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農業における人工知能市場ー業界洞察、主要プレーヤー・企業別、成長機会別、最新傾向別、開発別、主要な成長ドライバー別、主要な課題別によってセグメンテーション、予測


[ 英語タイトル ] Artificial Intelligence in Agriculture Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)


Product Code : MDAG00113005
Survey : Mordor Intelligence
Publish On : May, 2021
Category : Agriculture and Allied Activities
Report format : PDF
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Global

[Report Description]

The is Global Artificial Intelligence in Agriculture Market is projected to register a CAGR of 4.2% during the forecast period (2021-2026). Before Covid -19 the adoption of AI in the agriculture was already in rise but during covid the market has grown more. There is increase in the implementation AI through various products of sensors, drones, SaaS. These innovative technologies have helped farmers and save their crops and harvest from complete loss during covid. Hence, COVID-19 has a postive impact on the market. Maximize crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyze crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant. Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle. However, lack of standardization is restraining the market growth as lack of standards in data collection, and lack of data sharing is high, and machine learning and artificial intelligence and advanced algorithm design have moved so fast, but the collection of well-tagged, meaningful agricultural data is way behind.

Key Market Trends

Labor Shortage and Increasing Costs of Labor to Drive the Artificial Intelligence Market

Across the world, a huge decline of the workforce is observed due to many reasons, like the lack of skilled labor, aging of farmers, and young farmers finding farming an unattractive profession, thus encouraging trends for automated farming operations. According to NSS and PLFS (2018-19) report, the agriculture sectors contribution to employment has declined by 81.0% in 1983 to 58.0% in 2018 and according to the International Labor Organization(ILO), agricultural labors in the percentage of the workforce declined from 81.0% to 48.2% in developing countries in 2018. Also, developed countries are not an exception in such a huge decline. Asia-Pacific, where agriculture occupies a major part of the economy, has a huge decline in workforce, which was nearly about 9.0% from 2015 to 2017. In Japan, the number of people working in farms witnessed a steep fall to 1.7 million in the year 2015, a 15% decline from the previous year. The European agriculture sector has also faced such a huge decline in the workforce, which is nearly accounting to 12.8% for the corresponding period. The trend of decline in the agricultural workforce is encouraging government and private organizations to focus on automation operations by adopting artificial intelligence technologies in the agriculture sector. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.

China's Technological Innovations to Accelerate the Agriculture Sector

The technological innovations pertaining to the Chinese market, are also accelerating the growth and transforming the global artificial intelligence market in the agriculture sector. In recent years, the technologies such as AI have been aggressively deployed to accelerate the modernization of Chinese agriculture. These technology are being applied mainly in planting, animal husbandry, and agricultural services. For instance, McFly's Intelligent agricultural monitoring drone, GAGO's large scale application of AI technology in crop production and livestock farming, and UniStrong's "Huinong" Beidou navigation agricultural automatic driving system are few recent innovations prevailing in the Chinese Ai sector. Additionally, few technological giants have also begun to make deployment in the agricultural sector. For instance in the year 2018, JD.com's "Jing Dong Farm" has made its debut, similarly in June 2018, Alibaba's Et agricultural brain has been launched. Thus, increasing innovation in the Chinese AI sector is likely to further boost the adoption of AI in the agriculture in the coming future.

Competitive Landscape

The AI market in agriculture is fragmented, as a number of players supplying the same product at lower-cost make market competition stiff. Also, technological advancements by players and the high presence of local and regional players pose a major threat in a price-sensitive market. Key players are Microsoft Corp., IBM Corp. (NITI Aayog), Agribotix LLC, etc.

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1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.3 Market Restraints
4.4 Porter's Five Force Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry

5 MARKET SEGMENTATION
5.1 Application
5.1.1 Weather Tracking
5.1.2 Precision Farming
5.1.3 Drone Analytics
5.2 Deployment
5.2.1 Cloud
5.2.2 On-Premise
5.2.3 Hybrid
5.3 Geography
5.3.1 North America
5.3.1.1 United States
5.3.1.2 Canada
5.3.1.3 Mexico
5.3.1.4 Rest of North America
5.3.2 Europe
5.3.2.1 Germany
5.3.2.2 United Kingdom
5.3.2.3 Italy
5.3.2.4 Spain
5.3.2.5 Rest of Europe
5.3.3 Asia Pacific
5.3.3.1 China
5.3.3.2 Japan
5.3.3.3 India
5.3.3.4 Australia
5.3.3.5 Rest of Asia-Pacific
5.3.4 South America
5.3.4.1 Brazil
5.3.4.2 Argentina
5.3.4.3 Rest of South America
5.3.5 Africa
5.3.5.1 South Africa
5.3.5.2 Rest of Africa

6 COMPETITIVE LANDSCAPE
6.1 Most Adopted Strategies
6.2 Market Share Analysis
6.3 Company Profiles
6.3.1 Microsoft Corporation
6.3.2 IBM Corporation
6.3.3 Granular, Inc.
6.3.4 aWhere, Inc.
6.3.5 Prospera Technologies Ltd.
6.3.6 Gamaya SA
6.3.7 ec2ce
6.3.8 PrecisionHawk Inc.
6.3.9 Cainthus Corp.
6.3.10 Tule Technologies Inc.

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

8 AN ASSESSMENT OF COVID-19 IMPACT ON THE MARKET

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