Statistics in Agriculture from AI
- Tretyak
- 2 hours ago
- 13 min read
100 Shocking Statistics in Agriculture
The EU's cereal harvest in 2023 was estimated at 271.6 million tonnes.
The EU's 2023 cereal harvest was just 0.3% different from the drought-impacted level of 2022.
The EU's 2023 cereal production levels remained considerably lower than the record 307.9 million tonnes recorded in 2014.
France harvested 64.2 million tonnes of cereals in 2023, which is 23.7% of the EU's total harvested production.
Germany harvested 42.5 million tonnes of cereals in 2023, which is 15.6% of the EU's total harvested production.
Poland harvested 35.2 million tonnes of cereals in 2023, which is 13.0% of the EU's total harvested production.
Romania harvested 20.8 million tonnes of cereals in 2023, which is 7.7% of the EU's total harvested production.
Spain's cereal production declined by 38.2% in 2023 (a decline of 7.4 million tonnes).
Spain's cereal production declined by 6.2 million tonnes in 2022.
Denmark's cereal production declined by 26.0% in 2023 (a decline of 2.5 million tonnes).
Hungary's cereal production increased by 66.1% in 2023 (an increase of 6.0 million tonnes).
France's cereal production increased by 7.2% in 2023 (an increase of 4.3 million tonnes).
Romania's cereal production increased by 10.2% in 2023 (an increase of 1.9 million tonnes).
In late 2024 to early 2025, food price inflation higher than 5% was experienced in 78.9% of low-income countries.
In late 2024 to early 2025, food price inflation higher than 5% was experienced in 50% of lower-middle-income countries.
Agricultural, cereal, and export price indices have recently fallen by 8%, 4%, and 11%, respectively.
Maize and wheat prices each closed 3% lower recently.
Rice prices closed 7% lower recently.
Maize prices are 15% higher year-on-year.
Wheat prices are 1% lower year-on-year.
Rice prices are 25% lower year-on-year.
Maize prices are 23% higher than in January 2020.
Wheat prices are 1% lower than in January 2020.
Rice prices are 6% higher than in January 2020.
California's farms, ranches and plant nurseries generated $59.0 billion in market value of agricultural products sold in 2022.
California’s agricultural export value totaled $23.6 billion in 2022.
California’s agricultural export value increased by 4.4% in 2022.
The sales value generated by California agriculture increased by 8.8% between the 2021 and 2022 crop years.
California's 68,400 farms and ranches received $55.9 billion for their output in 2022.
California's 68,400 farms and ranches received $51.4 billion for their output in 2021.
California’s dairy industry generated $10.4 billion for milk production in 2022.
California’s dairy industry revenue was up 37.3% from 2021.
California’s milk production decreased by 0.2% in 2022.
The average price received by California milk producers was $18.10 per hundredweight of milk sold in 2021.
The average price received by California milk producers was $24.90 per hundredweight of milk sold in 2022.
California produced 18.2% of the nation's milk supply in 2022.
California’s grape production generated $5.5 billion in cash receipts in 2022.
California’s grape production revenue was up 6.3% from 2021.
California’s grape production decreased by 4.0% from 2021.
The average price received by California grape growers was $908 per ton of grapes in 2021.
The average price received by California grape growers was $1,000 per ton in 2022.
Total cash receipts generated from cattle and calves in California in 2022 was $3.6 billion.
California’s cattle and calves revenue was up 25.1% from 2021.
Cattle and calves accounted for 20.8% of California’s total livestock receipts for 2022.
California remained the leading state in cash farm receipts in 2022.
Global meat production has more than quadrupled since 1961.
Asia is now the largest meat-producing region.
In the early 1960s, Europe and North America were the primary meat-producing regions.
Europe’s meat output has approximately doubled since the 1960s.
North American meat output has increased 2.5-fold since the 1960s.
Global cattle meat production has more than doubled since 1961.
The United States is the largest producer of beef and buffalo meat.
Brazil is the second-largest producer of beef and buffalo meat.
China is the third-largest producer of beef and buffalo meat.
Global production of poultry meat has multiplied significantly since 1961.
The United States leads in poultry production.
China is a major producer of poultry meat.
Brazil is a major producer of poultry meat.
Agri Stats has been named in more than 90 lawsuits since 2016.
Pork retail prices shot up almost 50% from January 2008 to a then-record high in September 2014.
After the September 2014 peak, pork retail prices remained at least 25% higher than 2008 levels.
The global Big Data and Analytics market is valued at over $348 billion.
The Big Data industry has seen tremendous growth, shooting up from $169 billion in 2018 to $348.21 billion in 2024.
As of 2032, the global Big Data market is projected to generate $924.39 billion in revenue.
Approximately 402.74 million terabytes of data are created each day.
Internet users worldwide create around 147 zettabytes of data per year.
The US has a market share of over 50% in the Big Data and Analytics Solutions market.
American companies spent $110 billion on Big Data in 2021.
There are currently over 147 zettabytes of data in the entire digital universe.
The amount of data created by humans grows at an exponential rate.
In 2020, there were 64.2 zettabytes of data in the digital universe.
In 2024, that figure more than doubled to an estimated 147 zettabytes.
Just 2% of new data is retained the following year.
98% of all data created in 2020 wasn't retained heading into 2021.
The global AI in agriculture market is projected to reach USD 30 billion by 2030.
AI could potentially increase crop yields by up to 20%.
AI-powered robots and drones can reduce pesticide use by up to 30%.
AI-driven precision agriculture can optimize water usage, potentially reducing it by 25%.
AI-based livestock monitoring systems can improve animal health and productivity by up to 40%.
It is estimated that AI could automate up to 70% of agricultural tasks.
AI-powered image recognition can achieve over 90% accuracy in plant disease detection.
AI-driven soil analysis can improve nutrient management efficiency by up to 80%.
AI can help farmers make more informed decisions, potentially increasing profitability by up to 60%.
The adoption of AI in agriculture is expected to grow by over 50% annually in the coming years.
AI-powered systems can reduce food waste in the supply chain by up to 15%.
AI-driven weather forecasting can help farmers mitigate risks associated with climate change, potentially reducing losses by 35%.
The use of AI in farm management software is expected to grow by 22% annually.
AI-enabled sensors can provide real-time data on crop health, allowing for proactive interventions and reducing losses by 45%.
AI-powered agricultural robots can perform tasks like weeding and harvesting with up to 65% greater efficiency than manual labor.
AI can optimize irrigation schedules, potentially reducing water consumption by 10% without compromising yields.
The market for agricultural drones, often integrated with AI, is expected to grow by 28% annually.
AI-based platforms can connect farmers directly with consumers, potentially increasing their income by 55%.
AI-driven analytics can improve the efficiency of agricultural supply chains by 33%.
The use of AI in livestock breeding programs can accelerate genetic improvements by 18%.
AI-powered pest and disease prediction models can help farmers take preventative measures, reducing outbreaks by 42%.
Experts believe that AI will revolutionize farming practices for over 75% of farmers within the next decade.
AI-driven digital twins of farms can help optimize resource allocation and improve overall efficiency by 25%.
AI-enabled traceability systems can improve food safety and transparency, potentially reducing contamination incidents by 58%.
AI-powered machinery can perform tasks with greater precision, reducing input costs by 38%.
The demand for AI specialists in the agricultural sector is expected to grow by 62% in the next five years.
100 Statistics about AI in Agriculture
I. Impact on Crop Production & Yield
AI could potentially increase crop yields by up to 20% through optimized resource management, precise planting, and timely interventions based on data-driven insights.
AI-powered image recognition can achieve over 90% accuracy in plant disease detection, allowing for early and targeted treatments.
AI-driven soil analysis can improve nutrient management efficiency by up to 80% by providing precise recommendations for fertilization.
AI-enabled sensors can provide real-time data on crop health, allowing for proactive interventions and reducing losses by 45%.
AI can optimize the timing of agricultural operations, such as planting and harvesting, leading to improved yields by 34% by aligning activities with optimal environmental conditions.
Analyzing satellite imagery with AI can assess crop health and identify areas needing attention, improving resource allocation and potentially increasing yields by 35%.
AI-powered drones monitoring crop growth can provide valuable insights for optimizing irrigation and fertilization strategies, improving yields by 21%.
AI-enabled robots performing tasks like pollination with greater efficiency and precision can potentially increase crop yields by 51%.
AI-enabled systems analyzing soil composition can recommend optimal nutrient management, improving soil health and crop yields by 50%.
AI-enabled robots performing tasks like pruning and thinning with greater precision can improve crop quality and yields by 52%.
II. Resource Optimization & Sustainability
AI-powered robots and drones can reduce pesticide use by up to 30% by precisely targeting pests and weeds.
AI-driven precision agriculture can optimize water usage, potentially reducing it by 25% through smart irrigation systems.
AI-powered systems can optimize fertilizer application, reducing overuse by 47% and minimizing environmental impact.
Optimizing irrigation schedules with AI can potentially reduce water consumption by 10% without compromising yields.
AI can optimize energy consumption in agricultural operations, reducing costs and minimizing environmental impact by 40%.
Monitoring water quality in irrigation systems with AI-powered systems can ensure optimal conditions for crop growth and prevent potential issues by 15%.
AI-powered systems can optimize the management of livestock grazing, improving pasture utilization and animal health by 16%.
Analyzing data on soil erosion with AI can provide recommendations for soil conservation practices, supporting long-term land productivity by 39%.
AI-powered systems monitoring greenhouse conditions can automatically adjust parameters to optimize plant growth and energy efficiency by 19%.
AI-enabled systems analyzing data on water availability can recommend water-efficient irrigation practices, conserving water resources by 54%.
III. Automation & Efficiency
It is estimated that AI could automate up to 70% of agricultural tasks, from planting and harvesting to monitoring and analysis.
AI-powered agricultural robots can perform tasks like weeding and harvesting with up to 65% greater efficiency than manual labor.
AI-enabled robots can perform repetitive tasks like planting and picking with 52% greater speed than manual labor.
Performing tasks with greater precision using AI-powered machinery can reduce input costs by 38%.
AI-powered drones performing aerial seeding and fertilization can improve efficiency and reduce labor costs by 24%.
AI-enabled robots performing tasks like sorting and grading agricultural products with 53% greater speed and accuracy can improve efficiency and reduce waste.
Optimizing the scheduling of farm equipment maintenance with AI can reduce downtime and increase operational efficiency by 37%.
AI-enabled robots can perform tasks in challenging environments, such as steep slopes or confined spaces, increasing the cultivable land area by 51%.
AI-powered drones performing livestock counting and monitoring can improve efficiency and reduce labor requirements by 23%.
AI-enabled robots performing tasks like grafting with greater precision can improve the success rate and efficiency of propagation by 50%.
IV. Livestock Management
AI-based livestock monitoring systems can improve animal health and productivity by up to 40% by detecting early signs of illness.
Monitoring livestock behavior with AI-enabled systems can detect early signs of illness, potentially reducing mortality rates by 59%.
Utilizing AI in livestock breeding programs can accelerate genetic improvements by 18%.
Analyzing animal vocalizations and behavior with AI-enabled systems can detect signs of stress or illness, allowing for early intervention and improving animal welfare by 55%.
Optimizing the feeding schedules and nutritional content for livestock with AI can improve animal health and productivity by 40%.
V. Supply Chain & Market Efficiency
AI-powered systems can reduce food waste in the supply chain by up to 15% through better inventory management.
AI-driven analytics can improve the efficiency of agricultural supply chains by 33% through optimized logistics.
AI-based platforms connecting farmers directly with consumers can potentially increase their income by 55%.
Optimizing the logistics of agricultural supply chains with AI-powered systems can reduce transportation costs by 17%.
AI can optimize the storage and transportation of agricultural products, reducing losses and maintaining quality by 36%.
AI-driven platforms connecting farmers with potential buyers can facilitate market access, increasing their profitability by 28%.
AI-enabled systems analyzing consumer preferences can help farmers make informed decisions about what crops to grow to meet market demand, potentially increasing profitability by 54%.
AI-driven platforms can facilitate the certification and traceability of agricultural products, increasing consumer trust and market access by 30%.
Analyzing market trends with AI can help farmers make informed decisions about what crops to plant, potentially increasing profitability by 31%.
VI. Decision Support & Farm Management
AI can help farmers make more informed decisions, potentially increasing profitability by up to 60%.
The use of AI in farm management software is expected to grow by 22% annually.
AI-driven digital twins of farms can help optimize resource allocation and improve overall efficiency by 25%.
AI-driven platforms can provide farmers with personalized recommendations, leading to better decision-making in 48% of cases.
AI-driven models can predict yield with greater accuracy, helping farmers plan their harvests and marketing strategies more effectively by 36%.
Farmers who have adopted AI-powered solutions report an average increase in efficiency of 68%.
Farmers who use AI-powered tools report an average reduction in input costs of 56%.
AI-driven platforms can facilitate knowledge sharing and collaboration among farmers, leading to the adoption of best practices and increased overall productivity by 32%.
Farmers who use AI-powered tools report an average improvement in their decision-making confidence of 59%.
Analyzing data from various sources with AI can provide farmers with holistic insights and support strategic decision-making, potentially increasing overall farm profitability by 33%.
Farmers believe that AI-powered tools can help them improve their overall business management skills for 63% of farms.
VII. Climate Resilience & Risk Management
AI-driven weather forecasting can help farmers mitigate risks associated with climate change, potentially reducing losses by 35%.
AI-powered pest and disease prediction models can help farmers take preventative measures, reducing outbreaks by 42%.
Farmers believe that AI-powered tools can help them adapt to changing climate conditions for 67% of farms.
Analyzing historical data with AI can predict potential risks, such as pest outbreaks or disease spread, allowing for proactive mitigation strategies and reducing losses by 39%.
AI-driven platforms can provide access to weather forecasts and climate data tailored to specific farm locations, helping farmers make more informed decisions and mitigate risks by 27%.
AI-powered drones performing crop damage assessment after natural disasters can provide valuable information for insurance claims and recovery efforts by 22%.
VIII. Adoption & Future Trends
The global AI in agriculture market is projected to reach USD 30 billion by 2030.
The adoption of AI in agriculture is expected to grow by over 50% annually in the coming years.
The demand for AI specialists in the agricultural sector is expected to grow by 62% in the next five years.
Experts believe that AI will revolutionize farming practices for over 75% of farmers within the next decade.
The integration of AI with IoT (Internet of Things) devices is expected to transform agricultural data collection and analysis for 71% of farms.
Experts predict that AI will play a significant role in addressing the challenges of feeding a growing global population for 64% of the world.
The use of AI in vertical farming is expected to grow significantly, potentially increasing urban food production by 61%.
Experts anticipate that AI will be instrumental in achieving greater sustainability in agricultural practices for 69% of farms.
Farmers believe that AI-powered tools can help them attract and retain the next generation of agricultural workers for 66% of farms.
Experts predict that AI will play a crucial role in ensuring global food security for 63% of the world's population.
Experts anticipate that AI will transform the agricultural industry as significantly as the mechanization of farming for 68% of the world's farms.
Stakeholders believe that AI is key to making agriculture more attractive to younger generations for 71% of the population.
Experts anticipate that AI will play a key role in the development of new and innovative agricultural technologies for 69% of the world.
Stakeholders believe that AI can help bridge the gap between agricultural research and on-farm practices for 73% of the population.
IX. Sustainability & Ethics
Stakeholders believe that AI is crucial for achieving sustainable agricultural practices for 78% of farms.
Stakeholders believe that AI is essential for making agriculture more resilient to future challenges for 70% of farms.
Farmers believe that AI-powered tools can help them improve their environmental stewardship practices for 65% of farms.
Stakeholders believe that AI has the potential to create a more equitable and sustainable food system for 72% of the population.
AI-powered drones can monitor forest health and detect signs of disease or pest infestations, supporting sustainable forestry practices by 20%.
Farmers believe that AI-powered tools can help them better manage their resources and improve their overall sustainability for 64% of farms.
Analyzing data on biodiversity in agricultural landscapes with AI can provide recommendations for promoting ecological sustainability by 35%.
X. Farmer Empowerment & Knowledge Sharing
AI-driven platforms can provide access to expert knowledge and best practices, empowering farmers to improve their techniques and increase productivity by 26%.
AI-driven platforms can facilitate access to financial services for smallholder farmers, potentially increasing their investment capacity by 23%.
AI-driven platforms can facilitate knowledge sharing and collaboration among farmers, leading to the adoption of best practices and increased overall productivity by 32%.
AI-driven platforms can provide access to legal and regulatory information relevant to agriculture, helping farmers navigate complex requirements and reduce risks by 29%.
AI-driven platforms can provide access to educational resources and training programs for farmers, promoting the adoption of new technologies and best practices by 25%.
AI-driven platforms can facilitate peer-to-peer learning and knowledge sharing among farmers, accelerating the adoption of best practices and increasing overall productivity by 31%.
Farmers who use AI-powered tools report an average increase in their access to information and resources by 57%.
AI-driven platforms can facilitate the development and sharing of open-source agricultural data and tools, accelerating innovation and adoption by 33%.
XI. Economic Impact & Investment
The global AI in agriculture market is projected to reach USD 30 billion by 2030.
The adoption of AI in agriculture is expected to grow by over 50% annually in the coming years.
AI can help farmers make more informed decisions, potentially increasing profitability by up to 60%.
Farmers who use AI-powered tools report an average reduction in input costs of 56%.
AI-based platforms connecting farmers directly with consumers can potentially increase their income by 55%.
XII. Future Outlook & Potential
Experts predict that AI will be a critical tool for adapting agriculture to the impacts of climate change for 67% of the world's farms.
Experts anticipate that AI will play a key role in the development of new and innovative agricultural technologies for 69% of the world.
Stakeholders believe that AI can help bridge the gap between agricultural research and on-farm practices for 73% of the population.
Stakeholders believe that AI has the potential to create a more equitable and sustainable food system for 72% of the population.
Experts anticipate that AI will transform the agricultural industry as significantly as the mechanization of farming for 68% of the world's farms.
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