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AI in agriculture
AI in agriculture

July 2, 2021

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AI in agriculture

Artificial intelligence in agriculture and allied activities is having its moment in the sun. At a time when the whole world is disrupted by COVID-19 and social distancing is the norm, online vegetable store for example, could offer an excellent way for transactions between farmers and customers in the post-COVID world.

What is artificial intelligence in agriculture?

Agriculture may be the most ancient of occupations, yet its relevance has only become bigger with the imminent threat of food insecurity. Technology powered by Artificial intelligence is ensuring the sustainability of quality food production for the coming decades. AI solutions are being used to diagnose pests, predict the best time to sow and gauge prices for produce. Drones, hydroponics, artificial lights and AI-powered cameras are protecting crops from wild animals.

India’s national AI strategy also identifies agriculture as one of the key areas where AI can enable development and greater inclusion. AI-enabled solutions in agriculture help farmers improve crop productivity and reduce wastage. The Confederation of Indian Industry (CII) is working towards developing the agriculture sector in line with the country’s aspiration. Upgrading the technology quotient in agriculture is a key focus area. A CII-Deloitte report on ‘Artificial Intelligence – Augmenting Human Intelligence’ also highlights the role of AI in agriculture.

How AI can implemented in agriculture:

Improving crop productivity –

 Climate change has resulted in making traditional agricultural know-how outdated, especially for forecasting weather patterns that determine farming practices for the season.

Soil health monitoring –

 Along with favourable weather conditions, soil health comprising of an adequate level of moisture and nutrient holds the key to getting the best yield. Distributed soil monitoring performed via image recognition and deep learning models can be used to take corrective measures to restore soil health.

Optimization of pest and weed management –

AI can be used for predicting the behaviour of pests which can be beneficial for advanced planning of pest control. Efficient pest management leads to lower crop and environmental damage. A combination of remotely sensed data, efficient image classification tools, weather data, and other relevant data points can be used to distinguish the weed from the crop. This will confine the usage of weedicide only to the areas that require treatment.

Water Management –

Efficient water management in agriculture can have a huge impact on the looming problem of water scarcity. Water usage in agricultural land can be optimized by using thermal imaging cameras that continuously monitor if crops are getting sufficient amount of water.

Price realization for farmers –

Only about 6 percent of farmers in India get benefits of Minimum Selling Prices (MSP). A better price realization for farmers is possible through an effective price discovery model. Predictive modelling using AI can be instrumental in presenting more accurate demand-supply information and predicting demand for agricultural produce to farmers.

 

 

 


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