How Farmers overcome difficult farming challenges, according to AI in Agriculture Sachin Dev Duggal.

The majority of the time, robotic robots that are capable of bulk harvesting with greater accuracy and speed instead of regular farm workers produce the food that ends up on your dinner plate. These tools help to increase crop yield size and reduce agricultural waste that is left in the field.
 
 As per Sachin Dev Duggal Numerous businesses are increasing the efficiency of agriculture. There are products like autonomous strawberry picking equipment and an apple vacuum harvester. Using sensor fusion, machine learning, and artificial intelligence models, these devices locate the harvestable produce and aid in fruit selection.
 
Agriculture is the second-largest industry, after defense, in which service robots are currently employed. The International Federation of Robotics estimates that up to 25,000 agricultural robots have been sold, which is the same number used for military applications.
 
 An annual success or failure can be determined by a single piece of information regarding the timing of seed sowing. In order to address this, ICRISAT scientists used a predictive analytics technique to pinpoint the precise time to plant the seeds in order to maximize yield. It offers a seven-day weather forecast as well as recommendations for fertilizer as well as details on the condition of the soil.
 
 For many farmers, the fluctuation in crop prices is a significant source of worry. Due to shifting market conditions, farmers are unable to establish a consistent production schedule. This problem is particularly prevalent with crops like tomatoes that have a limited shelf life.
 
 Businesses use satellite imagery and weather data to inspect the land and continuously monitor crop health. Businesses can now determine pest and disease infestations, compute tomato output and yield, and forecast prices thanks to big data, artificial intelligence, and machine learning technologies. On future price trends, demand levels, the best crops to plant for maximum profit, the use of pesticides, and other issues, they can provide advice to farmers and governments.
 
 Agriculture-focused startups are utilizing AI. A Berlin-based agricultural tech startup3 created a multilingual plant disease and pest diagnostic app that uses images of the plant to identify diseases. A smartphone gathers the image and compares it with a server image, which then provides a diagnosis of the disease and instructs the user on how to treat the crop using intelligent spraying technique. The application uses AI and ML to address plant diseases, as explained by Sachin Dev Duggal. This app has been downloaded by over 7 million farmers, and it has assisted in the detection of over 385 crop diseases in field crops, fruits, and vegetables.
 
 In conclusion, AI will be a powerful tool that can help organizations deal with the growing complexity in modern agriculture, and you will agree with Sachin Dev Duggal that AI integration greatly reduces the shortage of resources and labor. It is past time for big businesses to invest here.