MULTAN: Innovative tools in Artificial Intelligence (AI) are proving to be a huge success in smart agriculture, leading to increased productivity. One example of AI-driven automation of pest detection is how cotton growers are using AI pest detection and pheromone traps to control bollworms.
The system helps farmers determine when and how much pesticide is needed to avoid overspraying and increase yields. The potential of data science, drone technology and other smart agriculture innovations also makes AI a great tool to increase productivity while minimizing costs. Drone technology is currently being used for spraying in villages across Punjab, helping to increase productivity, reduce production costs and improve the health of farmers. The South Punjab Agriculture Department (SPAD) is also working hard to develop new AI tools to enhance pest management and increase productivity.
As part of the series on promoting AI tools in smart agriculture in South Punjab, SPAD has launched the ‘Virtual Cotton Pest Management Hub.’ Under the leadership of Agriculture Secretary, South Punjab, Saqib Ali Atil, an online Google workbook called ‘Virtual Cotton Pest Management Hub’ has been developed and launched.
This workbook allows for online tracking of cotton pest scouting, management, and other related activities. The workbook consists of three separate sheets, each named and color-coded according to the type of data received from the Agricultural Extension Office and the Pest Alert Monitoring Team. The Google Sheet, developed by SPAD, is intended for real-time monitoring of cotton data. Only authorized personnel can enter data into this Google Sheet.
The objective of developing this Google Sheet is to monitor cotton data in real time. Atil further explained that all other field activities like nutrition and pest surveys, which will be recorded in a workbook, will also be monitored. He added that 11 entomologists from various departments of South Punjab Agriculture Ministry have been assigned the task of monitoring cotton pests and cross-verifying the data recorded by the Pest Alert and Extension Department. Each monitor will be responsible for monitoring at least 70 hotspots per month. The observations made by the monitors will be recorded in a third sheet of the Virtual Cotton Pest Management Hub during their visits.
Hotspots and treatment status are recorded in a Google spreadsheet by agricultural extension and pest warning staff who are also responsible for verifying recommendations. They can also check the cotton crop status in designated areas and monitor pesticide use, nozzles, types of machinery used for spraying, and spraying methods.
Moreover, you can write your comments in the respective Google Spreadsheet. He stressed that the aim of developing this online mechanism is to achieve better production by using modern technology to control cotton pests in a timely manner. Agricultural scientists have also set up an AI research institute in Pakistan in collaboration with China to promote AI smart agriculture and boost agriculture in the province. The institute aims to promote cutting-edge agricultural practices to increase field productivity. AI can assist breeders in decision-making by providing data-driven insights. For example, it can recommend which plants should be bred to achieve desired traits or identify the best environmental conditions for a particular variety. An important point to mention here is that AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence. These tasks include learning from experience, problem solving, pattern recognition, natural language understanding, and decision-making. Machine learning (ML) develops algorithms that learn to perform specific tasks based on a given set of data. It is a subfield of artificial intelligence that is widely used in research and industry. Supervised learning tasks aim to predict an output (a discrete label in the case of classification or a numeric value in the case of regression) for a given object based on a set of input features that describe the object. Supervised methods use labeled input data, whereas unsupervised methods do not use labels but identify groups or trends in the data observed by agricultural scientists. Plant breeding is the science and art of selecting and crossing plants with desirable traits to develop plant varieties better suited for a particular purpose, such as improving crop yield, disease resistance, tolerance to environmental stresses, and overall plant quality. AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, they added.
