It’s Time for Digitizing Agriculture: Manoj Kummari

Agriculture is an individual process that is complex, but interdependent. In order to ensure a good yield, agriculture must be organised into efficient stages. The conditions for successful agricultural practises are clearly established by digitisation.

Agriculture is an individual process that is complex, but interdependent. In order to ensure a good yield, agriculture must be organised into efficient stages. The conditions for successful agricultural practises are clearly established by digitisation.

Automated steering systems, targeted data-driven fertilisers and pesticides applications, field robots and drones, soil sensors, autonomous driving - digitisation in agriculture as elsewhere is advancing.

Overview

In Today’s scenario, Digitisation is gaining high momentum. In 2015, 30 percent of the world's agricultural machines value was generated by software, electronics and sensors, which three times overcame the value created in the automotive industry. The figures on digital progress speaks for themselves, especially with regard to agriculture. Processes must be adapted to the digital concept for farmers and the environment, because innovative processes can lead to efficient sustainable agriculture that is resource friendly.

In digital agriculture, there is already a strong potential to tackle the challenges of global food production and to teach the technology industry to handle complex processes.

While smartphone sales have gone up a little earlier in 2018, India also plays a role in bringing more online users with its recent rise to cost effective 4G telephones. Look at Pradhan Mantri Fasal Bima Yojana, which encourages farmers to use modernised machinery, leading to growth in productivity and soil health.

Card Scheme to increase knowledge of fertiliser. Most farmers are now faced with a digital platform promise that provides farmers with knowledge (crop selection, varietal of seed), context (plant protection, weather, best practises for cultivation) and also market information (market demand, market prices, logistics).

Effective use of digital agricultures supports the development and timely delivery of nutritious, secure and affordable nutritious, targeted (locally) service information and services.

In order to empower digital farming, it is important to improve rural connectivity via apps, new media and social media etc. It also enabled rural youth to fully comprehend their potential with easy information access and low-cost Internet connectivity. By accessing equitable markets and rural businesses to offer value-added services, this increases their profitability.

The diverse and modern agriculture techniques are developed for digitalisation. One of them is precision farming and other being smart farming.

Precision Farming

Precision agriculture is an agricultural concept involving new methods of production and management that use the data on a specific location and crop intensively. For the optimization of production processes and growth conditions, sensor technology and application methods are used. Digital data can increase resource and cost efficiency and reduce environmental impacts by contrast to traditional agricultural practises.

Smart Farming

The use of information and data technology to optimise complex agricultural systems is smart agriculture (also known as Farming 4.0 and Digital farming). The integration of smart agricultural technologies and of modern data technologies makes seed planting adaptable to a particular field in order to ensure an efficient production process. The use of ICT helps farmers to make informed decisions on the basis of specific information.

Ways in which Farms can be Digitalized

Digital agriculture provides farmers with access to valuable insights in due course in order to adopt best practises and manage farms more efficiently to reduce losses and maximise profits.

Technology for agriculture offers numerous solutions for digital agriculture. IoT consists in agriculture of sensors, drone and computer imagery, which are integrated with analytical tools to generate insights for action.

Physical equipment placement on farms monitors and records data for insight. Because of advances in satellite imagery, machine learning and cloud-based information storage, predictive analytics software is highly scalable and easy to use.

Conclusion

The dynamics of the agri sector in digital technology are currently changing but the process has not been systematic. To fulfil the full potential of digital agriculture, all players in the agricultural value chain will therefore have to cooperate.