Crop Surveys

PAR conducts different Crop Surveys (through field & virtual interviews with farmers and growers) across crop cycles according to the Kharif and Rabi seasons. After analyzing the data, PAR publishes this information to facilitate crop management decisions. Yearly balance sheets are created for major commodities grown across Pakistan.

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PAR Agronomist taking a survey in a notepad, standing in a field.

Types of Crop Surveys

1: Intention (cotton)
2: Sowing (cotton, sugarcane, wheat,
rice, maize, pulses)
3: Crop Condition (cotton, sugarcane,
wheat, rice, maize, pulses)
4: Post Harvest (cotton, sugarcane,
wheat, rice, maize, pulses)
5: Consolidated Survey Report (cotton,
sugarcane, wheat, rice, maize, pulses)

Farmer staring into a rice field. There are a few trees along the horizon.

1: Intention Survey

Corn seedlings. Lines of corn sprouts in a field. Young maize/corn plants. Field post sowing season.

2: Sowing Survey

Hands holding a bunch of sugarcanes together

3: Crop Condition Survey

Sacks of rice after harvest ready for packing.

4: Post Harvest Survey

PAR Consolidated Survey Report handbook.

5: Consolidated Survey Report

Benefits

Crop Surveys allow users to track and ascertain how crops are doing at every stage of its production.

This enables users to make better procurement and consumption decisions.

PAR has an 87% accuracy rate for its crop estimates that are projected after the sowing survey is completed.

Subscribe to PAR’s Crop Surveys

PAR agronomist using PAR’s mobile app to inspect crops

Use Cases

Industrial Entities and Mills can track how crops are progressing throughout the crop cycle

International Research Houses and Government Entities can estimate production levels according to our intention and sowing surveys

Farmers and growers can trace the performance of a commodity across its crop cycle.

Young and an elderly farmers tracing the performance of a yield across its crop cycle using the insights provided by PAR.

Take decisions strategically using Pakistan's most accurate agricultural data.