A Biofloc-Based Aquaculture System Bio-augmented with Probiotic Bacteria Bacillus tequilensis AP BFT3 Improves Culture Environment, Production Performances, and Proteomic Changes in Penaeus vannamei

Effects of Commercial Probiotics on the Growth Performance, Intestinal Microbiota and Intestinal Histomorphology of Nile Tilapia (Oreochromis niloticus) Reared in Biofloc Technology (BFT)

Though different types of commercial probiotics are supplemented in biofloc technology (BFT), very little information is available on their effects on the farmed fish. Therefore, this study focused on evaluating the effects of three most commonly used commercial probiotics on the growth performance, intestinal histomorphology, and intestinal microbiota of Nile tilapia (Oreochromis niloticus) reared in BFT. Tilapia fry, with an average weight of 3.02 ± 0.50 g, were stocked at a density of 60 fry/0.2 m3, and cultured for 90 days. Three commercial probiotics were administered, with three replications for each: a single-genus multi-species probiotic (Bacillus spp.) (T1), a multi-genus multi-species probiotic (Bacillus sp., Lactobacillus sp., Nitrosomonas sp., Nitrobacter sp.) (T2), and a multi-species probiotic (Bacillus spp.) combined with enzymes including amylase, protease, cellulase, and xylanase (T3). The results showed significant variations in growth and feed utilization, with T3 outperforming other treatments in terms of weight gain, liver weight, and intestine weight. Adding Bacillus spp. with enzymes (T3) to water significantly increased the histomorphological parameters (villi length, villi depth, crypt depth, muscle thickness, intestinal thickness) as well as microbes (total viable count and total lactic acid bacteria) of intestine of fish compared to T1 and T2, leading to improved digestion and absorption responses. It is concluded that the supplementation of commercial probiotics has potential benefits on farmed fish species in BFT.

Swinging between the beneficial and harmful microbial community in biofloc technology: A paradox

Biofloc Technology (BFT) is proven to be the fulcrum of sustainable recirculating aquaculture system especially under zero water discharge condition. The efficiency of BFT system is reinforced by an unswerving microbial community in the system. Several researchers have made copious reports on the microorganisms in BFT and identified heterotrophic bacteria predominant in the microbial composition. A summary of these researches considers these microorganisms playing the role of chemo-photosynthetic autotrophs, organic detoxifiers, probiotic, decomposers/bioflocculants, bio-leachers and pathogens. Although these functional roles are well identified, the reports have failed to sufficiently illustrate the borderline at which these microbial communities fail to serve their beneficial roles in BFT system. This review paper firstly presents a snapshot of some indispensable water quality conditions and zootechnical variables aided by the microbial community in floc as well as the amphibolic process that synthesizes nutrient from the organic deposit in BFT. Furthermore, information on the microbial community in BFT is evaluated to have Bacillus sp., Lecane sp. and Pseudomonas sp. serving all-encompassing role in BFT while Vibrio sp. and Enterobacter sp. are pathogenic under unsuitable water quality conditions. Functional characterisation of the commonly reported microorganisms in BFT categorised 21.95 % as most critical, whose abundance indicates an efficient BFT.

Prediction of ammonia contaminants in the aquaculture ponds using soft computing coupled with wavelet analysis

Intensive aquaculture practices generate highly polluted organic effluents such as biological oxygen demand (BOD), alkalinity, total ammonia, nitrates, calcium, potassium, sodium, iron, and chlorides. In recent years, Inland aquaculture ponds in the western delta region of Andhra Pradesh have been intensively expanding and are more concerned about negative environmental impact. This paper presents the water quality analysis of aquaculture waters in 64 random locations in the western delta region of Andhra Pradesh. The average water quality index (WQI) was 126, with WQI values ranging from 21 to 456. Approximately 78% of the water samples were very poor and unsafe for drinking and domestic usage. The mean ammonia content in aquaculture water was 0.15 mg/L, and 78% of the samples were above the acceptable limit set by the World Health Organization (WHO) of 0.5 mg/L. The quantity of ammonia in the water ranged from 0.05 to 2.8 mg/L. The results show that ammonia levels exceed the permissible limits and are a significant concern in aquaculture waters due to toxicity. This paper also presents an intelligent soft computing approach to predicting ammonia levels in aquaculture ponds, using two novel approaches, such as the pelican optimization algorithm (POA) and POA coupled with discrete wavelet analysis (DWT-POA). The modified and enhanced POA with DWT can converge to higher performance when compared to standard POA, with an average percentage error of 1.964 and a coefficient of determination (R²) value of 0.822. Moreover, it was found that prediction models were reliable with good accuracy and simple to execute. Furthermore, these prediction models could help stakeholders and policymakers to make a real-time prediction of ammonia levels in intensive farming inland aquaculture ponds.