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How AI can Revolutionize The Agriculture Industry – And What It Means For Farmers



What is Artificial Intelligence?


Human intellect may be characterized in a way that makes it easy for a machine to duplicate and complete tasks of any complexity. This is the foundation of artificial intelligence. Artificial intelligence's three fundamental goals are learning, thinking, and perception.


Farmers' difficulties using conventional farming techniques


Some of the most typical problems in agriculture are listed below.


  • Climate factors, including temperature, humidity, and rainfall, all have an impact on agricultural output. Farmers find it challenging to make decisions about how and when to prepare the soil, plant seeds, and harvest due to climate change due to rising deforestation and pollution.
  • Every crop needs a certain kind of soil nutrient. As a result of the field's uneven soil fertility, different nutrients are needed at different times. Crops with insufficient nutrients may provide poor-quality products.
  • In order to produce crops, weed control is essential. If unchecked, it can increase production costs and deplete soil nutrients, Leading to nutritional deficits in the populace.
  • Labor shortage during the height of the harvest
  • Timely market intelligence is available.
  • Agri Product traceability for the certification 


Artificial intelligence applications in agriculture


In order to improve a wide range of agriculture-related tasks throughout the food supply chain, the industry is turning to Artificial Intelligence technologies. These technologies can help produce healthier crops, control pests, monitor soil and growing conditions, organize data for farmers, lessen workloads, and organize pests.


  1. Utilization of weather forecasting: 

With the aid of artificial intelligence, farmers can use weather forecasting to analyze current weather conditions and decide what crops can be cultivated and when seeds should be sowed.


  1. System for assessing the health of crops and soil:

A German digital start-up named PEAT has developed Plantix. This AI-based application can identify plant pests and illnesses and nutrient deficiencies in the soil and advise farmers on how to apply fertilizer to improve the quality of their harvest. The farmer might take pictures of their plants on a smartphone. Short videos on this application demonstrate soil restoration techniques and suggestions, and additional solutions.


While Trace Genomics, a machine learning-based business, helps farmers with soil assessments. A farmer may monitor the quality of their soil and crops using such an app, leading to healthier, more fruitful harvests. For AI projects, visit Artificial Intelligence Course in Hyderabad to get experience in real-world projects an boost your portfolio.  


  1. Predictive analytics and Precision Agriculture:

Applications of agriculture AI have created tools and apps that help farmers practice proper and regulated farming by providing appropriate guidance on water management, crop rotation, timely harvesting, crop type to be grown, optimal planting, insect attacks, and nutrition management.


  • AI-enabled technologies use data like temperature, precipitation, wind speed, and solar radiation in conjunction with machine learning algorithms and images taken by satellites and drones to predict weather conditions, analyze farms for the presence of diseases or pests and inadequate plant nutrition, and assess crops for sustainability.
  • Using basic technology like an SMS-enabled phone and the Sowing App, farmers without an internet connection can currently benefit from AI. In the meantime, farmers with Wi-Fi connectivity can continuously use AI programs to get an AI-tailored strategy for their farms.
  • AI, computer vision, and robotics are all combined by Blue River Technology to cut expenses and use fewer pesticides. Each plant is defined uniquely by computer vision, and machine learning determines the traits.
  • AI-enabled system to identify pests: AI systems employ satellite photos and historical data to determine whether any insects have landed and what kind, such as locusts, grasshoppers, or other insects. AI aids farmers in their battle against pests by sending alerts to their cell phones so that farmers can take the necessary precautions and employ pest management.


Challenges with Using AI in Agriculture

  • Indian agriculture system's complexity
  • lack of necessary datasets for AI model training
  • Cost of various AI system hardware and software
  • Handling enormous amounts of data in a secure 



To sum up, in agriculture, artificial intelligence and data science help farmers automate their agricultural processes and make adjustments to precision farming for better crop output and quality while using fewer resources. Visit Learnbay's Data science course in Hyderabad for additional details on how to learn about artificial intelligence tools and techniques used by data science professionals. 



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