB (Sweden).
The study includes an in-depth competitive analysis of these key players in the smart agriculture market with their company profiles, recent developments, and key market strategies.
Smart Agriculture Market Report Scope
|
Report Metric |
Details |
|
Estimated Market Size |
USD 16.2 billion |
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Expected Market Size |
USD 25.4 billion |
|
Growth Rate |
CAGR of 9.4% |
|
Market Size Available for Years |
2019–2028 |
|
Base Year |
2022 |
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Forecast Period |
2023–2028 |
|
Units |
Value (USD Million/USD Billion) |
|
Segments Covered |
|
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Regions Covered |
|
|
Market Leaders |
DeLaval (Sweden), AKVA Group (Norway), Afimilk Ltd. (Israel), and Heliospectra AB (Sweden) |
|
Top Companies in North America |
Deere & Company (US), Trimble Inc. (US), AGCO Corporation (US), Topcon Positioning Systems (US), Allflex Livestock Intelligence (US), Innovasea Systems Inc. (US). |
|
Key Market Driver |
Rising adoption of IoT, ROVs, and AI in aquaculture farming |
|
Key Market Opportunity |
Rising adoption of livestock monitoring solutions in emerging countries |
|
Largest Growing Region |
Asia Pacific |
|
Hightest Market CAGR |
Precision Aquaculture Segment |
Smart Agriculture Market Highlights
This research report categorizes the smart agriculture market based on offering, agriculture type, farm size, application, and region.
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Segment |
Subsegment |
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Based on by Offering |
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Based on Agriculture Type |
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Based on Farm Size |
|
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Based on Application |
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Based on Region |
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Recent Developments in Smart Agriculture Industry
- In October 2022, Trimble Inc. launched new displays, GFX-1060 and GFX-1260, for precision agriculture applications. Farmers can carry out in-field tasks swiftly and effectively with these next-generation displays, allowing them to map and monitor field data in real time precisely..
- In September 2022, Deere & Company launched three new self-propelled forage harvesters to its existing lineup. They are designed to address the requirements of dairy and livestock producers, contractors, and harvesters to overcome challenges such as shorter harvesting windows, a smaller pool of skilled workers, and increased operating costs.
- In April 2021, Topcon Positioning Systems launched the manual guidance and autosteering receivers—the AGM 1 and AGS 2, and new Topnet Live cellular, satellite, and bridging correction services—Realpoint, Starpoint, and Skybridge. The new AGM 1 and AGS 2 are used for machine operations and all associated tasks where tracking location data is relevant to crop optimization, including soil preparation, seeding, crop care, and harvesting. They deliver reliable connection stability worldwide through a constantly improving network and a variety of cost-effective subscription models.
- In February 2021, AKVA Group signed a five-year agreement with Trollvika Drift AS to install 45 SmartEye Precision HD cameras with AKVAconnect 4 camera system controls at the Enkeltstein, Ystevika, Trollvika, and Svartskjær in Troms, Northern Norway locations.
- In December 2020, Afimilk Ltd. and Livestock Improvement Corporation (LIC), a herd improvement and agri-tech cooperative, signed a distributive partnership. According to the partnership, LIC will market Afimilk's AfiCollar in New Zealand.
Frequently Asked Questions (FAQ):
What is the market size of smart agriculture market?
In 2023, the smart agriculture market was valued USD 16.2 billion and is projected to reach USD 25.4 billion by 2028.
Who are the key players in the smart agriculture market share?
Deere & Company (US), Trimble Inc. (US), AGCO Corporation (US), Topcon Positioning Systems (US), DeLaval (Sweden), are some of the key players in the smart agriculture market.
What are the trends in the smart agriculture market share?
Integration of 5G, IoT, AI, and Machine learning in agriculture equipment and machinery is enabling users to obtained enhanced yield and reduced operational costs. Furthermore, emergence of agriculture 4.0 is to transform the global agriculture sector.
What are the major opportunities for the focused ion beam market?
Rising adoption of livestock monitoring solutions in emerging countries and growing use of unmanned aerial vehicles or drones in agricultural farms are among the key opportunities that are expected to support market growth in future.
What are the growing applications in the smart agriculture market share?
The smart agriculture market is led by precision farming segment. Besides, the demand from precision aquaculture segment is expected to generate huge demand for advanced aquaculture solutions in future.
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 39)
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
1.3.2 GEOGRAPHIC SCOPE
1.3.3 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 UNITS CONSIDERED
1.6 STAKEHOLDERS
1.7 SUMMARY OF CHANGES
1.7.1 RECESSION IMPACT
2 RESEARCH METHODOLOGY (Page No. - 45)
2.1 RESEARCH DATA
FIGURE 1 SMART AGRICULTURE MARKET: RESEARCH DESIGN
2.1.1 SECONDARY AND PRIMARY RESEARCH
2.1.2 SECONDARY DATA
2.1.2.1 Secondary sources
2.1.2.2 List of key secondary sources
2.1.3 PRIMARY DATA
2.1.3.1 Primary interviews with experts
2.1.3.2 List of key primary respondents
2.1.3.3 Breakdown of primaries
2.1.3.4 Key data from primary sources
2.1.3.5 Key industry insights
2.2 FACTOR ANALYSIS
FIGURE 2 MARKET SIZE ESTIMATION METHODOLOGY: APPROACH 1 – TOP-DOWN (SUPPLY SIDE): REVENUES GENERATED BY COMPANIES FROM SALES OF SMART AGRICULTURE SOLUTIONS
FIGURE 3 MARKET SIZE ESTIMATION METHODOLOGY: APPROACH 1 – TOP-DOWN (SUPPLY SIDE): ILLUSTRATION OF REVENUE ESTIMATIONS FOR DEERE & COMPANY IN MARKET
2.3 MARKET SIZE ESTIMATION
2.3.1 BOTTOM-UP APPROACH
2.3.1.1 Approach to obtain market size using bottom-up analysis (demand side)
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH
2.3.2 TOP-DOWN APPROACH
2.3.2.1 Approach to obtain market size using top-down analysis (supply side)
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH
2.3.3 MARKET GROWTH PROJECTIONS AND FORECAST ASSUMPTIONS
TABLE 1 MARKET GROWTH PROJECTIONS AND FORECAST ASSUMPTIONS
2.4 MARKET BREAKDOWN AND DATA TRIANGULATION
FIGURE 6 DATA TRIANGULATION
2.5 RESEARCH ASSUMPTIONS
2.6 RESEARCH LIMITATIONS
2.7 RISK ASSESSMENT
TABLE 2 RISK FACTOR ANALYSIS
2.8 IMPACT OF RECESSION ON SMART AGRICULTURE MARKET
3 EXECUTIVE SUMMARY (Page No. - 61)
3.1 OVERVIEW OF RECESSION IMPACT ON SMART AGRICULTURE MARKET
3.1.1 GLOBAL ECONOMY OUTLOOK
3.1.2 PRE-RECESSION SCENARIO
3.1.3 POST-RECESSION SCENARIO
FIGURE 7 GROWTH PROJECTION OF MARKET IN PRE- AND POST-RECESSION SCENARIOS
FIGURE 8 SERVICES SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 9 PRECISION FARMING SEGMENT TO LEAD MARKET FROM 2023 TO 2028
FIGURE 10 SMALL FARMS TO EXHIBIT HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 11 ASIA PACIFIC TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
4 PREMIUM INSIGHTS (Page No. - 66)
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN SMART AGRICULTURE MARKET
FIGURE 12 RISING GLOBAL POPULATION AND EMERGENCE OF AGRICULTURE 4.0 TO FUEL MARKET GROWTH
4.2 MARKET, BY OFFERING
FIGURE 13 HARDWARE SEGMENT TO DOMINATE MARKET DURING FORECAST PERIOD
4.3 MARKET, BY AGRICULTURE TYPE
FIGURE 14 PRECISION FARMING PROJECTED TO LEAD SMART AGRICULTURE MARKET FROM 2023 TO 2028
4.4 MARKET, BY FARM SIZE
FIGURE 15 MEDIUM-SIZED FARMS TO DOMINATE SMART AGRICULTURE MARKET DURING FORECAST PERIOD
4.5 MARKET, BY REGION
FIGURE 16 AMERICAS TO CAPTURE LARGEST MARKET SHARE FROM 2023 TO 2028
4.6 SMART AGRICULTURE MARKET, BY COUNTRY
FIGURE 17 CHINA TO REGISTER FASTEST GROWTH DURING FORECAST PERIOD
5 MARKET OVERVIEW (Page No. - 69)
5.1 INTRODUCTION
5.2 DEVELOPMENT OF SMART AGRICULTURE PRACTICES
FIGURE 18 EVOLUTION OF SMART AGRICULTURE
5.3 MARKET DYNAMICS
FIGURE 19 SMART AGRICULTURE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
5.3.1 DRIVERS
5.3.1.1 Increasing global population creating pressure on food supply system
FIGURE 20 GLOBAL CONSUMPTION OF MAJOR FIELD CROPS, 2005–2050
5.3.1.2 Shortage of skilled labor in agriculture sector
5.3.1.3 Surging use of modern technologies in agriculture
5.3.1.4 Benefits offered by livestock monitoring solutions
5.3.1.5 Rising adoption of IoT, ROVs, and AI in aquaculture farming
FIGURE 21 MARKET: DRIVERS AND THEIR IMPACT
5.3.2 RESTRAINTS
5.3.2.1 High cost of smart agriculture solutions
5.3.2.2 Fragmented agriculture sector
FIGURE 22 MARKET: RESTRAINTS AND THEIR IMPACT
5.3.3 OPPORTUNITIES
5.3.3.1 Growing vegetarian and vegan population
FIGURE 23 TOTAL NUMBER OF PARTICIPANTS IN VEGANUARY PROGRAM, 2014–2022
5.3.3.2 Rising adoption of livestock monitoring solutions in emerging countries
FIGURE 24 GLOBAL MILKING ROBOTS INSTALLED BASE, 2017–2030 (UNITS)
5.3.3.3 Growing use of UAVs or drones in agricultural activities
5.3.3.4 Increasing popularity of land-based recirculating aquaculture systems
FIGURE 25 MARKET: OPPORTUNITIES AND THEIR IMPACT
5.3.4 CHALLENGES
5.3.4.1 Reduced profitability due to rising cost of cattle feed
FIGURE 26 TOTAL PRICE OF FEED (INDEX), 2011–2023
5.3.4.2 Adverse impact of livestock farming on environment
FIGURE 27 SMART AGRICULTURE MARKET: CHALLENGES AND THEIR IMPACT
5.4 SUPPLY CHAIN ANALYSIS
FIGURE 28 SMART AGRICULTURE MARKET: SUPPLY CHAIN ANALYSIS
5.4.1 MAJOR STAKEHOLDERS IN SMART AGRICULTURE MARKET
5.5 ECOSYSTEM MAPPING
FIGURE 29 SMART AGRICULTURE ECOSYSTEM
TABLE 3 SMART AGRICULTURE ECOSYSTEM
5.6 PRICING ANALYSIS
TABLE 4 AVERAGE SELLING PRICES OF SMART AGRICULTURE SOLUTIONS, BY HARDWARE OFFERING
FIGURE 30 AVERAGE SELLING PRICE TREND FOR SMART AGRICULTURE HARDWARE OFFERINGS, 2019–2028 (USD)
FIGURE 31 PRECISION FARMING DATA ANALYTICS SERVICE COST PER HECTARE FOR DIFFERENT FARM SIZES IN 2021
5.7 REVENUE SHIFT AND NEW REVENUE POCKETS FOR PLAYERS IN MARKET
FIGURE 32 REVENUE SHIFT IN MARKET
5.8 TECHNOLOGICAL TRENDS
5.8.1 INTERNET OF THINGS (IOT)
5.8.2 M2M SOLUTIONS
FIGURE 33 INCREASING USE OF M2M SOLUTIONS IN AGRICULTURE—LEADING TREND AMONG KEY MARKET PLAYERS
5.8.3 ROBOTICS
5.8.4 AI AND BLOCKCHAIN IN LIVESTOCK FARMING
FIGURE 34 BLOCKCHAIN AND AI IN LIVESTOCK MONITORING
5.8.5 ADOPTION OF ROBOTIC CAGES AND UNDERWATER DRONES IN AQUACULTURE FARMS
5.8.6 INTEGRATION OF TELEMATICS WITH FOREST MECHANIZATION IN PRECISION FORESTRY
5.8.7 ADVENT OF LIDAR-FITTED UAVS IN PRECISION FORESTRY
5.9 PORTER’S FIVE FORCES ANALYSIS
FIGURE 35 SMART AGRICULTURE MARKET: PORTER’S FIVE FORCES ANALYSIS
TABLE 5 MARKET: PORTER’S FIVE FORCES ANALYSIS
5.9.1 INTENSITY OF COMPETITIVE RIVALRY
5.9.2 BARGAINING POWER OF SUPPLIERS
5.9.3 BARGAINING POWER OF BUYERS
5.9.4 THREAT OF SUBSTITUTES
5.9.5 THREAT OF NEW ENTRANTS
5.10 KEY STAKEHOLDERS AND BUYING CRITERIA
5.10.1 KEY STAKEHOLDERS IN BUYING PROCESS
FIGURE 36 INFLUENCE OF STAKEHOLDERS IN BUYING PROCESS, BY APPLICATION
TABLE 6 INFLUENCE OF STAKEHOLDERS IN BUYING PROCESS, BY APPLICATION (%)
5.10.2 BUYING CRITERIA
FIGURE 37 KEY BUYING CRITERIA, BY APPLICATION
TABLE 7 KEY BUYING CRITERIA, BY APPLICATION
5.11 CASE STUDY ANALYSIS
5.11.1 INTRODUCTION
5.11.2 OPEN BLUE
TABLE 8 INNOVASEA SYSTEM INC. HELPS OPEN BLUE BECOME LARGEST OPEN-OCEAN FISH FARM IN WORLD
5.11.3 EARTH OCEAN FARMS
TABLE 9 INNOVASEA SYSTEM INC. ENABLES EARTH OCEAN FARMS TO EXPAND PRODUCTION WITH RUGGED EVOLUTION PENS
5.11.4 GIFAS
TABLE 10 PHILIPS LED SOLUTIONS OFFER NEW POSSIBILITIES FOR SALMON INDUSTRY
5.11.5 ERKO SEAFOOD AS
TABLE 11 AKVA GROUP HELPS ERKO SEAFOOD AS WITH PRECISION AQUACULTURE PRODUCTS
5.12 TRADE ANALYSIS
TABLE 12 IMPORT DATA OF AGRICULTURAL, HORTICULTURAL, OR FORESTRY MACHINERY OF SOIL PREPARATION OR CULTIVATION, BY COUNTRY, 2017–2021 (USD MILLION)
FIGURE 38 MARKET: IMPORT DATA FOR MAJOR COUNTRIES, 2017–2021
TABLE 13 EXPORT DATA OF AGRICULTURAL, HORTICULTURAL, OR FORESTRY MACHINERY OF SOIL PREPARATION OR CULTIVATION, BY COUNTRY, 2017–2021 (USD MILLION)
FIGURE 39 SMART AGRICULTURE: EXPORT DATA FOR MAJOR COUNTRIES, 2017–2021
5.13 PATENT ANALYSIS
FIGURE 40 TOP 10 COMPANIES WITH HIGHEST NO. OF PATENTS IN LAST 10 YEARS
5.13.1 JURISDICTION ANALYSIS
FIGURE 41 JURISDICTION ANALYSIS
5.13.2 TOP PATENT OWNERS
TABLE 14 TOP 20 PATENT OWNERS (US) IN LAST 10 YEARS
TABLE 15 SOME KEY INNOVATIONS AND PATENT REGISTRATIONS FROM SEL
5.14 KEY CONFERENCES AND EVENTS, 2023–2024
TABLE 16 SMART AGRICULTURE MARKET: DETAILED LIST OF CONFERENCES AND EVENTS
5.15 TARIFF AND REGULATORY LANDSCAPE IN SMART AGRICULTURE
5.15.1 US: AGRICULTURAL DATA ACT 2018
5.15.2 NATIONAL MISSION FOR SUSTAINABLE AGRICULTURE (NMSA)
5.15.3 ENVIRONMENTAL IMPACT ASSESSMENT (EIA)
5.15.4 NATURE CONSERVATION – EUROPEAN UNION (EU)
5.15.5 TARIFF AND REGULATIONS RELATED TO PRECISION FARMING AND SMART GREENHOUSES
TABLE 17 TARIFF REGULATIONS: PRECISION FARMING AND SMART GREENHOUSES
5.15.6 TARIFF AND REGULATIONS RELATED TO PRECISION AQUACULTURE
TABLE 18 TARIFF REGULATIONS: PRECISION AQUACULTURE
5.16 GOVERNMENT POLICIES AND SUBSIDIES
5.16.1 INTRODUCTION
5.16.2 CHINA
5.16.2.1 National plan for agricultural and rural informatization: China 14th five-year plan (2021–2026)
5.16.2.2 New guidelines for modernization of agriculture sector in China
5.16.2.3 Current state of development of smart agriculture machinery in China
5.16.2.4 Pollution and climate smart agriculture in China (PACSAC)
5.16.2.5 World bank initiatives toward promoting green agriculture and rural development in China
FIGURE 42 AGRICULTURE SUBSIDIES IN CHINA AND OTHER MAJOR COUNTRIES (% OF TOTAL GDP)
5.16.3 INDIA
TABLE 19 CURRENT AGRICULTURE SUBSIDIES SUPPORT TO INDIAN FARMERS FROM CENTRAL AND STATE GOVERNMENTS (USD BILLION)
5.16.3.1 Greenhouse farming subsidy in India
5.16.3.2 Government initiatives for promoting organic farming in India
5.16.3.3 Government partnerships for smart agriculture
5.16.4 NETHERLANDS
5.16.4.1 Climate smart agriculture initiatives in Netherlands
5.16.4.2 Major government initiatives and subsidy programs in Netherlands
5.16.4.3 Support for organic farmers
5.16.4.3.1 Greenhouse as source of energy
5.16.4.3.2 Subsidy scheme for agricultural innovation North Brabant, 2020–2023
5.16.5 AZERBAIJAN
FIGURE 43 TOTAL AGRICULTURE LAND UNDER CULTIVATION, 2012–2022 (MILLION HA)
5.16.5.1 Government investments and support for agriculture sector in Azerbaijan
FIGURE 44 AGRICULTURE EXPORT VALUE, BY PRODUCT, 2020 VS. 2021 (USD MILLION)
FIGURE 45 AGRICULTURE IMPORT VALUE, BY PRODUCT, 2020 VS. 2021 (USD MILLION)
5.16.5.2 Recent government reforms and policies in agriculture sector
5.16.5.3 Digital agriculture transformation in Azerbaijan through setting up agroparks
5.16.6 SPAIN
FIGURE 46 TOTAL AGRICULTURAL LAND UNDER CULTIVATION IN SPAIN, 2013–2020 (MILLION HA)
FIGURE 47 SHARE OF MAJOR AGRICULTURE PRODUCTS IN SPAIN
FIGURE 48 IMPORT AND EXPORT VALUE OF AGRICULTURE PRODUCTS IN SPAIN, 2021 (USD MILLION)
5.16.6.1 Recent government policies in agriculture
5.16.6.1.1 Spanish government approved strategic plan for economic recovery and transformation (PERTE) of agri-food sector in early 2022
5.16.6.1.2 Ministry of Agriculture, Fisheries and Food and National Innovation Company (ENISA) in Spain allocated euro 13 million to technology-based agriculture business projects
5.16.6.1.3 Subsidy schemes for irrigation projects in Spain
5.16.7 TURKEY
5.16.7.1 Current landscape of smart agriculture technology in Turkey
FIGURE 49 TOTAL AGRICULTURE LAND UNDER CULTIVATION, 2013–2020 (MILLION HA)
5.16.7.2 Policies and implementation of smart agriculture technologies in Turkey
5.16.7.2.1 Eleventh development plan was created in July 2019
6 DIFFERENT CONNECTING TECHNOLOGIES USED IN SMART AGRICULTURE (Page No. - 132)
6.1 INTRODUCTION
FIGURE 50 DIFFERENT TECHNOLOGIES IN SMART AGRICULTURE
6.2 INTERNET OF THINGS (IOT)
6.3 CELLULAR IOT
6.3.1 LTE-M
6.3.2 NB-IOT
6.4 LORA
6.5 GLOBAL NAVIGATION SATELLITE SYSTEM (GNSS)
7 SMART AGRICULTURE MARKET, BY AGRICULTURE TYPE (Page No. - 134)
7.1 INTRODUCTION
FIGURE 51 SMART AGRICULTURE MARKET, BY AGRICULTURE TYPE
TABLE 20 MARKET, BY AGRICULTURE TYPE, 2019–2022 (USD MILLION)
FIGURE 52 PRECISION FARMING EXPECTED TO DOMINATE SMART AGRICULTURE MARKET FROM 2023 TO 2028
TABLE 21 MARKET, BY AGRICULTURE TYPE, 2023–2028 (USD MILLION)
7.2 PRECISION FARMING
7.2.1 IMPROVES FARM EFFICIENCY AND INCREASES CROP PRODUCTIVITY
TABLE 22 PRECISION FARMING: SMART AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION)
FIGURE 53 VARIABLE RATE TECHNOLOGY TO REGISTER HIGHEST CAGR FROM 2023 TO 2028
TABLE 23 PRECISION FARMING: MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION)
TABLE 24 PRECISION FARMING: MARKET, BY FARM SIZE, 2019–2022 (USD MILLION)
TABLE 25 PRECISION FARMING: MARKET, BY FARM SIZE, 2023–2028 (USD MILLION)
TABLE 26 PRECISION FARMING: MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 27 PRECISION FARMING: MARKET, BY REGION, 2023–2028 (USD MILLION)
7.3 LIVESTOCK MONITORING
7.3.1 USES CUTTING-EDGE TECHNOLOGIES AND TOOLS TO ENHANCE PRODUCTIVITY AND PROFITABILITY IN DAIRY FARMING
TABLE 28 LIVESTOCK MONITORING: SMART AGRICULTURE MARKET, BY FARM SIZE, 2019–2022 (USD MILLION)
TABLE 29 LIVESTOCK MONITORING: MARKET, BY FARM SIZE, 2023–2028 (USD MILLION)
TABLE 30 LIVESTOCK MONITORING: MARKET, BY REGION, 2019–2022 (USD MILLION)
FIGURE 54 ASIA PACIFIC TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD
TABLE 31 LIVESTOCK MONITORING: MARKET, BY REGION, 2023–2028 (USD MILLION)
7.4 PRECISION AQUACULTURE
7.4.1 IMPLEMENTING SMART TECHNOLOGIES HELPS MONITOR AQUAFARMS
7.4.2 SMART FEEDING SYSTEMS
7.4.2.1 Determine sizes and eating behavior of fishes
7.4.3 MONITORING AND CONTROL SYSTEMS
7.4.3.1 Improve efficiency of aquafarms
7.4.4 UNDERWATER REMOTELY OPERATED VEHICLES
7.4.4.1 Monitor underwater species to improve aquafarm operations
TABLE 32 PRECISION AQUACULTURE: SMART AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 33 PRECISION AQUACULTURE: SMART AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
7.5 PRECISION FORESTRY
7.5.1 USES MODERN TECHNOLOGIES TO GATHER REAL-TIME INFORMATION FOR DECISION-MAKING
TABLE 34 PRECISION FORESTRY: MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION)
FIGURE 55 CUT-TO-LENGTH (CTL) TECHNOLOGY TO CAPTURE LARGEST SHARE OF PRECISION FORESTRY MARKET FROM 2023 TO 2028
TABLE 35 PRECISION FORESTRY: MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION)
TABLE 36 PRECISION FORESTRY: MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 37 PRECISION FORESTRY: MARKET, BY REGION, 2023–2028 (USD MILLION)
7.6 SMART GREENHOUSE
7.6.1 IMPROVES OPERATIONS USING WIRED AND WIRELESS TECHNOLOGIES
TABLE 38 SMART GREENHOUSE: SMART AGRICULTURE MARKET, BY SUB-TYPE, 2019–2022 (USD MILLION)
TABLE 39 SMART GREENHOUSE: MARKET, BY SUB-TYPE, 2023–2028 (USD MILLION)
TABLE 40 SMART GREENHOUSE: MARKET, BY FARM SIZE, 2019–2022 (USD MILLION)
TABLE 41 SMART GREENHOUSE: MARKET, BY FARM SIZE, 2023–2028 (USD MILLION)
TABLE 42 SMART GREENHOUSE: MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 43 SMART GREENHOUSE: MARKET, BY REGION, 2023–2028 (USD MILLION)
7.7 OTHERS
TABLE 44 OTHERS: SMART AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
FIGURE 56 ORCHID FARMING SEGMENT TO REGISTER HIGHEST CAGR FROM 2023 TO 2028
TABLE 45 OTHERS: MARKET, BY TYPE, 2023–2028 (USD MILLION)
TABLE 46 OTHERS: MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 47 OTHERS: MARKET, BY REGION, 2023–2028 (USD MILLION)
8 SMART AGRICULTURE MARKET, BY OFFERING (Page No. - 152)
8.1 INTRODUCTION
FIGURE 57 SMART AGRICULTURE MARKET, BY OFFERING
TABLE 48 MARKET, BY OFFERING, 2019–2022 (USD MILLION)
FIGURE 58 SERVICES SEGMENT TO WITNESS HIGHEST CAGR FROM 2023 TO 2028
TABLE 49 MARKET, BY OFFERING, 2023–2028 (USD MILLION)
8.2 HARDWARE
8.2.1 PRECISION FARMING HARDWARE
8.2.1.1 Growing availability of precision farming tools
TABLE 50 PRECISION FARMING: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 51 PRECISION FARMING: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 52 PRECISION FARMING HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (USD MILLION)
TABLE 53 PRECISION FARMING HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (USD MILLION)
8.2.1.2 Automation and control systems
TABLE 54 AUTOMATION AND CONTROL SYSTEMS: MARKET, BY DEVICE TYPE, 2019–2022 (USD MILLION)
FIGURE 59 DRONES TO ACCOUNT FOR LARGEST SHARE OF AUTOMATION AND CONTROL SYSTEMS MARKET FROM 2023 TO 2028
TABLE 55 AUTOMATION AND CONTROL SYSTEMS: MARKET, BY DEVICE TYPE, 2023–2028 (USD MILLION)
8.2.1.2.1 Drones/UAVs
8.2.1.2.1.1 Provide more accurate data useful in VRT applications
8.2.1.2.2 Irrigation controllers
8.2.1.2.2.1 Improve water efficiency, reduce energy consumption, and maximize crop productivity
8.2.1.2.3 GPS/GNSS devices
8.2.1.2.3.1 Help farmers work in poor visibility conditions
8.2.1.2.4 Flow and application control devices
8.2.1.2.4.1 Eliminate overlap and double coverage, saving inputs and promoting efficiency
8.2.1.2.5 Guidance and steering systems
8.2.1.2.5.1 Reduce overlap and inward drift
8.2.1.2.6 Handheld mobile devices/handheld computers
8.2.1.2.6.1 Allow collection of field records, soil nutrient data, and soil moisture information
8.2.1.2.7 Displays
8.2.1.2.7.1 Allow farmers to view farm-related information in real time
8.2.1.2.8 Others
8.2.1.3 Sensing and monitoring devices
TABLE 56 SENSING AND MONITORING DEVICES: SMART AGRICULTURE MARKET, BY DEVICE TYPE, 2019–2022 (USD MILLION)
TABLE 57 SENSING AND MONITORING DEVICES: MARKET, BY DEVICE TYPE, 2023–2028 (USD MILLION)
8.2.1.3.1 Yield monitors
8.2.1.3.1.1 To hold largest market share during forecast period
8.2.1.3.2 Soil sensors
8.2.1.3.2.1 Provide real-time data on various soil properties
8.2.1.3.3 Nutrient sensors
8.2.1.3.3.1 Measure levels of essential plant nutrients
8.2.1.3.4 Moisture sensors
8.2.1.3.4.1 Manage irrigation systems more efficiently
8.2.1.3.5 Temperature sensors
8.2.1.3.5.1 Help farmers make sowing decisions and check soil sustainability for planting
8.2.1.4 Water sensors
8.2.1.4.1 Assist farmers in determining most efficient and effective times to water crops
8.2.1.5 Climate sensors
8.2.1.5.1 Help monitor and record climate changes
8.2.1.6 Others
8.2.2 LIVESTOCK MONITORING HARDWARE
8.2.2.1 Enable efficient resource management, livestock tracking, and devising and managing feeding and milking plans
TABLE 58 LIVESTOCK MONITORING: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 59 LIVESTOCK MONITORING: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 60 LIVESTOCK MONITORING HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (USD MILLION)
FIGURE 60 RFID TAGS AND READERS TO CAPTURE LARGEST SHARE OF LIVESTOCK MONITORING HARDWARE MARKET DURING FORECAST PERIOD
TABLE 61 LIVESTOCK MONITORING HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (USD MILLION)
TABLE 62 LIVESTOCK MONITORING HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (MILLION UNITS)
TABLE 63 LIVESTOCK MONITORING HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (MILLION UNITS)
8.2.2.2 RFID tags and readers
8.2.2.2.1 Help track and monitor livestock, crops, and farm assets' location and health
8.2.2.3 Sensors
8.2.2.3.1 Help improve livestock monitoring applications
8.2.2.4 Transmitters and mounting equipment
8.2.2.4.1 Used to send wireless video and audio signals from barn to livestock owner’s house
8.2.2.5 GPS
8.2.2.5.1 Aids in animal management
8.2.2.6 Others
8.2.3 PRECISION FORESTRY HARDWARE
8.2.3.1 Help optimize efficiency and accuracy of forest management operations
TABLE 64 PRECISION FORESTRY: SMART AGRICULTURE MARKET, BY OFFERING, 2019–2022 (USD MILLION)
FIGURE 61 HARDWARE SEGMENT TO LEAD PRECISION FORESTRY APPLICATIONS IN SMART AGRICULTURE MARKET IN 2023
TABLE 65 PRECISION FORESTRY: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 66 PRECISION FORESTRY HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (USD MILLION)
TABLE 67 PRECISION FORESTRY HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (USD MILLION)
8.2.3.2 Harvesters and forwarders
8.2.3.2.1 Play crucial role in precision forestry operations
8.2.3.3 UAVs/drones
8.2.3.3.1 Used for planting trees and reducing associated costs
8.2.3.4 GPS
8.2.3.4.1 Used for site-specific tree management with high precision
8.2.3.5 Cameras
8.2.3.5.1 Help users monitor trees in forests
8.2.3.6 Sensors and RFID tags
8.2.3.6.1 Help prevent illegal cutting and smuggling of trees
8.2.3.7 Variable rate controllers
8.2.3.7.1 Beneficial in application of herbicides and fertilizers
8.2.3.8 Others
8.2.4 PRECISION AQUACULTURE HARDWARE
8.2.4.1 Enable effective management of aquaculture farms
TABLE 68 PRECISION AQUACULTURE: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 69 PRECISION AQUACULTURE: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 70 PRECISION AQUACULTURE HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (USD MILLION)
FIGURE 62 MONITORING DEVICES TO LEAD PRECISION AQUACULTURE HARDWARE MARKET FROM 2023 TO 2028
TABLE 71 PRECISION AQUACULTURE HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (USD MILLION)
8.2.4.2 Monitoring devices
8.2.4.2.1 Help increase aquatic farm efficiency and productivity
8.2.4.2.2 Temperature and environmental monitoring devices
8.2.4.2.2.1 Ensure water temperature remains within optimal range for aquatic species
8.2.4.2.3 pH and dissolved oxygen sensors
8.2.4.2.3.1 Ensure good health and growth of aquaculture species
8.2.4.2.4 Others
8.2.4.3 Camera systems
8.2.4.3.1 Used to monitor feeding response, feeding rate, and fish behavior
8.2.4.4 Control systems
8.2.4.4.1 Provide comprehensive control over aquaculture operations
8.2.4.5 Others
8.2.5 SMART GREENHOUSE HARDWARE
8.2.5.1 Improve plant growth, increase yields, and reduce waste
TABLE 72 SMART GREENHOUSE: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 73 SMART GREENHOUSE: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 74 SMART GREENHOUSE HARDWARE: MARKET, BY HARDWARE TYPE, 2019–2022 (USD MILLION)
TABLE 75 SMART GREENHOUSE HARDWARE: MARKET, BY HARDWARE TYPE, 2023–2028 (USD MILLION)
8.2.5.2 HVAC systems
8.2.5.2.1 Provide improved indoor environment in smart greenhouses
8.2.5.3 LED grow lights
8.2.5.3.1 Used as supplemental lighting source where natural sunlight is insufficient for plant growth
8.2.5.4 Irrigation systems
8.2.5.4.1 Help in proper and timely watering of each zone in greenhouses
8.2.5.5 Material handling equipment
8.2.5.5.1 Used for mechanization of greenhouses
8.2.5.6 Valves and pumps
8.2.5.6.1 Help maintain an optimal flow of water in greenhouses
8.2.5.7 Control systems
8.2.5.7.1 Help ease heating and cooling operations
8.2.5.8 Sensors and cameras
8.2.5.8.1 Provide quantitative information to guide farm owners
8.2.6 OTHERS
TABLE 76 OTHERS: SMART AGRICULTURE MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 77 OTHERS: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
8.3 SOFTWARE
TABLE 78 PRECISION FARMING SOFTWARE: SMART AGRICULTURE MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 79 PRECISION FARMING SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
TABLE 80 LIVESTOCK MONITORING SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 81 LIVESTOCK MONITORING SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
TABLE 82 PRECISION AQUACULTURE SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 83 PRECISION AQUACULTURE SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
TABLE 84 PRECISION FORESTRY SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 85 PRECISION FORESTRY SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
TABLE 86 SMART GREENHOUSE SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 87 SMART GREENHOUSE SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
TABLE 88 OTHER SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
TABLE 89 OTHER SOFTWARE: MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
8.3.1 ON-PREMISES SOFTWARE
8.3.1.1 Offer lower cost of ownership
8.3.2 ON-CLOUD
8.3.2.1 Provide shared processing of resources and data to users
8.3.2.2 Software-as-a-Service (SaaS)
8.3.2.2.1 Allow users to connect to cloud-based applications over internet
8.3.2.3 Platform-as-a-Service (PaaS)
8.3.2.3.1 Help organizations to reduce upfront costs
8.3.3 AI & DATA ANALYTICS
8.3.3.1 Help improve harvest quality and accuracy
8.3.3.2 Farm management software
8.3.3.2.1 Used to optimize and manage farm operations and production activities
8.4 SERVICES
TABLE 90 PRECISION FARMING SERVICES: SMART AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
TABLE 91 PRECISION FARMING SERVICES: MARKET, BY TYPE, 2023–2028 (USD MILLION)
TABLE 92 LIVESTOCK MONITORING SERVICES: MARKET, BY TYPE, 2019–2022 (USD MILLION)
TABLE 93 LIVESTOCK MONITORING SERVICES: MARKET, BY TYPE, 2023–2028 (USD MILLION)
TABLE 94 PRECISION AQUACULTURE SERVICES: MARKET, BY TYPE, 2019–2022 (USD MILLION)
TABLE 95 PRECISION AQUACULTURE SERVICES: MARKET, BY TYPE, 2023–2028 (USD MILLION)
TABLE 96 SMART GREENHOUSE SERVICES: MARKET, BY TYPE, 2019–2022 (USD MILLION)
TABLE 97 SMART GREENHOUSE SERVICES: MARKET, BY TYPE, 2023–2028 (USD MILLION)
TABLE 98 OTHER SERVICES: MARKET, BY TYPE, 2019–2022 (USD MILLION)
TABLE 99 OTHER SERVICES: MARKET, BY TYPE, 2023–2028 (USD MILLION)
8.4.1 SYSTEM INTEGRATION AND CONSULTING SERVICES
8.4.1.1 Involved in troubleshooting and diagnosing farm management issues
8.4.2 MANAGED SERVICES
8.4.2.1 Provide suggestions to farmers to enhance production
8.4.2.2 Farm operation services
8.4.2.2.1 Help generate records and integrate unstructured data
8.4.2.3 Data services
8.4.2.3.1 Provide common platform to meet demand and supply requirements
8.4.2.4 Analytics services
8.4.2.4.1 Provide right calls and alerts on farming operations
8.4.3 CONNECTIVITY SERVICES
8.4.3.1 Ensure proper communication between devices and end users
8.4.4 ASSISTED PROFESSIONAL SERVICES
8.4.4.1 Help improve and implement standards of projects
8.4.4.2 Supply chain management services
8.4.4.2.1 Help mitigate frequent hardware system failures
8.4.4.3 Climate information services
8.4.4.3.1 Help plan farming activities better
8.4.4.4 Others
8.4.5 MAINTENANCE AND SUPPORT SERVICES
8.4.5.1 Ensure farm operations run smoothly and efficiently
8.4.5.2 Installation and deployment services
8.4.5.2.1 Ensure optimal machine performance
9 SMART AGRICULTURE MARKET, BY FARM SIZE (Page No. - 197)
9.1 INTRODUCTION
FIGURE 63 SMART AGRICULTURE MARKET, BY FARM SIZE
TABLE 100 MARKET, BY FARM SIZE, 2019–2022 (USD MILLION)
FIGURE 64 MEDIUM-SIZED FARMS TO CAPTURE LARGEST SHARE OF MARKET DURING FORECASAT PERIOD
TABLE 101 MARKET, BY FARM SIZE, 2023–2028 (USD MILLION)
9.2 LARGE FARMS
9.2.1 HEAVILY RELY ON HIRED LABOR TO MANAGE THEIR OPERATIONS
TABLE 102 LARGE FARMS: MARKET, BY REGION, 2019–2022 (USD MILLION)
FIGURE 65 AMERICAS EXPECTED TO LEAD MARKET FOR LARGE FARMS FROM 2023 TO 2028
TABLE 103 LARGE FARMS: MARKET, BY REGION, 2023–2028 (USD MILLION)
9.3 MEDIUM-SIZED FARMS
9.3.1 POTENTIAL TO LOWER LABOR COSTS AND IMPROVE PRODUCTIVITY
TABLE 104 MEDIUM-SIZED FARMS: MARKET, BY REGION, 2019–2022 (USD MILLION)
FIGURE 66 ASIA PACIFIC TO REGISTER FASTEST GROWTH RATE FOR MEDIUM-SIZED FARMS FROM 2023 TO 2028
TABLE 105 MEDIUM-SIZED FARMS: MARKET, BY REGION, 2023–2028 (USD MILLION)
9.4 SMALL FARMS
9.4.1 SMALL FARMS TO RECORD HIGHEST GROWTH RATE DURING FORECAST PERIOD
TABLE 106 SMALL FARMS: MARKET, BY REGION, 2019–2022 (USD MILLION)
FIGURE 67 AMERICAS TO LEAD MARKET FOR SMALL FARMS DURING FORECAST PERIOD
TABLE 107 SMALL FARMS: MARKET, BY REGION, 2023–2028 (USD MILLION)
10 SMART AGRICULTURE MARKET, BY APPLICATION (Page No. - 204)
10.1 INTRODUCTION
FIGURE 68 SMART AGRICULTURE MARKET, BY APPLICATION
TABLE 108 MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
FIGURE 69 PRECISION FARMING SEGMENT TO ACCOUNT FOR LARGEST SHARE OF MARKET IN 2023
TABLE 109 MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
10.2 PRECISION FARMING
10.2.1 HELPS OPTIMIZE AGRICULTURAL PRODUCTION
TABLE 110 PRECISION FARMING: MARKET, BY SUB-APPLICATION, 2019–2022 (USD MILLION)
FIGURE 70 YIELD MONITORING SEGMENT TO LEAD MARKET FOR PRECISION FARMING APPLICATIONS FROM 2023 TO 2028
TABLE 111 PRECISION FARMING: SMART AGRICULTURE MARKET, BY SUB-APPLICATION, 2023–2028 (USD MILLION)
10.2.2 YIELD MONITORING
10.2.2.1 Helps farmers maximize their yield
TABLE 112 BENEFITS OF YIELD MONITORING
10.2.2.2 On-farm yield monitoring
10.2.2.2.1 Accurately measures quantity of crop harvested at specific locations and times
10.2.2.3 Off-farm yield monitoring
10.2.2.3.1 Beneficial for analyzing health of yield after harvesting
10.2.3 CROP SCOUTING
10.2.3.1 Critical crop management tool important for making timely decisions during harvesting
10.2.4 FIELD MAPPING
10.2.4.1 Helps farmers in decision-making related to yield production
10.2.4.2 Boundary mapping
10.2.4.2.1 Creates digital representation of field boundaries
10.2.4.3 Drainage mapping
10.2.4.3.1 Helps minimize water costs
10.2.5 VARIABLE RATE APPLICATION
10.2.5.1 Optimize crop input for efficient farming
10.2.5.2 Precision irrigation
10.2.5.2.1 Reduces water wastage and improves soil fertility
10.2.5.3 Precision seeding
10.2.5.3.1 Leads to uniform and high-quality produce
10.2.5.4 Precision fertilization
10.2.5.4.1 Provides ideal combination of hydration and nourishment to plant roots
10.2.5.5 Pesticide VRA
10.2.5.5.1 Prevents overuse of pesticides on crops
10.2.6 WEATHER TRACKING & FORECASTING
10.2.6.1 Helps take precautionary measures for farm protection from natural calamities
10.2.7 INVENTORY MANAGEMENT
10.2.7.1 Used to track and organize materials, irrigation parts, chemicals, and others
10.2.8 FARM LABOR MANAGEMENT
10.2.8.1 Helps track various activities of farm workers
10.2.9 FINANCIAL MANAGEMENT
10.2.9.1 Helps farmers or growers make strategic decisions
10.3 LIVESTOCK MONITORING
10.3.1 ENABLES REAL-TIME MONITORING OF HEALTH AND WELL-BEING OF ANIMALS
TABLE 113 LIVESTOCK MONITORING: MARKET, BY SUB-APPLICATION, 2019–2022 (USD MILLION)
FIGURE 71 BREEDING MANAGEMENT SEGMENT OF LIVESTOCK MONITORING TO CAPTURE LARGEST MARKET SHARE DURING FORECAST PERIOD
TABLE 114 LIVESTOCK MONITORING: MARKET, BY SUB-APPLICATION, 2023–2028 (USD MILLION)
10.3.2 MILK HARVESTING MANAGEMENT
10.3.2.1 Reduces labor costs and increases milking efficiency through automated milk harvesting
10.3.3 BREEDING MANAGEMENT
10.3.3.1 Helps increase animal productivity in long term
10.3.4 FEEDING MANAGEMENT
10.3.4.1 Helps accurately formulate cow’s diet
10.3.5 HEAT STRESS MANAGEMENT
10.3.5.1 Reduces cattle mortality rate due to improper ventilation
10.3.6 ANIMAL COMFORT MANAGEMENT
10.3.6.1 Helps ensure animal health and well-being
10.3.7 BEHAVIOR MONITORING AND CONTROL
10.3.7.1 Provides early detection of any deviations in animal behavior
10.3.8 OTHERS
10.4 PRECISION AQUACULTURE
10.4.1 HELPS OPTIMIZE AQUACULTURE PRODUCTION AND MANAGEMENT
TABLE 115 PRECISION AQUACULTURE: MARKET, BY SUB-APPLICATION, 2019–2022 (USD MILLION)
FIGURE 72 FEEDING MANAGEMENT TO LEAD PRECISION AQUACULTURE MARKET FROM 2023 TO 2028
TABLE 116 PRECISION AQUACULTURE: SMART AGRICULTURE MARKET, BY SUB-APPLICATION, 2023–2028 (USD MILLION)
10.4.2 FEEDING MANAGEMENT
10.4.2.1 Helps avoid overfeeding
10.4.3 MONITORING, CONTROL, AND SURVEILLANCE
10.4.3.1 Minimize waste and environmental impact
10.4.4 OTHERS
10.5 PRECISION FORESTRY
10.5.1 HELPS IMPROVE SUSTAINABILITY OF FORESTRY PRACTICES
TABLE 117 PRECISION FORESTRY MARKET, BY SUB-APPLICATION, 2019–2022 (USD MILLION)
TABLE 118 PRECISION FORESTRY MARKET, BY SUB-APPLICATION, 2023–2028 (USD MILLION)
10.5.2 GENETICS AND NURSERIES
10.5.2.1 Use of UAVs in seed planting is highly efficient and time-saving
10.5.3 SILVICULTURE AND FIRE MANAGEMENT
10.5.3.1 Minimize damage and casualties due to wildfires
10.5.4 HARVESTING MANAGEMENT
10.5.4.1 Reduces damage to forests and maximizes yield of wood products
10.5.5 INVENTORY AND LOGISTICS MANAGEMENT
10.5.5.1 Diminishes manual error and enables quick reporting and data processing
10.6 SMART GREENHOUSE
10.6.1 BENEFICIAL FOR INDOOR CROPS
TABLE 119 SMART GREENHOUSE: MARKET, BY SUB-APPLICATION, 2019–2022 (USD MILLION)
FIGURE 73 HVAC MANAGEMENT TO CAPTURE LARGEST SHARE OF SMART GREENHOUSE MARKET
TABLE 120 SMART GREENHOUSE: MARKET, BY SUB-APPLICATION, 2023–2028 (USD MILLION)
10.6.2 HVAC MANAGEMENT
10.6.2.1 Regulates temperature for favorable plant growth
10.6.3 YIELD MONITORING AND HARVESTING
10.6.3.1 Improves efficiency and productivity of greenhouse operations
10.6.4 WATER AND FERTILIZER MANAGEMENT
10.6.4.1 Reduces water waste and production costs of greenhouses
10.6.5 OTHERS
10.7 OTHERS
11 SMART AGRICULTURE MARKET, BY REGION (Page No. - 229)
11.1 INTRODUCTION
FIGURE 74 REGIONAL CLASSIFICATION OF SMART AGRICULTURE MARKET
TABLE 121 SMART AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
FIGURE 75 ASIA PACIFIC TO WITNESS HIGHEST CAGR IN SMART AGRICULTURE MARKET DURING FORECAST PERIOD
TABLE 122 MARKET, BY REGION, 2023–2028 (USD MILLION)
11.2 AMERICAS
FIGURE 76 AMERICAS: SMART AGRICULTURE MARKET SNAPSHOT
TABLE 123 AMERICAS: MARKET, BY REGION, 2019–2022 (USD MILLION)
TABLE 124 AMERICAS: MARKET, BY REGION, 2023–2028 (USD MILLION)
TABLE 125 AMERICAS: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 126 AMERICAS: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 127 AMERICAS: MARKET, BY AGRICULTURE TYPE, 2019–2022 (USD MILLION)
TABLE 128 AMERICAS: MARKET, BY AGRICULTURE TYPE, 2023–2028 (USD MILLION)
11.2.1 NORTH AMERICA
TABLE 129 NORTH AMERICA: SMART AGRICULTURE MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
FIGURE 77 US TO ACCOUNT FOR LARGEST SHARE OF SMART AGRICULTURE MARKET IN 2023
TABLE 130 NORTH AMERICA: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
TABLE 131 NORTH AMERICA: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 132 NORTH AMERICA: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
11.2.1.1 US
11.2.1.1.1 Presence of key players to boost market growth
11.2.1.2 Canada
11.2.1.2.1 Government initiatives and investments to fuel market growth
11.2.1.3 Mexico
11.2.1.3.1 Government initiatives promoting use of remote sensing technology to accelerate market growth
11.2.2 SOUTH AMERICA
TABLE 133 SOUTH AMERICA: SMART AGRICULTURE MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
FIGURE 78 BRAZIL TO CAPTURE LARGEST MARKET SHARE IN 2023
TABLE 134 SOUTH AMERICA: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
TABLE 135 SOUTH AMERICA: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 136 SOUTH AMERICA: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
11.2.2.1 Brazil
11.2.2.1.1 Availability of large lands at low cost to propel market
11.2.2.2 Argentina
11.2.2.2.1 Highest CAGR during forecast period to lead to market growth
11.2.2.3 Rest of South America
11.3 EUROPE
FIGURE 79 EUROPE: SMART AGRICULTURE MARKET SNAPSHOT
TABLE 137 EUROPE: MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
FIGURE 80 GERMANY TO ACCOUNT FOR LARGEST MARKET SHARE DURING FORECAST PERIOD
TABLE 138 EUROPE: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
TABLE 139 EUROPE: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 140 EUROPE: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 141 EUROPE: MARKET, BY AGRICULTURE TYPE, 2019–2022 (USD MILLION)
TABLE 142 EUROPE: MARKET, BY AGRICULTURE TYPE, 2023–2028 (USD MILLION)
11.3.1 GERMANY
11.3.1.1 Presence of livestock farms to drive market growth
11.3.2 UK
11.3.2.1 Conducive environment to carry out innovations supports market growth
11.3.3 FRANCE
11.3.3.1 Increased adoption of smart agriculture technologies in country to drive market growth
11.3.4 ITALY
11.3.4.1 Gradual shift toward smart farming techniques to spur market growth
11.3.5 NETHERLANDS
11.3.5.1 Rising adoption of advanced technologies for harvesting processes to fuel market growth
11.3.6 REST OF EUROPE
11.4 ASIA PACIFIC
FIGURE 81 ASIA PACIFIC: SMART AGRICULTURE MARKET SNAPSHOT
TABLE 143 ASIA PACIFIC: MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
FIGURE 82 CHINA TO REGISTER HIGHEST CAGR IN MARKET DURING FORECAST PERIOD
TABLE 144 ASIA PACIFIC: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
TABLE 145 ASIA PACIFIC: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 146 ASIA PACIFIC: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 147 ASIA PACIFIC: MARKET, BY AGRICULTURE TYPE, 2019–2022 (USD MILLION)
TABLE 148 ASIA PACIFIC: MARKET, BY AGRICULTURE TYPE, 2023–2028 (USD MILLION)
11.4.1 CHINA
11.4.1.1 Government to play key role in country’s agriculture sector growth
11.4.2 JAPAN
11.4.2.1 Labor shortage to fuel demand for smart agriculture solutions
11.4.3 AUSTRALIA
11.4.3.1 Government support and presence of research organizations to play major role in market growth
11.4.4 INDIA
11.4.4.1 Government initiatives and players' contributions to increase adoption of smart agriculture solutions
11.4.5 SOUTH KOREA
11.4.5.1 Rising need to produce high-value agricultural products to fuel market growth
11.4.6 REST OF ASIA PACIFIC
11.5 ROW
TABLE 149 ROW: SMART AGRICULTURE MARKET, BY REGION/COUNTRY, 2019–2022 (USD MILLION)
TABLE 150 ROW: MARKET, BY REGION/COUNTRY, 2023–2028 (USD MILLION)
TABLE 151 ROW: MARKET, BY OFFERING, 2019–2022 (USD MILLION)
TABLE 152 ROW: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
TABLE 153 ROW: MARKET, BY AGRICULTURE TYPE, 2019–2022 (USD MILLION)
TABLE 154 ROW: MARKET, BY AGRICULTURE TYPE, 2023–2028 (USD MILLION)
11.5.1 RUSSIA
11.5.1.1 Increasing awareness about benefits of smart agriculture in country to support market
11.5.2 AFRICA
11.5.2.1 Increasing awareness among farmers to contribute to market growth
11.5.3 MIDDLE EAST
11.5.3.1 Rapid developments in big data analytics and cloud-computing platforms to drive market growth
12 COMPETITIVE LANDSCAPE (Page No. - 258)
12.1 OVERVIEW
12.2 MARKET EVALUATION FRAMEWORK
TABLE 155 REVIEW OF STRATEGIES ADOPTED BY KEY SMART AGRICULTURE MANUFACTURERS
12.2.1 PRODUCT PORTFOLIO
12.2.2 REGIONAL FOCUS
12.2.3 MANUFACTURING FOOTPRINT
12.2.4 ORGANIC/INORGANIC STRATEGIES
12.3 MARKET SHARE ANALYSIS, 2022
FIGURE 83 MARKET SHARE ANALYSIS OF TOP FIVE PLAYERS IN SMART AGRICULTURE MARKET, 2022
TABLE 156 MARKET SHARE ANALYSIS OF TOP FIVE COMPANIES, 2022
12.4 REVENUE ANALYSIS: TOP FOUR COMPANIES (2018–2022)
FIGURE 84 FIVE-YEAR REVENUE ANALYSIS OF TOP FOUR PLAYERS IN SMART AGRICULTURE MARKET, 2018–2022
12.5 COMPANY EVALUATION QUADRANT, 2022
12.5.1 STARS
12.5.2 EMERGING LEADERS
12.5.3 PERVASIVE PLAYERS
12.5.4 PARTICIPANTS
FIGURE 85 COMPANY EVALUATION QUADRANT, 2022
12.6 COMPANY FOOTPRINT
TABLE 157 COMPANY OFFERING FOOTPRINT
TABLE 158 COMPANY APPLICATION FOOTPRINT
TABLE 159 COMPANY REGION FOOTPRINT
TABLE 160 COMPANY OVERALL FOOTPRINT
12.7 STARTUPS/SMES EVALUATION MATRIX/QUADRANT, 2022
12.7.1 COMPETITIVE BENCHMARKING
TABLE 161 SMART AGRICULTURE MARKET: DETAILED LIST OF KEY STARTUPS/SMES
TABLE 162 SMART AGRICULTURE MARKET: COMPETITIVE BENCHMARKING OF KEY PLAYERS (STARTUPS/SMES)
12.7.2 PROGRESSIVE COMPANIES
12.7.3 RESPONSIVE COMPANIES
12.7.4 DYNAMIC COMPANIES
12.7.5 STARTING BLOCKS
FIGURE 86 STARTUPS/SMES EVALUATION QUADRANT, 2022
12.8 COMPETITIVE SCENARIO
12.8.1 PRODUCT LAUNCHES
TABLE 163 PRODUCT LAUNCHES AND DEVELOPMENTS, 2020–2022
12.8.2 DEALS
TABLE 164 DEALS, 2020–2022
12.8.3 OTHERS
TABLE 165 OTHERS, 2020–2022
13 COMPANY PROFILES (Page No. - 278)
(Business overview, Products/Services/Solutions offered, Recent Developments, MNM view)*
13.1 KEY PLAYERS
13.1.1 DEERE & COMPANY
TABLE 166 DEERE & COMPANY: BUSINESS OVERVIEW
FIGURE 87 DEERE & COMPANY: COMPANY SNAPSHOT
TABLE 167 DEERE & COMPANY: PRODUCT LAUNCHES
TABLE 168 DEERE & COMPANY: DEALS
13.1.2 TRIMBLE INC.
TABLE 169 TRIMBLE INC.: BUSINESS OVERVIEW
FIGURE 88 TRIMBLE INC.: COMPANY SNAPSHOT
TABLE 170 TRIMBLE INC.: PRODUCT LAUNCHES
TABLE 171 TRIMBLE INC.: DEALS
13.1.3 AGCO CORPORATION (PRECISION PLANTING, LLC)
TABLE 172 AGCO CORPORATION: BUSINESS OVERVIEW
FIGURE 89 AGCO CORPORATION: COMPANY SNAPSHOT
TABLE 173 AGCO CORPORATION: PRODUCT LAUNCHES
TABLE 174 AGCO CORPORATION: DEALS
TABLE 175 AGCO CORPORATION: OTHERS
13.1.4 TOPCON POSITIONING SYSTEMS
TABLE 176 TOPCON POSITIONING SYSTEMS: BUSINESS OVERVIEW
TABLE 177 TOPCON POSITIONING SYSTEMS: PRODUCT LAUNCHES
TABLE 178 TOPCON POSITIONING SYSTEMS: DEALS
TABLE 179 TOPCON POSITIONING SYSTEMS: OTHERS
13.1.5 DELAVAL
TABLE 180 DELAVAL: BUSINESS OVERVIEW
FIGURE 90 DELAVAL: COMPANY SNAPSHOT
TABLE 181 DELAVAL: PRODUCT LAUNCHES
TABLE 182 DELAVAL: DEALS
13.1.6 AKVA GROUP
TABLE 183 AKVA GROUP: BUSINESS OVERVIEW
FIGURE 91 AKVA GROUP: COMPANY SNAPSHOT
TABLE 184 AKVA GROUP: DEALS
13.1.7 ALLFLEX LIVESTOCK INTELLIGENCE (MSD ANIMAL HEALTH)
TABLE 185 ALLFLEX LIVESTOCK INTELLIGENCE: BUSINESS OVERVIEW
TABLE 186 ALLFLEX LIVESTOCK INTELLIGENCE: PRODUCT LAUNCHES
TABLE 187 ALLFLEX LIVESTOCK INTELLIGENCE: DEALS
TABLE 188 ALLFLEX LIVESTOCK INTELLIGENCE: OTHERS
13.1.8 INNOVASEA SYSTEMS INC.
TABLE 189 INNOVASEA SYSTEMS INC.: BUSINESS OVERVIEW
TABLE 190 INNOVASEA SYSTEMS INC.: PRODUCT LAUNCHES
TABLE 191 INNOVASEA SYSTEMS INC.: DEALS
TABLE 192 INNOVASEA SYSTEMS INC.: OTHERS
13.1.9 AFIMILK LTD.
TABLE 193 AFIMILK LTD.: BUSINESS OVERVIEW
TABLE 194 AFIMILK LTD.: DEALS
13.1.10 HELIOSPECTRA AB
TABLE 195 HELIOSPECTRA AB: BUSINESS OVERVIEW
FIGURE 92 HELIOSPECTRA AB: COMPANY SNAPSHOT
TABLE 196 HELIOSPECTRA AB: PRODUCT LAUNCHES
TABLE 197 HELIOSPECTRA AB: DEALS
13.2 OTHER PLAYERS
13.2.1 PONSSE OYJ
13.2.2 RAVEN INDUSTRIES, INC. (CNH INDUSTRIAL N.V.)
13.2.3 KOMATSU FOREST
13.2.4 SCALEAQ
13.2.5 TIGERCAT INTERNATIONAL INC.
13.2.6 AG LEADER TECHNOLOGY
13.2.7 CERTHON
13.2.8 NEDAP N.V.
13.2.9 AGJUNCTION LLC
13.2.10 ARGUS CONTROL SYSTEMS LIMITED
13.2.11 DAIRYMASTER
13.2.12 DICKEY-JOHN
13.2.13 ABACO GROUP
13.2.14 TEEJET TECHNOLOGIES
13.2.15 FANCOM BV (SUBSIDIARY OF CTB, INC.)
13.2.16 LUMIGROW, INC.
13.2.17 CERES IMAGING, INC.
13.2.18 SENSAPHONE
13.2.19 BOUMATIC
13.2.20 CPI EQUIPMENT INC.
*Details on Business overview, Products/Services/Solutions offered, Recent Developments, MNM view might not be captured in case of unlisted companies.
14 APPENDIX (Page No. - 364)
14.1 DISCUSSION GUIDE
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.3 CUSTOMIZATION OPTIONS
14.4 RELATED REPORTS
14.5 AUTHOR DETAILS
The study involved four major activities in estimating the size of the smart agriculture market. Exhaustive secondary research was done to collect information on the market. The next step was to validate these findings, assumptions, and sizing with smart agriculture industry experts across the supply chain through primary research. Both top-down and bottom-up approaches were employed to estimate the total market’s size. After that, market breakdown and data triangulation were used to determine the market sizes of segments and sub-segments.
Secondary Research
In the secondary research process, various secondary sources have been referred to identify and collect information relevant to this study. The secondary sources include annual reports, press releases, and investor presentations of companies; white papers, certified publications, and articles from recognized authors; directories; and databases. Secondary research has been mainly conducted to obtain key information about the industry's supply chain, value chain of the market, the total pool of key players, market classification and segmentation according to smart agriculture industry trends, geographic markets, and key developments from both market- and technology-oriented perspectives.
Primary Research
Extensive primary research has been conducted after understanding and analyzing the smart agriculture market scenario through secondary research. Several primary interviews have been conducted with key opinion leaders from both the demand- and supply-side vendors across four major regions—Americas, Europe, Asia Pacific, and Rest of the World (Russia, the Middle East, and Africa). Approximately 25% of the primary interviews have been conducted with the demand side and 75% with the supply side. This primary data has been collected mainly through telephonic interviews, which consists 80% of total primary interviews; however, questionnaires and e-mails have also been used to collect the data.
After interacting with smart agriculture industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject matter experts’ opinions, has led us to the findings as described in the remainder of this report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
The bottom-up approach has been employed to determine the overall size of the smart agriculture market from the cost incurred by key players and their revenue contribution to the market. The global market size has been validated through primary interviews with smart agriculture industry stakeholders and subject matter experts.
- Entities in the smart agriculture value chain that influence the entire smart agriculture industry were identified
- Analyzing all major companies offering smart agriculture solutions and related services
- Estimating the market for smart agriculture by offering, agriculture type, farm size, and application
- Tracking the ongoing and upcoming developments in smart agriculture applications and forecasting the market based on these developments and other critical parameters
- Undertaking multiple discussions with key opinion leaders to understand the implementation of smart agriculture solutions and their services, which helped analyze the impact of developments undertaken by each major company to increase their share in the smart agriculture market
- Verifying and crosschecking estimates at every level with key opinion leaders, including chief executive officers (CEOs), directors, and operation managers, and then finally with the domain experts at MarketsandMarkets
- Studying various paid and unpaid sources of information such as annual reports, press releases, white papers, and databases for the company- and region-specific developments undertaken in the smart agriculture market
In the top-down approach, the overall market size has been used to estimate the size of the individual markets (mentioned in the market segmentation) through percentage splits obtained from the secondary and primary research processes.
- Focusing initially on the investments and expenditures undertaken in the ecosystem of smart agriculture; the further split is provided on the basis of new installations, upgrades of smart agriculture products and solutions, and key developments in key market areas
- Identifying key players in the smart agriculture market based on smart agriculture hardware, services, and software solutions as well as their applications and verifying the findings through secondary research and brief discussions with smart agriculture industry experts.
- Analyzing revenues, product mix, geographic presence, and key end-use applications of smart agriculture to estimate and arrive at the percentage splits
- Discussing these splits with smart agriculture industry experts to validate the information and identify key growth pockets across all major segments
- Breaking down the total market based on verified splits and key growth pockets across all segments
Data Triangulation
After arriving at the overall size of the smart agriculture market through the process explained above, the total market has been split into several segments and sub-segments. Market breakdown and data triangulation procedures have been employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics for all segments and sub-segments. The data has been triangulated by studying various factors and trends from the demand and supply sides. The market has also been validated using the top-down and bottom-up approaches.
Report Objectives:
- To define, describe, segment, and forecast the smart agriculture market, by agriculture type, offering, application, farm size, and region, in terms of value
- To describe and forecast the smart agriculture market in four key regions: Americas, Europe, Asia Pacific (APAC), and Rest of the World (RoW), in terms of value
- To forecast the smart agriculture market for RFID tags used for livestock monitoring applications, in terms of volume
- To provide detailed information regarding the drivers, restraints, opportunities, and challenges influencing the growth of the smart agriculture market
- To study the complete supply chain of the smart agriculture market and provide detailed information regarding Porter's five forces, technology trends, product pricing trade, use cases, and import and export trends pertaining to the smart agriculture market
- To provide a detailed impact of the recession on the global smart agriculture market
- To analyze opportunities in the market for stakeholders by identifying high-growth segments of the smart agriculture ecosystem
- To strategically profile the key players and comprehensively analyze their market position in terms of ranking and core competencies2, along with detailing the competitive landscape of the market
- To analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the overall market
- To analyze strategic approaches, such as product launches, contracts, agreements, alliances, collaborations, joint ventures, partnerships, expansions, investments, and acquisitions, in the market
Available Customizations:
With the given market data, MarketsandMarkets offers customizations according to the company’s specific needs. The following customization options are available for the report:
- Detailed analysis and profiling of additional market players based on various blocks of the supply chain
Generating Response ...
Growth opportunities and latent adjacency in Smart Agriculture Market
Dairy farm automation and livestock monitoring management have picked up its growth in recent years. Application such as early detection of diseases and feeding management is of focus area for ranchers and farm owners. Have you covered these applications for livestock industry in your reserach survey?
"Adoption of technologies such as GPS, IoT, remote sensing and AI has witnessed substantial adoption in recent years. I am looking for application areas like Yield monitoring, crop scouting, harvesting management, and crop health analytics."
I would like to procure data with breakdown for Asian countries for the smart agricultural report.
I'm working now on the smart farming in the hay and straw market, if you have something in this topic ill might be interested
Have you include aquaculturetechnology in your scope or it is just limited to precision agriculture industry ?