Abstract
Fish farmers are likely to cultivate poor quality fish to accommodate the rising demands for food due to the ever-increasing population. Fish growth monitoring greatly helps on producing higher quality fish products which leads to a better impact in the aquatic animal food production industry. However, monitoring through manual weighing and measuring stresses them that affects their health resulting to poorer quality or even fish kills. This paper presents a low-cost monitoring and Hough gradient method-based weight prediction system for Nile Tilapia (Oreochromis niloticus) using Raspberry Pi microcontroller and two low-cost USB cameras. This study aims to improve fish growth rate through monitoring the growth of the fishes with image processing eliminating the traditional way of obtaining fish measurements. By using paired t-test, the acquired values imply that the weight algorithm used to measure the weight of the fishes is accurate and acceptable to use. Growth performance of 10 Nile Tilapia was obtained in two intensive aquaculture setups – one for automated fish weighing through image processing and predictive analysis and the other setup for manual weighing. In response to weight prediction application, the growth of the fishes increased by 47.88%.
Highlights
Due to the world’s ever-growing population, humans need alternative food sources
Growth performance of 10 Nile Tilapia was obtained in two intensive aquaculture setups – one for automated fish weighing through image processing and predictive analysis and the other setup for manual weighing
The authors developed an automated aquaculture setup with weight prediction technology that makes use of image processing techniques and predictive analysis which yields to a higher growth and survival rate for Nile Tilapia
Summary
Due to the world’s ever-growing population, humans need alternative food sources. Aquaculture is an essential contributor when it comes to food safety and daily living. It is the fastest growing sector in the food industry worldwide having its economic significance greatly increasing at the same time [1]. Aquaculture is having difficulties in terms of production resulting on problems settling in the market [2]. In order to accommodate the growing demands for food, fish farmers tend to harvest poor quality fish. Monitoring the growth of the fish helps to a great extent on producing a higher quality product
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