Back

Growth performance and nutritional composition of Clarias gariepinus in flood-and-drain aquaponics coupled with three species of leafy vegetable.

OLANREWAJU, G. O.; AREMU, A. O.; Sarpong, D. D.; ADE-ADEMILUA, O. E.

2022-10-07 plant biology
10.1101/2022.10.06.511190 bioRxiv
Show abstract

Recirculating aquaponics integrate aquaculture and hydroponics with the aid of microorganisms to ensure a sustainable supply of fish and vegetables. In this study, we designed and constructed a flood-and-drain aquaponic system with Clarias gariepinus as the aquaculture and Celosia argentea, Corchorus olitorius, and Ocimum gratissimum as plant components. Nitrogenous waste from the aquaculture unit was circulated to the plant growth beds, which served as bio-oxidizers of toxic ammonia to nitrate and returned less toxic water back to the aquaculture unit. An evaluation of the growth parameters of C. gariepinus in aquaponics and control fish tanks revealed that aquaponics-raised C. gariepinus gained an additional 205.6% of their initial mean weight, whereas those grown in the control fish tank gained an additional 182.2% of their initial mean weight. The majority (37.5%) of aquaponics-raised C. gariepinus weighed 750 g -1 kg, whereas the highest percentage of C. gariepinus raised in the control fish tank (23.4%) weighed 500 g - 700 g. C. gariepinus raised in aquaponics had significantly higher gross feed conversion efficiency and protein efficiency ratio than those raised in the control tank. The mortality rate in the aquaponic fish tank was 0% compared to the 11.43% mortality rate in the control fish tank. There was no significant difference in the nutritional composition of C. gariepinus raised in either tank; however, the aquaponic fish tank had a higher nitrogen retention rate. This study showed that C. gariepinus raised in aquaponics had better biomass accumulation than those raised in conventional fishponds.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.