The global agricultural industry is undergoing a profound transformation with advancements in artificial intelligence (AI) technology. AI is transforming and improvising various aspects of agriculture, from increasing productivity and efficiency to improving sustainability and reducing waste.
SwissCognitive Guest Blogger: Kashish Khan – “Top 10 AI Trends to Catapult the Global Agricultural Landscape in 2024”
In 2024, we can expect to see the following top 10 AI trends that will reshape the agricultural landscape worldwide.
This shift from traditional agriculture to advanced and modern precision agriculture provides for a suitable avenue to the agriculture industry to grow, providing lucrative opportunities for agritech companies and agribusinesses.
According to data insights from BIS Research, a market research company, the global precision agriculture market was valued at $7.89 billion in 2022 and is expected to reach $14.61 billion in 2027, following a CAGR of 13.12% during 2022-2027.
In 2024, we can expect to see the following top 10 AI trends that will reshape the agricultural landscape worldwide.
1. Autonomous Tractors and Farming Equipment
Autonomous tractors and farming equipment are set to become a game-changer in the agriculture industry. These self-driving machines will leverage AI and computer vision to perform tasks such as plowing, planting, and harvesting with utmost precision. By eliminating the need for human intervention, autonomous farming equipment will enhance productivity, reduce labor costs, and optimize resource utilization.
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For instance, John Deere’s 8R, a fully autonomous tractor was revealed at CES 2022, which is equipped with GPS guidance, lidar, and advanced cameras.
Similarly, AgXeed Drive, an autonomous tractor equipped with GPS guidance, cameras, and radar was developed by AgXeed, a Dutch company.
Furthermore, Several companies have launched autonomous weeding robots, including FarmBot, EcoRobotix, and Naio Technologies. These robots use cameras and sensors to identify weeds and then remove them without the use of herbicides.
2. Big Data Analytics and Decision Support Systems
The abundance of data generated in agriculture can overwhelm farmers. However, AI-powered big data analytics and decision support systems will provide actionable insights, helping farmers make informed decisions. By analyzing various data points such as weather patterns, soil conditions, and crop health, these systems will optimize planting schedules, predict disease outbreaks, and recommend appropriate fertilization techniques.
In April 2023, an AI agricultural advisor named “Norm” was launched, marking a significant development in the field. Norm possesses the ability to rapidly provide crucial information, such as methods to combat specific pests, the most suitable seed varieties for specific soil types, and strategies for identifying and preventing cattle diseases.
3. Plant Health Sensors
Plant health sensors integrated with AI algorithms will enable farmers to monitor the well-being of crops in real-time. These sensors can detect diseases, nutrient deficiencies, and pest infestations early on, allowing for timely intervention. AI algorithms can process the data collected by these sensors, providing farmers with precise information on crop health and optimizing the use of pesticides and fertilizers.
In April 2023, Researchers at North Carolina State University developed a wearable electronic patch that can be placed on plant leaves to monitor the presence of pathogens and environmental stressors. The small patch incorporates sensors and electrodes to detect temperature, humidity, and moisture levels. In experiments with tomato plants, the patch successfully identified pathogenic infections and stressors. The researchers plan to make the patches wireless and test them in real-world conditions, aiming to assist growers in preventing crop problems and addressing food security challenges.
4. Agriculture Drones and Robots
Agriculture drones and robots equipped with AI capabilities will transform the way farmers manage their fields. Drones can survey large areas quickly, capturing high-resolution images of crops. AI algorithms can then analyze these images to identify areas requiring attention, such as water stress or weed infestations. Robots, on the other hand, can perform labor-intensive tasks like weeding or pruning with precision and efficiency, reducing the need for manual labor.
In June 2023, Precision AI, a Canadian startup, developed autonomous AI-powered drones for plant-level herbicide application. The drones aim to address the challenges faced by farmers in meeting food demand through intensive agricultural practices that result in environmental pollution. The technology offers real-time insights, data collection, and predictions for individual plant management, reducing water use, costs, and chemical excess while promoting soil health. Precision AI’s drones use edge computing to function without internet connectivity, providing near-instant weed identification. With $20 million in funding, the company plans to be operational by 2026 and expand into other applications such as insecticide reduction and fungicide optimization.
5. Farm Management Software
AI-powered farm management software will consolidate various aspects of farming, from inventory management to financial planning. These systems will integrate data from multiple sources, such as weather forecasts, market trends, and field conditions, to provide farmers with holistic insights into their operations. By streamlining workflows and optimizing resource allocation, farm management software will enhance productivity and profitability.
In March 2023, Bushel Inc., an independent software company launched Bushel Farm, a next-generation farm management software designed to reduce manual data entry for farmers and provide grain marketing insights. The software, built upon the company’s FarmLogs solution, offers a comprehensive feature set for mobile and desktop experiences while maintaining user-friendly design.
Moreover, Bushel will release an integration that enables farmers to automatically import their individual grain sales data into Bushel Farm, reducing the need for manual entry. This integration will provide valuable time savings for farmers and enhance the software’s capabilities. The software is available for both individual farms and commercial grain buyers/agribusinesses seeking to strengthen relationships and streamline grain marketing. Moreover, integrations with John Deere Operations Center™ and Climate FieldView® enhance data imports, and data privacy controls ensure authorized sharing.
6. Climate-Smart Technology
The agricultural industry is under increasing pressure to mitigate the effects of climate change. AI-driven climate-smart technology will aid in the development of sustainable farming practices. By analyzing historical climate data, AI algorithms can predict weather patterns and help farmers adapt their cultivation techniques accordingly. This will enable the industry to optimize water usage, reduce greenhouse gas emissions, and enhance overall resilience.
In May 2023, the University of Minnesota was granted $20 million over five years from the National Science Foundation (NSF) and the U.S. Department of Agriculture’s National Institute of Food and Agriculture (NIFA) to establish a National Artificial Intelligence Research Institute. The institute, known as AI-CLIMATE, aims to leverage artificial intelligence (AI) to develop climate-smart practices that simultaneously absorb and store carbon while promoting economic growth in the agriculture and forestry sectors.
7. Resiliency in Supply Chain
AI technology can bolster the resiliency of agricultural supply chains. By leveraging predictive analytics, machine learning, and data from multiple sources, AI systems can optimize logistics, inventory management, and demand forecasting. This will enable farmers to respond to market demands more effectively, reduce wastage, and ensure a steady supply of fresh produce.
In March 2023, Helios Artificial Intelligence, Inc. launched the open beta of its platform that detects agricultural supply chain disruptions in advance. The platform provides customized climate and economic risk insights for over 200 commodities in 180 countries, enabling agricultural importers to stay ahead of their competitors. Helios helps users predict supply availability, identify risks to yields, and provide valuable input for negotiation processes. Customers have already experienced transformative results, gaining actionable insights and proactively mitigating disruptions. The platform offers transparency into ESG, climate, economic, and political factors affecting suppliers.
8. Convergence with IoT
The convergence of AI with the Internet of Things (IoT) will amplify the transformative potential of agriculture. IoT devices, such as soil moisture sensors and smart irrigation systems, can collect vast amounts of data. AI algorithms can then process this data to automate and optimize irrigation, fertilizer application, and other farming operations. The integration of AI and IoT will enable farmers to achieve higher yields, conserve resources, and enhance sustainability.
In June 2023, Trilogy Networks, Veea, and Microclimates formed a partnership to offer an all-in-one agritech solution. Trilogy Networks, a leader in the agritech IoT-edge-cloud-platform market, aims to combine their technologies and platforms with Veea and Microclimates. The new Trilogy platform allows farmers and enterprises to collect, compute, and protect data at the edge, enhancing operational efficiency and reducing costs. Veea provides unified connectivity between the cloud, endpoints, edge, and devices. Microclimates specializes in smart climate-controlled environment management, enabling farmers to monitor and control temperature, humidity, CO2 levels, watering, and ambient light. Their platform supports thousands of sensors and provides 24/7 live monitoring.
9. AI Integration in Agriculture Biotechnology
AI is playing a pivotal role in advancing agricultural biotechnology. Genetic algorithms and machine learning techniques can accelerate the breeding process, helping develop crops with improved traits, such as disease resistance or higher yields. AI can also facilitate gene editing techniques, such as CRISPR, enabling precise and efficient modifications to plant genomes. These advancements will drive the development of resilient, high-performing crops.
For instance, in March 2023, InnerPlant and Mertec LLC joined forces to develop crops that can communicate biological stresses before they become visible to farmers. By integrating InnerPlant’s seed technology with Mertec’s soybean germplasm, the aim is to create crops that emit signals when they are under stress from pathogens, water deficiency, or nutrient deficiency. These signals, visible from satellites and tractors, provide early detection of problems weeks before they would be noticeable in the field
10. Precision Irrigation
Water scarcity is a significant challenge in agriculture, making precision irrigation a critical trend. AI algorithms can analyze data from various sources, including weather forecasts and soil moisture sensors, to optimize irrigation schedules. By delivering the right amount of water at the right time, precision irrigation enhances water-use efficiency, conserves resources, and minimizes environmental impact.
In April 2023, BASF and AGCO Corporation partnered to integrate and commercialize smart spraying technology on Fendt Rogator sprayers. Developed by Bosch BASF Smart Farming, this advanced solution allows precise herbicide application for effective weed control and cost optimization. Trials for the technology began in May 2021, showcasing its targeted spraying capabilities in various conditions, day, or night. The system saves herbicide through precise application, advanced sensors, automated sensitivity thresholds, and weed identification technology.
Conclusion
As we look forward to 2024, the global agricultural landscape is poised to undergo significant transformations driven by AI technology. Embracing the aforementioned advancements will empower farmers to overcome challenges, enhance productivity and profitability, and ensure a sustainable future for the agricultural sector.
About the Author:
Kashish Khan is a seasoned content writer with extensive experience in writing on various deep tech verticals concerning Artificial Intelligence and and IoT. She is affiliated with a reputed market research firm through which I receive critical insights into the industry.
The global agricultural industry is undergoing a profound transformation with advancements in artificial intelligence (AI) technology. AI is transforming and improvising various aspects of agriculture, from increasing productivity and efficiency to improving sustainability and reducing waste.
SwissCognitive Guest Blogger: Kashish Khan – “Top 10 AI Trends to Catapult the Global Agricultural Landscape in 2024”
This shift from traditional agriculture to advanced and modern precision agriculture provides for a suitable avenue to the agriculture industry to grow, providing lucrative opportunities for agritech companies and agribusinesses.
According to data insights from BIS Research, a market research company, the global precision agriculture market was valued at $7.89 billion in 2022 and is expected to reach $14.61 billion in 2027, following a CAGR of 13.12% during 2022-2027.
In 2024, we can expect to see the following top 10 AI trends that will reshape the agricultural landscape worldwide.
1. Autonomous Tractors and Farming Equipment
Autonomous tractors and farming equipment are set to become a game-changer in the agriculture industry. These self-driving machines will leverage AI and computer vision to perform tasks such as plowing, planting, and harvesting with utmost precision. By eliminating the need for human intervention, autonomous farming equipment will enhance productivity, reduce labor costs, and optimize resource utilization.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
For instance, John Deere’s 8R, a fully autonomous tractor was revealed at CES 2022, which is equipped with GPS guidance, lidar, and advanced cameras.
Similarly, AgXeed Drive, an autonomous tractor equipped with GPS guidance, cameras, and radar was developed by AgXeed, a Dutch company.
Furthermore, Several companies have launched autonomous weeding robots, including FarmBot, EcoRobotix, and Naio Technologies. These robots use cameras and sensors to identify weeds and then remove them without the use of herbicides.
2. Big Data Analytics and Decision Support Systems
The abundance of data generated in agriculture can overwhelm farmers. However, AI-powered big data analytics and decision support systems will provide actionable insights, helping farmers make informed decisions. By analyzing various data points such as weather patterns, soil conditions, and crop health, these systems will optimize planting schedules, predict disease outbreaks, and recommend appropriate fertilization techniques.
In April 2023, an AI agricultural advisor named “Norm” was launched, marking a significant development in the field. Norm possesses the ability to rapidly provide crucial information, such as methods to combat specific pests, the most suitable seed varieties for specific soil types, and strategies for identifying and preventing cattle diseases.
3. Plant Health Sensors
Plant health sensors integrated with AI algorithms will enable farmers to monitor the well-being of crops in real-time. These sensors can detect diseases, nutrient deficiencies, and pest infestations early on, allowing for timely intervention. AI algorithms can process the data collected by these sensors, providing farmers with precise information on crop health and optimizing the use of pesticides and fertilizers.
In April 2023, Researchers at North Carolina State University developed a wearable electronic patch that can be placed on plant leaves to monitor the presence of pathogens and environmental stressors. The small patch incorporates sensors and electrodes to detect temperature, humidity, and moisture levels. In experiments with tomato plants, the patch successfully identified pathogenic infections and stressors. The researchers plan to make the patches wireless and test them in real-world conditions, aiming to assist growers in preventing crop problems and addressing food security challenges.
4. Agriculture Drones and Robots
Agriculture drones and robots equipped with AI capabilities will transform the way farmers manage their fields. Drones can survey large areas quickly, capturing high-resolution images of crops. AI algorithms can then analyze these images to identify areas requiring attention, such as water stress or weed infestations. Robots, on the other hand, can perform labor-intensive tasks like weeding or pruning with precision and efficiency, reducing the need for manual labor.
In June 2023, Precision AI, a Canadian startup, developed autonomous AI-powered drones for plant-level herbicide application. The drones aim to address the challenges faced by farmers in meeting food demand through intensive agricultural practices that result in environmental pollution. The technology offers real-time insights, data collection, and predictions for individual plant management, reducing water use, costs, and chemical excess while promoting soil health. Precision AI’s drones use edge computing to function without internet connectivity, providing near-instant weed identification. With $20 million in funding, the company plans to be operational by 2026 and expand into other applications such as insecticide reduction and fungicide optimization.
5. Farm Management Software
AI-powered farm management software will consolidate various aspects of farming, from inventory management to financial planning. These systems will integrate data from multiple sources, such as weather forecasts, market trends, and field conditions, to provide farmers with holistic insights into their operations. By streamlining workflows and optimizing resource allocation, farm management software will enhance productivity and profitability.
In March 2023, Bushel Inc., an independent software company launched Bushel Farm, a next-generation farm management software designed to reduce manual data entry for farmers and provide grain marketing insights. The software, built upon the company’s FarmLogs solution, offers a comprehensive feature set for mobile and desktop experiences while maintaining user-friendly design.
Moreover, Bushel will release an integration that enables farmers to automatically import their individual grain sales data into Bushel Farm, reducing the need for manual entry. This integration will provide valuable time savings for farmers and enhance the software’s capabilities. The software is available for both individual farms and commercial grain buyers/agribusinesses seeking to strengthen relationships and streamline grain marketing. Moreover, integrations with John Deere Operations Center™ and Climate FieldView® enhance data imports, and data privacy controls ensure authorized sharing.
6. Climate-Smart Technology
The agricultural industry is under increasing pressure to mitigate the effects of climate change. AI-driven climate-smart technology will aid in the development of sustainable farming practices. By analyzing historical climate data, AI algorithms can predict weather patterns and help farmers adapt their cultivation techniques accordingly. This will enable the industry to optimize water usage, reduce greenhouse gas emissions, and enhance overall resilience.
In May 2023, the University of Minnesota was granted $20 million over five years from the National Science Foundation (NSF) and the U.S. Department of Agriculture’s National Institute of Food and Agriculture (NIFA) to establish a National Artificial Intelligence Research Institute. The institute, known as AI-CLIMATE, aims to leverage artificial intelligence (AI) to develop climate-smart practices that simultaneously absorb and store carbon while promoting economic growth in the agriculture and forestry sectors.
7. Resiliency in Supply Chain
AI technology can bolster the resiliency of agricultural supply chains. By leveraging predictive analytics, machine learning, and data from multiple sources, AI systems can optimize logistics, inventory management, and demand forecasting. This will enable farmers to respond to market demands more effectively, reduce wastage, and ensure a steady supply of fresh produce.
In March 2023, Helios Artificial Intelligence, Inc. launched the open beta of its platform that detects agricultural supply chain disruptions in advance. The platform provides customized climate and economic risk insights for over 200 commodities in 180 countries, enabling agricultural importers to stay ahead of their competitors. Helios helps users predict supply availability, identify risks to yields, and provide valuable input for negotiation processes. Customers have already experienced transformative results, gaining actionable insights and proactively mitigating disruptions. The platform offers transparency into ESG, climate, economic, and political factors affecting suppliers.
8. Convergence with IoT
The convergence of AI with the Internet of Things (IoT) will amplify the transformative potential of agriculture. IoT devices, such as soil moisture sensors and smart irrigation systems, can collect vast amounts of data. AI algorithms can then process this data to automate and optimize irrigation, fertilizer application, and other farming operations. The integration of AI and IoT will enable farmers to achieve higher yields, conserve resources, and enhance sustainability.
In June 2023, Trilogy Networks, Veea, and Microclimates formed a partnership to offer an all-in-one agritech solution. Trilogy Networks, a leader in the agritech IoT-edge-cloud-platform market, aims to combine their technologies and platforms with Veea and Microclimates. The new Trilogy platform allows farmers and enterprises to collect, compute, and protect data at the edge, enhancing operational efficiency and reducing costs. Veea provides unified connectivity between the cloud, endpoints, edge, and devices. Microclimates specializes in smart climate-controlled environment management, enabling farmers to monitor and control temperature, humidity, CO2 levels, watering, and ambient light. Their platform supports thousands of sensors and provides 24/7 live monitoring.
9. AI Integration in Agriculture Biotechnology
AI is playing a pivotal role in advancing agricultural biotechnology. Genetic algorithms and machine learning techniques can accelerate the breeding process, helping develop crops with improved traits, such as disease resistance or higher yields. AI can also facilitate gene editing techniques, such as CRISPR, enabling precise and efficient modifications to plant genomes. These advancements will drive the development of resilient, high-performing crops.
For instance, in March 2023, InnerPlant and Mertec LLC joined forces to develop crops that can communicate biological stresses before they become visible to farmers. By integrating InnerPlant’s seed technology with Mertec’s soybean germplasm, the aim is to create crops that emit signals when they are under stress from pathogens, water deficiency, or nutrient deficiency. These signals, visible from satellites and tractors, provide early detection of problems weeks before they would be noticeable in the field
10. Precision Irrigation
Water scarcity is a significant challenge in agriculture, making precision irrigation a critical trend. AI algorithms can analyze data from various sources, including weather forecasts and soil moisture sensors, to optimize irrigation schedules. By delivering the right amount of water at the right time, precision irrigation enhances water-use efficiency, conserves resources, and minimizes environmental impact.
In April 2023, BASF and AGCO Corporation partnered to integrate and commercialize smart spraying technology on Fendt Rogator sprayers. Developed by Bosch BASF Smart Farming, this advanced solution allows precise herbicide application for effective weed control and cost optimization. Trials for the technology began in May 2021, showcasing its targeted spraying capabilities in various conditions, day, or night. The system saves herbicide through precise application, advanced sensors, automated sensitivity thresholds, and weed identification technology.
Conclusion
As we look forward to 2024, the global agricultural landscape is poised to undergo significant transformations driven by AI technology. Embracing the aforementioned advancements will empower farmers to overcome challenges, enhance productivity and profitability, and ensure a sustainable future for the agricultural sector.
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