Artificial intelligence holds the baton of driving an agricultural revolution at a time when the world must produce more food using fewer resources. Speaking from the statistics, agriculture employs 20% of the world’s population with a $3 trillion valuation. However, with the population increasing so rapidly, a 600% crop yield rise has been registered in the past 100 years. With land being a constant value and climate changing unfavorably it is going to get worse. The population is predicted to surge by 2 billion by 2050 with only an additional 4% of agricultural land. To sustain our food security along with environmental safety, it will be unavoidable to increase crop productivity further, decrease the use of water, fertilizer, and pesticides.

Therefore, it’s extremely crucial that we employ the assistance if AI in Agriculture. Here are a few applications of the same

A. Precision Agriculture

This technology benefits from guidance systems and sensors will allow farmers to customize their practices to generate greater yield. Coming to the technological aspects, Precision agriculture uses a comprehensive set of information technologies that rely on site-specific field information to vary production and management practices across the entire farm. So far, these advanced solutions have and are predicted to increase the efficiency of farming.

B. Advanced Agricultural Machinery

With the growing needs, it’s a prerequisite to have smarter and upgraded machines. The accuracy of seed placement, their alignment, status, the health of saplings, the composition of the soil (organic matter, nitrogen, moisture), GPS auto-guidance with line-of-sight to make sure row planting doesn’t overlap with neighboring row borders, calling out for needed refills- are a few tasks which need attention. All of this can be done quickly in the fourth Industrial Revolution, and a few unique projects have been run for the same.

C. Automated Workforce

According to research studies, 66% of the global population would inhabit urban areas by the end of 2050. It will create a workforce shortage in rural areas where the agricultural industry majorly exists. Adopting the latest technologies is the best way to address this situation. Using automated processes empowered by artificial intelligence, many agricultural operations can be remotely done which will help farmers to make faster and smarter decisions.

D. Predicting Soil Requirements

Forecasting an ever-variable subject is a hard task. In the case of soil, take an example of Nitrogen. Nitrogen is one of the greatest contributors to increasing crop yield. Due to its comparatively economical cost and huge potential return, farmers seldom use excessive amounts to maximize yield which isn’t very eco-friendly. To solve this problem and cut the investment, next-generation cloud computing infrastructure, big-data analysis techniques, high-resolution climate data, soil characteristics are combined with the latest crop and Precision Nitrogen Management (PNM) models to predict soil nitrogen requirements on a dynamic basis.

E. Livestock Farming

Livestock farming is old as well as hard practice. It requires a lot of monitoring to ensure healthy growth. To address this problem, computer vision systems can be devised for the identification and tracking of individual animals. Also, analysis of animal weight via an intelligent camera application can be done. It will be productive, efficient and time-saving.

As, the farmers always say- “You shall reap what you sow.” It’s high time that the Agriculture industry combines with Industry 4.0 to match with the pace of the world, solve the existential crisis and produce fruitful results. With the same belief, Tvarit AI is marching and researching dedicatedly to contribute to the upcoming agricultural revolution.

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Tvarit The Team
We’re based out of Frankfurt Germany having the perfect team composition - a German founder bringing vast know-how of machinery coupled with high-quality software expertise of the Indian founders.