Staff Report
ISLAMABAD: At the 14th episode of PAS Agriculture Policy Debate webinar series themed “Weed Ecology and Management” held recently, speakers suggested the application of machine vision based intelligent sprayer for site-specific usage of agrochemicals to tackle the challenges posed by weeds to Pakistani agriculture.
Machine vision and intelligence are two key points of digital agriculture which is the trend for the future. In recent years, China’s digital agriculture has been developing rapidly and has great potential for cooperation with Pakistan.
Currently, Farmland Digital Integrated Management System implemented in east China’s Shandong Province by Shandong ARK IT Company has matured in operation and the company is carrying out digital agriculture construction in Pakistan. While providing high-quality drip irrigation and sprinkler irrigation equipment, the company can also help Pakistan’s small farmers and large-scale plantations save costs and increase efficiency by providing artificial intelligence technology.
“Current measures for notifying farmers when to plant or how to control diseases and insect pests, taken by the agricultural sector of Pakistan, tend to serve individual farmers by making phone calls and sending messages, which is low-efficient for large-scale planting base. Our system can help Pakistani friends to better and faster transform towards digital agriculture.” Qi Haitao, General Manager of Shandong ARK IT Company, spoke to Gwadar Pro.
The Farmland Digital Integrated Management System was launched in 2019, with a construction scale of about 1200 mu. It is the first rural demonstration project on digital agriculture in Zibo City, Shandong Province in 2020.
Machine vision and intelligence, which run through the Farmland Digital Integrated Management System, are mainly applied to the monitoring of plant diseases and insect pests. The system relies on the industry’s most powerful AI think tank and massive plant diseases and insect pest database to realize crop yield prediction and pest control and other issues, with artificial intelligence technologies such as computer vision, image recognition and deep learning.
