In every nation, agriculture is a vital component of the economy. It is estimated that by 2050, there will be 10 billion people on the planet, putting tremendous pressure on the agriculture industry to boost crop yields and productivity (Eli Chukwu N.C., 2019). There are two possible ways to deal with the impending food shortage: either embracing innovative practices and using technology to increase productivity on existing farmland, or increasing land use and implementing large-scale farming. Artificial Intelligence (AI) is becoming one of the most important technologies having a major impact on the agriculture sector. AI protects the agriculture industry from a variety of threats, including population growth, climate change, job losses in this industry, and food security. AI has enabled today’s agriculture system to function at a whole new level. Crop productivity has increased with real-time monitoring, harvesting, processing, and marketing thanks to Artificial Intelligence. Many advanced computer-based systems are aimed at identifying several important parameters, including crop quality, yield detection, weed identification, and many others.
Introduction
The foundation of artificial intelligence is the idea that human intelligence can be described in a way that makes it simple for a machine to replicate and carry out tasks, from the most basic to the most complex.
Artificial Intelligence (AI) aims to accomplish the following: perception, reasoning, and learning. There is currently an insufficient supply of technology to meet the need of farmers using traditional methods. Therefore, to meet these needs and give great job opportunities to many people in these industry, some new automation technologies are introduced.
The modern agriculture landscape is changing and transforming into various innovative directions as a result of several obstacles to achieving the desired farming productivity, including limited land holdings, labor shortages, climate change, environmental issues, and declining soil fertility, to name a few. Farming has undoubtedly advanced from the days of hand plows and horse-drawn equipment. New technologies are introduced every season with the aim of increasing productivity and optimising yield. However, the opportunities that artificial intelligence in agriculture offers to their farming methods are often missed by small-scale farmers and large international agribusinesses.
Over time, technology has transformed farming, and advances in this area have had a multifaceted impact on the agriculture sector. In many countries around the world, agriculture is the primary source of income. However, as the world population grows – the United Nations predicts that it will grow from 7.5 billion to 9.7 billion in 2050 – only 4% more land will be under cultivation by that time, putting further pressure on land. Farmers will therefore need to do more with less. The same survey states that to feed an additional two billion people, food production must increase by 60%. Traditional approaches, however, are insufficient to meet this huge demand. This is leading farmers and agribusinesses to look for new approaches to boost production and cut waste. As a result, artificial intelligence is becoming more and more prevalent in the agricultural sector, as is technology. The aim is to double the world’s food production by 50% by the year 20502 to feed an additional two billion people.
Practical Applications of Artificial Intelligence in the Agriculture Sector:
1. Weather and Price Forecasting: As we have covered in the previous challenges, climate change makes it harder for farmers to make the best decisions about harvesting, sowing, and planting. However, farmers can plan the type of crop to grow, the seeds to plant, and the process of harvesting the crop with the help of AI weather forecasting, which provides information about weather analysis (Kumar, A. & Vats, V., 2018). Price forecasting can help farmers maximize their profits by giving them a better idea of the price of crops in the next few weeks.
2. Crop Health Monitoring: Soil type and nutrition have a significant impact on crop quality. However, soil quality is deteriorating daily due to the increasing rate of deforestation, and it is difficult to measure. Artificial Intelligence has developed a new program called Plantix to solve this problem. Pete created it to detect soil deficiencies, such as diseases and pests that affect plants. Farmers can use this application to get ideas about how to apply better fertilizer, which will enhance the quality of the crop. Through the use of image recognition technology of AI in this app, farmers can take pictures of their plants and get quality information (Harwood and Trevor, 2019).
3. Agricultural Robotics: Many industries, mainly the manufacturing sector, use robotics extensively to complete difficult tasks. Currently, many AI startups are creating robots for use in the agriculture industry. These AI robots are designed to be able to complete various agricultural tasks. AI robots are trained to inspect the quality of crops, identify and manage weeds, and harvest the crop much more quickly than a human.
4. Intelligent Spraying: Weeds are easily detected by AI sensors, which can also identify areas where weed growth has occurred. Herbicides can be precisely sprayed in these areas to reduce their use and save time and crop damage. Many artificial intelligence companies are developing robots that combine artificial intelligence and computer vision to spray weeds. AI sprayers have the potential to significantly reduce the amount of chemicals applied to fields, improving crop quality and resulting in cost savings.
5. Disease diagnosis: With AI predictions, farmers can easily learn about diseases. With this, they can diagnose diseases quickly and accurately using the right approach. This can spare farmers time and save plant lives. First, computer vision technology is used to pre-process plant images to achieve this. This guarantees that plant photos are correctly divided into sections that are diseased and sections that are not. The diseased part is cut out after being discovered and sent to the laboratory for additional diagnosis. Moreover, this method helps in identifying pests, nutrient deficiencies and many other issues (Bush.K., 2017).
6. Precision Farming: It’s all about the “proper right place, proper right time, and right products” in precision farming. The labor-intensive part of farming that involves performing various types of repetitive tasks can be replaced with a much more accurate and controlled method called precision farming. Identifying plant stress levels is an application of precision farming. High resolution photos and various plant sensor data can be used to achieve this. After that, a machine learning model receives the sensor data as input to identify the stress.
Benefits in Agriculture
1. AI enables better decision making: The agriculture sector really benefits from predictive analytics. It assists farmers in solving major problems associated with farming, such as analyzing market demands, estimating prices, and determining the best time to plant and harvest crops. Additionally, AI-powered tools can assess crop quality, monitor weather, make recommendations for fertilizer, and assess the health of soil and crops. Farmers are able to practice efficient farming and make better decisions thanks to all these benefits of AI in agriculture.
2. AI brings cost savings: AI-enabled tools for precision farming enable farmers to grow more crops with less money and resources. AI gives farmers access to real-time information that helps them make informed decisions at every stage of farming. This intelligent choice results in less product and chemical loss as well as cost and time savings. Additionally, it enables farmers to pinpoint the exact areas that need pesticide treatment, fertilization, and irrigation, thereby reducing the amount of chemicals used excessively on the crop. In summary, all these factors lead to less herbicide use, higher crop quality, and more profits with fewer resources.
3. AI reduces labor shortage: The agriculture sector has long struggled with labor shortages. AI can address this problem of farming automation. Examples of how farmers can increase productivity without hiring more employees include driverless tractors, intelligent sprinklers, intelligent irrigation and fertilization systems, vertical farming software, and AI-powered harvesting robots. When compared to human farmhands, AI-driven machinery and equipment are significantly faster and more accurate.
Challenges of AI Adoption in Agriculture
1. Lack of Familiarity with AI Machines: Even though there are many advantages to implementing AI in agriculture, most people around the world are not familiar with the use of AI-enabled tools and solutions. To address problems, AI companies must first give farmers basic tools, and then, as they become accustomed to it, more sophisticated machinery.
2. Insufficient Familiarity with New Technologies: For developing countries, implementing AI and other cutting-edge technologies in agriculture can be difficult. In places where such agricultural technology is not being used, it will be extremely difficult to sell such technologies. Farmers in these areas need assistance from someone to use these technologies.
3. Privacy and security issues: AI can give rise to many legal concerns as there are currently no clear rules and guidelines for its use. Also, there can be security and privacy issues like cyber attacks and data leaks due to the use of software and the internet. For farmers or farm owners, all these problems can pose serious challenges.
AI Startups in Agriculture
1. Prospera: Founded in 2014, Prospera is an Israeli startup. This business develops clever methods for productive farming. It creates cloud-based solutions that collect all field data – soil and water, aerial photos, etc. and integrate it with the equipment used on the field. This device, dubbed the Prospera Device, uses this data to generate insights. Several sensors and technologies, including computer vision, power the device.
2. Blue-River Technology: In 2011, Blue River Technology, a start-up based in California, was founded. It uses robotics, AI, and computer vision to create next-generation agricultural equipment. This equipment uses computer vision to identify individual plants; machine learning determines the course of action, and robotics carries it out. This helps farmers save money and reduce the use of chemicals.
3. FarmBot: It is an open-source CNC precision farming device and software that can be used by anyone at home to grow crops. With a purchase of $4000, the complete “FarmBot” product allows anyone to perform all aspects of farming themselves, from weed identification to seed planting, using an open-source software system and a physical bot. In addition, it provides a web application that can be downloaded on any computer or smartphone, enabling us to oversee farming from anywhere at any time.
4. Fasal: Around the world, the application of AI in the agriculture sector is growing daily. However, compared to the rich region, the poor region has less agricultural holdings per farmer. This is good for automated monitoring as it requires fewer low-bandwidth and small-sized devices to capture all the agricultural data. Indian startup Fasal is working in this space. It provides farmers access to real-time data and insights through the use of affordable sensors and AI. Farmers can achieve this by having access to current, useful information about the daily operations of their farm. The tools offered by the company are simple to use in small spaces. They are creating AI-enabled tools to enable accessible precision farming.
5. One Soil: This application aims to assist farmers in making better decisions. For precision farming, this app uses computer vision and machine learning algorithm. It calculates fertilizer rates for nitrogen, phosphorus, and potassium, detects issues in fields, and monitors crops remotely.
Conclusion
The rise of AI solutions will determine how farming uses AI in the future. Despite massive research and some commercially available applications, the agriculture industry remains underserved. Furthermore, research is currently underway to develop predictive solutions to address a real problem that farmers face in their farming operations. AI largely addresses labor and resource shortages and will be a powerful tool to assist organizations in managing the growing complexity agriculture. The larger of the contemporary corporations should definitely invest in this sector. Artificial Intelligence will various undoubtedly challenge and enhance human decision making while also improving farming practices. These technological advancements should improve farming yields and practices while improving the lives of farmers on a qualitative level.
Read Also:
- Application Of Artificial Intelligence (AI) In Agriculture: An Indian Perspective
- Challenges And Opportunities Of Artificial Intelligence In Agriculture
- Artificial Intelligence For Agriculture
- Artificial Intelligence In Agriculture
- Role Of Artificial Intelligence In Indian Agriculture
- Artificial Intelligence (AI) Techniques Used For Diseases Detection In Agriculture
- Study On Artificial Intelligence Applications Uses In Agriculture
- Advantages And Disadvantages Of Robots In Agriculture
- Role Of Robots In Agriculture
- Artificial Intelligence In Agriculture
- A Glimpse About Artificial Intelligence (AI) In Agriculture
Leave a Reply