Global Intelligent Agriculture Market Analysis by Application, Types, Segment, Opportunity & Industry Demand 2018
The Global Intelligent Agriculture Market was worth USD 6.27 billion in 2017 and estimated to be growing at a CAGR of 13.44%, to reach USD 11.78 billion by 2022. Intelligent Agriculture involves technology-driven information analysis of data acquired from the fields and the application of inputs according to the data analysis for raising crop productivity.
It includes the use of modern technologies of farming which help in improving the quality of food and growing the yield of farms.
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Smart agriculture tools are most extensively used in precision farming since they play a vital role in improving farm efficiency and help growers in maximizing their yields of crop.
Yield monitoring is a major application of precision farming used to identify the field variability information, which includes soil properties, weather conditions, and fertilizers. Soil monitoring is a major application of yield monitoring, which helps in identifying different soil parameters in order to maintain the nutrient level of the soil.
The driving factors of global Intelligent Agriculture market are increasing application of technologies in agriculture, rising need of monitoring livestock performance and health, government’s support to adopt modern agricultural techniques, and increasing demand for food worldwide. The major constraining factors for the growth of the smart agriculture market include the high initial investments and the lack of technical awareness among the growers.
The global Intelligent Agriculture market is segmented based on the basis of agriculture type into livestock monitoring, precision farming, smart greenhouses, fish farming and others. By application, the market is divided into livestock monitoring applications, precision farming applications, fish farming applications, smart greenhouse applications and others.
Precision Farming Applications is further divided into Yield Monitoring, Field Mapping, Crop Scouting, Weather Tracking & Forecasting, Irrigation Management, Inventory Management, Farm Labor Management, Financial Management and others. Livestock Monitoring Applications is further segmented into Feeding Management, Heat Stress Management, Milk Harvesting, Breeding Management, Animal Comfort Management, Behavior Monitoring & Management and others.
Fish Farming Applications is further categorised into Fish Tracking & Fleet Navigation, Feeding Management, Water Quality Management and others. Smart Greenhouse Applications is further divided into Hvac Management, Yield Monitoring and Water & Fertilizer Management.
By offering, market is categorised into Hardware, Software and Services. Hardware is further segmented into Hardware for Precision Farming, Hardware for Livestock Monitoring, Hardware for Fish Farming, Hardware for Smart Greenhouse and Hardware for Others Market.
Software is further divided into Local/Web Based and Cloud Based. Services is further segmented into System Integration and Consulting, Managed Services, Connectivity Services, Assisted Professional Services and Maintenance and Support.
The Global Intelligent Agriculture market is divided based on geography into North America, Latin America, Asia-Pacific, Middle East and Africa and Europe. North America has the leading market for Intelligent Agriculture in the world, which is followed by Europe and Asia Pacific regions.
Asia Pacific region is expected to have the fastest growth rate during the forecast period, owing to rising populations and economies in the region.
Some of the major players in the market are European GNSS Agency (GSA) (Czech Republic), Precision Ag Institute (U.S.), International Society for Precision Agriculture (ISPA) (U.S.), SPAA Precision Agriculture (Australia), CropLife (CropLife Media Group) (U.S.), Precision Agriculture Association (New Zealand), and Agricultural Research Organization (Israel).
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Some Point from Table of Content:
1.1 Market Definition
1.2 Study Deliverables
1.3 Base Currency, Base Year and Forecast Periods
1.4 General Study Assumptions
- Research Methodology
2.2 Research Phases
2.2.1 Secondary Research
2.2.2 Primary Research
2.2.3 Econometric Modelling
2.2.4 Expert Validation
2.3 Analysis Design
2.4 Study Timeline
3.1 Executive Summary
3.2 Key Inferences
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