http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/16 2026-08-16T23:27:38Z http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4871 Investigation of Antibiotic Residues in Meat, Milk and Egg Samples Islam, Rafiza Investigation of Antibiotic Residues in Meat, Milk, and Egg Samples Broad-spectrum antibiotics are widely administrated in poultry and cattle farms for the prevention and treatment of infectious diseases and in some cases are inappropriately used as feed additives to enhance growth in food-producing animals. The presence of antibiotic residues in animal protein is a public health concern because long-term regular consumption of foods containing antibiotic residues may pose health risks due to continuous exposure to these residual antibiotics. The extensive use of sulfa drugs (SAs), fluoroquinolones (FQs), tetracyclines (TCs), chloramphenicol (CAP), derivatives of nitrofuran metabolites (NFs) in cattle and poultry farms production has been recognized as a key contributor of antibiotic resistance. This study aimed to identify and quantify residual amounts of sulfa drugs namely sulfadimethoxine (SMX), sulfadiazine (SDZ), sulfamethazine (SMT), fluoroquinolones like ciprofloxacin (CIP), enrofloxacin (ENR), levofloxacin (LEV), tetracyclines namely tetracycline (TC) oxytetracycline (OTC), chlortetracycline (CTC), chloramphenicol, derivatives of nitrofuran metabolites of 3-Amino-2-oxazolidinone (AOZ), 3-Amino-5-morpholinomethyl-2-oxazolidinone (AMOZ), and 1-Aminohydantion (AHD) in poultry meat, beef, egg, milk, and poultry feed samples using reported methods after modification and validation. Poultry meat, beef, egg, milk, and poultry feed samples were collected from poultry farms, and slaughter houses, different local markets and super shops around Dhaka and Gazipur cities, Bangladesh. Sample preparation was carried out using modified QuEChERS (Quick Easy Chief Effective Rugged and Safe) method and solid phase extraction using n-hexene, ethyl acetate, methanol, water, acetic acid and other solvents where needed. Clean-up was carried out using primary secondary amine (PSA) and C18 gel (particle form). Antibiotic residues were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) system consists of a Triple Quadrupole (QqQ) mass spectrometer equipped with electrospray ionization (ESI) and liquid chromatography (LC) separation system. The mass spectrometer was operated in both positive and negative ion modes with a capillary voltage of 3-4 kV. Method parameters were optimized in different optimized conditions such as desolvation and column oven temperature, pressure, gas flow. Chromatographic separation was performed on C18 column using optimized mobile phase compositions. Identifications were based on LC- vii MS/MS analysis, and quantifications were performed by comparing analyte peaks with those corresponding standards. Method linearities were measured within concentration range of 1.25-100 μg L-1, 5-200 μg L-1, 1.5-100 μg L-1, 1.5-100 μg L-1, and 1-200 μg L-1 for SAs, FQs, TCs, CAP and NFs, respectively. Limit of detection (LOD) and limit of quantification (LOQ) were established as the minimum analyte level that produced a signal to noise ratio (S/N) of 3 and 10, respectively ensuring that the signal could be distinguished from baseline noise with confidence. Method validations were performed using spiked sample at ppb levels such as 5 (n=3) and 10 (n=3) ppb for SAs and NFs, 20 and 25 ppb for FQs, 10 and 15 ppb for TCs and CAP, respectively. Recoveries were evaluated for poultry meat, beef, egg, milk and poultry feed samples; control samples spiked with two levels of CRM (certified reference materials) for each class of antibiotics, spiking levels 5 and 10 ppb were in the range of 91-101% with RSD% from 6.12-8.22% in poultry meat, 96-103% with RSD% from 3.38-9.85% in beef, 93-98% with RSD% from 4.32-7.55% in egg, 93-97% with RSD% from 4.39-8.73% in milk, and 88-97% with RSD% from 4.98-7.85% in poultry feed for SMX, SDZ, SMT. FQs recoveries were done at two concentration levels of 20 and 25 ppb and found to be in the range of 97-101% with RSD% from 5.40-7.62% in poultry meat, 98-101% with RSD% from 3.82-7.25% in beef, 99-102% with RSD% from 4.31-9.49% in egg, 98-102% with RSD% from 4.24-9.31% in milk, and 93-98% with RSD% from 3.66-5.75% in poultry feed for CIP, ENR, LEV. TCs recoveries were done such as 10 and 15 ppb level with the range 100-103% with RSD% from 4.00-8.79% in poultry meat, 100-108% with RSD% from 4.00-10.90% in beef, 88-102% with RSD% from 6.21-9.70% in egg, 99-102% with RSD% from 5.59-9.01% in milk, and 87-97% with RSD% from 4.58-7.15% in poultry feed for TC, OTC, and CTC. CAP recoveries were done at 10 and 15 ppb level and found in the range 94-100% with RSD% from 8.38-8.52% in poultry meat, 102% with RSD% from 7.47-8.24% in beef, 97-99% RSD% from 7.88-8.17% in egg, 98-99% with RSD% from 8.59-9.97% in milk, and 99-100% with RSD% from 8.03-8.14% in poultry feed. NFs recoveries were done at 5 and 10 ppb level with the range 95-104% with RSD% from 3.26-7.17% in poultry meat, 95-102% with RSD% from 4.63-9.14% in beef, 92-101% RSD% from 5.44-8.02% in egg, 95-103% with RSD% from 4.15-7.86% in milk, and 95-103% with RSD% from 3.97-6.79% in poultry feed for NP-AOZ, NP-AMOZ, NP-AHD. In all of the experiments, recovery values remained within the accepted ranges of 70-120% viii specified by CODEX guidelines. World Health Organization (WHO), Food and Agriculture Organization (FAO) and Bangladesh Food Safety Authority (BFSA) have imposed maximum residue limits (MRLs) to protect consumers from harmful exposure to veterinary drug residues. In our present studies, among the targeted 750 analyzed samples, residues were detected in 13 samples collected from different place of Dhaka and Gazipur cities however detected residual concentrations were below MRL values. This thesis is submitted for the degree of Doctor of Philosophy. 2026-08-06T00:00:00Z http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4851 Development of Rapid Testing Technique to Diagnose Antibiotic Resistance Hossain, Md. Uzzal Antibiotic resistance is a rapidly growing global health concern, creating an urgent need for detection methods that are both rapid and reliable. Antibiotic resistance occurs when microorganisms survive or grow despite exposure to antibiotic drugs designed to kill or inhibit them. It happens due to several factors like inappropriate prescribing, overuse, misuse, antibiotic residue intake from food items like eggs, meats, vegetables. Recent data shows, approximately 1.27 million deaths occurring each year, and the figure could increase to 39 million by 2050 if failed to take action. Besides, the overuse and misuse of antibiotics have led to the rise of multidrug-resistant organisms, commonly known as "superbugs," which are resistant to multiple antibiotics and complicate the treatment. The economic impact is also alarming. World Bank is projecting potential global GDP losses of up to $3.4 trillion annually by 2030 due to the antibiotic resistance. Traditional methods for detecting antibiotic resistance primarily involve phenotypic tests like disk diffusion, broth/ agar dilution, e-test and some automated systems that observe the growth response of bacteria to antibiotics. Though traditional methods are widely used for detecting antibiotic resistance but it has several drawbacks like time-consuming, labor-intensive, variability in data or results. The main challenge for the doctors is getting test data prior to prescribe right antibiotics to the patient. Considering the patient situation, most of the cases doctor prescribe antibiotic based on the assumption. This doctoral research introduces an electrochemical sensing strategy for the detection of antibiotics and the assessment of resistance phenomena, built upon a poly-L-glutamic acid (PGA) modified glassy carbon electrode (GCE). The objective is to seek a rapid and reliable detection mechanism of antibiotic resistance. Aligning with the research objectives, the work is divided into four experimental phases, each addressing a distinct objective in sensor development and application like antibiotic determination and evaluation of resistance phenomena. In the first phase, the glassy carbon electrode surface was modified through electropolymerization of L-glutamic acid to form a PGA coating. The modification was confirmed through a combination of analytical techniques. Cyclic Voltammetry (CV) demonstrated enhanced redox activity of the PGA modified GCE as compared to the bare GCE. Infrared (IR) spectroscopy revealed characteristic peak shifts consistent with polymer formation. Electrochemical Impedance Spectroscopy (EIS) showed reduced charge transfer resistance and improved sensitivity in Nyquist plots. Scanning Electron Microscopy (SEM) visualized a uniform polymer layer with increased surface roughness. These vi results verified the successful fabrication of PGA modified electrode with a highly responsive electrode surface. In the second phase of the study, we targeted to apply the PGA modified electrode to the detection of Ceftibuten, a β-lactam antibiotic. Versatile CV and Differential Pulse Voltammetry (DPV) were employed in phosphate buffer (pH 6.8), enabling trace-level detection of Ceftibuten. A model experiment for the detection of Ceftibuten was carried out; ie., in-vitro experiments with blood serum confirmed the method’s applicability in complex biological matrices. A simulation study incorporating β-lactamase enzyme demonstrated the sensor’s ability to detect antibiotic degradation, as indicated by a marked reduction in peak current corresponding to β-lactam ring cleavage. This will ultimately, facilitate to recognize the extend clinical study to determine the antibiotic content in blood or urine samples thus the detection of antibiotic resistance. The third phase was extended for the approach applying the same system to Cefuroxime, another β-lactam antibiotic, following the same methodological framework. The PGA-modified GCE again exhibited high sensitivity in both buffer and serum samples. Enzymatic degradation by β-lactamase produced a consistent decline in electrochemical signal, confirming the PGA modified GCE capability to monitor resistance-related biochemical changes. In the fourth phase, the PGA modified GCE was evaluated for Levofloxacin, a fluoroquinolone antibiotic. Trace detection was of Levofloxacin was achieved in buffer and serum as well as in a simulation study using Escherichia coli ATCC culture sample containing Levofloxacin revealed a significant drop in peak current after bacterial exposure, indicating detection of antibiotic interaction and potential resistance development for the antibiotics. This demonstrated a platform for the versatility for the detection of the resistance of both β-lactam and non-β-lactam antibiotics. Overall, the findings establish PGA-modified GCE-based electrochemical system as rapid, sensitive, and dependable tools for antibiotic detection and their resistance assessment. Unlike conventional microbiological assays, which often require more than 24 hours, this approach can deliver actionable results within 2-4 hours, offering a substantial advantage for timely clinical decision-making. The outcomes of this research provide a foundation for future development of point-of-care diagnostic systems and encourage further investigation across a wider range of antibiotic classes and resistance mechanisms. This thesis is submitted for the degree of Doctor of Philosophy. 2026-08-03T00:00:00Z http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4816 A Comprehensive Analysis of Residual Antibiotics, Organochlorine Pesticides and Heavy Metals in Beef and Chicken Parvin, Nargis Bangladesh is renowned for its agriculture-based economy. The farming of poultry and livestock is extremely popular in the country. Consumers in Bangladesh have a strong preference for beef and chicken meat, and these products are widely available. Toxic substances from various sources can permeate food animals through their feed and the environment, eventually making their way through the entire food chain via bioaccumulation and biomagnification. Additionally, these chemicals can enter the human body through the consumption of these foods, leading to significant public health concerns. This doctoral research focuses on identifying and measuring chemical pollutants such as leftover antibiotics, organochlorine pesticides, and heavy metals in beef and broiler chicken meat as well as liver samples, while assessing the health risks associated with each contaminant. Additionally, it aims to explore potential methods for reducing these contaminants. In this research, the presence of antibiotic residues (including tetracycline, oxytetracycline, chlortetracycline, amoxicillin, and patulin) in samples of beef meat, liver, and chicken meat, liver was examined utilizing reversed-phase High Performance Liquid Chromatography with a photodiode array detector (HPLC-PDA). Organochlorine pesticides and heavy metals were assessed using Gas Chromatography with an electron capture detector (GC-ECD) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), respectively. The beef and chicken meat and liver samples were extracted employing a modified version of the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method designed for antibiotics and organochlorine pesticides. A total of 180 biological samples, including beef meat, beef liver, and broiler chicken meat and liver, were collected for this study from local markets of Dhaka North and South City, Bangladesh. A total of one hundred and twenty samples (with 30 each of beef meat, beef liver, chicken meat, and chicken liver) were examined for each antibiotic. The correlation coefficients (r²) demonstrated a linear relationship, measuring 0.9978, 0.9980, and 0.9988 for oxytetracycline, tetracycline, and chlortetracycline, respectively, across six concentration levels. Matrix-matched calibration was performed for each matrix, resulting in linear correlation coefficients (r²) of 0.9980, 0.9990, and 0.9981 for beef meat; 0.9985, 0.9984, and 0.9973 for beef liver; 0.9988, 0.9982, and 0.9993 for chicken meat; and 0.9980, 0.9985, and 0.9991 for chicken liver concerning oxytetracycline, tetracycline, and chlortetracycline, respectively. The intra-day and inter-day recovery tests for each of the tetracyclines (TCs) were conducted, with relative standard deviation (RSD%) remaining below 10%. The Limit of Detection (LOD) for oxytetracycline, tetracycline, and chlortetracycline were recorded at 1.11, 1.15, and 1.19 μg/kg, respectively, with the associated Limit of Quantification (LOQ) being 3.17, 3.84, and 3.96 μg/kg. Residual oxytetracycline was V found and measured in eight beef liver samples, with levels varying from 86.76 to 368.97 μg/kg, all below the Maximum Residue Limit (MRL) set by Codex. However, one beef liver sample surpassed the MRL established by the European Union (EU), registering at 368.97 μg/kg. Oxytetracycline was detected in three chicken meat samples (220.94, 153.45, and 101.32 μg/kg), tetracycline was present in two samples (715.00 and 698.88 μg/kg), and chlortetracycline was found in one sample (677.35 μg/kg). Four of the positive samples exceeded the Codex recommended MRL, while six positive chicken meat samples were above the MRL limit set by the EU. The linear correlation coefficient (r²) for standard amoxicillin across six different concentrations was determined to be 0.9982. For amoxicillin in various samples, the respective linear correlation coefficients (r²) were 0.9979 for beef meat, 0.9980 for beef liver, 0.9995 for chicken meat, and 0.9981 for chicken liver. The intra-day and inter-day recovery experiments were conducted for amoxicillin, yielding a relative standard deviation (RSD%) within 10%. The limit of detection (LOD) and limit of quantification (LOQ) for the validated method were found to be 0.55 and 1.84 μg/kg for standard amoxicillin, respectively. The Codex Alimentarius Commission and the EU have established a maximum residue level (MRL) of 50 μg/kg for amoxicillin in beef and chicken meat and liver. Residual levels of amoxicillin were identified in seven beef meat samples, with concentrations ranging from 4.89 to 9.36 μg/kg, and in fifteen beef liver samples, which varied from 10.39 to 89.47 μg/kg. Among the beef liver samples, two exceeded the MRL, with values of 53.46 μg/kg (BL10) and 89.47 μg/kg (BL14). The linear correlation coefficient (r²) was determined to be linear at 0.9991 for standard patulin across six different concentrations. For patulin, the correlation coefficients (r²) were found to be linear at 0.9984, 0.9983, 0.9980, and 0.9990 in beef meat, beef liver, chicken meat, and chicken liver, respectively. An intra-day and inter-day recovery study was conducted for patulin, and the RSD% remained within 10%. The limit of detection (LOD) for the proposed method was established at 0.18 and 0.60 μg/kg for standard patulin. Residual levels of patulin antibiotic (as well as mycotoxin) were identified in twenty-five beef samples, with concentrations ranging from 47.72 to 193.91 μg/kg, and in eighteen chicken meat samples, with levels from 16.94 to 310.53 μg/kg. Patulin was detected in six beef liver samples, with concentrations between 43.31 and 166.91 μg/kg, and in eleven chicken liver samples, with levels ranging from 14.75 to 52.88 μg/kg. The health risk for each antibiotic was assessed for adults, and the hazard index (HI) was found to be less than 1. A total of one hundred and twenty samples (30 each of beef meat, beef liver, chicken meat, and chicken liver) were subjected to analysis for organochlorine pesticides (OCPs). To establish a standard calibration curve, six varying concentrations of a standard solution (comprising 20 OCPs) were injected into the gas chromatograph-electron capture detector VI (GC-ECD). The correlation coefficients (r²) showed a linear relationship, with values of 0.9999, 0.9994, 0.9990, 0.9988, 0.9980, 0.9997, 0.9991, 0.9994, 0.9993, 0.9996, 0.9983, 0.9978, 0.9995, 0.9985, 0.9990, 0.9997, 0.9981, 0.9991, 0.9994, and 0.9998 for alpha- BHC, gamma-BHC, beta-BHC, delta-BHC, heptachlor, aldrin, heptachlor epoxide, transchlordane, cis-chlordane, endosulfan I, 4, 4’-DDE, dieldrin, endrin, 4, 4’-DDD, endosulfan II, endrin aldehyde, 4, 4’-DDT, endosulfan sulfate, methoxychlor, and endrin ketone, respectively. Recovery experiments for intra-day and inter-day were conducted for 20 OCPs, and the relative standard deviation percentage (RSD%) remained within the acceptable limit of 20%. Out of thirty beef meat samples tested, alpha-BHC was detected in 11 samples (ranging from 1.01 to 62.49 μg/kg), gamma-BHC in 9 samples (with levels from 1.22 to 103.01 μg/kg), beta-BHC in 9 samples (from 1.13 to 8.94 μg/kg), and delta- BHC in 28 samples (with concentrations between 84.45 and 329.08 μg/kg). Heptachlor was found in 13 samples (ranging from 0.97 to 29.64 μg/kg), while aldrin was present in 20 samples (from 0.96 to 61.71 μg/kg). Heptachlor epoxide appeared in 28 samples (with levels from 57.87 to 304.25 μg/kg), trans-chlordane was found in 14 samples (from 0.86 to 7.90 μg/kg), and cis-chlordane in 18 samples (ranging from 0.61 to 6.22 μg/kg). Endosulfan I was detected in 26 samples (with concentrations between 1.23 and 22.86 μg/kg), and 4, 4´-DDE was found in 20 samples (ranging from 0.17 to 21.41 μg/kg). Dieldrin was present in 22 samples (from 0.47 to 36.50 μg/kg), endrin in 17 samples (ranging from 0.63 to 16.98 μg/kg), and 4, 4´-DDD was detected in 23 samples (with levels from 0.48 to 38.94 μg/kg). Endosulfan II was found in 27 samples (ranging from 1.61 to 187.29 μg/kg), and endrin aldehyde was present in 19 samples (from 0.98 to 24.70 μg/kg). Additionally, 4, 4´-DDT was detected in 15 samples (ranging from 0.24 to 76.81 μg/kg), endosulfan sulfate in 12 samples (with levels from 0.83 to 11.10 μg/kg), methoxychlor was found in 18 samples (ranging from 0.77 to 14.04 μg/kg), and endrin ketone was present in 4 samples (from 0.83 to 10.55 μg/kg), all measured in μg/kg. Among the thirty beef liver samples analyzed, alpha-BHC was detected in 28 samples (ranging from 17.40 to 340.42 μg/kg), gamma-BHC in 16 samples (from 1.75 to 15.79 μg/kg), beta- BHC in 16 samples (from 2.87 to 42.82 μg/kg), delta-BHC in 24 samples (from 2.24 to 26.41 μg/kg), heptachlor in 22 samples (ranging from 4.67 to 16.67 μg/kg), aldrin in 21 samples (from 0.66 to 20.93 μg/kg), heptachlor epoxide in 28 samples (ranging from 65.92 to 197.61 μg/kg), trans-chlordane in 16 samples (from 0.43 to 29.68 μg/kg), cis-chlordane in 10 samples (from 1.19 to 6.22 μg/kg), endosulfan I in 24 samples (ranging from 1.15 to 5.02 μg/kg), 4, 4´-DDE in 11 samples (from 0.10 to 3.38 μg/kg), dieldrin in 21 samples (ranging from 1.03 to 6.43 μg/kg), endrin in 20 samples (from 1.03 to 6.43 μg/kg), 4, 4´- DDD in 7 samples (ranging from 0.59 to 1.84 μg/kg), endosulfan II in 20 samples (from 0.22 to 25.55 μg/kg), endrin aldehyde in 26 samples (from 0.21 to 31.55 μg/kg), 4, 4´-DDT VII in 9 samples (ranging from 3.08 to 17.75 μg/kg), endosulfan sulfate in 2 samples (from 0.04 to 0.05 μg/kg), and methoxychlor in 8 samples (ranging from 0.26 to 11.67 μg/kg). In the thirty chicken meat samples, alpha-BHC was detected in 2 samples (at 1.00 and 2.87 μg/kg), gamma-BHC in 1 sample (at 4.94 μg/kg), delta-BHC in 27 samples (ranging from 5.91 to 201.65 μg/kg), heptachlor in 4 samples (ranging from 6.81 to 8.93 μg/kg), aldrin in 10 samples (from 1.60 to 33.93 μg/kg), heptachlor epoxide in 25 samples (ranging from 137.76 to 270.60 μg/kg), trans-chlordane in 13 samples (from 3.64 to 27.96 μg/kg), cischlordane in 7 samples (ranging from 0.44 to 2.24 μg/kg), endosulfan I in 25 samples (from 1.72 to 5.91 μg/kg), 4, 4´-DDE in 2 samples (at 0.41 and 1.69 μg/kg), dieldrin in 12 samples (ranging from 0.72 to 13.53 μg/kg), endrin in 10 samples (from 0.44 to 12.73 μg/kg), 4, 4´-DDD in 17 samples (ranging from 1.48 to 5.75 μg/kg), endosulfan II in 9 samples (from 0.97 to 56.96 μg/kg), endrin aldehyde in 16 samples (ranging from 0.93 to 5.03 μg/kg), 4, 4´-DDT in 7 samples (from 1.39 to 71.84 μg/kg), endosulfan sulfate in 6 samples (ranging from 0.21 to 3.14 μg/kg), and methoxychlor in 13 samples (from 1.59 to 5.95 μg/kg). In a study of thirty chicken liver samples, alpha-BHC was detected in 23 samples, with concentrations ranging from 2.12 to 159.13 μg/kg. Gamma-BHC was present in 3 samples, showing levels between 2.17 and 5.85 μg/kg, while beta-BHC was found in 10 samples, with values between 13.87 and 69.96 μg/kg. Delta-BHC was identified in 25 samples, displaying concentrations from 1.67 to 224.65 μg/kg. Heptachlor was detected in 3 samples, at levels ranging from 3.01 to 7.78 μg/kg. Aldrin appeared in 10 samples, with concentrations varying from 0.91 to 259.93 μg/kg. Heptachlor epoxide was found in 28 samples, with a range of 58.71 to 196.47 μg/kg. Trans-chlordane was present in 3 samples, with levels from 5.26 to 336.49 μg/kg, and cis-chlordane was identified in 4 samples, showing concentrations between 0.12 and 280.64 μg/kg. Endosulfan I was found in 26 samples, with values ranging from 1.23 to 22.86 μg/kg. The compound 4, 4'-DDE was detected in 9 samples (0.54 to 12.79 μg/kg), while dieldrin was present in another 9 samples, ranging from 0.84 to 9.09 μg/kg. Endrin was found in 9 samples, with concentrations between 1.24 and 40.29 μg/kg, and 4, 4'-DDD was detected in 10 samples, showing levels from 0.35 to 28.90 μg/kg. Endrin aldehyde appeared in 18 samples, with concentrations ranging from 1.12 to 307.65 μg/kg. 4, 4'-DDT was identified in 12 samples, at levels between 1.37 and 29.80 μg/kg, while endosulfan sulfate was found in 5 samples (0.97 to 204.26 μg/kg) and methoxychlor in another 5 samples, ranging from 0.72 to 5.68 μg/kg. Endrin ketone was present in 4 samples, with concentrations from 1.95 to 4.47 μg/kg. The health risks associated with these pesticides were assessed, revealing that the hazard indices for delta-BHC, heptachlor, aldrin, heptachlor epoxide, endrin, endrin aldehyde, and endrin ketone exceeded 1 for both adults and children. VIII A total of 120 biological samples were examined, comprising 30 each of beef meat, beef liver, chicken meat, and chicken liver for ten heavy metals. The samples underwent digestion with concentrated HNO3 and H2O2. In the ICP-MS, four varying concentrations of a standard solution (a mix of the ten metals) were injected to establish calibration curves. A linear correlation coefficient (r²) was determined for chromium (Cr), nickel (Ni), lead (Pb), cadmium (Cd), arsenic (As), manganese (Mn), cobalt (Co), copper (Cu), zinc (Zn), and selenium (Se), with values of 0.9988, 0.9989, 0.9990, 0.9991, 0.9991, 0.9994, 0.9991, 0.9994, 0.9998, and 0.9993, respectively. The Limits of Detection (LOD) and Limits of Quantification (LOQ) were calculated for each of the ten metals. Copper (Cu), manganese (Mn), cobalt (Co), zinc (Zn), and selenium (Se) were detected and quantified across all beef and chicken meat and liver samples. The concentration of Cu ranged from 2.82 x 10⁻⁵ to 1.24 x 10⁻⁴, 0.09 to 0.23, 0.93 to 4.68, and 3.94 to 12.52; Mn levels ranged from 1.77 x 10⁻³ to 6.69 x 10⁻², 7.62 to 57.28, 0.005 to 0.05, and 0.04 to 0.10; Co concentrations were between 2.89 x 10⁻³ to 2.95 x 10⁻², 5.33 to 11.82, 0.03 to 6.28, and 2.95 to 9.18; Zn levels varied from 0.11 to 0.55, 81.03 to 203.27, 23.70 to 41.20, and 41.26 to 152.73, while Se was found in a range of 5.02 x 10⁻⁵ to 4.40 x 10⁻⁴, 0.38 to 1.54, 0.48 to 0.81, and 1.12 to 2.54 in all beef meat, beef liver, chicken meat, and chicken liver samples, respectively. Cr concentrations were found to be between 2.63 x 10⁻⁵ to 3.20 x 10⁻⁴, 0.06 to 0.20, 0.58 to 1.68, and 0.32 to 1.42 in 30 beef meat, 9 beef liver, 30 chicken meat, and 30 chicken liver samples. Ni levels varied from 2.43 x 10⁻⁵ to 9.86 x 10⁻⁵, 0.04 to 0.92, 0.10 to 1.45, and 0.06 to 42.63 in 30 beef meat, 29 beef liver, 29 chicken meat, and 30 chicken liver respectively. Pb was found at concentrations ranging from 1.12 x 10⁻⁶ to 7.46 x 10⁻⁴, 0.05 to 24.36, 0.05 to 1.71, and 0.03 to 5.28 in 30 beef meat, 29 beef liver, 26 chicken meat, and 22 chicken liver. Cd levels were detected between 4.82 x 10⁻⁶ to 5.61 x 10⁻⁴, 0.04 to 1.17, 0.14 to 0.18, and 0.04 to 0.24 in 30 beef meat, 12 beef liver, 2 chicken meat, and 3 chicken liver respectively. As concentration ranged from 1.34 x 10⁻⁶ to 4.41 x 10⁻⁴, 0.01 to 0.69, 0.005 to 0.52, and 0.005 to 10.79 mg/kg in 30 beef meat, 28 beef liver, 19 chicken meat, and 24 chicken liver samples respectively. The health risk assessment (EDI, THQ, HI, TCR) for heavy metals was conducted for both adults and children. Chemical pollutants can build up in the fatty tissues of beef and poultry, potentially changing the fatty acid profile and causing genetic mutations. Therefore, the fatty acid composition and overall fat content were examined using gas chromatography with a flame ionization detector (GCFID). The average fat content (%) calculated was 1.57, 6.19, 0.78, and 2.95% for beef meat, beef liver, broiler chicken meat, and liver, respectively. This research underscores comprehensive evidence of the occurrence of antibiotic, pesticide, and heavy metal residues in raw beef and broiler chicken meat and liver in Bangladesh. Although most samples were within internationally accepted limits, several exceeded Codex and EU MRLs, posing potential public health concerns. This thesis is submitted for the degree of Doctor of Philosophy. 2026-04-19T00:00:00Z http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4810 Optimal Production Planning Models for Garment Industries in Bangladesh under Stochastic Atmosphere Suraiya, Sayma A key pillar of Bangladesh’s economy, the ready-made garment (RMG) industry makes a substantial contribution to the country’s GDP, foreign exchange earnings, and job creation. This study presents a thorough modeling framework for production planning optimization in Bangladesh’s RMG sector under both deterministic and stochastic circumstances. In order to maximize profit and optimize production planning of the RMG industry, this study develops first a deterministic linear programming (LP) model. The model finds the optimal product mix and output levels to effectively meet demand while lowering production costs and increasing profitability when it is applied to a real-world factory setting in Gazipur, Dhaka. Uncertainties in global demand trends, variable manufacturing costs, volatile raw material prices, and dynamic international trade rules etc. are the most vital reasons of the continuously increased challenges to the industry. This research seeks to develop strong decision-making frameworks to support strategic and tactical decision-making under such uncertainty. Taking into consideration economic fluctuations, the deterministic LP is expanded in this stage into stochastic programming models (SLP) in which all significant factors are represented as random variables, including cost coefficients, demand levels, labor availability, and processing durations. Another stochastic model also formed in this research by combining all the scenarios, as it is not actually predictable which situation would be come. This approach provides a strong planning for RMG under a variety of circumstances by capturing holistic uncertainty. A two-stage stochastic linear programming model (TSLP), in which only a chosen subset of parameters remains stochastic, is developed next in this study to reduce uncertainty. Following the revelation of parameter realizations, decisions taken in stage one are modified in stage two. This model improves tractability and increases adaptability. Expected Value of Perfect Information (EVPI) and Value of the Stochastic Solution (VSS), two important parameters in stochastic programming that measure the advantages of uncertainty modeling and perfect foresight, are used to assess the performance of deterministic, general stochastic, and two-stage stochastic models. xiii In next, two separate two-stage stochastic (TSLP) models are formulated in this study, where the demand uncertainty represents various scenarios, including seasonal variations. In this case, the fluctuation of one product’s demand is presented. Key uncertainties in demand, export prices, labor costs, raw material costs, and operational costs related to that specific product are included in scenarios that are created using historical data and probabilistic distributions. These models are then expanded into a multistage stochastic programming (MSLP) model, which simulates a decision process by allowing decision variables to change over several stages as demand unfolds and gradually adapting decisions at each stage to capture dynamic changes and integrating learning over time. By applying these models, a RMG factory can be able to decide the best production planning along with the profit and cost optimization. A comparison between the two-stage and multistage is presented next. LINDO and AMPL (A Mathematical Programming Language) are used to solve all the deterministic and stochastic models, while Excel Solver is applied for preparing all the graphical presentations of this study. In terms of predicted profit, robustness to uncertainty, and overalsl operational efficiency, the stochastic models perform noticeably better than the deterministic model, according to computational results validated using real-world data gathered from RMG companies in Bangladesh. By offering an integrated optimization framework that enables RMG stakeholders to use scenario-based planning, efficient, uncertainty-aware design tools from deterministic LP to comprehensive multistage stochastic programming. Optimization tools to increase profitability, the study adds both theoretically and practically significant, as global markets continue to vary. By presenting a thorough modeling framework designed to address the unique difficulties faced by Bangladesh’s RMG industry in order to facilitate adaptable and proactive decision-making. In the geopolitically unstable environment, where flexibility and risk-aware planning are critical also in the post-COVID atmosphere, these findings are especially pertinent. And provide resiliency in a world economy that is becoming more and more uncertain. This thesis is submitted for the degree of Doctor of Philosophy. 2026-04-13T00:00:00Z