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Shrimp farming is a multibillion-dollar industry, with production expected to reach 6 million metric tons in 2023. The industry also faces numerous challenges, such as a rise in the cost of aquaculture input (feed, energy, transportation), volatile demand that impacts the farmgate price, diseases and unstable climatic conditions that affect survival and growth rates. An additional challenge, especially in Asia, is the fragmented status of the farming industry, with numerous stakeholders involved in the postlarvae production, the supply of animal health products and feed, and the farming and harvesting before delivery to the fresh market or the processors.
In order to improve production efficiency, farmers first looked at ways to optimise feeding, i.e., their highest cost. It started with automated feeders to deliver feed over longer periods of time and reduce feed wastage while controlling labour costs. However, feeding must be adapted to the shrimp’s weight, health status, and rearing conditions. This requires farmers to regularly check feed intake (using a feeding tray), measure water parameters (temperature, dissolved oxygen, pH, ammonia, nitrite, minerals, etc.), and assess the shrimp size and health status. This is where new technologies started to play key roles: • Measurement of physicochemical parameters using IoT probes allows farmers to have an accurate and real-time overview of the rearing condition in their ponds, implementing changes and feeding management. Issues with the probes’ cost and the need for self-cleaning and calibration (shrimp pond condition favour fouling) delayed their rollout. • Measurement of shrimp size or weight using image analysis. Although it still requires a representative sample to be collected, it facilitates the calculation of the shrimp growth rate. Based on this calculation, water parameters and historical data, shrimp health is estimated and the feeding protocols and pond management protocols are revised. • Feed management can also be adapted based on the real-time measurement of feed intake. Without information on the shrimp’s health or size, the feeding regime would be revised based on the monitored feeding needs. The feeding protocol can be controlled either by farmers using the report for the decision or an algorithm.In order to improve production efficiency, farmers first looked at ways to optimize feeding, i.e. their largest cost
