Artificial Intelligence: An Agricultural Revolution
If you are what you eat, then the food you consume might have been more intelligently produced than ever before. Advances in technology have had a significant impact on agriculture and food production, with the inclusion of technologies like Artificial Intelligence (AI) shaping the entire food supply chain, starting with the seed and culminating in the consumer’s plate.
Agriculture is an industry that is not new to innovation or the incorporation of technologies to increase efficiency. Farmers have employed technologies like irrigation and planting tools for centuries to improve yields and reduce the chances of crop failure. However, AI is not your garden-variety tech solution but instead, an amalgamation of computing power and machine learning changing the industry in new ways nobody thought possible.
Today, AI is increasingly finding applications in the agricultural industry, with global agriculture implementing AI technology to address multiple challenges, including food security, climate change, and population expansion. Droughts, floods, pests, and diseases pose severe threats to food security, causing a severe imbalance in global food production. The loss of crops due to climate change and failed agricultural practices, including excessive use of pesticides, could further lead to food insecurity. AI technology comes in handy, bringing an agricultural revolution by helping farmers navigate soil and weather conditions, reduce chemical usage, and increase yields.
How is AI revolutionizing agriculture?
Precision Agriculture
Farmers and researchers have been developing software models for things like nutrient and crop management for decades. However, The use of AI has added an extra layer of, well, precision. AI-powered systems can combine Big Data analysis with agricultural science to identify square meter by square meter what crops need specific inputs, like irrigation, fertilizer, and planting space. Informed decisions on planting density, fertilizer needs, and pest management can be done with precision.
Autonomous and smart agricultural machinery
From autonomous tractors and programable irrigation systems to drones, AI has enabled the automation of many aspects of agriculture. More crops can be monitored on large farms, as sensors and cameras allow farmers to observe potential problems such as pest infestations and water or nutrient deficiencies quicker, allowing farmers to take corrective action at an appropriate time. These systems can also generate data that can allow farmers to reduce input, optimize their agricultural practices and increase their yields.
Early detection and response to crop diseases
Crop diseases represent a significant threat to food production, and detecting diseases early enough can help prevent them from spreading. A UK-based farming technology firm has been developing an AI tool to improve the detection of Banana Xanthomonas Wilt (BXW), a one devastating crop disease affecting Bananas in East Africa. Unlike previous diagnostic techniques that took up to three weeks to produce results, the AI tool analyses leaf images and other data in under three minutes. The AI diagnostic tool enables farmers to identify specific crops that require attention and preventative measures to protect them from future outbreaks of crop diseases.
Increased food safety
The implementation of AI in food processing plants can detect potential hazards such as chemicals, defects, and contaminants. In food processing, AI systems also aid in the sorting and grading of food products based on their quality, shape, and size. AI can also be used to predict the spoilage of food products by analyzing environmental details and overseeing temperature control. This predictive capability can help to reduce waste and facilitate shelf life extension.
Considerations for the successful integration of AI in agriculture
The potential applications of AI are vast, but implementation involves a multi-faceted approach.
Adoption
Farmers need to be convinced of the utility of AI and its potential to bring more yields and more efficient farming practices. They may need help to understand how to integrate AI technology into their daily farming routines.
Data capacity
Big Data analysis and learning algorithms are critical elements that make AI solutions possible. Farmers must ensure that they have access to data streams relevant to their operations. This data includes weather information, soil moisture, farm equipment details, and much more.
AI bias
The data used for AI applications require scrutiny to ensure they are not biased and lead to unfair outcomes that discriminate. Algorithm bias in AI and IoT devices can produce efficient biases in automated agricultural practices leading to unsafe or unsuitable agricultural practices.
Security
IoT devices and AI generate many data points; hence security must be a priority when employing these technologies in agriculture.
In conclusion
AI and IoT devices are becoming an essential element in the optimization of agriculture. The integration of AI into agriculture practices is spreading. AI has the potential to bring more sustainable practices that will be beneficial to the environment, help produce more food, and lead to more efficient farming techniques. AI will likely transform agriculture, and its use has the potential to make significant progress towards global food security. Agriculture may have started with manual labor, but the future of farming seems smart, sustainable, and powered by AI.