The rise of technology is set to alter agricultural challenges while reimagining its landscape and unravelling countless possibilities
Moreover, AI in agriculture is also helping farmers deduct the onset of stress in the standing crop and make timely input so that damage can be prevented.
Mr. Navneet Rai, Chief Digital Officer, Arya.ag
Technological disruptions in every sector have proved to be a boon for its economy. However, one sector that still awaits its benevolence is agriculture. Over the years, a variety of factors have influenced the quality and flow of agricultural operations, including changing climate conditions, a labour scarcity, lack of access to capital, uncertainty over adapting new technology, and pesticide use, which has increasingly impacted its functioning and scaling. Smart farming is a clear solution for fighting major challenges faced by the agriculture sector since it helps farmers leverage new technologies to fundamentally use less and grow more.
IoT, Artificial Intelligence, Machine Learning, Drones Technology, Automation and Robotics will aid farmers to farm better and drive profitability. Understanding how migration patterns of animals, birds, and insects, crop-specific fertilisers and pesticides affect production is an apt challenge for machine learning to churn out effective solutions. Potential data has never been more important in determining the financial success of a crop cycle than now. According to BI Intelligence Research, global spending on smart, connected agricultural technologies and systems, including AI and machine learning, is expected to treble by 2025, hitting $15.3 billion.
Tackling unpredictability
Climate change is the most important, but still the most complex global issue till-date, that is yet to have a solution that is holistic. It is no less of a defiance for the agriculture sector. While smart farming is here to optimise farm productions, farmers face the indomitable and aggressive weather patterns that are unpredictable, shorter growing seasons, droughts and extreme temperatures. Here, the conception of climate-smart farming can help farmers foresee such occurrences and equip themselves to not just sail through these situations but thrive by preserving or even improving their farm production.
Data-driven procedures powered by AI and machine learning with big data technologies and high-performance computing can aid in boosting productivity and output, preserving ecosystems, strengthening ability for adaptation to climate change, tackling extreme weather like drought, flood, and other calamities, and gradually improving land and soil quality.
The rise of AI
In India, AI-based technologies are already shaping agricultural methods. Some Indian farmers with a large amount of cultivable land are now leaning toward smart farming infused by AI-enabled sophisticated technologies, autonomous tractors equipped with GPS and various other sensors including digital cameras to plant crops, apply fertilisers, spray pesticides, manage weeds, determine the need for irrigation, predict yield, and so on in more efficient ways than ever before. Farmers can leverage AI to improve agricultural yields by learning how to care for their crops and determining the optimal quantity of water or fertiliser to apply.
Moreover, AI in agriculture is also helping farmers deduct the onset of stress in the standing crop and make timely input so that damage can be prevented. In fact, the tech is super precise in analysing the farm area and pointing out the type of intervention needed in a particular area, in order to optimise farm production.
As per the Indian Network for Climate Change Assessment, Agriculture alone contributes to 18% of total GHG emissions in India. The capacity to measure greenhouse gas emissions along the whole value chain from farm to shelf for a given product is critical for improving transparency and lowering emissions. AI is potentially capable to help farmers understand optimising certain areas that can lower carbon emission and therefore, provide a nudge towards sustainable farming practices.
Farmers can maximise farm productivity by producing enough to remain food secure while commercialising excess harvest by receiving contextually relevant information about crop health based on weather forecasts and specific soil conditions, which will therefore help them in deciding the right exercises such as irrigation or crop selection to adapt to prevailing factors in a timely manner.
It is clear that technology will help farmers bridge the gap between practices and productivity. These sorts of adaptive technology can help to alleviate the effects of climate change, but more drastic steps are required to ensure global food security in the face of rising temperatures.
The technological disruption, that are now called the future of agriculture, can only be a boon for the sector if its scalable and made easily accessible to all. Therefore, a government push to ease accessibility, ensure affordability, and enable a wider adoption of technology will pave the way for advancing the agriculture sector.
