This study investigates biometric relationships in Oreochromis niloticus (gray tilapia) reared in controlled pond environments at the Centro de Investigación Piscícola (CINPIS), Universidad Nacional Agraria La Molina (Perú), over a 3-year period (2021–2023). Focusing on total length ( $${L}_{t}$$ L t ), standard length ( $${L}_{s}$$ L s ), height ( $$H$$ H ), and width ( $$A$$ A ), we developed models to estimate weight ( $$W$$ W ) based on these parameters, achieving strong model performances with R² values between 0.899 and 0.994. The model using $${L}_{t}$$ L t as a predictor of $$W$$ W proved most accurate with a mean relative error (MRE) of 11.2%, while models incorporating additional dimensions ( $$H$$ H and $$A$$ A ) did not enhance predictive accuracy. Comparative analyses show our model aligns with some studies on tilapia, though variations in L-W relationships due to environmental and breeding conditions are evident. Our results affirm the utility of $${L}_{t}$$ L t in non-invasive biomass estimation for aquaculture, while highlighting the limitations of applying these models universally across different conditions and fish populations. Condition factor ( $$K$$ K ) and relative condition factor ( $${K}_{r}$$ K r ) analyses further demonstrated stable and optimal growth conditions (mean $$K$$ K ≈ 1.76; $${K}_{r}$$ K r ≈ 1.01) for tilapia under local culture practices. Accordingly, we propose the L-W relationship $$W= {0.0265L}^{2.8469}$$ W = 0.0265 L 2.8469 for estimating the weight of gray tilapia grown in ponds with groundwater. This study provides a basis for the development of biomass estimation methods based on active acoustics or stereo video.

As global aquaculture continues to expand, there is increasing interest in sustainable and non-invasive tools for monitoring fish growth. Nile tilapia (Oreochromis niloticus) is one of the most farmed species worldwide. Its biomass estimation often relies on manual sampling or stereo-camera systems limited by water turbidity. This study establishes a robust relationship between lateral target strength (TS) and the total length (TL) and weight (W) of Nile tilapia using a cost-effective 201 kHz single-beam echosounder. Measurements were conducted with free-swimming fish in a controlled pond environment (TL range, 13–44 cm). The results show a strong linear correlation between acoustic and biometric data. Specifically, the relationship for mean TS was defined as TS_mean = 20.4log(TL) − 68.8 (R² = 0.93) and TS_mean = 6.3log(W) − 55.4 (R² = 0.96), proving the system’s accuracy for biomass estimation. Furthermore, the Method of Fundamental Solutions (MFS) was employed for numerical validation based on X-ray morphometry of the swim bladder. Very good agreement was observed between experimental data and numerical simulations, reinforcing the validity of the acoustic models despite the inherent complexity of biological targets. These findings demonstrate that calibrated single-beam acoustic systems provide a viable, non-intrusive tool for real-time monitoring in aquaculture ponds.

As global aquaculture continues to expand there is an increasing interest for sustainable and non-invasive tools to monitor fish growth. Nile tilapia (Oreochromis niloticus) is one of the most farmed species worldwide. Its biomass estimation often relies on manual sampling or stereo-cameras systems limited by water turbidity. This study establishes a robust relationship between lateral Target Strength (TS) and the total length (TL) and weight (W) of Nile tilapia using a cost-effective 201 kHz single-beam echosounder. Measurements were conducted with free-swimming fish in a controlled pond environment (TL range 13–44 cm). The results show a strong linear correlation between acoustic and biometric data. Specifically, the relationship for mean TS was defined as TS_mean = 20.1log(TL) − 66.7 (R2=0.91) and TS_mean = 6.3log(W) − 55.4 (R2=0.96), proving the system’s accuracy for biomass estimation. Furthermore, the Method of Fundamental Solutions (MFS) was employed for numerical validation based on X-ray morphometry of the swim bladder. A very good agreement was observed between experimental data and numerical simulations, reinforcing the validity of the acoustic models despite the inherent complexity of biological targets. These findings demonstrate that calibrated single-beam acoustic systems provide a viable, non-intrusive tool for real-time monitoring in aquaculture ponds.