The next decade is set to challenge the agricultural industry’s capacity to adapt, innovate, and provide. As global population estimates climb, farmers are under pressure to feed a constantly growing population while balancing this objective with addressing the increasing challenges of climate change, resource depletion, and environmental degradation. While traditional resource-intensive agricultural practices may have been sufficient to keep the global population satiated, it is becoming increasingly clear that they are no longer fit for purpose in a changing world.
However, just as modernization brings problems, it brings solutions as well. The emergence of artificial intelligence in recent years is already transforming modern agriculture and empowering farmers to optimize key aspects of their farming processes.
This article will explore the impact of AI on global food production systems, examining how AI can increase crops’ resistance to climate change and leverage its data analysis capabilities to strengthen food production and address the complex issues plaguing the agricultural industry.
Problem
Climate change isn’t just approaching – it’s already here, and the agriculture industry is feeling its impact firsthand. Existing food production systems are threatened by changing rainfall and precipitation patterns, rising temperatures, and more frequent disasters such as heat waves, floods, and droughts.
These crises are already disrupting the carefully calibrated conditions where farmers grow their crops, specifically throughout the Global South, where regions are already experiencing natural disasters that irreparably alter their growing capabilities. Resource constraints compound these problems.
As the frequency of droughts increases, water sources are becoming more scarce and less reliable, introducing problems for regular irrigation systems.
Soil degradation due to monocropping and the over-usage of chemical fertilizers is also likely to limit the amount of land where farmers can grow crops, with the UN estimating that 33% of the world’s soil supply is between moderately to highly degraded. Smallholder farmers will be pitted against each other as they compete for what little water and soil remain in the aftermath, destroying trust and collaboration within farming cooperatives.
Finally, a rapidly growing future population creates an additional stressor for the industry. The UN estimates that the global population of 7.6 billion will reach 9.8 billion by 2050, and 11.2 billion in 2100, leading to significantly increased demand for food. With increasing populations and decreasing food security, the question for scientists, farmers, retailers, and policymakers remains: how can we produce more food with fewer resources while preserving the health of our planet?
Solution
Artificial intelligence is providing the tools, insights, and technologies necessary to combat these complex agricultural challenges.
At the core of AI’s potential to address these problems is the introduction of precision farming, an approach that incorporates AI’s data collection and analysis capabilities into everyday farming practices. By using data-driven technologies, AI can rapidly calculate the optimal level of land, water, fertilizer, and other resources required to grow crops at a sustainable rate.
AI sensors or automated harvesters can monitor crops’ conditions at scale in real-time, ensuring that farmers can detect diseases and pests that pose a threat to their crops quickly and adjust resource use depending on the soil constitution in a particular area. AI also leverages its data processing capabilities to assist agriculture researchers in developing climate-resistant crops.
Machine learning models are uniquely able to collect data on and identify the specific genetic traits contained in certain strains’ genes, specifically, the genes that make strains more resistant to heat, cold, drought, and disease. This can accelerate the development of genetically modified crops, ensuring that farmers can begin planting crops that are resistant to unpredictable weather conditions and shrinking amounts of arable land.
Lastly, AI is better equipped than farmers to analyze large datasets at a high level of detail, improving crop management and extracting useful insights for farmers. Data in farming is crucial – it can provide insights into harvest health, the nutrients certain crops require, and patterns of growth throughout a farmer’s plots of land that they would otherwise not have access to.
As plants grow, AI algorithms can process data gathered by drones to track plant growth levels across hectares of farmland, enabling farmers to optimize their crops’ rotation and predict crop yields more accurately. While farmers will have to adapt their approach to agriculture, by working side by side with AI, they can remain ahead of the curve.
Impact
The widespread incorporation of AI into agriculture is positioned to produce tangible benefits for farmers and consumers alike. One of the most important benefits is the increase in crop yields: because AI can optimize farming practices, farmers will be able to grow increased quantities of food with fewer inputs and resources.
For example, AI-enabled irrigation systems can reduce the amount of water used to grow crops, ensuring that plants are not over-watered and farmers can conserve limited water resources. As water supplies become more scarce, this innovation is a crucial step in water conservation. In addition to this, AI will also be instrumental in reducing the environmental impact of agriculture.
AI-powered tools can cut fertilizer use, decreasing the extent to which soil is acidified and fertilizer runs off into local water sources, preventing further pollution of both resources. Precision pest management, another AI-driven approach, can help farmers minimize pesticide use to what is absolutely necessary, cutting down on harmful chemicals entering the soil and water close to their farms and preventing pesticides from breaking down ecosystems. Beyond resource optimization, AI will also enhance risk management in agriculture.
When it is made accessible to farmers, AI will give them a greater capacity to address risks to their farming models.
Climate change is likely to create a very unstable environment for farmers, with rapidly changing weather patterns forcing them to constantly review and adapt their farming practices. AI’s predictive capabilities will therefore enable farmers to assess risks like droughts, pest infestations, and diseases, allowing for more proactive measures to mitigate crop loss. By using predictive models and algorithms to analyze the likelihood of crop failures and weather patterns, AI can allow farmers to plan around these failures and build them into their business models.
Conclusion
As we look to the future, the role of AI in agriculture is likely to grow as farmers face increasing strains on their resources and pressures to keep pace with the global population increase.
AI-driven solutions are not only prepared to help farmers reduce the amount of inputs in growing crops, mitigating resource usage and increasing productivity, but they will also make crops more resilient to the shocks of climate change.
However, these plans mean nothing without widespread adoption and implementation. As AI is introduced, it is important to strategically collaborate across stakeholders to ensure access to AI-powered agricultural technology is affordable for smallholder farmers.
Access to affordable AI tools and infrastructure must be a priority for governments, especially for smallholder farmers in developing regions, who are often the most vulnerable to the impact of climate change and least equipped to implement technological innovations such as AI solutions. Policy frameworks that support innovation and ensure equitable access will be essential in maximizing the benefits of AI for farmers around the world.
Ultimately, the introduction of AI and its embrace by the agricultural sector will not just be a boon for agricultural productivity, but also for the creation of a resilient, sustainable food production system equipped to meet the demands of the 21st century.
