Umitron releases AI tool for shrimp farmers
March 31, 2022 By Nestor Arellano
Umitron PTE LTD, a Singapore-based technology company has launched an artificial intelligence (AI) enabled analytics tool that can help shrimp farmers track multiple biological conditions and other factors in real time.
The company said its Umitron Eagle software shrimp producers can now optimize their feeding protocols easily and automatically using real-time analytics.
Despite the rapid growth of the shrimp production industry, producers are still plagued by many issues ranging from disease outbreaks, general health management and poor environmental management protocols that can lead to mass mortality events and disrupt the supply chain, according to Umitron.
“While solutions exist to remotely control feeding (via timer-based automatic feeders) and monitor environmental parameters using sensors, they are currently unable to analyse the real-time conditions of the shrimp. This is further exacerbated by the fact that most farming environments have poor visibility (i.e. high turbidity) and that digital transformations have been slower and more limited for shrimp than their fish counterparts,” a press release from the company said.
The tool developed by the company also assess shrimp production conditions in real-time using customized AI algorithms. These include but are not limited to real-time appetite analysis, health and growth conditions, and biomass. While important, these metrics are not always actively charted and monitored due to a lack of available resources and solutions on the market, be it manpower or automation-wise.
According Unitrom, their solution can help shrimp producers achieve:
- improvements in FCR, growth and harvest amounts for each crop
- improved biosecurity measures and work protocols
- a reduction in feed wastage which may contribute to undesirable environmental conditions such as poor water quality and highly-turbid conditions and require frequent water changes
- better long-term farming management protocols and optimized operations using the accumulated production data
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