The combo of AI and Agriculture is out here !!!
- Jul 2, 2023
- 9 min read
Updated: Jul 9, 2023
We are lucky to experience this era where agriculture and AI are working together in the world .
In many nations throughout the world, agriculture is the main source of income, and as the world's population rises—from 7.5 billion to 9.7 billion people, according to UN estimates—there will be increased pressure on the planet's resources because only 4% more land will be cultivated by 2050.
Farmers will consequently need to work harder with less resources.
The same report estimates that in order to feed an additional two billion people, food output must rise by 60%. Traditional approaches, nevertheless, are unable to meet this enormous demand. This is pushing farmers and agricultural businesses to develop fresh strategies for raising output and cutting waste. As a result, Artificial Intelligence (AI) is progressively becoming a part of the technical advancement of the agriculture sector.
AI-powered solutions will help farmers to improve efficiency while also improve quantity, quality and ensure faster go-to-market for crops. However, AI is not a technology that works independently. As the next step on the way from traditional to innovative farming, AI can supplement already implemented technologies.
Can you imagine ? AI can be used for different purposes in Agriculture . Lets explore together how AI helps in agriculture -
1. AI for intelligent chemical spraying reduces costs
In terms of temperature, soil, water use, weather, etc., farms generate hundreds of data points every day. This data is utilized in real-time with the aid of artificial intelligence and machine learning models in order to get insightful knowledge, such as the best time to plant seeds, which crops to choose, which hybrid seeds to choose to increase yields,etc.
AI systems are helping to improve the overall harvest quality and accuracy – known as Precision Agriculture.
AI technology aids in the detection of pests, plant diseases, and undernutrition in farms. Artificial intelligence (AI) sensors can identify and target weeds before deciding which herbicide to use in the area. This lowers the need for herbicides and lowers costs.
Many technological firms created robots that precisely monitor weeds with spray guns by using computer vision and artificial intelligence. These robots are able to eliminate 80% of the volume of the chemicals normally sprayed on the crops and bring down the expenditure of herbicide by 90%. By substantially reducing the amount of pesticides required in the fields, these smart AI sprayers can increase the quality of agricultural output while also bringing about economic efficiency.
2. Face the labour challenge with AI-based farm harvesting robots.
Have you ever thought who actually picks the produce from the agricultural land? Well, in most cases, it is not the traditional farm worker but robotic machines that are capable of doing bulk harvesting with more accuracy and speed that are responsible for getting the food on your kitchen table. These machines help improve the size of the yield and reduce waste from crops being left in the field.
A lot of companies are trying to increase agricultural efficiency. There are items like an autonomous strawberry-picking machine and a vacuum apparatus that can harvest mature apples from trees. These devices locate the produce that may be harvested and assist in fruit selection using sensor fusion, machine vision, and artificial intelligence models.
Agriculture is the second largest industry after Defense where service robots market have been deployed for professional use. According to the International Federation of Robotics, up to 25,000 agricultural robots have been sold, which is the same amount utilized for military applications.
3. AI for predictive analytics – Facilitates wise decision-making
Predicting the best time to sow -
The difference between a profitable year and a failed harvest is just the timely information on a simple data point of timing of sowing the seed. In order to avoid this, ICRISAT scientists employed a predictive analytics method to determine the exact time to plant seeds in order to get the most yield.
It also provides a seven-day weather forecast, insights into the condition of the soil, and fertilizer advice.
4. Crop yield predictions and price forecasts
The variation in the crop's price is a major source of concern for many farmers. Farmers are never able to set a specific production pattern because of fluctuating prices. When it comes to crops with a short shelf life, like tomatoes, this issue is particularly common. Companies examine the land and continuously monitor crop health using satellite imagery and weather data on real time basis.
Companies are able to identify pest and disease infestations, calculate the output and yield of tomatoes, and predict prices with the aid of technologies like big data, AI, and machine learning. They can advise governments and farmers on a variety of topics, including future pricing trends, consumer demand, the best crops to plant for optimal yield, the use of pesticides, etc.
Innovative startups are using AI in the field of agriculture. A Berlin-based agricultural tech startup created a multilingual plant disease and pest diagnostic app that uses images of the plant to identify diseases.
A smartphone gathers the image and compares it with a server image, which then provides a diagnosis of that specific disease that is then applied to the crop using intelligent spraying technique. The application addresses plant diseases in this manner by utilizing AI and ML. This app has been downloaded by many farmers all over world, and it has assisted in the detection of over 385 agricultural diseases in field crops, fruits, and vegetables.
5. AI addresses labor shortages
Agricultural work is hard, and there have always been labour shortages in this sector. This issue can be resolved by farmers using automation. Farmers can do the work without adding additional employees by using driverless tractors, intelligent irrigation and fertilizing systems, smart spraying, vertical farming software, and AI-based harvesting robots, as some examples. AI-driven machines are faster, tougher, and more precise than any human farm worker.
6. Supports Monitoring soil health and Harvesting
AI systems are able to assess soil chemically and calculate the amounts of nutrients that are missing with high accuracy also AI can be used to automate harvesting and even forecast when it will be most effective.
7. Feeding crops
AI is useful for identifying optimal irrigation patterns and nutrient application times and predicting the optimal mix of agronomic products.
Farmers can face problems while implementing AI-
Considering the benefits of artificial intelligence for sustainable farming, implementing this technology may look like a logical step for every farmer. However, there are still some serious constraints.
1. Lengthy technology adoption process
A common misconception among farmers is that artificial intelligence (AI) only exists in the world of technology. They might not understand how it will help them do their jobs on the actual land. They do not do this, though, because they are conservative or afraid of the unknown. Because they do not understand how AI tools can be used in practical settings, they are hesitant.
Farmers need to be aware that artificial intelligence (AI) is really an improved version of earlier technology for processing, acquiring, and monitoring field data. For AI to function, the right technological infrastructure is needed. Due to this, even farms with some technology in place can struggle to advance.
New technologies can come seen as complex and overly expensive, and AgriTech vendors typically fail to explain why their solutions are helpful and how precisely they should be deployed. Despite the potential advantages of AI, there is still a lot that has to be done by technology companies to help farmers use it effectively.
This is also a challenge for software companies. They should approach farmers gradually, giving them simpler technology first, such as an agriculture trading platform. After farmers become accustomed to a simpler solution, it will be appropriate to advance and provide something else, such as AI functions.
2. Lack of experience with emerging technologies
The farming sector in developing nations are distinct from those in Western Europe and the US. Artificial intelligence in agriculture may be advantageous in some areas, but it may be challenging to market such technology in places where agricultural technology is uncommon. Farmers will probably require assistance implementing it.
As a result, tech companies that want to conduct business in areas with developing agricultural economies might have to be proactive. In addition to providing their products, they’ll have to provide training and ongoing support for farmers and agribusiness owners who are ready to take on innovative solutions.
3. Privacy and security issues
Since there are no clear policies and regulations around the use of AI not just in agriculture but in general, precision agriculture and smart farming raises various legal issues that often remain unanswered. Farmers may experience significant issues as a result of privacy and security threats like cyberattacks and data leaks. Unfortunately, many farms are vulnerable to these threats.
How AI should be combined with other technologies ?
AI can’t exist without other technologies already in place such as big data, sensors, and software.
Similar to how AI is required for other technologies to work successfully. For instance, huge data does not necessarily have much value by itself. What matters most is how it's interpreted and whether it's relevant.
Whether AI recommendations based on a set of data will be beneficial depends on the situation, the setting, and the selection criteria. To make AI technology work, it's crucial to have competent data engineers and analysts.
Let’s talk about the uses of artificial intelligence in farming in more detail.
1. Big data for informed decision-making
The real goal of producing and collecting data is putting it to use. Data analytics in farming can lead to enormous production gains and huge cost reductions. Farmers can receive reliable advice based on well-organized real-time information about crop needs by combining AI and big data. In turn, this will eliminate any uncertainty and allow for more exact farming techniques including irrigation, fertilizing, crop protection, and harvesting.
2. IoT sensors for capturing and analyzing data
Farmers may monitor, measure, and save field data in real time using IoT sensors and other supporting technology (such as drones, GIS, and other tools). Farmers may quickly obtain more accurate information by integrating AI farming technologies with IoT hardware and software.
Better data means better decisions and less time and money spent on trial and error
3. Automation and robotics for minimizing manual work
Artificial intelligence combined with autonomous tractors and IoT can solve one of the most common problems in farming: a shortage of labor. These technologies are also potentially cost-effective because they’re more accurate and thus reduce errors. Taken together, AI, autonomous tractors, and IoT are the key to precision agriculture.
Robotics is a less popular yet quickly developing technology. Already, agricultural robots are utilized for manual tasks like lettuce thinning and fruit and vegetable picking. Robots have many benefits over human farmworkers. They are more accurate, have a longer working time, and are less prone to mistakes.
Indeed all these points discussed looks good on paper !!! Lets explore together how this things look in reality -
Reality vs expectations of artificial intelligence for sustainable farming
The benefits of AI in agriculture are undeniable. Small, repetitive, and time-consuming chores can be completed by smart farming tools and vertical farming systems, saving up farm employees' time for more complex jobs that call for human intelligence. However, it's crucial to understand that, unlike a tractor, AI cannot be purchased and used immediately. AI is an intangible concept. It's a collection of technologies that have been programmed to be automated.
Artificial intelligence simply simulates thinking; it learns from data and solves problems. The development of smart farming has progressed to AI, but for AI to be effective, other technologies must also be in place. In other words, farmers must first invest in a technology infrastructure in order to reap the full benefits from AI. Building that infrastructure will take some time—possibly years—to complete. However, doing so will enable farmers to create a strong technology ecosystem that will survive the test of time.
For the time being, technology providers must consider a few things: how to make their products better, how to assist farmers in overcoming their difficulties, and how to clearly and simply explain how machine learning helps solve genuine problems, such as lowering manual labour. AI in agriculture will undoubtedly have a bright future.
Can farmers' traditional expertise be replaced by AI? The answer is probably not right now, but there is no doubt that AI will challenge and complement current decision-making processes and enhance agricultural practices in the near future. These technology interventions are probably going to result in better agricultural practices, yields, and qualitatively better farmer lifestyles.
Summary
AI will be a potent instrument that may assist organizations in managing the growing complexity in modern agriculture because it significantly eliminates the shortage of resources and labour.
Imagine an industry that involves more risk than agriculture!!! You reap what you sow, they say. But what they forget to add is “if you’re lucky.” When the weather strikes or crops get affected by disease, farmers can hardly talk about yields. Or when a global pandemic hits, all of a sudden it gets harder to manage various processes because most are not digital.
Concerns about food security, population expansion, and climate change have pushed for new technological farming solutions. Artificial intelligence is becoming more prevalent as a potential remedy for increased agricultural productivity.
We need to look for ways to help farmers minimize their risks, or at least make them more manageable. Implementing artificial intelligence in agriculture on a global scale is one of the most promising opportunities.
AI has the ability to transform the way we think about agriculture by allowing farmers to produce more with less work while also providing a number of additional advantages.
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