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Emerging Technologies Transforming The Agriculture Industry

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Technology has redefined farming over the years and technological advances are impacting the agriculture industry in more ways than one. Agriculture is still considered to be the primary source of livelihood in India as nearly 58% of the total population is dependent on it. Moreover, worldwide over one billion people work in agriculture generating $2.4 trillion for the global economy. This emphasizes the growth potential of this sector.

However, traditional methods of farming cannot sustain this growth. Hence, the industry is finding newer ways to increase agriculture produce and reduce wastage. As a result, emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) are making inroads into this sector and revolutionizing its different functions.

Let us look at some of these functions…

Reinventing the field sprayer – Over-spraying of pesticides is adversely impacting the agriculture industry. Farmers spend a major proportion of their income in procuring these pesticides, and they are often wasted on being sprayed on healthy plant or getting mixed with the soil and contaminating it. AI technology helps in detecting diseases in plants. AI sensors can detect and target weeds and then decide which herbicide to apply within the region. As a result, smart spraying allow farmers to target the weed affected crop and save the wastage, thereby lowering costs of pesticides by almost 90 percent.

Accurate decision making with predictive analytics – The agriculture industry traditionally relied on their experience to make critical decisions regarding the weather and climate conditions. There was no data to analyze, draw patterns and make informed decisions based on insights and knowledge. With the integration of emerging technologies such as IoT, sensors are being used in the field to collect farm data in real-time. Further, analytics is being run on this data to derive actionable insights that allow farmers to arrive at important decisions related to the weather and the appropriate time to sow seeds to ensure maximum productivity.

Monitoring soil and crop health – AI in agriculture applications can be used for identifying potential defects and nutrient deficiency in the soil. The image recognition technology can identify the defects through the images captured by the user’s smartphone. The user, then, is provided with various soil restoration techniques. The same way, this technology can be utilized to detect diseases, pests, and nutrition deficiency in the crop and restore its health.

Farm harvesting using AI robots – Owing to the ongoing pandemic, the agriculture industry is struggling with labor shortage. Farmers and other agri-producers are finding it difficult to hire daily wagers for crop harvesting. The AgriTech companies are tackling this problem with the introduction of AI-enhanced robotic harvester. For instance, the agricultural robotics and artificial intelligence company “Root AI” has announced the launch of its robo-harvester, named “Virgo”. In the latest video released by the company, titled “Going Cross-Crop”, Virgo is shown pickling cucumbers and strawberries in the field. As per a press release issued by the company, Virgo leverages a host of sensors as well as artificial intelligence to analyze crop positions and ripeness and then uses a specialized gripper to pick produce once it’s ready. It also replicates a human being’s ability to harvest multiple crops.

Wrapping up

Emerging technologies have the potential to solve the various complexities of the agriculture industry. The traditional practice of farming was a laborious practice and entailed higher expenses. Now, with the integration of emerging technologies, farmers can not only reduce their efforts and work hours but also plethora of miscellaneous expenses. They no longer need to depend on uncertainty while making critical decisions that can impact them financially and emotionally. With the introduction of these technologies, they can collect data, run analysis, and plan meticulous strategies based on in-depth knowledge and deep understanding.

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