3 Ways Farmers Can Use AI Right Now To Overcome Modern Agribusiness Challenges

Sandy Rivers
By Sandy Rivers

While artificial intelligence often grabs headlines for its potential, AI’s real impact shines in practical applications. In agriculture, where the stakes are high for human health, the environment, and food security, AI is rapidly becoming a powerful ally for farmers. The AI tools and innovations are so promising that experts predict the market for AI-powered agricultural solutions will surge to an estimated US$12 billion by 2032. As a researcher specializing in agricultural and rural policy, I’m excited to explore three key developments in agricultural AI that hold tremendous promise: federated learning, pest and disease detection, and price forecasting.

Securely Sharing Data So Everyone Grows

Modern agriculture has embraced robotics, sensors, and information technology to enhance efficiency and reduce chemical use. These technologies are a boon for farmers, as they provide valuable data for optimizing management systems and decision-making. However, a significant hurdle arises: data sharing among stakeholders. Many farmers harbor concerns about sharing their data, driven by a lack of trust in federal agencies and private companies. These fears stem from worries about data security breaches and the potential manipulation of markets and regulations.

Federated learning emerges as a game-changing solution. This technique allows machine learning algorithms to train on data from multiple parties without the need for these parties to expose their sensitive information to each other.

Instead of centralizing data on a vulnerable server, a farmer can place their data on a local computer accessible to the algorithm. This approach enhances data privacy and drastically reduces the risk of compromise.

Imagine a future where farmers willingly share their data through federated learning, creating a collaborative ecosystem that benefits everyone involved. 

For instance, farmers cultivating chickpeas could pool data on crop conditions, enabling a model trained on this collective dataset to provide each of them with more accurate forecasts for their chickpea yields. This collaborative approach surpasses individual data models, empowering farmers to make better decisions and align with sustainability goals.

Dr. Emma Rodriguez, an AI expert in agriculture, emphasizes the potential of federated learning, saying, “Federated learning not only enhances data security but also unlocks the untapped potential of collective intelligence. It empowers farmers with valuable insights and encourages a shared commitment to sustainable practices.”

Screenshot of Agremo's crop monitoring and data sharing application.

AI in Pest and Disease Detection - Safeguarding Agriculture's Future

As we navigate the complex landscape of modern agriculture, the specter of plant diseases and pests casts a long shadow over farmer livelihoods and global food security. The Food and Agriculture Organization’s alarming estimate of annual worldwide losses, totaling a staggering $290 billion, with 40% of global crop production impacted, serves as a grim reminder of the challenges we face.

Traditionally, farmers have resorted to chemical sprays to preempt outbreaks of pests and diseases. However, the excessive use of these chemicals carries dire consequences, including adverse effects on human health, soil quality, water quality, and biodiversity. More troubling still, many pathogens are developing resistance to existing treatments, rendering our conventional approaches increasingly ineffective.

Amid this crisis, the need to reduce chemical reliance takes center stage, and artificial intelligence emerges as a potential savior that began with one common goal… bananas.

The Consortium of International Agricultural Research Centers has pioneered a groundbreaking solution in the form of a mobile phone app named “Tumaini.” 

The smartphone app, called Tumaini – which means “hope” in Swahili – helps banana farmers scan plants for signs of major diseases and pests. Farmers upload a photo to the app of an affected crop, which then uses image-recognition technology from a dataset of over 50,000 images to scan for symptoms of diseases and pests. If the app detects an issue, it recommends steps to address the problem.

Arugga AI Farming’s robots autonomously travel down a row in a greenhouse and use AI and cameras to quickly identify flowers ready for pollinating, and then blast them with air to pollinate them.

Targeted Solutions for Farmers

When integrated with farm management tools, apps like Tumaini become invaluable assets. They enhance farmers’ capacity to precisely target their spraying efforts and make well-informed decisions about chemical usage. These efficiencies have the potential to significantly reduce pesticide application, mitigate the risk of resistance, and curtail spillovers that jeopardize both human well-being and environmental health.

Dr. Maria Gonzalez, a prominent researcher in agricultural technology, underscores the significance of AI-driven solutions, stating, “AI-powered pest and disease detection not only safeguards crops but also represents a paradigm shift towards a more sustainable and environmentally conscious agriculture.”

AI's Price Forecasting Prowess - Navigating Market Volatility

In the realm of agriculture, market volatility and the unpredictability of prices cast a long shadow over farmers’ decisions. These fluctuations not only influence how farmers invest, but also dictate their crop choices. The pervasive uncertainty often discourages farmers from taking risks on new developments and innovative practices.

However, artificial intelligence has emerged as a beacon of hope in this sea of uncertainty. AI-driven price forecasting tools offer a lifeline to farmers, enabling them to navigate the complex market terrain with more confidence. Companies like Agtools, Agremo, and GeoPard provide AI-powered farm decision tools that revolutionize the way farmers approach pricing strategies.

These tools offer real-time analysis of price points and market data, shedding light on long-term trends that empower farmers to optimize their production methods.

The data provided by AI-driven tools empowers farmers to adapt swiftly to price changes and adopt more strategic planning. As economic resilience improves within the farming community, the likelihood of investing in new opportunities and cutting-edge technologies increases. This synergy benefits not only individual farms but also the broader food system.

While AI carries inherent risks, including biased algorithms, data privacy concerns, and the potential for manipulation, it also offers substantial promise. The agricultural sector stands to benefit from AI’s transformative potential.

These applications of AI in agriculture offer a glimmer of hope for farmers and the broader food industry. To harness the full potential of AI, the agricultural sector must champion the utility of these innovations while simultaneously developing robust frameworks to mitigate potential harm. In doing so, AI can play a pivotal role in reducing the modern agricultural sector’s impact on human health and the environment, while simultaneously enhancing global food security in the 21st century.

AI's Promising Path in Agriculture

In an age marked by unprecedented challenges in agriculture, AI emerges as a powerful ally for farmers. It provides solutions to some of the sector’s most pressing issues, from pest and disease management to market uncertainty. While AI carries risks, it also embodies tremendous potential to revolutionize farming practices and promote sustainability.

As we look ahead, the fusion of AI and agriculture represents a beacon of optimism. By embracing AI responsibly and collaboratively, we can usher in a new era where technology serves as a catalyst for improving human health, environmental conservation, and global food security. The 21st century beckons with opportunities to harness AI for the greater good, ushering in a future where agriculture thrives sustainably, benefitting both farmers and society at large.

Share This Article
Leave a comment