Artificial intelligence for the agriculture of the future

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Professor Manish Kr Sharma & Shavi Gupta

Artificial intelligence is spreading its footprints in almost every nook and cranny of scientific research, where its formidable caliber and revolutionary operational engine have exposed almost every arena to a new light. Generally speaking, artificial intelligence is a new and robust substitute for almost all conventional methods which otherwise lack the expertise to adequately solve, manage and address situations. It has the potential to revolutionize and transform science and technology into new clothing. Amid the use and deployment of artificial intelligence in almost every field, how can one forget to mention the essence of artificial intelligence in the field of agriculture? More specifically, more than half of India’s population is directly dependent on agriculture and farming as their main livelihood as the issue is not just limited to the factum of livelihoods but nurtures obviously a nation for its survival. Even the population of the world is increasing enormously and with this increase the demand for food and employment is also increasing. According to the Food and Agriculture Organization of the United Nations, the world’s population will increase by another 2.1 billion in 2050, but the area of ​​cultivated land will represent only 4.2% of the total land area at that time. era. As we know, agriculture faces multiple challenges such as heavy dependence on monsoon, resource intensity – intensive use of resources (water, inorganic fertilizers and pesticides), land degradation and loss of soil fertility, and low yield per hectare, among others. To overcome the above-mentioned challenges in agriculture, it is time to opt for precision farming using artificial intelligence methods to meet the shooting demands of the expanding population. Since Artificial Intelligence methods support decision support systems in agriculture, help to optimize storage and transport processes, and allow to predict the costs incurred depending on the chosen management direction. Thus, in the field of agriculture, we need more efficient farming methods that can be achieved by using recent technical developments and solutions to current bottlenecks in agriculture.

Artificial intelligence in agriculture has brought an agricultural revolution. Artificial intelligence can be used in the field of agriculture to solve challenges such as the right time to sow, irrigate, weed, spray, harvest using sensors and other means embedded in robots and machines. drones. The direct deployment of artificial intelligence or artificial intelligence in the agricultural sector may be the culmination of a paradigm shift in the way agriculture is now practiced. Artificial intelligence having one of its prodigious and desperate traits has its remarkable influence in solving the aforementioned challenges in agriculture and even tends to take them to inexplicable heights. In other words, AI in agriculture not only helps farmers automate their farming, but also shifts to precise cultivation for higher crop yield and quality while using fewer resources. Thus, artificial intelligence can play a catalytic role in raising awareness and also increases a farmer’s knowledge and efficiency. This will help improve crop yield from various factors such as climate change, population growth, employment issues and food security issues. In this context, Artificial Intelligence can give rise to precision agriculture, that is to say “in the right place, at the right time and with the right products”. Even a number of start-ups have been launched on the basis of artificial intelligence in the field of agriculture like Blue River Technology, FarmBot, Prospera, Fasal, OneSoil, Cropin and many others.
Weather is a primary challenge as it plays a very important role in agriculture and it is difficult for farmers to make the right decision for harvesting, sowing and land preparation due to climate change. But with the help of artificial intelligence, weather forecast data helps farmers to have weather analysis information and hence they can plan what kind of crop to grow, what seeds to sow and how much to grow. crop harvest. When the crop is harvested at the right time, with the help of price forecasting, farmers can get a better idea of ​​the crop price for the next few weeks, which can help them get maximum profit. By implementing such a practice helps in making a smart decision on time. After the weather forecast, land preparation is very important before sowing the seeds. Soil preparation depends on various factors such as water content, nutrients present in the soil, and soil pH. To prepare the soil, farmers need to consider two main factors, namely soil management and irrigation management. Because soil and irrigation management are critical issues in the field of agriculture, as both of these factors lead to the degradation of the quality of a crop. In soil management, AI techniques are widely used to detect and adjust soil parameters that provide a favorable environment for agricultural growth. To properly manage the soil, there is an agricultural start-up InCeres that has developed an application that can predict soil quality and fertility based on soil application and nutrient uptake. The analysis is based on data on soil chemistry, weather conditions, crop types and satellite images showing plant growth rates. Irrigation is one of the most labor intensive agricultural processes. To solve the problem of irrigation, artificial intelligence can train machines that know historical weather conditions, soil quality and the type of crops to be grown, so that machines can automate irrigation and increase overall yield. . Since almost 70% of the world’s freshwater resources are used for irrigation, automated irrigation using artificial intelligence can conserve water and help farmers manage their water problems.
For overall crop management, remote sensing, one of the main artificial intelligence techniques, is used. Remote sensing techniques along with hyperspectral imaging and 3D laser scanning are key to establishing crop measurements over thousands of acres. It has the potential to bring a revolutionary change in terms of how farmers monitor farmland, both in terms of time and effort. This technology will also be used to monitor crops throughout their life cycle, including generating reports in the event of anomalies.
For a good yield of a crop, artificial intelligence helps to determine the crop quality which largely depends on the soil type and soil nutrition. But with the increase in the rate of deforestation, the quality of the soil is deteriorating day by day, and it is difficult to determine it. To solve this problem, artificial intelligence has come up with a new application called Plantix. It was developed by PEAT to identify soil deficiencies, including plant pests and diseases. With the help of this app, farmers can get an idea to use better fertilizer which can improve the quality of the crop. In this application, AI image recognition technology is used by which the farmers can capture the images of the plants and get information about the quality of the crop.
In addition to other challenges in the field of agriculture, weeds are one of the major threats to all agricultural activities and also affect crop yield. To solve this problem, artificial intelligence helps to reduce weeds on the farm as it manages weeds by implementing computer vision, robotics and machine learning that collects data to control weeds, thus helping farmers to spray chemicals only where weeds are present and reducing the use of the chemical to spray an entire field. Ultimately, it effectively reduces weeds and also reduces the use of herbicides in the field compared to the volume of chemicals normally sprayed. Hortibot is one of the examples used to weed the farm. In conjunction with other challenges faced by farmers, crop diseases are also a major source of concern for farmers. Disease detection in a crop can be achieved through artificial intelligence using the concept of image detection and analysis to ensure that images of plant leaves are segmented into surface areas such as l background, the diseased area and the non- diseased area of ​​the leaf. The infected or diseased area is then harvested and sent to the laboratory for further diagnosis. It also helps with pest identification, recognition of nutrient deficiencies and more. However, besides the satisfaction derived from AI in a plethora of fields, its application as a tool is another crucial aspect to think about. The challenges neutralized by Artificial Intelligence are indeed co-terminal with the challenges posed by Artificial Intelligence with regard to its operation and the sufficient expertise required to pilot it in order to obtain procedural results. . In other words, possessing the qualitative ability to deploy and use Artificial Intelligence is a purely distinctive and parallel subject that requires equal attention insofar as a driverless vehicle is nonetheless a fiction. Moreover, since artificial intelligence has sincerely attributed itself to progressive research and opened new doors for innovation, a multidimensional approach to its various aspects is an essential mantra for its effective and robust implementation. In addition, imparting skills and knowledge to take advantage of AI is the need for an hour that, in addition to replacing traditional methods, will contribute to capacity building and make the most of the results and usefulness . Artificial intelligence is an enabler with a huge capacity to accelerate the pace of technology, but its planned and organized application in language with emotional intelligence would be a decisive factor in achieving the desired results.

(The authors work as a director and researcher in the Statistics and Informatics Division, SKUAST-J).

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