Making AI an ally for sustainable agriculture in the face of climate change
Abstract
Climate change is profoundly reshaping socio-economic structures worldwide, posing challenges to various sectors, especially agriculture. The agricultural industry is particularly vulnerable to unpredictable weather patterns, increased extreme events and the degradation of natural resources. These disruptions threaten food production, global food security, economic stability and community livelihoods. As agriculture both influences and is affected by climate change, it is crucial to develop and implement solutions that address these complex issues to foster resilience and sustainability. This article explores the role of technology and artificial intelligence (AI) in mitigating the effects of climate change on agriculture. By examining the sector’s challenges, the article highlights the importance of data and technological innovation in transforming agricultural practices, particularly in developing countries. Through the innovative work of SenseGrass, it illustrates how AI-driven solutions are transforming farming, enhancing sustainability and building climate resilience. Based on examples from the industry, this article provides a glimpse into the future, demonstrating AI's potential to drive positive change not only in agriculture, but also in addressing broader issues posed by climate change.
Outline
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Introduction
- 1 See the article by Jessica Fanzo in the second section of the review: Climate change and food syste (...)
1Climate change is increasingly impacting agriculture. Rising temperatures, unpredictable precipitation and more frequent extreme weather events disrupt crop growth cycles, reduce yields and compromise food quality. For instance, while hotter temperatures may accelerate crop growth, they also increase pests and diseases, leading to significant losses. The disruption of agriculture – a vital industry – has far-reaching consequences on human health. Lower yields not only reduce the quantity of food available but also lead to higher prices, pushing vulnerable populations toward food insecurity and malnutrition. Children are particularly at risk, as reduced access to nutritious food can lead to stunted growth and long-term health problems.1 Sudden floods and droughts often wipe out entire harvests, leaving farmers in a vulnerable and precarious situation.
2The challenges extend beyond immediate climate impacts. Indirect consequences such as altered ecosystems and dwindling resources further strain agriculture. Water scarcity, reduced soil fertility and changing pollinator behaviors significantly affect crop production. Farmers, already grappling with direct climate impacts, face these indirect effects as well. The socio-economic repercussions are profound, with increased food prices and heightened food insecurity impacting vulnerable communities the hardest.
The Importance of Soils
- 2 The nutrient cycle is a system where energy and matter are transferred between living organisms and (...)
- 3 Food and Agriculture Organization. (2015). Agroecology to reverse soil degradation and achieve food (...)
3Soils are vital for agriculture, essential for plant growth, water regulation and nutrient cycling.2 They support diverse ecosystems, enhance crop resilience and play a crucial role in mitigating climate change through carbon sequestration. However, climate change threatens soil health. Elevated temperatures and irregular precipitation accelerate soil erosion, nutrient depletion and organic matter loss, weakening soil structure and fertility. According to the Food and Agriculture Organization of the United Nations (FAO), 33% of soils worldwide were already moderately to highly degraded in 2015, and over 90% of soils could undergo degradation by 2050.3
4Extreme weather exacerbates soil degra-dation as well. Heavy rains cause severe erosion, while prolonged droughts desiccate soils and diminish microbial activity, and rising sea levels and over-irrigation can lead to salinization. Healthy soils are essential in sustaining agricultural productivity. Without urgent action, the cascading effects of climate change will continue to erode food security and environmental stability. Only through innovation, resilience and collective commitment can we hope to avert these disastrous risks.
The role of Data and Technology in Agriculture
5In the face of climate change, data and technology have emerged as important allies. Modern agriculture increasingly relies on advanced technologies and artificial intelligence (AI) to enhance productivity, manage resources efficiently and mitigate the adverse effects of climate change. The integration of data-driven insights allows farmers to make informed decisions, optimize crop yields and improve the overall resilience of agricultural systems.
Technological Solutions Overview
6Numerous technological solutions are remodelling agriculture, providing farmers with tools to monitor, analyze and respond to various challenges. Here are some key innovations:
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- 4 GIS (Geographic Information System) is a spatial and geographic data technology that allows users t (...)
- 5 IoT (Internet of Things) refers to a network of interconnected devices that collect and share data (...)
Precision Agriculture: Utilizing GIS4 and IoT5 sensors, precision agriculture enables farmers to monitor soil conditions, crop health and weather patterns in real-time, allowing for precise application of water, fertilizers and pesticides.
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Remote Sensing: Satellite imagery and drone technology offer valuable insights into crop health, soil moisture levels and pest infestations, facilitating timely interventions and reducing resource wastage.
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AI, Machine Learning and Big Data Analytics: AI-powered models predict crop yields, detect diseases and recommend optimal planting schedules, helping farmers enhance productivity and reduce losses.
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Climate-Smart Solutions: Technologies that focus on climate resilience, such as drought-resistant crop varieties and efficient irrigation systems, are essential for adapting to the impacts of climate change.
7These technological advancements are transforming traditional farming practices, making agriculture more efficient, sustainable and resilient.
SenseGrass: Innovating with Artificial Intelligence
- 6 Food and Agriculture Organization of the United Nations. (n.d.). India at a glance | FAO in India. (...)
8SenseGrass was born out of a deep connection to agriculture and a desire to address the challenges that small-scale famers face globally, especially as climate change exacerbates their difficulties. Growing up in India a community of farmers, I witnessed firsthand how unpredictable weather patterns, droughts and storms further strain those who depend on their land for sustenance and income. Agriculture remains a backbone of many economies, especially in developing nations. 70% of India’s rural households still depend primarily on agriculture for their livelihood, with 80 % of farmers being small or marginal.6 Many of them are forced to take up additional jobs to survive, while their farms suffer from soil degradation and outdated agricultural practices.
9In fact, traditional soil analysis methods, commonly used in India and around the world, are costly, slow and inaccessible to the majority of smallholder farmers. Farmers typically have to send soil samples to labs, where testing takes weeks and often produces inaccurate or incomplete results. In Rajasthan for instance, despite the government spending billions of Rupees on mobile testing vans and labs, many farmers avoid using them as they find the process too complex and of little practical value. As a result, soil health data remains inaccessible, contributing to significant crop loss. This led us to create SenseGrass, to transform agriculture through the power of Artificial Intelligence (AI), Machine Learning (ML) and Internet of Things (IOT). Our product combines both hardware and software technologies, with the IoT-based system representing the hardware and the AI based system representing the software:
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The Artificial Intelligence (AI) technology analyses data to formulate smart solutions for existing challenges related to soil health, fertilizer conditions and other environmental factors. It provides real-time notifications and actionable solutions to end users. Acting like a personal “human” agronomist, the AI software empowers farmers with precise, data-driven recommendations.
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The Internet of Things (IoT) system is responsible for sensing and monitoring soil conditions, water levels, rainfall predictions, temperature and other relevant metrics. It measures 18+ parameters in real-time, with no need to send soil samples to a lab. In short, it automates the entire process of sensing, data collection, and analysis, transitioning from manual to automated operations.
- 7 Fertilizer and Climate Change | MIT Climate Portal. (2021). MIT Climate Portal. https://climate.mit (...)
10Additionally, we use satellite data to provide information on vegetative indices, enabling farmers to monitor crop health effectively. By identifying the precise health needs of soils at any given time, our technology addresses the common agricultural challenge of over-fertilization. On average, crops absorb only about 50% of the nitrogen in fertilizers, with the excess often running off into waterways or being broken down by soil microbes, releasing harmful nitrous oxide into the atmosphere. Although nitrous oxide contributes a smaller share of global greenhouse gas emissions, it has a warming potential 300 times greater than carbon dioxide.7 Thus, with SenseGrass, farmers can make informed decisions that improve soil health, ultimately reducing their dependency on fertilizers.
Pilot AI Projects
11In addition to our long-running project, we are running several pilot projects designed to harness the power of AI.
Yield Prediction Model
12We have developed an advanced AI model to predict crop yields, with a particular focus on data from farms in Nepal. By integrating historical yield data, weather patterns and remote sensing inputs, the AI models generate yield forecasts for wheat crop. These predictions help farmers plan their planting schedules, allocate resources efficiently and anticipate potential challenges.
Crop Insurance Weather Index AI
13SenseGrass is developing an AI-based weather index models for crop insurance, particularly for rice farmers across over 300 districts in India. By analyzing historical weather data, crop performance and climate patterns, the AI models establish correlations between weather events and crop losses. This approach allows for the creation of weather-indexed insurance products that offer timely and accurate compensation to farmers affected by adverse weather conditions.
Carbon Credit Framework
14SenseGrass is also working on the development of a global carbon credit framework, based on 17 specific AI models tailored to individual terrestrial biomes. This initiative aims to quantify and monetize the carbon sequestration potential of agricultural practices. By integrating remote sensing data, estimated soil carbon measurements and advanced Machine Learning algorithms, SenseGrass's AI models estimate the carbon capture capacity for different biomes globally. This framework would enable farmers to participate in carbon credit markets, providing them with an additional revenue stream while promoting climate-friendly practices.
15Today, more than 12,000 farmers are impacted by our technology globally. Our presence in key states in India including Rajasthan, Utar Pradesh and Punjab but also in the USA, France, Chile, the UK and Finland, testify of the global need for innovative solutions to ensure sustainable agricultural practices.
Concurrent AI and Technology in Agriculture
16AI and technology are transforming agriculture. These advancements offer farmers tools to monitor, analyze and respond to various challenges, ensuring a more efficient and adaptive agricultural sector. Here are some notable examples of structures and startups showing how AI and technology are revolutionizing farming practices:
Technological Innovations
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Plantix: Plantix, a German start-up, uses advanced image recognition technology to diagnose plant diseases, pests and nutrient deficiencies. Farmers capture images of affected plants using a smartphone and the app leverages machine learning to compare these images against a vast database. Farmers receive a diagnosis and actionable recommendations within seconds. This democratizes access to expert-level diagnostic tools, empowering farmers with essential knowledge and resources.
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Blue River Technology: Acquired by John Deere, an American corporation specialized in farm machinery and industrial equipment, Blue River Technology has developed the "See & Spray" system, which employs computer vision and machine learning to identify and precisely apply herbicides only where weeds are present. This targeted approach reduces the use of chemicals, lowers costs and minimizes the environmental impact of farming practices.
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Agribotix: Specializing in drone-enabled technologies, Agribotix provides data analytics and insights through aerial imagery captured by drones. Their AI-powered platform analyzes crop health, identifies areas of stress and generates actionable reports for farmers, helping to optimize field management.
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Prospera: Through its “irrigation insights” solution, Prospera leverages real-time data on soil moisture, weather conditions and crop health to make precise water management decisions. This technology helps farmers both grow healthier crops and use resources more efficiently by preventing over-irrigation.
AI & Technology in Addressing Climate Change to guarantee a better Human Health
Link Between Climate, Environment and Health
17Climate change significantly impacts both environmental and human health, presenting challenges that require innovative solutions. For example, AI-driven climate models can forecast extreme weather events, allowing for early warnings that help communities prepare and respond effectively. Additionally, AI can track and model the spread of vector-borne diseases influenced by changing climate conditions, enabling targeted interventions to protect vulnerable populations. AI and data-driven technology have the potential to tackle many of the challenges posed by climate change.
Future Directions – AI and technology solutions for agriculture and beyond
18As we look into the future, potential developments in AI and technology for the green sector are vast and diverse:
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- 8 Martineau, K. (2024, September 23). Introducing Prithvi WxC, a new general-purpose AI model for wea (...)
Advanced Climate Modelling and Prediction: Future advancements in AI could lead to even more accurate and granular climate models, enhancing our ability to prepare for and mitigate the impacts of climate change. IBM, in collaboration with NASA, is developing an advanced open-source foundation model for weather and climate prediction.8 This AI-powered model processes vast amounts of data, including NASA's satellite information, to improve the accuracy of weather forecasts and climate projections. The project aims to help anticipate extreme weather events and offer long-term insights into climate patterns, which are crucial for climate resilience and sustainable development. Singularly, the model is designed to be accessible and can run on standard desktop computers, making it more widely usable for researchers, developers, and organizations globally.
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- 9 Nguyen, L. (2021, November 4). What animals will be extinct by 2100? Earth.Org. https://earth.org/w (...)
- 10 Wild Me. https://www.wildme.org/.
Precision Conservation: It is estimated that by the end of 2100, nearly half of the world’s species will disappear from planet Earth.9 AI and machine learning can help with conservation efforts. The non-profit organization Wild Me utilizes Microsoft’s AI for Earth program to identify and track animals in the wild, analysing photos taken around the world by tour operators, tourists and researchers.10 Their efforts enable better monitoring of endangered species, such as the Whale shark, ensuring targeted conservation actions. Similarly, another of Microsoft’s program called the Global Fishing Watch initiative uses satellite data and AI to monitor illegal fishing activities.
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- 11 Global Open Data for Agriculture and Nutrition. https://www.data4sdgs.org/partner/global-open-data- (...)
Global Collaboration and Data Sharing: The future of AI in addressing climate change will also involve increased global collaboration and data sharing. Open AI platforms and international partnerships can facilitate the exchange of knowledge and best practices, accelerating the adoption of innovative solutions worldwide. The Global Open Data for Agriculture and Nutrition (GODAN) works to build high-level support among key stakeholders including governments, NGOs, and private sector organizations to ensure data is accessible and beneficial for famers and the health of consumers.11 Through leveraging growing data generated by new technologies, the initiative seeks to tackle long-standing agricultural and food security challenges.
Conclusion
19Throughout this article, we have explored the role of AI and technology in addressing the challenges posed by climate change. Enhancing agricultural practices through advanced data analytics and predictive modelling is pivotal in promoting sustainability and resilience. We also highlighted the work of SenseGrass in developing AI-driven solutions for yield prediction, soil health monitoring and carbon credit framework, demonstrating the practical impact of technology in the agricultural sector for the past, present and future.
20The future of AI and technology in the green sector is promising. Ongoing innovation is not just beneficial but imperative for us to address the complex challenges of climate change. By investing in and supporting these advancements, we can contribute to a sustainable, resilient and prosperous future for all.
Notes
1 See the article by Jessica Fanzo in the second section of the review: Climate change and food systems interactions: Ensuring resilient and healthy diets.
2 The nutrient cycle is a system where energy and matter are transferred between living organisms and non-living parts of the environment, as animals and plants consume nutrients found in the soil that are then released back into the environment via death and decomposition.
3 Food and Agriculture Organization. (2015). Agroecology to reverse soil degradation and achieve food security. FAO. https://openknowledge.fao.org/server/api/core/bitstreams/bb2a86db-7f53-4e70-91ca-35ceb9d777db/content.
4 GIS (Geographic Information System) is a spatial and geographic data technology that allows users to understand patterns, relationships and trends related to location.
5 IoT (Internet of Things) refers to a network of interconnected devices that collect and share data through the internet, enabling real-time monitoring and automation.
6 Food and Agriculture Organization of the United Nations. (n.d.). India at a glance | FAO in India. FAO. https://www.fao.org/india/fao-in-india/india-at-a-glance/en/.
7 Fertilizer and Climate Change | MIT Climate Portal. (2021). MIT Climate Portal. https://climate.mit.edu/explainers/fertilizer-and-climate-change.
8 Martineau, K. (2024, September 23). Introducing Prithvi WxC, a new general-purpose AI model for weather and climate. IBM Research. https://research.ibm.com/blog/foundation-model-weather-climate.
9 Nguyen, L. (2021, November 4). What animals will be extinct by 2100? Earth.Org. https://earth.org/what-animals-will-be-extinct-by-2100/.
10 Wild Me. https://www.wildme.org/.
11 Global Open Data for Agriculture and Nutrition. https://www.data4sdgs.org/partner/global-open-data-agriculture-and-nutrition.
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References
Bibliographical reference
Lalit Gautam, “Making AI an ally for sustainable agriculture in the face of climate change”, Field Actions Science Reports, Special Issue 27 | 2025, 138-142.
Electronic reference
Lalit Gautam, “Making AI an ally for sustainable agriculture in the face of climate change”, Field Actions Science Reports [Online], Special Issue 27 | 2025, Online since 15 December 2024, connection on 13 February 2025. URL: http://journals.openedition.org/factsreports/7898
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