- How can we use artificial intelligence for sustainable agriculture?
- Predictive analytics and diagnostics help improve decision making
- AI in vertical farming can help countries meet rising demands
- Autonomous harvesting with AI robots helps facilitate sustainable methods
- AI precision farming – efficiency equals more sustainability
With our world population speeding towards 8 billion, we are faced with huge challenges. According to 18th century economist Thomas Malthus, “human population increases geometrically, while food production increases only arithmetically”. This means that the more civilisation grows and thrives, the less likely we will be able to keep up with the demand for food. The agricultural sector is already under immense pressure to meet this fast rising demand, and since the amount of arable land is decreasing as well, the need to transition to beyond traditional agriculture is becoming more and more urgent. It’s important to find ways to assist businesses in agriculture and one way is to implement artificial intelligence. AI can help farmers to achieve better results with less effort, and improve sustainability.
Agriculture production accounts for approximately one third of total greenhouse gas emissions, as well as about 70 per cent of the world’s fresh water consumption.CNBC
How can we use artificial intelligence for sustainable agriculture?
Artificial intelligence can bring tangible benefits to the agricultural sector. It can help improve efficiency, reduce costs, and help tackle existing challenges. By combining artificial intelligence with traditional agricultural technologies, farmers can streamline a wide range of agricultural processes, many of which are still performed manually. Among other things, farmers can use AI to analyse market demand, determine what produce is likely to bring most profits, and adjust their crop selection accordingly. AI can also be used to help farmers eliminate errors in business processes by leveraging the power of forecasting and predictive analytics, as well as reduce the chance of crop failures.
What’s more, farmers can use AI to collect all sorts of valuable information about plant growth, which they can then use to produce crops that are more resistant to disease and adverse weather conditions. They can also use it to analyse the chemical composition of the soil and determine which nutrients may be missing, identify optimal irrigation patterns, ascertain which mix of agronomic products will produce optimal results, and calculate the best times to apply nutrients. AI can also help farmers protect their crops by monitoring their state around the clock, automatically detecting signs of disease, and suggesting the most effective solutions. Additionally, farmers can use AI to automate various processes, such as harvesting.
Last but not least, AI can help reduce agriculture’s environmental impact, which is far from negligible. In fact, it’s estimated that agriculture production accounts for approximately one third of total greenhouse gas emissions, as well as about 70 per cent of the world’s fresh water consumption. In this article, we are going to present some of the most interesting ways AI can help make agriculture more sustainable, including predictive analytics and diagnostics, vertical farming, autonomous harvesting, and AI precision farming.
1. Predictive analytics and diagnostics help improve decision making
In recent years, the adoption of predictive analytics tools in agriculture has increased significantly. These innovative tools aim to predict future trends by analysing both current and historical data using data mining, machine learning, predictive modelling, and other similar statistical methods. The data in question is gathered from a wide range of sources and may include everything from agricultural and biological to climate and hydrological data. Farmers can then use these predictions to obtain actionable insights, which will enable them to better manage inputs, improve their agronomic performance, optimise the use of resources, reduce their environmental impact, predict market conditions, and address both current and future challenges.
For instance, scientists at ICRISAT have developed a predictive analytics tool that can calculate the exact date when seeds need to be sowed to maximise crop yield. While it may not seem that something as simple as the timing of sowing can have a major impact on the success of your harvest, in reality it’s one of the most important decisions a farmer needs to make, one that can determine whether they will have a good year or not. In addition to recommending the best time to sow, the tool offers several other useful insights related to soil health and the choice of fertiliser, as well as a weekly weather forecast.
Unstable crop prices is another major problem farmers face on a daily basis, which severely restricts their ability to devise an exact production pattern. Some crops are more affected by this issue than others, though, especially those with a limited shelf life, such as tomatoes. To get around this problem, companies are increasingly using technologies like AI, machine learning, and big data to monitor crop health in real time, detect signs of disease or pest infestations, estimate crop yields, and forecast prices. This data can then be used to provide farmers with valuable insights about future price patterns and demand levels, and help them decide which crops to sow or how much pesticide to use.
PEAT, a Berlin-based agritech startup, has developed an app called Plantix, which uses AI and machine learning to diagnose plant disease, pest infestations, and nutrient deficiencies. After a farmer snaps a photo of the afflicted plant, the app takes the image and compares it to existing images in the database to identify the disease. So far, more than seven million farmers have downloaded the app and used it to identify more than 385 different crop diseases on their farms.
2. AI in vertical farming can help countries meet rising demands
Back in 1999, researchers at Columbia University presented the idea for a skyscraper that would be able to feed thousands of people, which was the first time ever someone proposed the concept of a vertical food system. Ever since then, we have been hearing stories about how vertical indoor farming was going to revolutionise the agriculture sector. While that prediction hasn’t exactly come true yet, vertical farming is increasingly used to help farmers around the world respond to growing demand for food, address existing inefficiencies in traditional agricultural systems, and protect food supply chains from future disruptions. Vertical farming also offers a more sustainable alternative to traditional farming methods, as it uses up to 95 per cent less water.
Despite requiring less water, vertical indoor farming systems can produce more food and do it at a much faster pace, with a single vertically farmed acre capable of producing the same quantities of food as four to six soil-based acres. Another advantage of vertical farming is that it doesn’t use soil but nutrient-rich growth systems, which not only reduces pressure on shrinking arable land but allows us to bring production sites closer to urban communities. This in turn helps reduce transport-related emissions and makes the supply chain more resistant to disruption. What’s more, food grown in vertical farming systems could potentially help resolve our food waste problem, as it has a longer shelf life while also being tastier and more nutritious.
Bowery Farming, a New York-based vertical farming company, uses an AI system called BoweryOS to monitor thousands of crops that are grown across its farms and deliver personalised attention to each and every one. Using a vast network of sensors and cameras, the system collects billions of data points about the condition of each plant, which are then processed by machine learning algorithms to produce valuable insights. For instance, the system can identify which plants require more light or which ones are ready to be harvested.
3. Autonomous harvesting with AI robots helps facilitate sustainable methods
As the world’s agricultural workforce continues to grow older and field workers increasingly turn to less demanding lines of work, the agricultural sector is facing a growing labour shortage. To address this issue, farmers around the world are increasingly turning to automation and artificial intelligence. However, self-driving agricultural machinery and autonomous drones can do far more than help farmers resolve the lack of field workers. Coupled with data mining and predictive analytics, these innovative technologies can also help farmers make better-informed decisions and significantly increase their crop yields. Furthermore, they can make agriculture more sustainable by enabling farmers to conserve resources, accelerate time to market (TTM), and reduce the use of chemicals.
The Boston-based agricultural robotics startup Root AI has developed a new robotic harvesting system called Virgo, which could one day replace human field workers. The robot uses artificial intelligence and computer vision technologies to identify crops grown on a farm before picking them with a custom end-of-arm tool (EOAT). At this point, it can only identify tomatoes, but the company plans to expand its abilities to include other specialty crops as well, such as peppers, grapes, melons, strawberries, raspberries, avocados, eggplants, and cucumbers. “AI is the big piece of the puzzle for us”, explains Josh Lessing, the CEO and co-founder of Root AI. “Computer vision algorithms can’t touch the physical world, they can just look at it. Robots are the bridge, and at Root we’re building machine learning algorithms that will enable robots to do physical work in complex, real-world environments.”
“To really eliminate waste, to really get to that next level of sustainability and impact, we have to rethink the entire grow process”.Brandon Alexander
4. AI precision farming – efficiency equals more sustainability
One of the concepts that have attracted a great deal of attention in agricultural circles in recent years is AI-powered precision farming. The term ‘precision farming’ refers to a wide range of technologies that allow farmers to monitor and control their agricultural activity with a high degree of accuracy. Precision farming offers numerous advantages over traditional farming methods, including more efficient production, reduced environmental impact, and cheaper, higher-quality food. With this in mind, it’s no surprise that the popularity of precision farming continues to grow, as recent studies reveal that 86 per cent of farmers now use some form of precision farming, while 95 per cent of them consider the concept to be very helpful.
The agritech startup Iron Ox recently unveiled a farm that is run entirely by robots. The farm uses a sophisticated hydroponics system to grow a number of crops, including basil and strawberries. The crops are monitored around the clock by an AI system, which keeps an eye on their condition and makes sure that they receive plenty of water, sunshine, and nutrients. The process works as follows: the crops are first transported to a dosing station by a robot named Grover. This is where the second robot called Ada steps in and lifts the plants out of the water to inspect their roots and check the levels of nutrients like nitrogen, potassium, and phosphorus. If the system determines that the levels of any nutrients are insufficient, it will use the hydroponics system to deliver additional quantities and thus ensure optimal growth. According to CEO Brandon Alexander, this enables the farm to reduce waste, improve crop yields, and minimise its environmental impact. “To really eliminate waste, to really get to that next level of sustainability and impact, we have to rethink the entire grow process”, adds Alexander.
As the world’s population continues to grow at a rapid pace, so does the pressure on the agricultural sector to produce enough food to feed everyone. Unfortunately, traditional farming methods are simply not up to this task, forcing farmers to turn to technology for help. One of the technologies that could prove particularly helpful in this regard is artificial intelligence, which is predicted to have a profound impact on the sector by 2030. Among other things, AI can help farmers cut their costs, increase crop yields, and produce more nutritious food. Perhaps even more importantly, it can help make agriculture more sustainable through the implementation of innovative concepts like predictive analytics and diagnostics, vertical farming, autonomous harvesting, and AI precision farming. This should ensure that AI will take on an increasingly prominent role in the agricultural sector in the upcoming period, forever changing how we produce food.