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Agriculture Analytics Market was valued at USD 2.3 billion in 2023 and is estimated to register a CAGR of over 10% between 2024 and 2032. The market is expanding owing to the growing adoption of precision farming, government support, food security concerns, technological advancements, environmental sustainability, and increasing investments. Precision farming involves the use of analytics and data to manage farming practices efficiently. This technology enhances crop yields, optimizes input usage, and improves farm management.
For instance, in April 2024, the U.S. Department of Agriculture reported a 25% increase in the adoption of precision farming techniques among farmers in the U.S. over the past three years. It highlighted that precision farming is significantly improving productivity and resource management in agriculture.
Governments worldwide are providing subsidies and support for the adoption of advanced agricultural technologies, including analytics. These initiatives aim to boost agricultural productivity and sustainability. For instance, in January 2024, the European Commission announced a USD 1.07 billion subsidy program for digital agriculture, which focuses on analytics tools to enhance farm productivity and sustainability. This initiative is part of the EU's common agricultural policy for 2024-2027.
Report Attribute | Details |
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Base Year: | 2023 |
Agriculture Analytics Market Size in 2023: | USD 2.3 Billion |
Forecast Period: | 2024-2032 |
Forecast Period 2024-2032 CAGR: | 10% |
2032 Value Projection: | USD 5.4 Billion |
Historical Data for: | 2021-2023 |
No. of Pages: | 240 |
Tables, Charts & Figures: | 310 |
Segments covered: | Offering, Farm Size, Application, Technology |
Growth Drivers: |
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Pitfalls & Challenges: |
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Implementing advanced analytics Software can be expensive, including costs for hardware, software, and training. Many small-scale farmers find it difficult to justify these investments due to uncertain returns on investment. Many rural areas, where agriculture is predominant, suffer from limited internet connectivity and infrastructure. This hampers the deployment and effectiveness of cloud-based analytics software. Also, farmers’ concerns about data privacy and the security of their agricultural data may limit adoption.