Machine Learning For Crop Yield Prediction Market Forecast 2025-2034: Comprehensive Analysis And Growth Opportunities

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What Is the Projected Growth of the Machine Learning For Crop Yield Prediction Market?
Exponential growth has been observed in the market size for machine learning for crop yield prediction in the recent past. It is anticipated to increase from $0.79 billion in 2024 to $1.01 billion in 2025, with a compound annual growth rate (CAGR) of 26.9%. This surge during the historical period can be credited to the growing global population and their demand for food, the escalating usage of previous data for modelling, the burgeoning acceptance of precision agriculture, the uptick in investments and financing in agtech, as well as climate-smart agriculture.It is expected that the market for machine learning in crop yield prediction will experience tremendous growth in the coming years. The market is projected to expand to $2.58 billion by 2029, with a Compound Annual Growth Rate (CAGR) of 26.6%. Factors contributing to this projected growth during the forecast period include improved accuracy and efficiency of ML-driven predictions, escalating global population with limited resources, the emergence of big data in the agricultural sector, environmental variations and climate change, and the implementation of sustainable farming methods. Key trends during the forecast period are predicted to be AI technology, machine learning technologies used for crop yield prediction, integration of the Internet of Things (IoT), technological evolution, and the deployment of AI-controlled autonomous tractors.

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What Are the Different Machine Learning For Crop Yield Prediction Market Segments?
The machine learning for crop yield prediction market covered in this report is segmented -

1) By Component: Software, Services
2) By Deployment Model: Cloud-Based, On-Premises
3) By Farm Size: Small, Medium, Large
4) By End User: Farmers, Agricultural Cooperatives, Research Institutions, Government Agencies, Other End Users

Subsegments:
1) By Software: Predictive Analytics Software, AI-Powered Crop Monitoring Software, Weather And Climate Data Analytics Software, Remote Sensing And Satellite Imaging Software, Farm Management Software
2) By Services: Consulting And Advisory Services, Implementation And Integration Services, Training And Support Services, Data Analytics And Custom Modeling Services, Cloud-Based Agricultural AI Services

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What Are the Primary Drivers Shaping the Machine Learning For Crop Yield Prediction Market?
The push towards sustainable agricultural methods is anticipated to fuel the machine learning for crop yield prediction market's expansion. The concept of sustainable agriculture encompasses a comprehensive approach to farming, with an emphasis on food and other agricultural goods production, resource preservation, biodiversity promotion, economic sustainability, and social fairness for current and future generations. The importance of sustainable agriculture is growing in response to increasing anxieties about environmental destruction, resource shortages, climate change, and the desire for healthier, more robust food systems that offer long-term food security and community wellness. Machine learning for crop yield prediction plays a crucial role in sustainable agriculture by enabling data-driven decision-making, promoting optimal resource use, reducing waste, increasing crop productivity, and enhancing efficiency while minimizing environmental damage. For example, in February 2024, IFOAM Organics International, a German non-profit organization, noted a more than 20 million hectare increase in the global organic farming area in 2022, bringing the total to 96 million hectares. The number of organic producers grew significantly, exceeding 4.5 million. Organic food sales also nearly hit 135 billion euros in 2022. Thus, sustainable agricultural practices are propelling the expansion of the machine learning for crop yield prediction market.

Which Companies Are Leading in the Machine Learning For Crop Yield Prediction Market?
Major companies operating in the machine learning for crop yield prediction market are Microsoft Corp., BASF SE, International Business Machines Corp., Bayer AG, Ninjacart, Raven Industries Inc., Cropin Technology Solutions Pvt., Terramera Inc., FarmWise Labs Inc., Sentera Inc., Taranis, Ceres Imaging Inc., CropX Inc., PrecisionHawk, Aerobotics Ltd., Fasal, IUNU Inc., AgriWebb Pty Ltd., Keymakr Inc., Trace Genomics Inc., Bloomfield Robotics, Agrograph Inc., Xyonix Inc., AiDOOS Corp., FruitSpec

What Are the Major Trends Shaping the Machine Learning For Crop Yield Prediction Market?
Key players in the machine learning market for predicting crop yields are prioritizing the development of platforms incorporating GenAI to facilitate the creation of unique, data-dependent solutions. These GenAI-integrated platforms are sophisticated systems that merge generative artificial intelligence with other innovations to assist in the creation, adaptation, and distribution of AI-produced content and solutions across a variety of sectors and uses. As an example, CropIn, an agtech firm from India, joined forces with the U.S technology firm, Google (Gemini), to launch the GenAI-enabled agri-tech platform, Sage, in July 2024. The distinctiveness of Sage lies in its ability to provide intricate, grid-oriented insights on crop behavior across varying time periods through merging generative AI, sophisticated crop and weather models, and observational data from Earth. Through this merging, Sage has the capacity to create a one-of-a-kind grid-based map for agricultural data, featuring unparalleled scale, accuracy, and speed. It revolutionizes how crop dynamics, climate influences and ideal farming practices are understood by stakeholders, facilitating informed, data-based decisions in several languages throughout global agricultural operations.

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What Are the Top Revenue-Generating Geographies in the Machine Learning For Crop Yield Prediction Market?
North America was the largest region in the machine learning for crop yield prediction market in 2024. The regions covered in the machine learning for crop yield prediction market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Frequently Asked Questions:
1. What Is the Market Size and Growth Rate of the Machine Learning For Crop Yield Prediction Market?
2. What is the CAGR expected in the Machine Learning For Crop Yield Prediction Market?
3. What Are the Key Innovations Transforming the Machine Learning For Crop Yield Prediction Industry?
4. Which Region Is Leading the Machine Learning For Crop Yield Prediction Market?

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