Length-weight relationship and condition factor of Nile tilapia (<i>Oreochromis niloticus</i>) fed diets supplemented with guava and star gooseberry leaf extract

Manoj Tukaram Kamble; Krishna Rugmini Salin; Balasaheb Ramdas Chavan; Seema Vijay Medhe; Kim D. Thompson; Nopadon Pirarat

doi:10.12688/f1000research.145369.2

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Research Article

Revised

Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract

[version 2; peer review: 3 approved]

Manoj Tukaram Kamble^1,2, Krishna Rugmini Salin¹, Balasaheb Ramdas Chavan³, Seema Vijay Medhe², Kim D. Thompson⁴, Nopadon Pirarat ²

Manoj Tukaram Kamble^1,2, Krishna Rugmini Salin¹, [...] Balasaheb Ramdas Chavan³, Seema Vijay Medhe², Kim D. Thompson⁴, Nopadon Pirarat ²

PUBLISHED 23 Oct 2024

Author details Author details

¹ Aquaculture and Aquatic Resources Management (AARM), Department of Food, Agriculture and Bioresources, School of Environment, Resources, and Development, Asian Institute of Technology, Khlong Nueng, Pathum Thani, 12120, Thailand
² Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand
³ Department of Aquaculture, College of Fisheries, Ratnagiri, Maharashtra, 415629, India
⁴ Moredun Research Institute, Pentlands Science Park, Penicuik, Scotland, EH26 0PZ, UK

Manoj Tukaram Kamble
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Krishna Rugmini Salin
Roles: Conceptualization, Data Curation, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Review & Editing

Balasaheb Ramdas Chavan
Roles: Conceptualization, Funding Acquisition, Project Administration, Resources, Software, Writing – Review & Editing

Seema Vijay Medhe
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Software, Writing – Original Draft Preparation, Writing – Review & Editing

Kim D. Thompson
Roles: Conceptualization, Formal Analysis, Supervision, Visualization, Writing – Review & Editing

Nopadon Pirarat
Roles: Conceptualization, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Agriculture, Food and Nutrition gateway.

Abstract

Background

Nile tilapia (Oreochromis niloticus) is predominant cultured species in aquaculture. However, there is a scarcity of literature regarding relationship between guava and star gooseberry leaf extract and the condition factor. Thus, the present study aims to investigate the effect of guava and star gooseberry leaf extract-supplemented diets on the specific growth rate, length-weight relationship, and condition factor of Nile tilapia.

Methods

Six hundred and thirty Nile tilapia (8.7±0.4 g) were randomly distributed among twenty-one tanks (30 fish per tank) within a recirculation system. Over a 60-day period, the fish were fed diets supplemented with 5g/Kg and 10g/Kg of guava leaf extract (GLE-5, GLE-10), star gooseberry leaf extract (SGLE-5, SGLE-10), and a mixture of both (MxLE-5, MXLE-10). Subsequently, specific growth rate, length-weight relationship, and condition factor were determined.

Results

After 60 days, the specific growth rate was significantly higher in all the GLE, SGLE, and MxLE groups compared to the control group. The final lengths and weights differed significantly both in the control group and all the GLE, SGLE, and MxLE groups. The analysis of the regression equation indicated a positive correlation (r = 0.970, 0.977, 0.976, 0.974, 0.974, 0.974, and 0.969) between the length and weight of Nile tilapia in the control group and in all the GLE, SGLE, and MxLE groups. The regression exponent “b” values in all the GLE, SGLE, and MxLE groups were >3, indicating a positive allometric growth pattern in Nile tilapia compared to the control (b=2.866), which exhibited a negative allometry. The final condition factor values did not differ significantly in either the control group or any of the plant extract groups.

Conclusions

Nile tilapia exhibited positive allometric growth patterns and maintained good health when fed with GLE, SGLE, and MxLE groups. Therefore, these plant extracts demonstrate suitability for commercial Nile tilapia production.

Keywords

Nile tilapia, length-weight relationship, condition factor, specific growth rate, guava, star gooseberry

Corresponding author: Nopadon Pirarat

Competing interests: No competing interests were disclosed.

Grant information: This research was funded by the Second Century Fund (C2F) Postdoctoral Fellowship, Chulalongkorn University, Bangkok, Thailand and the Social Justice and Special Assistance Department, Government of Maharashtra, India.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2024 Kamble MT et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Kamble MT, Salin KR, Chavan BR et al. Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract [version 2; peer review: 3 approved]. F1000Research 2024, 13:540 (https://doi.org/10.12688/f1000research.145369.2) First published: 28 May 2024, 13:540 (https://doi.org/10.12688/f1000research.145369.1) Latest published: 23 Oct 2024, 13:540 (https://doi.org/10.12688/f1000research.145369.2)

Revised Amendments from Version 1

We sincerely appreciate the reviewers' insightful comments, which have greatly contributed to the improvement of the second version of our manuscript. Based on their suggestions, we have made the following revisions:
First, we have included a Pearson correlation matrix to thoroughly analyze the relationship between water quality parameters (e.g., temperature, dissolved oxygen, ammonia) and fish biometric parameters (length and weight). The results of this analysis are now presented in a detailed tabular format.
Additionally, we have expanded the discussion section to provide a more comprehensive interpretation of the correlation matrix, emphasizing the potential effects of water quality on fish growth and overall health. This enhanced analysis offers deeper insights into the interrelationships between environmental conditions and fish biometrics, enriching the manuscript and aligning it with the reviewers' recommendations. We believe these revisions significantly strengthen the scientific rigor and clarity of our study.

See the authors' detailed response to the review by Agumassie Tesfahun
See the authors' detailed response to the review by Dr.Sheikh Muhammad Azam

Introduction

Nile tilapia (Oreochromis niloticus) is recognized as an important species in aquaculture within tropical and subtropical regions, owing to its faster growth, heightened productivity, and notable resistance to diseases.¹^–⁴ In 2020, the global production of Nile tilapia nearly reached 4.9 million metric tons (Mmt), and the continuous growth is attributed to the robust worldwide demand.⁵ Furthermore, technological advancements with high stocking densities play a significant role in the occurrence of disease outbreaks, resulting in substantial economic losses and impeding the sustainable progression of tilapia culture globally.⁶

The incorporation of plant extracts into aquafeed is significant in finfish aquaculture⁷ because the indiscriminate use of antibiotics has led to the development of drug-resistant bacteria.⁸^,⁹ Plant extracts can serve as cost-effective and environmentally sustainable prophylactic or antimicrobial agents. Guava (Psidium guajava) leaf (GLE) are rich in various phenolic and flavonoid compounds¹⁰ and possess antimicrobial,¹¹ antiviral,¹² and antioxidant¹³ activities. GLE have been employed as supplements in fish feed to boost the growth, immune response, and protection against diseases for various fish species.¹⁴^–²⁰ Star gooseberry (Phyllanthus acidus) leaf (SGLE) contain flavonoids, kaempferol, hypogallic acid, caffeic acid, and phenolic compounds.²¹^,²² SGLE exhibited antioxidant, anti-inflammatory and antimicrobial activities.²³^,²⁴ It is also employed as a dietary supplement to augment the immune response of fish⁹^,²⁵ and chickens.²⁶

The length-weight relationship (LWR) plays an essential role in estimating the biomass of diverse fish populations.²⁷ Additionally, LWR is valuable for assessing fish condition and growth patterns.²⁸ The condition factor (CF) contributes to comprehending the development and adaptability of fish.²⁹ A heightened condition factor indicates the robust health and positive growth of the fish.³⁰ Hence, the condition factor can be employed to assess the feeding activity of a species, indicating its effective utilization of available feeding sources.²⁷ Previous studies have investigated the length-weight relationship and feeding habits of tilapia.²⁷^,³⁰^–³³ Unfortunately, there is a scarcity of literature regarding relationship between guava and star gooseberry leaf extract and the condition factor. Thus, the present study aims to investigate the effect of guava and star gooseberry leaf extract-supplemented diets on the specific growth rate, length-weight relationship, and condition factor of Nile tilapia.

Methods

Chemicals

The analytical grade chemicals utilized for the determination of Ammonia, Nitrite, and Nitrate from the experimental tanks included Sodium Hypochlorite 10% (Commercial, U&V Holding (Thailand) CO., LTD), Hydrochloric acid, 37% (Fisher Scientific UK), Sodium hydroxide (Pine Chemical, Finland), Phenol, 99+% (Fisher Scientific UK), Sulfanilamide (Acros Organics Bvba, Belgium), N-(1-Naphthyl) ethylenediamine dihydrochloride (Alfa Aesar, USA), Cadmium granular (ALDRICH Chemical, USA), Manganese (II) Sulphate H2O, Ammonium Chloride, Sodium Nitrite, Copper (II) sulfate, and Ethylenediamine Tetra Acetic acid (Daejung Chemicals and Metals, South Korea), as well as Sodium Tetraborate and Potassium Nitrate (KEMAUS, Australia) (Underlying Data).³⁴

Preparation of guava and star gooseberry leaf aqueous extracts

The guava (P. guajava) and star gooseberry (P. acidus) leaf powder were received from All-Season Herbs Pvt. Ltd., Bangalore, India and the aqueous extract was prepared.³⁵ Briefly, distilled water (100 mL) was mixed with leaf powder (10 g) and homogenized using an orbital shaker (Hsiangtai D500) at 100 rpm for 20 h at room temperature (RT). The resultant mixture underwent centrifugation at 8,000 rpm for 15 min at RT. A rotavapor (BÜCHI R-200/205) at 35 °C used to evaporate the supernatant and continue drying for 48 h in a hot air oven at 50 °C. The dried samples obtained were placed in bottles and kept refrigerated at 4°C until further use.

Ethical statement

This study was conducted under the project entitled ‘Application of Phytobiotic Supplementation to Improve Disease Resistance of Nile Tilapia (Oreochromis niloticus)’ and funded by the Social Justice and Special Assistance Department, Government of Maharashtra, India, and Second Century Fund (C2F) Postdoctoral Fellowship, Chulalongkorn University, Bangkok, Thailand. This study was carried out in strict accordance with the recommendations of the Asian Institute of Technology (AIT), Thailand, and the protocol was approved by the Local Ethical Committee for Experiments on Animals of the AIT, Thailand (Project Number: AIT-AQ-18-01, May 2018–April 2019; April 29, 2018). Additionally, according to Thailand Legislation, the Nile tilapia were not categorized as a protected species. The research was carried out at the Laboratory of the Aquaculture and Aquatic Resources Management (AARM, Asian Institute of Technology (AIT), Thailand, over 60 days from February to March, 2019. This study is reported in line with the ARRIVE guidelines. A total of 630 fish were used in the experiment, with 90 fish allocated to each treatment. Each treatment comprised 30 fish per replicate, totaling three replicates. Prior to sampling, the fish underwent a 12-hour fasting period to empty their digestive tracts. In this study, to reduce stress on the experimental animals, the animals housed in the containers were gently anesthetized using 1 mL of clove oil per 10 L of water for a period of 2–3 min, after which their weights were measured. Following this, the fish were returned to their designated glass tanks according to their treatment and replication groups.

Fish

Nile tilapia monosex fingerlings (8.7 ± 0.4 g and 8.0 ± 1.0 cm) were obtained from a GMP Certified fish farm, Ayutthaya Province, Thailand. The research was conducted at the laboratory of Aquaculture and Aquatic Resources Management (AARM), Asian Institute of Technology (AIT), Thailand. For a period of 15 days, the fish were acclimatized in three fiberglass tanks (500 L) before the commencement of the experiment. Fish were fed pelleted feed twice daily at 4% of their body weight. Following the acclimatization period, the fish were randomly distributed among twenty-one 150-L glass tanks (30 fish per tank), all integrated into a recirculation system.

Preparation of experimental diets supplemented with guava and star gooseberry leaf aqueous extracts

Plant extracts (10 mg), dissolved in 1 mL distilled water, were mixed with commercial feed ((Charoen Pokphand (CP)-7710), and spaghetti-like strands were prepared using a mincer (MITSUYAMA YC80B-4). Pellets approximately 5 mm in length were formed and dried for 24 h at 50 °C in a hot air oven. The dried pellets were then stored at 4 °C until the end of the experiment. The proximate composition of the commercial diet, including moisture, ash, crude lipid, and crude protein, was 7.6%, 8.2%, 6.5%, and 30.5%, respectively.

Experimental design

In this study, a completely randomized design was employed, comprising seven experimental treatments: 5g/kg and 10g/kg of guava leaf extract (GLE-5, GLE-10), star gooseberry leaf extract (SGLE-5, SGLE-10), and a mixture of both (MxLE-5, MXLE-10). The mixed diets (MxLE) were prepared with an equal proportion (1:1) of GLE and SGLE extracts. The control group, on the other hand, was fed a diet without plant extract supplementation. Fish were fed twice daily at 4% of their body weight. Prior to sampling, the fish underwent a 12-hour fasting period to empty their digestive tracts. In this study, to reduce stress on the experimental animals, the animals housed in the containers were gently anesthetized using 1 mL of clove oil per 10 L of water for a period of 2–3 min, after which their weights were measured. Following this, the fish were returned to their designated glass tanks according to their treatment and replication groups. The specific growth rate, length-weight relationship, and condition factor were determined after 60 days of feeding.

Water quality parameters

During the experiment, a Eutech Cyberscan PC300 multi-parameter apparatus was employed to measure daily water quality parameters, including temperature, pH, and dissolved oxygen (DO). The weekly concentrations of ammonia-nitrogen (NH₃-N) were assessed using Phenate or indophenol method,³⁶ nitrite-nitrogen (NO₂-N) concentrations were quantified through direct spectrophotometric assay,³⁶ and nitrate-nitrogen (NO₃-N) levels were determined employing cadmium reduction method.³⁶

Specific growth rate of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

The specific growth rate³⁷ was evaluated after 60 days of feeding trials using the following equation

specific growth rate (SGR, % / day) = (100 \times (ln Final weight (g) - ln Initial weight (g)) / (experimental days (T))

Length-weight relationship (LWR) of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

Length-weight relationship (LWR)³⁸ between the total length and body weight was estimated using the following formula

W = {aL}^{b}

Where W is body weight of fish (g), L is the total length (cm), a is the exponent denotes the rate of weight change with length (constant), and b is the slope representing the weight of one unit length. These values are estimated through the linear regression equation, which is transformed by applying the natural logarithm (Log) to both sides.

Log W = Log a + b . Log L

Where b = 3, growth pattern is isometric. However, when b is greater or less than 3, an allometric pattern emerges. This allometric pattern can be positive, indicating increase in length relative to body thickness, or negative, signifying an increase in length relative to body thinness.²⁸

Relative condition factor (K_n) of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

The health condition of the tilapia was assessed by evaluating relative condition factor (K_n) in all the treatments.

K_{n} = W_{o} / W_{c}

where W_o = observed weight, and W_c = calculated weight.³⁹ When K_n is greater than 1, it indicates favorable growth conditions for the fish. Conversely, when K_n is less than 1, it suggests that the organism is in poorer growth condition compared to an average individual of the same length.

Data analysis

The results were presented as means ± SE, and statistical analysis was conducted using IBM SPSS Statistics software (SPSS, Inc., Version 29). The homogeneity of data was determined using Levine’s test. The impact of plant extract treatments on specific growth rate was assessed through one-way analysis of variance (ANOVA), followed by Tukey post-hoc tests for multiple comparisons. An independent t-test was used to determine the significant difference between the initial and final length and weight of Nile tilapia with plant extract treatments. Linear regression analysis was employed to evaluate the length-weight relationship. The Pearson correlation matrix was used to analyze relationship between water quality and fish biometric parameters. A significance level of p < 0.05 was considered for statistical significance.

Results

Water quality parameters

Water quality parameters such as Temperature, pH, DO, NH₃N, NO₂N, and NO₃N, did not show significant difference among the plant extract treatments and control during the experiment (Table 1). In all treatments, the average values for temperature, pH, DO, NH₃N, NO₂N, and NO₃N were 29.6 °C, 7.47, 5.49 mg/L, 0.15 mg/L, 0.13 mg/L, and 0.23 mg/L, respectively. Raw data are available as underlying data (Tables 1-6).³⁴

Table 1. Water quality parameters of Nile tilapia fed diets supplemented with plant extracts.

	Control	GLE-5	GLE-10	SGLE-5	SGLE-10	MxLE-5	MxLE-10
Temp (°C)	30.6±0.15	30.7±0.16	30.8±0.16	30.7±0.17	30.8±0.16	30.8±0.16	30.5±0.16
pH	7.39±0.02	7.16±0.02	7.18±0.01	7.31±0.03	7.21±0.02	7.26±0.02	7.27±0.02
DO (mg/L)	4.69±0.05	4.15±0.05	4.01±0.09	4.57±0.15	4.45±0.06	4.06±0.06	4.54±0.05
NH₃N (mg/L)	0.13±0.01	0.18±0.01	0.18±0.01	0.14±0.01	0.17±0.01	0.21±0.01	0.16±0.01
NO₂N (mg/L)	0.07±0.01	0.09±0.01	0.11±0.01	0.13±0.01	0.12±0.01	0.08±0.01	0.09±0.01
NO₃N (mg/L)	0.27±0.01	0.24±0.01	0.23±0.01	0.25±0.01	0.26±0.01	0.24±0.01	0.25±0.01

Specific growth rate

The survival rate was higher than 95% in all treatments. The specific growth rate was significantly higher in all plant extract treatments compared to the control group. GLE-10 exhibited a higher SGR, while MxLE-10 showed a lower SGR in the plant extract treatments (Figure 1). Raw data are available as underlying data (Table 7).³⁴

Figure 1. Specific growth rate of Nile tilapia fed diets supplemented with plant extracts.

Results with the means of three replicates ± SE; Different superscripts in the bar indicate significant difference (p < 0.05).

Length-weight relationship and growth pattern

The lengths were significantly different at the end of the experimental period in the control (t(148)=-30.327, p=0.01), GLE-5 (t(148)=-37.193, p=0.01), GLE-10 (t(148)=-32.297, p=0.01), SGLE-5 (t(148)=-37.552, p=0.01), SGLE-10 (t(148)=-28.491, p=0.01), MxLE-5 (t(148)=-31.824, p=0.01), and MxLE-10 (t(148)=-38.139, p=0.01) groups (Table 2). Additionally, the weights were significantly different at the end of the experimental period in the control (t(148)=-31.206, p=0.01), GLE-5 (t(148)=-38.611, p=0.01), GLE-10 (t(148)=-32.694, p=0.01), SGLE-5 (t(148)=-37.627, p=0.01), SGLE-10 (t(148)=-30.032, p=0.01), MxLE-5 (t(148)=-32.800, p=0.01), and MxLE-10 (t(148)=-38.197, p=0.01) groups.

Table 2. Length-weight relationship, growth pattern, and condition factor of Nile tilapia fed diets supplemented with plant extracts.

	Control	GLE-5	GLE-10	SGLE-5	SGLE-10	MxLE-5	MxLE-10
N	75	75	75	75	75	75	75
L_{Min-Max (}cm)	11.6-18.5	11.2-19.8	12.0-20.1	12.0-19.6	11.9-20.5	12.5-19.5	12.4-19.1
W_min-max (g)	25.0-106.0	24.0-145.0	28.0-157.0	29.6-132.0	28.8-156.0	30.0-134.0	31.0-128.0
a	-1.612	-1.797	-1.880	-1.853	-1.758	-1.917	-1.815
b	2.866	3.023	3.101	3.067	3.003	3.135	3.036
SE (b)	0.085	0.077	0.081	0.083	0.082	0.085	0.091
CI (b)	2.698-3.035	2.869-3.177	2.941-3.262	2.901-3.232	2.839-3.167	2.965-3.304	2.855-3.218
r	0.970	0.977	0.976	0.974	0.974	0.974	0.969
R²	0.940	0.955	0.953	0.949	0.948	0.949	0.939
p	0.001	0.001	0.001	0.001	0.001	0.001	0.001
t-test sig	0.001	0.001	0.001	0.001	0.001	0.001	0.001
Growth behavior	Negative allometry	Positive allometry	Positive allometry	Positive allometry	Positive allometry	Positive allometry	Positive allometry
K_n	1.004	1.002	1.003	1.003	1.004	1.003	1.003
Min-Max	0.865-1.177	0.886-1.178	0.824-1.097	0.840-1.282	0.817-1.162	0.857-1.136	0.822-1.162
SE	0.010	0.008	0.008	0.010	0.011	0.009	0.009

The analysis of the regression equation indicated a positive correlation (r = 0.970, 0.977, 0.976, 0.974, 0.974, 0.974, and 0.969) between the length and weight of Nile tilapia fed control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, MxLE-10 diets, respectively.

The regression exponent of “b” values in GLE-5 (b=3.023, t(73)=39.216, p=0.01), GLE-10 (b=3.101, t(73)=38.515, p=0.01), SGLE-5 (b=3.067, t(73)=36.981, p=0.01), SGLE-10 (b=3.003, t(73)=36.451, p=0.01), MxLE-5 (b=3.135, t(73)=36.816, p=0.01), and MxLE-10 (b=3.036, t(73)=33.390, p=0.01) were >3, indicating a positive allometric growth pattern in Nile tilapia compared to the control (b=2.866, t(73)=33.881, p=0.01), which exhibited negative allometry. The length-weight correlation regression graphs for the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, MxLE-10 diets are depicted in Figure 2. Raw data are available as underlying data (Tables 8-14).³⁴

Figure 2. Final logarithmic length-weight relationship with regression equation for Nile tilapia fed plant extracts.

Condition factor

The condition factors were not significantly different at the end of the experimental period in the control (t(148)=-0.599, p=0.275), GLE-5 (t(148)=-0.199, p=0.421), GLE-10 (t(148)=0.299, p=0.383), SGLE-5 (t(148)=0.818, p=0.207), SGLE-10 (t(148)=0.173, p=0.431), MxLE-5 (t(148)=0.371, p=0.356), and MxLE-10 (t(148)=-0.100, p=0.460) groups (Table 2). Additionally, the minimum and the maximum values of condition factor for control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups were 0.865-1.177, 0.886-1.178, 0.824-1.097, 0.840-1.282, 0.817-1.162, 0.857-1.136, and 0.822-1.162, respectively. Raw data are available as underlying data (Tables 8-14).³⁴

Correlation matrix for water quality and fish biometric parameters

The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Table 3. Correlation matrix between water quality and fish biometric parameters.

Parameter	Length	Weight	Temperature	DO	pH	NH₃-N	NO₂-N	NO₃-N
Length	1	0.969^**	0.364	-0.199	-0.312	0.403	0.489^*	-0.323
Weight	-	1	0.339	-0.215	-0.354	0.470^*	0.489^*	-0.258
Temperature	-	-	1	-0.684^**	-0.563^**	-0.060	0.426	-0.322
DO	-	-	-	1	0.887^**	-0.185	-0.269	0.331
pH	-	-	-	-	1	-0.328	-0.385	0.326
NH₃-N	-	-	-	-	-	1	-0.189	0.071
NO₂-N	-	-	-	-	-	-	1	-0.207
NO₃-N	-	-	-	-	-	-	-	1

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.

A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion

Aquafeed supplementation with herbal or plant extracts has proven to be an effective means of enhancing the growth performance, feed utilization, and immune response in farmed fish species.⁴⁰^,⁴¹ The supplementation of natural bioactive rich-plant extracts may boost natural immunity and improve disease resistance,⁴⁰ resulting in higher production and profitability in the aqua industry. The length-weight relationship is used to predict the weight of fish in proportion to their length over a certain period.³⁸ Therefore, the present study investigated the effects of plant extract-supplemented diets on the length-weight relationship and condition factor of Nile tilapia.

The water quality parameters in all treatments were within the acceptable range, consistent with the findings of previous studies on spotted snakehead (Channa punctata) under various feeding regimes involving agro-industrial by-products,⁴² and on silver barb (Barbonymus gonionotus) fingerlings fed with dietary blanched moringa leaf meal.⁴³ The specific growth rate showed a significant increase in all plant extract treatments. Similarly, the specific growth rate of spotted snakehead (C. punctata) and silver barb (B. gonionotus) was considerably improved under various feeding regimes involving agro-industrial by-products⁴² and dietary blanched moringa leaf meal.⁴³

Aqua farmers and consumers prefer fish with isometric growth or body structure.²⁷^,⁴⁴ Furthermore, the length-weight relationship provides insights into the growth and health of a fish species.⁴⁵^,⁴⁶ In the present study, plant extract-supplemented diets observed significant correlation between length and weight of Nile tilapia. Our results are corroborated with previous study involving different maltose levels fed to Nile tilapia (O. niloticus).²⁷ Importantly, Nile tilapia fed diets supplemented with GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups exhibited positive allometric growth pattern compared to the control. Similarly, silver barb (B. gonionotus) and zebrafish (Danio rerio) fed with dietary blanched moringa leaf meal⁴³ and plant-protein based diets⁴⁷ found positive allometric growth. On the contrary, gold fish (Carassius auratus) fed with different concentrations of carrot⁴⁸ and gurami sago (Osphronemus goramy) stocked in concrete ponds, floating net cages, and earthen freshwater ponds,⁴⁹ found negative allometric growth.

In the present study, plant extracts diets revealed a significant improvement in specific growth rate and positive allometric growth patterns of Nile tilapia. This can be ascribed to the presence of bioactive compounds in GLE and SGLE, including gallic acid, p-coumaric acid, quercetin, and kaempferol. These compounds have been demonstrated to enhance the growth of various fish species, including common carp Cyprinus carpio,⁵⁰ snakehead fish Channa argus,⁵¹ grass carp Ctenopharyngodon idellus,⁵² as well as certain animals.⁵³^,⁵⁴ Further research should be conducted in pond or cage culture systems to substantiate the positive allometric growth patterns exhibited by Nile tilapia when fed diets supplemented with GLE and SGLE.

The mean K_n values for both the plant extract diets and control were higher than one, indicating that the Nile tilapias were in good health condition during the experimental period. Similarly, condition factor values were more than one when Sargassum meal fed to Nile tilapia O. niloticus,³¹ Mansoa alliacea hydroalcoholic extracts fed to pirarucu Arapaima gigas,⁵⁵ different maltose levels fed to Nile tilapia O. niloticus.²⁷

The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance.⁵⁶ Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth.⁵⁷ In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance.⁵⁷^,⁵⁸ These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

Conclusion

The specific growth rate was significantly higher in GLE, SGLE, and MxLE groups compared to the control group. The analysis of the regression equation indicated a positive correlation between the length and weight of Nile tilapia in the control group and the GLE, SGLE, and MxLE groups. Furthermore, the GLE, SGLE, and MxLE groups exhibited a positive allometric growth pattern in Nile tilapia compared to the control. The final condition factor values did not differ significantly between the control group and any of the GLE, SGLE, and MxLE groups. Consequently, these plant extracts demonstrate suitability for commercial Nile tilapia production.

Data availability

Underlying data

zenodo: Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract. https://doi.org/10.5281/zenodo.11174309.³⁴

This project contains the following underlying data:

- Table 1: Weekly average temperature (°C) of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 2: Weekly average pH of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 3: Weekly average DO (mg/L) of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 4: Weekly average NH₃N (mg/L) of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 5: Weekly average NO₂N (mg/L) of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 6: Weekly average NO₃N (mg/L) of the control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 groups.
- Table 7: Specific growth rate of Nile tilapia (N=75) fed diets supplemented with control, GLE-5, GLE-10, SGLE-5, SGLE-10, MxLE-5, and MxLE-10 for 60 days.
- Table 8: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with control for 60 days.
- Table 9: Initial and final length (cm), weight (g), condition factor of Nile tilapia (N=75) fed diet supplemented with GLE-5 for 60 days.
- Table 10: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with GLE-10 for 60 days.
- Table 11: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with SGLE-5 for 60 days.
- Table 12: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with SGLE-10 for 60 days.
- Table 13: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with MxLE-5 for 60 days.
- Table 14: Initial and final length (cm), weight (g), and condition factor of Nile tilapia (N=75) fed diet supplemented with MxLE-10 for 60 days.
- Table 15: Summary of the chemicals and reagents used in the experiment.
- Authors checklist Manuscript No. 145369 (completed ARRIVE checklist).

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

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Version 2

VERSION 2 PUBLISHED 28 May 2024

Author details Author details

Krishna Rugmini Salin
Roles: Conceptualization, Data Curation, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Review & Editing

Balasaheb Ramdas Chavan
Roles: Conceptualization, Funding Acquisition, Project Administration, Resources, Software, Writing – Review & Editing

Seema Vijay Medhe
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Software, Writing – Original Draft Preparation, Writing – Review & Editing

Kim D. Thompson
Roles: Conceptualization, Formal Analysis, Supervision, Visualization, Writing – Review & Editing

Nopadon Pirarat
Roles: Conceptualization, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was funded by the Second Century Fund (C2F) Postdoctoral Fellowship, Chulalongkorn University, Bangkok, Thailand and the Social Justice and Special Assistance Department, Government of Maharashtra, India.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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https://doi.org/10.12688/f1000research.145369.2

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© 2024 Kamble MT et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Kamble MT, Salin KR, Chavan BR et al. Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract [version 2; peer review: 3 approved]. F1000Research 2024, 13:540 (https://doi.org/10.12688/f1000research.145369.2)

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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

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Reviewer Report 30 Jan 2025

Dr. Md. Abdullah-Al-Mamun, Professor, Fish Health Management, Sylhet Agricultural University, Sylhet, Sylhet Division, Bangladesh

Approved

https://doi.org/10.5256/f1000research.173657.r362059

The manuscript is well-written, with a clear research objective and structured methodology. The study provides valuable insights into the effects of guava and star gooseberry leaf extract on the growth performance and condition factor of Nile tilapia. The findings, particularly the positive allometric growth patterns and improved specific growth rate, contribute to the field of aquaculture nutrition. However, the authors could extend their research by evaluating disease resistance to determine whether these plant extracts offer any significant benefits in enhancing the immune response of Nile tilapia. My recommendation is for approval, with this suggestion for future studies.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: I specialize in aquaculture, finfish vaccination, aquaculture nutrition, fish immunology, and pathology. My research focuses on improving fish health and disease resistance through nutritional and immunological interventions.

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Reviewer Report 06 Sep 2024

Agumassie Tesfahun, Debre Tabor University, Debre Tabor, Ethiopia

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https://doi.org/10.5256/f1000research.159308.r320437

I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Assistant Professor in Fisheries and Aquatic Sciences

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Author Response 23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

23 Oct 2024

Author Response

Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please ... Continue reading Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.
Response: Thank you for your valuable feedback and appreciation of our work. We have incorporated a correlation matrix in the revised manuscript to analyze the relationships between water quality parameters and fish biometric data, specifically length and weight. This addition strengthens our analysis and aligns with your suggestion for more robust statistical evaluation.

Your point regarding the declining capture fishery due to human-induced impacts is well taken. As aquaculture emerges as a vital alternative for sustaining the growing global population, our research aims to provide essential insights for fish farmers and contribute to food security efforts within communities.

We appreciate your recognition of the significance of this work and look forward to any further suggestions you may have.

In the revised manuscript
Correlation matrix for water quality and fish biometric parameters
The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.
A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion
The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance. ⁵⁶Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth. ⁵⁷In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance. ^{57, 58} These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

References
56) Shin KW, Kim SH, Kim JH, Hwang SD, Kang JC: Toxic effects of ammonia exposure on growth performance, hematological parameters, and plasma components in rockfish, Sebastes schlegelii, during thermal stress. Fish Aquat Sci. 2016;19:1–8. 10.1186/s41240-016-0044-6.

57) Al-Harbi AH, Siddiqui AQ: Effects of tilapia stocking densities on fish growth and water quality in tanks. Asian Fish Sci. 2000;13(4):391–396. 10.33997/j.afs.2000.13.4.011.

58) Sanders E, Farmer SC: Aquatic models: Water quality and stability and other environmental factors. ILAR J. 2019;60(2):141–149. 10.1093/ilar/ilaa008.
Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.
Response: Thank you for your valuable feedback and appreciation of our work. We have incorporated a correlation matrix in the revised manuscript to analyze the relationships between water quality parameters and fish biometric data, specifically length and weight. This addition strengthens our analysis and aligns with your suggestion for more robust statistical evaluation.

Your point regarding the declining capture fishery due to human-induced impacts is well taken. As aquaculture emerges as a vital alternative for sustaining the growing global population, our research aims to provide essential insights for fish farmers and contribute to food security efforts within communities.

We appreciate your recognition of the significance of this work and look forward to any further suggestions you may have.

In the revised manuscript
Correlation matrix for water quality and fish biometric parameters
The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.
A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion
The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance. ⁵⁶Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth. ⁵⁷In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance. ^{57, 58} These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

References
56) Shin KW, Kim SH, Kim JH, Hwang SD, Kang JC: Toxic effects of ammonia exposure on growth performance, hematological parameters, and plasma components in rockfish, Sebastes schlegelii, during thermal stress. Fish Aquat Sci. 2016;19:1–8. 10.1186/s41240-016-0044-6.

57) Al-Harbi AH, Siddiqui AQ: Effects of tilapia stocking densities on fish growth and water quality in tanks. Asian Fish Sci. 2000;13(4):391–396. 10.33997/j.afs.2000.13.4.011.

58) Sanders E, Farmer SC: Aquatic models: Water quality and stability and other environmental factors. ILAR J. 2019;60(2):141–149. 10.1093/ilar/ilaa008.
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

23 Oct 2024

Author Response

Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please ... Continue reading Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.
Response: Thank you for your valuable feedback and appreciation of our work. We have incorporated a correlation matrix in the revised manuscript to analyze the relationships between water quality parameters and fish biometric data, specifically length and weight. This addition strengthens our analysis and aligns with your suggestion for more robust statistical evaluation.

Your point regarding the declining capture fishery due to human-induced impacts is well taken. As aquaculture emerges as a vital alternative for sustaining the growing global population, our research aims to provide essential insights for fish farmers and contribute to food security efforts within communities.

We appreciate your recognition of the significance of this work and look forward to any further suggestions you may have.

In the revised manuscript
Correlation matrix for water quality and fish biometric parameters
The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.
A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion
The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance. ⁵⁶Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth. ⁵⁷In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance. ^{57, 58} These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

References
56) Shin KW, Kim SH, Kim JH, Hwang SD, Kang JC: Toxic effects of ammonia exposure on growth performance, hematological parameters, and plasma components in rockfish, Sebastes schlegelii, during thermal stress. Fish Aquat Sci. 2016;19:1–8. 10.1186/s41240-016-0044-6.

57) Al-Harbi AH, Siddiqui AQ: Effects of tilapia stocking densities on fish growth and water quality in tanks. Asian Fish Sci. 2000;13(4):391–396. 10.33997/j.afs.2000.13.4.011.

58) Sanders E, Farmer SC: Aquatic models: Water quality and stability and other environmental factors. ILAR J. 2019;60(2):141–149. 10.1093/ilar/ilaa008.
Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.
Response: Thank you for your valuable feedback and appreciation of our work. We have incorporated a correlation matrix in the revised manuscript to analyze the relationships between water quality parameters and fish biometric data, specifically length and weight. This addition strengthens our analysis and aligns with your suggestion for more robust statistical evaluation.

Your point regarding the declining capture fishery due to human-induced impacts is well taken. As aquaculture emerges as a vital alternative for sustaining the growing global population, our research aims to provide essential insights for fish farmers and contribute to food security efforts within communities.

We appreciate your recognition of the significance of this work and look forward to any further suggestions you may have.

In the revised manuscript
Correlation matrix for water quality and fish biometric parameters
The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.
A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion
The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance. ⁵⁶Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth. ⁵⁷In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance. ^{57, 58} These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

References
56) Shin KW, Kim SH, Kim JH, Hwang SD, Kang JC: Toxic effects of ammonia exposure on growth performance, hematological parameters, and plasma components in rockfish, Sebastes schlegelii, during thermal stress. Fish Aquat Sci. 2016;19:1–8. 10.1186/s41240-016-0044-6.

57) Al-Harbi AH, Siddiqui AQ: Effects of tilapia stocking densities on fish growth and water quality in tanks. Asian Fish Sci. 2000;13(4):391–396. 10.33997/j.afs.2000.13.4.011.

58) Sanders E, Farmer SC: Aquatic models: Water quality and stability and other environmental factors. ILAR J. 2019;60(2):141–149. 10.1093/ilar/ilaa008.
Competing Interests: No competing interests were disclosed. Close
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Reviewer Report 07 Aug 2024

Dr.Sheikh Muhammad Azam, Department of Zoology, Division of Science and Technology, Lahore, University of Education Lahore, Punjab, Pakistan

Approved

https://doi.org/10.5256/f1000research.159308.r303303

Work will attract the scientist in the field. ... Continue reading

Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: fisheries, wildlife

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

Report a concern

Author Response 23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

23 Oct 2024

Author Response

Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. ... Continue reading Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. We appreciate your positive feedback and are glad to hear that you believe our work will engage scientists in the field. We aim to provide valuable insights that will benefit both farmers and aquaculturists, contributing to more sustainable practices in aquaculture. Your encouragement reinforces the importance of our research, and we look forward to sharing our findings with the broader community.
Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. We appreciate your positive feedback and are glad to hear that you believe our work will engage scientists in the field. We aim to provide valuable insights that will benefit both farmers and aquaculturists, contributing to more sustainable practices in aquaculture. Your encouragement reinforces the importance of our research, and we look forward to sharing our findings with the broader community.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

23 Oct 2024

Author Response

Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. ... Continue reading Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. We appreciate your positive feedback and are glad to hear that you believe our work will engage scientists in the field. We aim to provide valuable insights that will benefit both farmers and aquaculturists, contributing to more sustainable practices in aquaculture. Your encouragement reinforces the importance of our research, and we look forward to sharing our findings with the broader community.
Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. We appreciate your positive feedback and are glad to hear that you believe our work will engage scientists in the field. We aim to provide valuable insights that will benefit both farmers and aquaculturists, contributing to more sustainable practices in aquaculture. Your encouragement reinforces the importance of our research, and we look forward to sharing our findings with the broader community.
Competing Interests: No competing interests were disclosed. Close
Report a concern

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Version 2

VERSION 2 PUBLISHED 28 May 2024

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Dr.Sheikh Muhammad Azam, University of Education Lahore, Punjab, Pakistan
Agumassie Tesfahun, Debre Tabor University, Debre Tabor, Ethiopia
Dr. Md. Abdullah-Al-Mamun, Sylhet Agricultural University, Sylhet, Bangladesh

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30 Jan 2025 | for Version 2

Dr. Md. Abdullah-Al-Mamun, Professor, Fish Health Management, Sylhet Agricultural University, Sylhet, Sylhet Division, Bangladesh

4 Views Cite this report Responses(0)

Approved

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

I specialize in aquaculture, finfish vaccination, aquaculture nutrition, fish immunology, and pathology. My research focuses on improving fish health and disease resistance through nutritional and immunological interventions.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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27 Views

06 Sep 2024 | for Version 1

Agumassie Tesfahun, Debre Tabor University, Debre Tabor, Ethiopia

27 Views Cite this report Responses(1)

Approved

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Assistant Professor in Fisheries and Aquatic Sciences

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Author Response

23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

Comment 1: I advice the authors to include correlation matrix or principal component analysis (PCA) regarding the water quality parameter and fish biometric relationships (length and weight). To this end, please refer other published works in the same title. The paper is sound, however, it should be more sound if the authors include more statistical analysis such as correlation matrix or principal component analysis (PCA) to know the relationship between environmental variables and fish biometric data. Except for this issue, the paper is well presented and innovative for the scientific community.
Capture fishery is now declining due to human induced impacts on the water bodies. Aquaculture is the alternative option to feed this fast-growing population. Therefore, this work is very important for the fish farmers and the community as well for food security.
Response: Thank you for your valuable feedback and appreciation of our work. We have incorporated a correlation matrix in the revised manuscript to analyze the relationships between water quality parameters and fish biometric data, specifically length and weight. This addition strengthens our analysis and aligns with your suggestion for more robust statistical evaluation.

Your point regarding the declining capture fishery due to human-induced impacts is well taken. As aquaculture emerges as a vital alternative for sustaining the growing global population, our research aims to provide essential insights for fish farmers and contribute to food security efforts within communities.

We appreciate your recognition of the significance of this work and look forward to any further suggestions you may have.

In the revised manuscript
Correlation matrix for water quality and fish biometric parameters
The results of Pearson’s correlation analysis are presented in Table 3. A moderate positive correlation was observed between fish length and both ammonia (r = 0.403) and nitrite (r = 0.489), with the nitrite correlation being statistically significant at the 0.05 level (Table 3). This finding suggests that as fish increase in length, there may be a corresponding rise in ammonia and nitrite levels, potentially due to metabolic byproducts. Similarly, fish weight exhibited a positive correlation with ammonia (r = 0.470) and nitrite (r = 0.489), with the latter correlation also significant at the 0.05 level. These results indicate that fish biomass may contribute to the elevation of these water quality parameters.

Furthermore, a significant negative correlation (r = -0.684) was identified between temperature and dissolved oxygen at the 0.01 level, indicating that higher temperatures are associated with reduced dissolved oxygen levels. This phenomenon is well-documented, as warmer water typically holds less oxygen. Additionally, temperature demonstrated a moderate negative correlation with pH (r = -0.563), which was also significant at the 0.01 level. Elevated temperatures may influence the ionization of water, leading to decreased pH levels.
A strong positive correlation (r = 0.887) was observed between dissolved oxygen and pH, significant at the 0.01 level. Higher dissolved oxygen levels are often associated with elevated pH in aquatic systems, likely due to increased photosynthetic activity.

Discussion
The strong correlations between fish length, weight, and specific water quality parameters, particularly ammonia and nitrite, suggest a potential interplay between fish growth and water quality dynamics. As fish grow, their metabolic waste production, including ammonia, increases, which can accumulate in the environment if not adequately managed. This accumulation of ammonia and nitrite can adversely affect water quality and fish health, ultimately impacting growth rates and overall well-being. Several studies support these observations. Elevated ammonia concentrations are known to impair fish growth by disrupting metabolic processes and diminishing feeding efficiency. For instance, in the rockfish Sebastes schlegelii, exposure to high ammonia concentrations resulted in reduced growth performance. ⁵⁶Similarly, increased nitrite levels have been associated with oxidative stress and compromised respiratory function in fish, which can further inhibit growth. ⁵⁷In aquaculture systems, higher fish densities or insufficient water treatment often exacerbate the accumulation of ammonia and nitrite. Such conditions have been shown to decrease feed consumption and utilization efficiency, as demonstrated in studies examining the effects of stocking density on water quality and fish performance. ^{57, 58} These correlations underscore the necessity for meticulous management of water quality parameters in aquaculture to ensure optimal growth and health outcomes for fish populations.

References
56) Shin KW, Kim SH, Kim JH, Hwang SD, Kang JC: Toxic effects of ammonia exposure on growth performance, hematological parameters, and plasma components in rockfish, Sebastes schlegelii, during thermal stress. Fish Aquat Sci. 2016;19:1–8. 10.1186/s41240-016-0044-6.

57) Al-Harbi AH, Siddiqui AQ: Effects of tilapia stocking densities on fish growth and water quality in tanks. Asian Fish Sci. 2000;13(4):391–396. 10.33997/j.afs.2000.13.4.011.

58) Sanders E, Farmer SC: Aquatic models: Water quality and stability and other environmental factors. ILAR J. 2019;60(2):141–149. 10.1093/ilar/ilaa008.

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Competing Interests

No competing interests were disclosed.

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Reviewer Report

27 Views

07 Aug 2024 | for Version 1

Dr.Sheikh Muhammad Azam, Department of Zoology, Division of Science and Technology, Lahore, University of Education Lahore, Punjab, Pakistan

27 Views Cite this report Responses(1)

Approved

Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

fisheries, wildlife

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Author Response

23 Oct 2024

nopadon pirarat, Centre of Excellence in Wildlife, Exotic and Aquatic Animal Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand

Comment 1: Work will attract the scientist in the field. The results will be helpful for farmers and aquaculturists.
Response: Thank you for taking the time to review our manuscript. We appreciate your positive feedback and are glad to hear that you believe our work will engage scientists in the field. We aim to provide valuable insights that will benefit both farmers and aquaculturists, contributing to more sustainable practices in aquaculture. Your encouragement reinforces the importance of our research, and we look forward to sharing our findings with the broader community.

View more View less

Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract

Abstract

Background

Methods

Results

Conclusions

Keywords

Revised Amendments from Version 1

Introduction

Methods

Chemicals

Preparation of guava and star gooseberry leaf aqueous extracts

Ethical statement

Fish

Preparation of experimental diets supplemented with guava and star gooseberry leaf aqueous extracts

Experimental design

Water quality parameters

Specific growth rate of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

Length-weight relationship (LWR) of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

Relative condition factor (Kn) of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE

Data analysis

Results

Water quality parameters

Table 1. Water quality parameters of Nile tilapia fed diets supplemented with plant extracts.

Specific growth rate

Figure 1. Specific growth rate of Nile tilapia fed diets supplemented with plant extracts.

Length-weight relationship and growth pattern

Table 2. Length-weight relationship, growth pattern, and condition factor of Nile tilapia fed diets supplemented with plant extracts.

Figure 2. Final logarithmic length-weight relationship with regression equation for Nile tilapia fed plant extracts.

Condition factor

Correlation matrix for water quality and fish biometric parameters

Table 3. Correlation matrix between water quality and fish biometric parameters.

Discussion

Conclusion

Data availability

Underlying data

References

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Relative condition factor (K_n) of Nile tilapia fed diets supplemented with GLE, SGLE and MxLE