Nedunuri Kavya Shruthi, N.R.N.V. Gowripathi Rao, Vikas Kumar Ravat* and Ajit Kumar Singh Yadav
Abstract
Agriculture and Technology are becoming increasingly inextricably linked on a global basis. Agriculture technology innovations have transformed farming techniques, providing answers to some of the worldâs most urgent problems. Precision agriculture, enabled by technology such as GPS, drones, and data analytics, is increasing agricultural yields and reducing resource use. Genetic engineering and biotechnology have resulted in the creation of genetically engineered crops that are resistant to pests and thrive in harsh environments. Organic and regenerative agriculture, for example, are gaining popularity as a result of the desire to safeguard the environment. Furthermore, blockchain technology is improving transparency and traceability throughout the food supply chain. The Natural Language Processing (NLP) is having a big influence in the agricultural sector. NLP is transforming several parts of the business by using the capabilities of language understanding and processing. It aids agricultural monitoring and advising services by evaluating weather reports, research papers, and textual data to provide farmers with real-time advice on optimal planting schedules, pest and disease control, and harvest timing. By analyzing multiple data sources for signals of outbreaks, NLP assists in the early identification of pests and illnesses, allowing farmers to take appropriate preventative actions. It also plays an important role in market analysis and price prediction, analyzing massive volumes of textual market data to give insights into market patterns, price variations, and demand projections. NLP also benefits soil health and nutrient management by analyzing soil data and research materials to provide specific suggestions. Furthermore, NLP aids farm management by summarizing complicated data from several sources and helps with language translation and localization, making agricultural information available globally. Furthermore, NLP-powered chatbots and virtual assistants give rapid access to agricultural assistance, increasing farmersâ accessibility and convenience. Overall, NLPâs many agricultural applications contribute to more efficient, sustainable, and informed farming operations by bridging the gap between textual data and practical insights.