Cotton Report Pest Survey Punjab Dataset
Description
The following data was gathered and arranged from Punjab Pest Warning and Quality Control of Pesticides Department portal It is based on the “Cotton Crop Summary” reports published weekly by the Department of Agriculture, Punjab. These reports provide systematic field observations from multiple districts, capturing how pest populations fluctuate throughout each cotton-growing season. Overview This dataset represents the weekly occurrences of major cotton pests and their respective Economic Threshold Levels (ETL). The Economic Threshold Level (ETL) is the pest density level at which control actions become economically justified — meaning the potential crop loss equals or exceeds the cost of pest control. When pest counts exceed the ETL, intervention (chemical or biological) is recommended to avoid yield loss. When pest counts remain below the ETL, no control measures are typically required, reducing both input costs and environmental impact. Dataset Purpose By consolidating weekly field observations, this dataset allows detailed analysis of: Temporal trends in pest populations across growing weeks. District-wise variations in pest presence and severity. Patterns of ETL exceedance, indicating potential outbreak conditions. Predictive modeling opportunities for pest behavior and early-warning systems. Decision support in Integrated Pest Management (IPM). Potential Uses Time-series forecasting of pest occurrences. ETL-based risk modeling for precision agriculture. Visualization of seasonal pest dynamics across regions. Evaluation of pest control effectiveness and intervention timing.
Files
Steps to reproduce
Source Website Data collected from the Government of Punjab’s Pest Warning & Quality Control of Pesticides portal: https://pestwarning.agripunjab.gov.pk/reports Report Selection Chose the Cotton Summary Report for each available week. Data Collection Downloaded all weekly reports (PDF format) manually from the website. Table Extraction Used Tabula software to extract tabular data from the PDFs. Data Aggregation Combined extracted tables into a single file without further cleaning or standardization. Current Status The dataset is in its raw extracted form. Minor standardization (e.g., consistent headers, numeric formatting) may be required for analysis.
Institutions
- DHA Suffa University