Everyday agriculture using Artificial Intelligence: Benefits for the soybean industry

Artificial Intelligence or AI is perhaps one of the most popular topics in the 21^st century. To simply state, AI is the process wherein the computers perform complex tasks instead of humans to save time, energy, and labor. AI has had a profound impact on all walks of life, making everyday life less demanding. Agriculture is one such industry that has been continuously benefited by AI. 

From planting to harvesting and processing to marketing, AI has tremendously transformed all aspects of crop production.

Many nations such as the US, Australia, and China employ AI in their regular farming activities. These countries practice agriculture on huge stretches of land and if not for the AI, it would be extremely difficult to manage and tackle the problems occurring in the different aspects of crop production. 

Heavy mechanization complemented with AI helps growers to achieve higher crop productivity and returns, thus giving them the obvious advantage in the world market over those following traditional farm practices.

Now, let us look at the different ways AI could benefit the soybean industry?

Farm-machinery activities. Gone are those days when all the field activities were done by humans using draught animals. Our world has progressed to a state where the majority of the activities are now performed by machines. In the past few decades, farm machinery has seen an impressive phase of transformation in terms of construction and capabilities.

Now with the technological advancements and advent of AI, it is possible for us to remotely guide tractors using computers without being actually on them to work. Satellite-based remote sensing and GPS-guidance makes it possible to control the machinery precisely to even a few centimeter range.

Crop protection. Large scale mono-cropping of soybean invites several foliar and soil-borne diseases leading to massive yield losses. It is imperative that we accurately locate the point of origin, the extent of damage, and the direction of its spread, to provide timely treatment for saving the crop. 

This is where remote-sensing technology such as satellite and drone-base imaging comes to play. Further, the AI can efficiently analyze the images and tell us the location, nature, and extent of damage so that protective measures could be taken at the earliest.

According to the previous experience of ‘Evergreen FS’, an agricultural company, employing thermal imaging-based remote-sensing would help in identifying a disease origin way before it could be detected visually by our eyes.

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Crop nutrition & irrigation. Soil is the storehouse for nutrients that are essential to the plants. As farming progressed, new crop varieties were introduced that responded better to nutrient dosing through chemical fertilizers. Traditionally, fertilizers were made available by simple broadcasting by hand or line placement using tractors. This leads to a huge loss of nutrients since what's left after plant absorption would normally go wasted. 

Now, AI is helping in crop nutrient management through remote-sensing and robotics. Robots are being developed that are capable of local application of fertilizers after locating plants that are in real need of the specific nutrient. This would prevent any unnecessary nutrient loss and wastages through over-application.

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Similarly, AI can help in analyzing the soil water levels regularly to allow us to schedule the irrigation for our crop. It will prevent us from needlessly irrigating and wasting precious natural resources.

Post-harvest processing. Once the crops are harvested the produce undergoes several post-harvest processing steps before it finally reaches the consumers. Nowadays pretty much all such processes have become mechanized and automated where with a few sets of typed commands, the computer starts and regulates the entire technical processes. This ensures high efficiency and product uniformity in the least amount of time.

Market trend analysis. This is one of the areas where AI plays a very critical role. We can use computers to collect and analyze several years of market data for a location and generate meaningful trends for the current market. This will help the farmers to schedule planting and harvesting activities such that they can make their ultimate end-products meet the market at the time of peak demand and prices.

AI-based market trends help the US government to develop policies relating to soybean production to help them stay afloat in the competitive market.

Modeling & forecasting. With the advent of machine learning and AI, it is now possible to analyze enormous sets of data (both historic and real-time) relating to the climate, crops, pests, and diseases, market, etc. to help build predictive models. Using such models, it is possible to forecast location-specific likely scenarios that can occur in the forthcoming seasons or years of crop production. Based on the predictions farmers get to take timely decisions in their crop activities to ensure a good harvest.

An example would be the AI-based predictive model developed by a team of researchers from Stanford University. It can predict soybean production and yields using the data from satellite imagery.

Nothing beats a human mind for its analytical thinking and logical decision making. AI is only a tool that complements this thinking process. In the future, AI’s having even more capabilities will be developed to assist us in complex tasks.