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Punjab Government Approves Artificial Intelligence Based Shrimp Farming Expansion Project Across 30000 Acres

  • August 13, 2026
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The Punjab government has granted in-principle approval for a shrimp farming project spanning 30,000 acres across the province, as pilot schemes in Muzaffargarh and Sargodha move into the deployment of advanced machinery and artificial intelligence based monitoring technology. The initiative marks one of the more significant applications of artificial intelligence in Pakistan’s agriculture sector to date, combining large scale infrastructure development with data driven farming techniques aimed at improving yield accuracy and operational efficiency.

Chief Minister Punjab Maryam Nawaz Sharif chaired a meeting where officials briefed her on the progress of ongoing shrimp aquaculture initiatives across the province. Officials informed the meeting that around 5,500 acres have already been developed into 1,000 shrimp farms, where stocking and production have already begun. A survey conducted with the assistance of foreign experts identified nearly 40,000 potential sites suitable for shrimp farming across the province, indicating considerable room for further expansion beyond the areas currently under development. In the Shah Garh and Aliwala areas of Muzaffargarh, 737 ponds are planned across 5,300 acres, supported by a hatchery with an annual production capacity of 280 million units, reflecting the scale of infrastructure being built to support the wider rollout.

The project also includes plans for two processing plants in the Aliwala area, with capacities of ten tons and five tons per hour respectively, alongside what officials describe as the country’s first dedicated shrimp diagnostic laboratory, offering chemistry, pathology and microbiology facilities to support disease monitoring and quality control. A dedicated aquaculture mall is also planned for Shah Garh, intended to give farmers access to seed, feed and rental access to modern machinery, along with a training hall designed to build technical capacity among local farmers and new entrants to the sector. In Sargodha, a separate site in the village of 58 NB will host shrimp farming across 167 ponds spanning 500 acres, with an annual production capacity of 10 million post larvae, and will similarly include a hatchery, an aquaculture mall and a processing plant, with a hybrid solar energy system proposed to power operations at the site.

Officials said trials of modern machinery, including automated harvesters and auto feeders, had been successfully conducted at the Shah Garh site, with technology based monitoring systems reportedly delivering highly accurate results during testing. The use of artificial intelligence based monitoring is intended to help farmers track water quality, growth patterns and other operational variables more precisely than would be possible through manual oversight alone, an approach that has become increasingly common in commercial aquaculture operations internationally as producers look to reduce losses and improve consistency across large scale farming sites.

Around 100 people have already been trained under the project, which involves both university graduates and local farmers, with officials framing the initiative as one intended to generate employment opportunities while also boosting the province’s shrimp export potential. The scale of the planned expansion, combined with the integration of artificial intelligence based monitoring and modern processing infrastructure, positions the project as a notable example of how emerging technologies are being applied to non traditional sectors of Pakistan’s economy, extending beyond the software and information technology services that have typically dominated the country’s technology sector narrative.

Follow the SPIN IDG WhatsApp Channel for updates across the Smart Pakistan Insights Network covering all of Pakistan’s technology ecosystem. 

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Related Topics
  • agri-tech
  • aquaculture
  • Artificial Intelligence
  • Maryam Nawaz Sharif
  • punjab
  • shrimp farming
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