Environmental persistence of fluoroquinolones: Reverse‐phase high‐performance liquid chromatography‐based surveillance of contamination in water, soil, and food sources

Abstract

BACKGROUND

Fluoroquinolone (FQ) antibiotics persist in the environment, posing risks to ecosystems and public health through antimicrobial resistance and bioaccumulation. Effective analytical methods are essential for monitoring these residues and enforcing regulations to limit antibiotic pollution.

RESULTS

This study developed validated reversed‐phase high‐performance liquid chromatography (RP‐HPLC) approaches for the simultaneous detection of five FQs: norfloxacin (NFX), levofloxacin (LFX), enrofloxacin (ENR), ofloxacin (OFX), and ciprofloxacin (CFX). Two chromatographic methods were required due to structural similarities between LFX and OFX. Method I, using an Eclipse Plus phenyl hexyl column, produced retention times of 5.2 min for NFX, 5.7 min for LFX, and 7.9 min for ENR. Method II, utilizing a YMC C18 column, yielded retention times of 8.9 min for OFX and 10.7 min for CFX. Both methods demonstrated high selectivity, specificity, linearity (R ² > 0.998), and precision (relative standard deviation (RSD) < 2 %), with Photodiode Array (PDA) detection at 280 nm. Validation followed International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2R2 guidelines. Environmental samples from West Bengal, including water, soil, chicken muscle, and fish skin, were processed using solid‐phase extraction. Residues of all five FQs were detected, ranging from 0.1 to 1.4 μg g⁻¹. Ofloxacin and CFX were more frequently found in animal‐derived samples, whereas NFX and ENR were predominant in water and soil.

CONCLUSION

The validated RP‐HPLC methods provide robust tools for monitoring FQ residues in diverse matrices. The widespread contamination observed highlights the urgent need for stronger surveillance, stricter regulatory enforcement, and comprehensive risk assessment to mitigate antimicrobial resistance and protect public health. © 2026 Society of Chemical Industry.

ABBREVIATIONS

ACN

acetonitrile

ARGs

antibiotic resistance genes

CFX

ciprofloxacin

conc.

concentration

ENR

enrofloxacin

FA

formic acid

FQs

fluoroquinolones

ICH

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use

LFX

levofloxacin

LOD

limit of detection

LOQ

limit of quantification

MeOH

methanol

NFX

norfloxacin

OFX

ofloxacin

PVDF

polyvinylidene fluoride

R ²

regression coefficient

RP‐HPLC

reversed‐phase high‐performance liquid chromatography

RSD/%RSD

relative standard deviation/percentage relative standard deviation

R _t

retention time

INTRODUCTION

Fluoroquinolones (FQ) are a type of broad‐spectrum antibiotic that inhibits two important bacterial enzymes: deoxyribonucleic acid (DNA) gyrase and topoisomerase IV.^{1, 2} These enzymes are essential for bacterial DNA replication and transcription. Fluoroquinolones block them, causing breaks in bacterial DNA that prevent bacterial growth and eventually kill the bacteria. ³ Fluoroquinolones are frequently used to treat and prevent a range of illnesses in both humans and animals, ⁴ mostly respiratory and urinary tract infections. However, excessive and improper use of FQs in livestock feed causes residues to infiltrate the ecosystem, posing serious concerns regarding the environment and human health. ⁵

Figure 1 shows the five selected fluoroquinolones widely used in veterinary and human medicine to treat bacterial infections and manage resistance.

Figure 1.

Chemical structures of the investigated fluoroquinolone (FQ) standard drugs.

Norfloxacin, the first quinolone with a fluorine atom at the C6 position and a piperazine ring at C7, is a second‐generation agent that demonstrates a significant improvement in antibacterial activity, exhibiting broad effectiveness against both Gram‐positive and Gram‐negative bacteria. ⁶ Ofloxacin (OFX) is a fluoroquinolone antibiotic, effective against a wide range of acute and chronic infections, commonly used to treat urinary tract infections, respiratory tract infections, and osteomyelitis.^{7, 8} Levofloxacin (LFX) is a second‐generation fluoroquinolone antibiotic, approved in 1996, and is the active levo‐isomer of OFX. It possesses a wide spectrum of antibacterial action and is particularly effective against gram‐negative and atypical pathogens, including Legionella, Mycoplasma, and Chlamydia, as well as gram‐positive bacteria like Streptococcus pneumoniae and Staphylococcus aureus. ⁹ Levofloxacin causes bacterial cell death by blocking bacterial DNA gyrase, which interferes with DNA replication and supercoiling. Enrofloxacin (ENR) is a second‐generation fluoroquinolone antibiotic used only in veterinary medicine. It is effective in treating respiratory, digestive, and systemic infections in animals, including dogs, cats, cattle, pigs, poultry, and exotic species, due to its broad‐spectrum activity against both gram‐positive and gram‐negative bacteria. Targeted pathogens include Mycoplasma, Pasteurella, Escherichia coli, Haemophilus, and Mannheimia. ¹⁰ In certain species, such as fish and reptiles, ENR is partially metabolized to ciprofloxacin (CFX), which is a fluoroquinolone antibiotic that inhibits topoisomerase IV and bacterial DNA gyrase.^{11, 12, 13, 14} Bacterial mortality results from double‐strand breaks induced by blocking DNA replication and repair. It has bacteriostatic effects at low doses and bactericidal effects at high concentrations.

Due to inadequate elimination during sewage treatment, fluoroquinolones are mostly excreted in active form and persist in wastewater. ¹⁵ These compounds exhibit resistance to biodegradation as a result of their chemical stability, ability to form metal‐ion complexes, and strong affinity for soil and sludge. Consequently, they present significant concerns regarding environmental pollution, the development of antimicrobial resistance, and risks to both ecosystems and human health.^{16, 17} Antibiotics are widely used in both human and veterinary medicine, and large amounts enter the environment through wastewater irrigation, manure, and sewage sludge. They can persist, bioaccumulate, and stimulate the expression of antibiotic resistance genes (ARGs) in soils, which serve as a significant sink. However, due to their low concentrations and the complex composition of soil, monitoring remains challenging.^{18, 19}

Consumption of animal‐derived foods containing fluoroquinolone residues may lead to toxicity, allergic reactions, or gastrointestinal disturbances, especially upon repeated exposure. The rise of antimicrobial‐resistant bacteria, which render illnesses more challenging to treat, poses a greater risk. ²⁰ Antibiotic residues from veterinary use can enter food, soil, and water, posing allergic risks, fueling antimicrobial resistance, and persisting in the environment through excretion and accumulation. In contrast, fluoroquinolones act by disrupting bacterial DNA, thereby arresting growth. ²¹ Mechanisms of fluoroquinolone resistance include one or two of the three main mechanistic categories: alterations in the drug target, increased active efflux and alterations in drug permeation to reach its target. ²² Bacterial resistance arises mainly through mutations in the target enzymes (subunits GyrA, GyrB in DNA gyrase; subunits ParC and ParE in topoisomerase IV) and through efflux pumps or reduced drug entry, with newer agents designed to counteract these mechanisms. ²³

MATERIALS AND METHODS

Reagents and materials

Norfloxacin, levofloxacin, enrofloxacin, ofloxacin, and ciprofloxacin (purity ≥ 98%) were procured from Tokyo Chemical Industry (India) Pvt Ltd., Tamilnadu, India, High‐performance liquid chromatography (HPLC)‐grade acetonitrile (ACN), methanol, and formic acid (FA) were sourced from Thermo Scientific, Massachusetts, USA.

Instrumentation

An LC‐20 AD pump (Shimadzu) (Kyoto, Japan) was used to deliver the mobile phase to the analytical column. Detection was achieved using an SPD‐M20A ultraviolet‐visible (UV‐visible) detector (Shimadzu), and solvent degassing was performed using an ultrasonic bath. A CTO‐20A (Column oven) was utilized to maintain the column temperature, ensuring proper separation. An SIL‐20A HT autosampler was employed for sample injection. Solid‐phase extraction cartridges from Agilent Technologies (California, US) were used to extract the target analytes from the test samples.

Chromatographic condition

The chromatographic separation of five fluoroquinolones was achieved using a binary gradient elution with two different columns. Norfloxacin, LFX, and ENR were separated using an Agilent Eclipse Plus phenyl hexyl column (5 μm, 4.6 × 250 mm). In contrast, OFX and CFX were separated on a YMC C18 column (5 μm, 4.6 × 250 mm). Detection of all analytes in both methods was carried out at 280 nm. For Method I (NFX, LFX, and ENR), the mobile phase consisted of 0.1% FA in water (A) and ACN (B). A binary gradient program was employed with 20% B maintained from 0 to 10 min at a flow rate of 0.8 mL min⁻¹. For Method II (OFX and CFX), the mobile phase comprised 0.1% formic acid in water (A) and a mixture of ACN and methanol (1:2, v/v) containing 0.1% FA (B). A binary gradient program with 25% B from 0 to 15 min was used at a flow rate of 1.2 mL min⁻¹. The injection volume was fixed at 10 μL for both methods.

Standard, sample collection, and sample preparation

Primary standard solutions of NFX, LFX, ENR, OFX, and CFX were prepared by dissolving each analyte in methanol to obtain a concentration of 1 mg mL⁻¹. These stock solutions were further diluted to 100 μg mL⁻¹ and used for method development. Test samples (water, soil, chicken, and fish) were collected from different regions of West Bengal. Water samples were collected from a depth of 10–20 cm directly into Falcon tubes, adjusted to pH 3 to minimize biological activity, and stored at 4 °C until analysis. Soil samples were collected from the top layer and stored at room temperature. Chicken and fish samples were obtained from local shops in the respective regions for further analysis.

Solid phase extraction

After centrifugation, the supernatant was collected and directly loaded into the C18 polypropylene cartridge. The loaded matrices were washed using methanol containing 20% water, and finally target analytes from the test samples were eluted using 1 mL of methanol.

Water samples

Water samples were collected from different regions of West Bengal and analyzed using reversed‐phase high‐performance liquid chromatography (RP‐HPLC) to determine the presence of FQs. The samples were adjusted to pH 3 and stored at 4 °C until analysis. Fluoroquinolones were extracted using solid‐phase extraction. The SPE cartridge was first conditioned with 1 mL of methanol, followed by 1 mL of water. The prepared sample was then loaded onto the cartridge, followed by a washing step using 1 mL of water to remove interfering substances. Finally, the target analytes were eluted with 1 mL of methanol and collected for subsequent RP‐HPLC analysis.^{24, 25, 26}

Chicken samples

Chicken samples were collected, washed, and homogenized using ACN. The homogenate was centrifuged at 2800 × g for 5 min, and the resulting supernatant was collected. Solid‐phase extraction (SPE) was then performed: the cartridge was conditioned with 1 mL of methanol followed by 1 mL of water. The supernatant was loaded onto the cartridge, and interfering components were removed during the washing step. Finally, the target analytes were eluted with 1 mL of methanol, collected, and transferred into vials for subsequent RP‐HPLC analysis.^{27, 28, 29, 30}

Fish samples

Fish samples were collected from various locations in West Bengal. The samples were cleaned, homogenized using ACN, and centrifuged at 2800 × g for 5 min. The supernatant was then collected and subjected to SPE. The SPE cartridge was conditioned with methanol and water prior to sample loading. A washing step was performed using water to remove interfering substances. Finally, the target analytes were eluted with 1 mL of methanol and collected for further analysis.^{31, 32, 33}

Soil samples

Antibiotics in soil samples were analyzed by collecting soil from different regions, followed by sieving. Accurately weighed 1 g portions were transferred into 50 mL Falcon tubes. A mixture of methanol and 25% orthophosphoric acid (40:10, v/v) was added to each tube, and the contents were mixed thoroughly. The samples were then sonicated for 20 min and centrifuged at 2800 × g for 5 min. The resulting supernatant was collected and filtered through a 0.45 μm polyvinylidene fluoride (PVDF) filter prior to analysis.^{18, 34}

Method validation

The analytical methods for the five selected drugs were validated according to International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2R2 guidelines. ³⁵

Selectivity and specificity

Selectivity and specificity were determined by evaluating potential analyte interference through a comparison of the chromatograms of a standard sample and a spiked sample.

Accuracy and precision

Accuracy was determined by evaluating the mean recovery of the analytes, achieved through triplicate analysis of samples taken from the linearity ranges. Precision was determined by evaluating repeatability, intraday precision, and interday precision. Intraday precision was evaluated by a second analyst who analyzed the samples within a single day using the same instrument, whereas interday analysis was performed by repeating the procedure on two consecutive days.

$$\text{Accuracy}\left(\%\right)=\begin{array}{l}\frac{\left(\text{measured concentration of spiked sample}-\text{endogenous concentration}\right)}{\text{spiked concentration}}\times 100\%\end{array}$$ (1)

Linearity and range

The concentration ranges were selected based on the expected analyte levels observed in preliminary experiments, values reported in the literature, and the requirement to achieve a proportional and reliable analytical response across the studied range.  Different concentration levels were prepared through appropriate serial dilutions to cover the intended analytical application adequately and ensure satisfactory linearity of the calibration curve.

Dilutions for all five FQs were prepared from 1 mg mL⁻¹ stock solutions, yielding concentrations between 0.1 μg mL⁻¹ and 200 μg mL⁻¹. These dilutions were used to construct calibration curves by plotting peak area against concentration. The calibration curves, derived from the five prepared standards, were fitted to linear regression equations, and linearity was confirmed by examining the residual plots. The established linearity enables prediction of unknown analyte concentrations based on the instrument's response to known standards.^{36, 37, 38}

Limits of detection and quantification

The limit of detection (LOD) is defined as the lowest analyte concentration in a sample that is detectable but not necessarily quantifiable, with a signal‐to‐noise (S/N) ratio of 3:1 or more. The limit of quantification (LOQ) is the lowest concentration of an analyte that can be quantified with a signal‐to‐noise (S/N) ratio of 10:1 or more.^{36, 39}

Robustness

The method's robustness was evaluated by observing variations in chromatographic conditions – including flow rate, mobile phase pH, column temperature, and injection volume – at the low quality control (LQC) concentration of all five FQs.^{37, 40}

RESULTS

Ofloxacin (OFX) and LFX contain similar structures known as enantiomers and have the same chromophores. As Fig. 2 shows, the separation of five drugs in a single method resulted in the co‐elution of OFX and LFX. Hence, the separation of the selected FQs was achieved using two different methods, with two different chemistry columns. The compounds NFX, LFX, and ENR were separated using an Eclipse phenyl hexyl column at retention times (R _t) of 5.2, 5.7, and 7.9 min respectively, in Method I (Fig. 3). The remaining OFX and CFX were separated using a YMC C18 column, and peaks appeared at R _t of 8.9 and 10.7 min, respectively in Method II (Fig. 4). For Method I (NFX, LFX, and ENR), the mobile phase consisted of 0.1% FA in water (A) and ACN (B), with Pump‐A delivering the aqueous phase. Pump‐A delivered 0.1% FA in water (A) for both methods. Pump‐B delivered 100% ACN (HPLC grade) in Method I and 0.1% FA in water containing ACN and methanol in a ratio of 1:2 (ACN:MeOH) in Method II.

Figure 2.

Representative high‐performance liquid chromatography (HPLC) chromatogram showing the co‐elution behavior of levofloxacin (LFX) and ofloxacin (OFX) under optimized chromatographic conditions.

Figure 3.

Chromatographic characterization of norfloxacin (NFX), levofloxacin (LFX), and enrofloxacin (ENR): (A) two‐dimensional integrated chromatogram and (B) corresponding three‐dimensional high‐performance liquid chromatography (HPLC) profile highlighting peak distribution and separation.

Figure 4.

Chromatographic characterization of ofloxacin and ciprofloxacin: (A) integrated high‐performance liquid chromatography (HPLC) chromatogram and (B) corresponding three‐dimensional chromatographic profile.

Method validation

Selectivity and specificity

No interference was observed in these samples; the R _t showed the method's high degree of selectivity and specificity. The selectivity and specificity of NFX, LFX, and ENR were observed at an R _t of 5.2, 5.7, and 7.9 min, respectively, and are shown in Fig. 5. Ofloxacin and CFX were observed at an R _t of 8.9 and 10.7 min, and are shown in Fig. 6.

Figure 5.

Selectivity study of standard drugs using Method I, demonstrating analyte resolution in the absence of interference.

Figure 6.

Selectivity study of standard drugs using Method II, demonstrating analyte resolution in the absence of interference.

Accuracy and precision

Accuracy and precision were determined by evaluating repeatability, intraday precision, and interday precision. Repeatability was assessed using six sample solutions, each prepared at the LOQ concentration of the analyte. Accuracy was determined by evaluating the mean recovery of the analyte at the concentration levels of 0.45, 4, and 7 μg mL⁻¹, respectively for method I and 1.5, 7, and 15 μg mL⁻¹, respectively, for method II, as shown in Table 1. The intraday precision was evaluated within a single day by a second analyst with the same instrument, as shown in Table 2. Interday precision was evaluated by repeating the procedures on two consecutive days, as shown in Table 3. The overall accuracy and precision demonstrated that the data obtained fall within acceptable ranges as mentioned in the ICH Q2R2 guidelines.

Table 1.

Accuracy and recovery results of the proposed method at different concentration levels, expressed as percentage recovery.

	Actual conc. (μg mL−1)	Calculated conc. (μg mL−1)	Recovery (%)
NFX
LQC	0.45	0.53	117.78
MQC	4	4.19	104.75
HQC	7	7.24	103.43
LFX
LQC	0.45	0.54	120
MQC	4	3.7	92.5
HQC	7	6.51	93
ENR
LQC	0.45	0.52	115.56
MQC	4	3.88	97
HQC	7	7.23	103.29
OFX
LQC	1.5	1.73	115.33
MQC	7	7.56	108
HQC	15	17.84	118.93
CFX
LQC	1.5	1.59	106
MQC	7	6.67	95.29
HQC	15	17.89	119.27

Abbreviation: NFX, norfloxacin; LFX, levofloxacin; ENR, enrofloxacin; OFX, ofloxacin; CFX, ciprofloxacin; LQC, low quality control, MQC: middle quality control; HQC, high quality control.

Table 2.

Intraday precision of the method expressed as percentage relative standard deviation (%RSD) for replicate analyses within a single day.

Standard	QC Points	Concentration (μg mL−1)	Intraday			Average	STD.	RSD.	%RSD.
			Run‐I (μg mL−1)	Run‐II (μg mL−1)	Run‐III (μg mL−1)
NFX	LQC	0.45	0.60	0.54	0.61	0.58	0.04	0.07	6.72
	MQC	4	5.60	5.95	5.01	5.52	0.48	0.09	8.63
	HQC	7	8.97	9.12	8.33	8.81	0.42	0.05	4.75
LFX	LQC	0.45	0.65	0.67	0.59	0.64	0.04	0.07	6.94
	MQC	4	3.85	3.95	3.91	3.90	0.05	0.01	1.22
	HQC	7	6.78	7.00	7.53	7.11	0.39	0.05	5.43
ENR	LQC	0.45	0.43	0.39	0.36	0.40	0.04	0.09	9.45
	MQC	4	3.87	4.01	3.80	3.89	0.11	0.03	2.74
	HQC	7	5.84	5.81	5.82	5.82	0.01	0.00	0.26
OFX	LQC	1.5	1.56	1.66	1.52	1.58	0.07	0.04	4.43
	MQC	7	5.62	6.62	6.38	6.21	0.52	0.08	8.37
	HQC	15	21.18	18.85	19.38	19.80	1.22	0.06	6.17
CFX	LQC	1.5	1.59	1.78	1.56	1.65	0.12	0.07	7.34
	MQC	7	8.23	8.42	7.79	8.14	0.32	0.04	3.96
	HQC	15	22.72	21.23	22.76	22.23	0.87	0.04	3.93

Abbreviation: NFX, norfloxacin; LFX, levofloxacin; ENR, enrofloxacin; OFX, ofloxacin; CFX, ciprofloxacin; LQC, low quality control, MQC: middle quality control; HQC, high quality control.

Table 3.

Interday precision of the method expressed as percentage relative standard deviation (%RSD) across different days.

Standard	QC Points	Concentration (μg mL−1)	Interday			Average	STD	RSD	% RSD
			Run‐I (μg mL−1)	Run‐II (μg mL−1)	Run‐III (μg mL−1)
NFX	LQC	0.45	0.54	0.54	0.50	0.53	0.02	0.04	4.38
	MQC	4	3.79	4.35	4.44	4.19	0.35	0.08	8.40
	HQC	7	9.70	10.65	9.45	9.93	0.63	0.06	6.37
LFX	LQC	0.45	0.54	0.52	0.54	0.53	0.01	0.02	2.17
	MQC	4	3.05	3.51	3.75	3.44	0.36	0.10	10.35
	HQC	7	6.15	6.46	6.92	6.51	0.39	0.06	5.95
ENR	LQC	0.45	0.48	0.54	0.54	0.52	0.03	0.07	6.66
	MQC	4	3.96	4.04	3.63	3.88	0.22	0.06	5.61
	HQC	7	6.97	7.75	6.96	7.23	0.45	0.06	6.27
OFX	LQC	1.5	1.98	1.92	1.84	1.91	0.07	0.04	3.67
	MQC	7	7.47	7.33	7.32	7.37	0.08	0.01	1.14
	HQC	15	17.67	15.78	15.55	16.33	1.16	0.07	7.12
CFX	LQC	1.5	1.78	2.12	1.86	1.92	0.18	0.09	9.26
	MQC	7	9.21	10.62	10.89	10.24	0.90	0.09	8.81
	HQC	15	28.50	28.18	27.13	27.94	0.72	0.03	2.57

Abbreviation: NFX, norfloxacin; LFX, levofloxacin; ENR, enrofloxacin; OFX, ofloxacin; CFX, ciprofloxacin; LQC, low quality control, MQC: middle quality control; HQC, high quality control.

Linearity and range

The calibration curve is linear over the range of 0.15–10 μg mL⁻¹ for NFX, LFX, and ENR, and 0.4–20 μg mL⁻¹ for OFX and CFX (Fig. 7). Figure 8 shows various patterns observed in a residual plot corresponding to the linearity study. Table 4 shows linear regression and coefficient of determination values.

Figure 7.

Calibration (linearity) curves for fluoroquinolones (FQs): (A) norfloxacin (NFX), (B) levofloxacin (LFX), (C) enrofloxacin (ENR), (D) ofloxacin (OFX), and (E) ciprofloxacin (CFX), showing the relationship between concentration and peak area.

Figure 8.

Residual plots corresponding to the linearity study of (A) norfloxacin (NFX), (B) levofloxacin (LFX), (C) enrofloxacin (ENR), (D) ofloxacin (OFX), and (E) ciprofloxacin (CFX), confirming homoscedasticity and goodness‐of‐fit of the regression models.

Table 4.

Summary of validation parameters including regression equation, coefficient of determination (R ²), linearity range, limit of detection (LOD), and limit of quantification (LOQ).

Analyte	Range (μg mL−1)	LOD (μg mL−1)	LOQ (μg mL−1)	Equation	R 2
NFX	0.15–10	0.037	0.45	Y = 21 836x – 5323.4	0.9988
LFX	0.15–10	0.075	0.45	Y = 13 726x – 2588.4	0.9984
ENR	0.15–10	0.037	0.45	Y = 25 429x – 921.6	0.9999
OFX	0.4–20	0.20	1.5	Y = 4770.2x + 3617	0.9994
CFX	0.4–20	0.20	1.5	Y = 8070x – 1020.8	0.9961

Abbreviation: NFX, norfloxacin; LFX, levofloxacin; ENR, enrofloxacin; OFX, ofloxacin; CFX, ciprofloxacin; LOD, limit of detection; LOQ, limit of quantification.

Limit of detection

The LOD of NFX, LFX, and ENR was 0.15 μg mL⁻¹, and that of OFX and CFX was at 0.4 μg mL⁻¹, as shown in Table 4.

Limit of quantification

The LOQ of NFX, LFX, and ENR was 0.45 μg mL⁻¹, and the LOQ of OFX and CFX was 1.5 μg mL⁻¹, as shown in Table 4.

Robustness

The robustness of the method was evaluated by assessing variations in chromatographic conditions such as flow rate, mobile‐phase pH, column temperature, and injection volume. The results showed that changes in flow rate affected retention time, with higher flow rates decreasing retention time. However, small changes in mobile‐phase pH, column temperature, and injection volume showed no significant changes for either method, as reported in Table 5.

Table 5.

Evaluation of the robustness of the developed method with deliberate variations in chromatographic conditions

Factors and levels in fractional factorial design for HPLC method robustness at LQC level
Factors		−1 Level	+ Level	Average	STD	RSD	%RSD
pH (−2.8; +3.2)	NFX	15984	15 993	15988.5	4.5	0.0003	0.028
	LFX	9969	9986	9977.5	8.5	0.0009	0.09
	ENR	19854	19 867	19860.5	6.5	0.0003	0.03
	OFX	8326	8332	8329	3	0.0004	0.04
	CFX	1201	1217	1209	8	0.0066	0.66
Column oven temperature (°C)(−30; +40)	NFX	16004	16 013	16008.5	4.5	0.0003	0.03
	LFX	9984	9997	9990.5	6.5	0.0007	0.07
	ENR	19871	19 888	19879.5	8.5	0.0004	0.04
	OFX	8320	8338	8329	9	0.0011	0.11
	CFX	1231	1237	1234	3	0.0024	0.24
Mobile phase flow rate (mL min−1) (−0.7; +0.9 for method I, −1.1; +1.3 for method II)	NFX	15987	15 993	15990	3	0.0002	0.02
	LFX	9974	9986	9980	6	0.0006	0.06
	ENR	19853	19 867	19860	7	0.0007	0.07
	OFX	8317	8332	8324.5	7.5	0.0009	0.09
	CFX	1203	1217	1210	7	0.0058	0.58
Detection wavelength (−270; +290)	NFX	15991	16 001	15996	5	0.0003	0.03
	LFX	9979	9990	9984.5	5.5	0.0006	0.0800
	ENR	19859	19 872	19865.5	6.5	0.0003	0.03
	OFX	8319	8331	8325	6	0.0007	0.07
	CFX	1217	1231	11224	7	0.0057	0.57
Volume of injection (μL) (−9; +11)	NFX	15979	15 991	15985	6	0.0004	0.04
	LFX	9974	9980	9977	3	0.0003	0.03
	ENR	19857	19 870	19863.5	6.5	0.0003	0.03
	OFX	8308	8321	8314.5	6.5	0.0008	0.08
	CFX	1209	1217	1213	4	0.0033	0.33

Abbreviation: NFX, norfloxacin; LFX, levofloxacin; ENR, enrofloxacin; OFX, ofloxacin; CFX, ciprofloxacin.

The results showed that antibiotic residues were present across different regions at varying concentrations. In water samples, NFX ranged from 0.3 to 0.99 μg mL⁻¹, and LFX from 0.85 to 1.39 μg mL⁻¹ across all the regions, ENR concentrations ranged from 0.1 to 0.13 μg mL⁻¹ in all regions except Dum Dum, and CFX was detected only in Dum Dum at 0.95 μg mL⁻¹. Chicken samples contained NFX concentrations from 0.24 to 0.35 μg g⁻¹ except in Kalyani, and LFX between 0.32 and 1.33 μg g⁻¹ across all the regions; ENR at 0.12 μg g⁻¹ and OFX at 0.49 μg g⁻¹ were detected only in Bengal Chemicals and Pharmaceuticals effluent drainage zone associated with the plant, whereas CFX was not detected in any of the chicken samples collected from all regions. Fish samples exhibited limited contamination, with NFX and LFX both at 0.25 − 0.32 μg g⁻¹ in Dum Dum, and ENR and OFX detected in Bengal Chemicals and Pharmaceuticals effluent drainage zone associated with the plant at 0.15 and 0.6 μg g⁻¹, respectively. Soil samples revealed the highest accumulation, with NFX ranging from 1.04 to 1.14 μg g⁻¹ and ENR between 0.15 and 0.18 μg g⁻¹, restricted to Bengal Chemicals and Pharmaceuticals effluent drainage zone associated with the plant and Kalyani. Overall, the concentration range across all samples exceeded 0.1 μg g⁻¹, with water and chicken matrices showing consistent residues, soil samples demonstrating the highest values, and fish samples reflecting intermittent contamination, as shown in Table 6.

Table 6.

Quantitative determination of fluoroquinolones in test samples under the proposed analytical conditions

Test sample	Regions	NFX	LFX	ENR	OFX	CFX
Water sample (μg mL−1)	Bengal Chemicals and Pharmaceuticals	0.3	0.85	0.1	‐	‐
	Information Area Market	0.99	1.39	0.13	‐	‐
	Dum Dum	0.34	0.92	‐	‐	0.95
	Kalyani	0.32	1.13	0.11	‐	‐
Chicken sample (μg g−1)	Bengal Chemicals and Pharmaceuticals	0.35	1.3	0.12	0.49	‐
	Information Area Market	0.25	1.33	‐	‐	‐
	Dum Dum	0.24	0.32	‐	‐	‐
	Kalyani	‐	0.41	‐	‐	‐
Fish sample (μg g−1)	Bengal Chemicals and Pharmaceuticals	‐	‐	0.15	0.6	‐
	Information Area Market	‐	‐	‐	‐	‐
	Dum Dum	0.25	0.32	‐	‐	‐
	Kalyani	‐	‐	‐	‐	‐
Soil sample (μg g−1)	Bengal Chemicals and Pharmaceuticals	1.04	‐	0.18	‐	‐
	Information Area Market	‐	‐	‐	‐	‐
	Dum Dum	‐	‐	‐	‐	‐
	Kalyani	1.14	‐	0.15	‐	‐

DISCUSSION

This study demonstrated the successful development and validation of commonly used fluoroquinolone antibiotics (NFX, LFX, ENR, OFX, and CFX) in environmental and food matrices using two different chromatographically optimized RP‐HPLC methods for their simultaneous determination, ensuring their reliability for environmental surveillance of antibiotic residues as per the ICH Q2R2 criteria.

Although the analytical workflow was established successfully, several practical challenges were encountered during sample collection and preparation. As these are complex matrices, they often interfered with recovery and reduced the clarity of chromatographic results. Solid‐phase extraction gave inconsistent results, especially with fish samples high in protein and fat, where FQs tended to bind tightly to tissue. Soil samples contained organic matter and clay, and water samples exhibited high turbidity; these matrices were acidified immediately to prevent microbial degradation of the analytes. Particles from soil and biological samples frequently clogged cartridges and filters, increasing the difficulty of the process. During sample analysis, such matrix interferences can render quantification unreliable. To resolve these problems, solvent systems, washing and elution steps, and pretreatment methods – including centrifugation, sonication, and filtration – were carefully adjusted.

Initially, protein precipitation was used; however, this method resulted in low recovery rates and inconsistent results. To address these issues, particularly the poor extraction of fluoroquinolones from complex matrices and interference caused by proteins and fats, the protocol was revised. For soil samples, a mixture of methanol and 25% orthophosphoric acid in a 40:10 ratio was employed to disrupt the bonds between the analytes and the soil, which facilitated the dissolution of the fluoroquinolones. For water samples, the pH was adjusted to 3 to minimize bacterial interference and prevent analyte degradation. Chicken and fish samples were treated with a 1:1 (v/v) methanol–water solution, mixed thoroughly, sonicated for 20 min, centrifuged at 2800 × g for 5 min, and then the extracts were processed using solid‐phase extraction (SPE). These adjustments significantly improved fluoroquinolone recovery, reduced matrix effects, and led to more consistent outcomes, allowing for reliable detection across various sample types.

The techniques that were established proved reliable, repeatable, and sensitive enough to identify fluoroquinolone traces in complex matrices such as soil, water, and biological tissues, as confirmed by validation results. High analytical sensitivity was demonstrated by excellent linearity (R ² > 0.998) and low limits of detection (0.037–0.20 μg mL⁻¹), while accuracy and precision were reflected in recovery values ranging from 92.5% to 120% with relative standard deviations below 10%. The simplicity and reliability of the methods also make them suitable for routine monitoring in laboratories lacking advanced mass spectrometric equipment. Fluoroquinolone residues were detected in all sample types, raising environmental concerns. The predominance of NFX, LFX, and ENR in soil and water samples highlights their environmental mobility and persistence through agricultural runoff and wastewater discharge. The comparatively high concentration of LFX (up to 1.39 μg mL⁻¹) in water from urban and industrial areas indicates continuous input from household wastewater and pharmaceutical effluents, and the presence of NFX and ENR in soil samples (up to 1.14 μg g⁻¹) reflects their strong sorption to mineral surfaces and soil organic matter, consistent with previous findings that fluoroquinolones bind tightly to sediments and resist biodegradation.^{16, 34} This environmental persistence increases the risk of long‐term contamination and the possible transmission of antibiotic resistance genes (ARGs) in soil microbiota.

On the other hand, samples that originated from animals, such as fish and chicken tissues, were more likely to include OFX and CFX. These antibiotics may have been exposed to polluted feed, water, or direct veterinary treatment if they were found in edible tissues. Such results are consistent with research that found FQ residues in aquaculture and poultry products.^{20, 21} The capacity of these substances for bioaccumulation and their poor metabolism in animals present a direct pathway to human exposure. Even at minimal amounts, long‐term use of foods tainted with antibiotics may cause hypersensitivity responses and, more importantly, encourage the development of bacterial strains resistant to antibiotics in people.

The varied distribution of individual fluoroquinolones throughout matrices is indicative of their unique physicochemical characteristics, environmental stability, and consumption trends. The veterinary‐specific ENR and its metabolite CFX were detected outside of animal tissues, indicating excretion and subsequent discharge into the environment. Detecting parent–metabolite pairs in different areas shows that current waste management and treatment systems cannot completely remove or degrade these substances. This limitation leads to concerns about environmental pollution, antimicrobial resistance, and risks to both ecosystems and human health. This finding is consistent with earlier observations of FQ residues in surface and groundwater around animal farms and urban wastewater discharge locations.^{15, 24} Together, these findings offer compelling evidence that FQ contamination is pervasive and complex, involving interconnected routes across food, agricultural, and environmental systems. The validated RP‐HPLC techniques provide an efficient and cost‐effective analytical solution for the ongoing monitoring of these pollutants. Regular monitoring with standard methods is important for understanding of ecological exposure levels. These practices help shape regulations to reduce antibiotic pollution and offer valuable information for risk assessments. The connection between environmental contaminants and resistance gene propagation may also be clarified by combining these results with antimicrobial resistance monitoring.

CONCLUSION

This study emphasized the critical need for improved wastewater treatment technology, national residue monitoring systems, and more stringent regulations on the use of antibiotics in both human and veterinary medicine. The new RP‐HPLC method helps to support ongoing efforts toward sustainable environmental management and the global battle against antimicrobial resistance by enabling the accurate and sensitive identification of fluoroquinolones across a variety of matrices.

AUTHOR CONTRIBUTIONS

Hanumu Korra: writing – original draft, validation, investigation, graphical illustrations, formal analysis. Siva Bhukya: writing – original draft, validation, investigation, graphical illustrations, formal analysis. Ravi Adinarayan Somabattini: writing – original draft, validation, investigation, formal analysis. Sayantan Banerjee: investigation and formal analysis. Mallika Sengupta: investigation and formal analysis. Satheesh Kumar Nanjappan: supervision, resources, project administration, investigation.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.