National Council of Applied Economic Research
Opinion: Raka Saxena and Laxmi Joshi.
Unlocking the full potential of AI, ushering in an era where technology and agriculture converge.
In the dynamic landscape of agricultural development, rural progress undergoes a significant metamorphosis with the infusion of technology, contributing to a structural transformation that reverberates across rural communities.
Despite agriculture’s historical resistance to digital integration, the sector is experiencing a paradigm shift marked by the burgeoning development and commercialization of agricultural technologies. This evolution, albeit fraught with challenges, holds a promising trajectory as artificial intelligence (AI) emerges as a linchpin in the quest for optimal agricultural productivity and sustainability.
The COVID-19 pandemic, acting as a catalyst, spurred the integration of AI into agriculture, urgently demanding innovative solutions to surmount challenges and safeguard food security. From predictive and monitoring tools for droughts to robot-assisted methodologies addressing skilled manpower shortages, AI is a versatile ally in navigating the complexities of the agricultural landscape.
More than 87% agricultural holdings in India belong to smallholders (<2 ha). The small size of landholdings, giving rise to inefficient farming practices and restricting economies of scale, poses a formidable obstacle for farmers striving to embrace contemporary agricultural techniques. AI serves as a visionary partner to farmers, foreseeing and predicting agricultural yields with a precision that transcends traditional methods.
Further, crop diversification emerges as a viable solution to enhance resilience. A significant portion of agricultural land is dedicated to a few staple crops, contributing to soil health issues and increased susceptibility to pests and diseases.The predictive prowess of AI becomes especially evident in its capacity to anticipate crop health, identify nutritional deficits, and pinpoint pest incidences through the meticulous analysis of high-resolution images.
This, in turn, facilitates a level of accuracy in resource allocation and management. The fusion of AI with Global Positioning System (GPS) technology ensures the exact positioning of seeds, fostering consistent crop growth, optimizing nutrient utilization, and mitigating wastage appreciably.
Sustainability issues in the current arena are gaining momemtun. Several regions in India grapple with water scarcity, aggravated by inadequate water management. The challenge is compounded by inefficient irrigation methods and the excessive exploitation of groundwater.
The advent of AI-powered irrigation systems further underscores their efficacy, demonstrating promising outcomes in the realm of water conservation. Real-time data, coupled with weather predictions, becomes the guiding force behind AI-powered irrigation systems. These systems organize optimal watering schedules, that not only decrease water wastage but also usher in an era of efficient water consumption.
Furthermore, AI steps in as a vigilant tool, detecting early signs of diseases and insect infestations. The use of AI extends beneath the surface as well, as it continually monitors soil health. This empowers farmers to implement targeted soil management practices, enriching fertility and paving the way for long-term sustainability in agriculture.
The incidence of extreme events are increasing. Irregular weather patterns induced by climate change adversely affect crop yields, leading to increased occurrences of droughts, floods, and extreme weather events. Farmers often lack the resources to cope with these changes.
AI’s prowess is established in navigating the complex terrain of climate-related datasets, elevating the precision of climate predictions and providing profound insights into the future ramifications of climate change. This capacity proves pivotal in enhancing the accuracy of climate predictions, offering a clearer understanding of the impending impacts of climate change.
The volatile nature of agricultural input costs and the uncertainty surrounding crop prices expose farmers to significant financial risks, thereby deterring them from making crucial investments in modern technologies. This precarious situation further contributes to the absence of a stable income for farmers.
The dearth of rural infrastructure, spanning essential components such as roads, storage facilities, and market linkages, amplifies the challenges faced by the agricultural sector. Post-harvest losses are exacerbated, and the smooth movement of agricultural produce is impeded, adversely affecting the overall efficiency of the farming ecosystem.
The absence of transparent mechanisms for price discovery exacerbates the predicament, as farmers often find themselves at a disadvantage when negotiating the remuneration for their produce.
The literature unfolds the extraordinary potential of AI in reshaping the intricate web of agricultural supply networks. Equipped with real-time information, predictive analytics, and the robust foundation of blockchain technology, AI enhances efficiency throughout the supply chain.
It increases production, minimizes losses, and assures a level of operational efficiency that propels agriculture into a new era of productivity.
Logistics, a critical artery of the supply network, undergoes a metamorphosis under the influence of AI. The technology dissects numerous elements – transit routes, storage conditions, and demand patterns – with a precision that surpasses human capacity.
AI also delves into market patterns and historical pricing data, offering insights on futuristic agricultural commodity prices.
This foresight sensitizes the farmers and stakeholders, empowering them to make educated choices in a dynamic market landscape. Through nuanced analysis, AI categorizes products based on parameters such as size and ripeness, introducing a level of precision that enhances supply chain efficiency.
The transformative potential of AI in the realm of agricultural exports unfolds as a narrative of unprecedented growth, efficiency, and transparency. The integration of AI with radio-frequency identification (RFID) and blockchain technology transforms the export supply chain into a transparent and accountable ecosystem.
Nevertheless, for AI to transform the agricultural sector, government agencies and commercial enterprises might need to take a more active role in the transition. Such aspirations are especially important to ensure that the government and societal demand for reduced emissions and increased sustainability is met in the technological shift.
For the transformation to be successful, farmers must have continuous and easy ways to acquire up-to-date knowledge of how to apply smart technologies. Therefore, ensuring that technical, agricultural education is easily accessible through for example flexible, on-demand courses are needed.
Additionally, smart farming techniques need to be modifiable to match the varying transparency and adaptability demands that different farmers have. In the Transition of the agricultural sector into a more data-driven and digital environment, the technical infrastructure needs to be secure.
This narrative suggests a vision for collaborative efforts between institutions of eminence, like ICAR, IITs, Policy Think Tanks, and other institutions of excellence pooling resources and expertise to navigate the intricate landscape of AI implementation in agriculture.
This collaboration becomes a cornerstone for unlocking the full potential of AI, ushering in an era where technology and agriculture converge to shape a more efficient, transparent, and sustainable future for agricultural growth.
Dr Raka Saxena is Principal Scientist at National Institute of Agricultural Economics and Policy Research and Laxmi Joshi is Fellow at National Council of Applied Economic Research, NCAER. Views are personal