Browsing by Author "Pankaj Kumar Gupta"

Now showing 1 - 14 of 14

A comprehensive study on aquatic chemistry, health risk and remediation techniques of cadmium in groundwater
(Elsevier B.V., 2022) Monika Mahajan; Pankaj Kumar Gupta; Anita Singh; Barkha Vaish; Pooja Singh; Richa Kothari; Rajeev Pratap Singh
Cadmium (Cd), a non-essential trace element, it's intrusion in groundwater has ubiquitous implications on the environment and human health. This review is an approach to comprehensively emphasize on i) chemistry and occurrence of Cd in groundwater and its concomitant response on human health ii) sustainable Cd remediation techniques, iii) and associated costs. Current study is depending on meta-analysis of Cd contaminations in groundwater and discusses its distributions around the globe. Literature review primarily comprises from the last three decades online electronic published database, which mainly includes i) research literatures, ii) government reports. On the basis of meta-data, it was concluded that Cd mobility depends on multiple factors: such as pH, redox state, and ionic strength, dissolved organic (DOC) and inorganic carbon (DIC). A substantially high Cd concentration has been reported in Lagos, Nigeria (0.130 mg/L). In India, groundwater is continuing to be contaminated by Cd in the proximity of industrial, agricultural areas, high concentrations (>8.20 mg/L) were reported in Tamil Nadu and Maharashtra. Depending on chemical behavior and ionic radius cadmium disseminate into the food chain and ultimately cause health hazard that can be measured by various index-based assessment tools. Instead of chemical adsorbents, nanoparticles, phytoextraction, and bioremediation techniques can be very useful in the remediation and management of Cd polluted groundwater at a low-cost. For Cd pollution, the development of a comprehensive framework that links the hydro-geological, bio-geochemical processes to public health is important and need to be further studied. © 2021 Elsevier B.V.
A holistic review on trend, occurrence, factors affecting pesticide concentration, and ecological risk assessment
(Springer Science and Business Media Deutschland GmbH, 2023) Rajeev Pratap Singh; Monika Mahajan; Kavita Gandhi; Pankaj Kumar Gupta; Anita Singh; Prafull Singh; Rahul Kumar Singh; Mohd Kashif Kidwai
Demographic outbursts and increased food demands invoke excessive use of pesticides in the agricultural field for increasing productivity which leads to the relentless decline of riverine health and its tributaries. These tributaries are connected to a plethora of point and non-point sources that transport pollutants including pesticides into the Ganga river’s mainstream. Simultaneous climate change and lack of rainfall significantly increase pesticide concentration in the soil and water matrix of the river basin. This paper is intended to review the paradigm shift of pesticide pollution in the last few decades in the river Ganga and its tributaries. Along with this, a comprehensive review suggests the ecological risk assessment method which facilitates policy development, sustainable riverine ecosystem management, and decision-making. Before 2011, the total mixture of Hexachlorocyclohexane was found at 0.004–0.026 ng/mL in Hooghly, but now, the concentration has increased up to 0.465–4.132 ng/mL. Aftermath of critical review, we observed maximum residual commodities and pesticide contamination reported in Uttar Pradesh > West Bengal > Bihar > Uttara Khand possibly because of agricultural load, increasing settlement, and incompetency of sewage treatment plant in the reclamation of pesticide contamination. Graphical Abstract: [Figure not available: see fulltext.] © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Application of deep learning models for accurate classification of fluid collections in acute necrotizing pancreatitis on computed tomography: a multicenter study
(Springer, 2025) Pankaj Kumar Gupta; Ruby Siddiqui; Shravya Singh; Nikita Pradhan; Jimil Shah; Jayanta Samanta; Vaneet Jearth; Anupam Kumar Singh; Harshal Surendra Mandavdhare; Vishal Sharma; Amar Mukund; Chhagan Lal Birda; Ishan Kumar; N. Suresh Kumar; Yashwant Patidar; Ashish Agarwal; Taruna Yadav; Binit Sureka; Anurag Kumar Tiwari; Ashish Verma; Ashish Sravanth Kumar; Saroj Kant Sinha; Usha K. Dutta
Purpose: To apply CT-based deep learning (DL) models for accurate solid debris-based classification of pancreatic fluid collections (PFC) in acute pancreatitis (AP). Material and methods: This retrospective study comprised four tertiary care hospitals. Consecutive patients with AP and PFCs who had computed tomography (CT) prior to drainage were screened. Those who had magnetic resonance imaging (MRI) or endoscopic ultrasound (EUS) within 20 days of CT were considered for inclusion. Axial CT images were utilized for model training. Images were labelled as those with≤30% solid debris and >30% solid debris based on MRI or EUS. Single center data was used for model training and validation. Data from other three centers comprised the held out external test cohort. We experimented with ResNet 50, Vision transformer (ViT), and MedViT architectures. Results: Overall, we recruited 152 patients (129 training/validation and 23 testing). There were 1334, 334 and 512 images in the training, validation, and test cohorts, respectively. In the overall training and validation cohorts, ViT and MedVit models had high diagnostic performance (sensitivity 92.4–98.7%, specificity 89.7–98.4%, and AUC 0.908–0.980). The sensitivity (85.3–98.6%), specificity (69.4–99.4%), and AUC (0.779–0.984) of all the models was high in all the subgroups in the training and validation cohorts. In the overall external test cohort, MedViT had the best diagnostic performance (sensitivity 75.2%, specificity 75.3%, and AUC 0.753). MedVit had sensitivity, specificity, and AUC of 75.2%, 74.3%, and 0.748, in walled off necrosis and 79%, 74.2%, 75.3%, and 0.767 for collections >5 cm. Conclusion: DL-models have moderate diagnostic performance for solid-debris based classification of WON and collections greater than 5 cm on CT. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Bioaccumulation of fluoride in plants and its microbially assisted remediation: A review of biological processes and technological performance
(MDPI, 2021) Rakesh Kumar; Rama Sinha; Pushpa Kumari Sharma; Nishita Ivy; Pawan Kumar; Nishi Kant; Aprajita Jha; Prakash Kumar Jha; Pankaj Kumar Gupta; Prabhakar Sharma; Rakesh Kumar Singh; Rajeev Pratap Singh; Ashok Ghosh; P.V. Vara Prasad
Fluoride is widely found in soil–water systems due to anthropogenic and geogenic activities that affect millions worldwide. Fluoride ingestion results in chronic and acute toxicity, including skeletal and dental fluorosis, neurological damage, and bone softening in humans. Therefore, this review paper summarizes biological processes for fluoride remediation, i.e., bioaccumulation in plants and microbially assisted systems. Bioremediation approaches for fluoride removal have recently gained prominence in removing fluoride ions. Plants are vulnerable to fluoride accumulation in soil, and their growth and development can be negatively affected, even with low fluoride content in the soil. The microbial bioremediation processes involve bioaccumulation, biotransformation, and biosorption. Bacterial, fungal, and algal biomass are ecologically efficient bioremediators. Most bioremediation techniques are laboratory-scale based on contaminated solutions; however, treatment of fluoride-contaminated wastewater at an industrial scale is yet to be investigated. Therefore, this review recommends the practical applicability and sustainability of microbial bioremediation of fluoride in different environments. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Correction to: Application of deep learning models for accurate classification of fluid collections in acute necrotizing pancreatitis on computed tomography: a multicenter study (Abdominal Radiology, (2024), 50, 5, (2258-2267), 10.1007/s00261-024-04607-y)
(Springer, 2025) Pankaj Kumar Gupta; Ruby Siddiqui; Shravya Singh; Nikita Pradhan; Jimil Shah; Jayanta Samanta; Vaneet Jearth; Anupam Kumar Singh; Harshal Surendra Mandavdhare; Vishal Sharma; Amar Mukund; Chhagan Lal Birda; Ishan Kumar; N. Suresh Kumar; Yashwant Patidar; Ashish Agarwal; Taruna Yadav; Binit Sureka; Anurag Kumar Tiwari; Ashish Verma; Ashish Sravanth Kumar; Saroj Kant Sinha; Usha K. Dutta
The original version of this article unfortunately contained a mistake. The "Abstract" and "Keywords" sections were missing in the published version. However, now it is corrected. To apply CT-based deep learning (DL) models for accurate solid debris-based classification of pancreatic fluid collections (PFC) in acute pancreatitis (AP). This retrospective study comprised four tertiary care hospitals. Consecutive patients with AP and PFCs who had computed tomography (CT) prior to drainage were screened. Those who had magnetic resonance imaging (MRI) or endoscopic ultrasound (EUS) within 20 days of CT were considered for inclusion. Axial CT images were utilized for model training. Images were labelled as those with ≤ 30% solid debris and > 30% solid debris based on MRI or EUS. Single center data was used for model training and validation. Data from other three centers comprised the held out external test cohort. We experimented with ResNet 50, Vision transformer (ViT), and MedViT architectures. Overall, we recruited 152 patients (129 training/validation and 23 testing). There were 1334, 334 and 512 images in the training, validation, and test cohorts, respectively. In the overall training and validation cohorts, ViT and MedVit models had high diagnostic performance (sensitivity 92.4–98.7%, specificity 89.7–98.4%, and AUC 0.908–0.980). The sensitivity (85.3–98.6%), specificity (69.4–99.4%), and AUC (0.779–0.984) of all the models was high in all the subgroups in the training and validation cohorts. In the overall external test cohort, MedViT had the best diagnostic performance (sensitivity 75.2%, specificity 75.3%, and AUC 0.753). MedVit had sensitivity, specificity, and AUC of 75.2%, 74.3%, and 0.748, in walled off necrosis and 79%, 74.2%, 75.3%, and 0.767 for collections > 5 cm. DL-models have moderate diagnostic performance for solid-debris based classification of WON and collections greater than 5 cm on CT. Keywords acute necrotizing pancreatitis; computed tomography; deep learning The original article has been corrected. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
Deep learning-based segmentation of gallbladder cancer on abdominal computed tomography scans: a multicenter study
(Springer, 2025) Pankaj Kumar Gupta; Niharika Dutta; Ajay Tomar; Shravya Singh; Sonam Choudhary; Nandita Mehta; Vansha Mehta; Rishabh Sheth; Divyashree Srivastava; Salai Thanihai; Palki Singla; Gaurav Prakash; Thakur Deen Yadav; Lileswar Kaman; Santhosh Irrinki; Harjeet Singh; Niket Shah; Amit Kumar J. Choudhari; Shraddha Patkar; Mahesh Goel; Rajanikant R. Yadav; Archana Gupta; Ishan Kumar; Kajal Seth; Usha K. Dutta; Chetan P. Arora
Objectives: To train and validate segmentation models for automated segmentation of gallbladder cancer (GBC) lesions from contrast-enhanced CT images. Materials and methods: This retrospective study comprised consecutive patients with pathologically proven treatment naïve GBC who underwent a contrast-enhanced CT scan at four different tertiary care referral hospitals. The training and validation cohort comprised CT scans of 317 patients (center 1). The internal test cohort comprised a temporally independent cohort (n = 29) from center 1 (internal test 1). The external test cohort comprised CT scans from three centers [(n = 85)]. We trained the state-of-the-art 2D and 3D image segmentation models, SAM Adapter, MedSAM, 3D TransUNet, SAM-Med3D, and 3D-nnU-Net, for automated segmentation of the GBC. The models’ performance for GBC segmentation on the test datasets was assessed via dice score and intersection over union (IoU) using manual segmentation as the reference standard. Results: The 2D models performed better than 3D models. Overall, MedSAM achieved the highest dice and IoU scores on both the internal [mean dice (SD) 0.776 (0.106) and mean IoU 0.653 (0.133)] and external [mean dice (SD) 0.763 (0.098) and mean IoU 0.637 (0.116)] test sets. Among the 3D models, TransUNet showed the best segmentation performance with mean dice (SD) and IoU (SD) of 0.479 (0.268) and 0.356 (0.235) in the internal test and 0.409 (0.339) and 0.317 (0.283) in the external test sets. The segmentation performance was not associated with GBC morphology. There was weak correlation between the dice/IoU and the size of the GBC lesions for any segmentation model. Conclusion: We trained 2D and 3D GBC segmentation models on a large dataset and validated these models on external datasets. MedSAM, a 2D prompt-based foundational model, achieved the best segmentation performance. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
Development and Characterization of Cultured Buttermilk Fortified with Spirulina plantensis and Its Physico-Chemical and Functional Characteristics
(MDPI, 2023) Hency Rose; Shiva Bakshi; Prajasattak Kanetkar; Smitha J. Lukose; Jude Felix; Satya Prakash Yadav; Pankaj Kumar Gupta; Vinod Kumar Paswan
In recent years, there has been an unprecedented increase in the demand for fermented dairy products due to medical recommendations and lifestyle preferences. Cultured buttermilk, as an ancient fermented dairy beverage, is an appropriate product choice in this context. This study presents a novel cultured buttermilk formulated by fortification with high protein microalgae Spirulina platensis, thus making it valuable and attractive because of its antioxidant properties. The fermentation process, nutraceutical properties, and sensory characteristics of developed cultured buttermilk with various concentrations of Spirulina (0.25, 0.5, and 1%) were compared with the control sample (0% Spirulina buttermilk). Different concentrations of Spirulina in buttermilk result in a significant increase in chlorophyll and carotenoid content, boosting its antioxidant properties. The study also evaluated the prebiotic properties of Spirulina, thus, demonstrating its ability to promote a healthy digestive system. It was found that the addition of 0.25% Spirulina was able to ferment the product more quickly and retained the sensory acceptability of the finished product. The protein content, free radical scavenging activity, chlorophyll, carotenoid, and total phenolic content of 0.25% Spirulina-fortified buttermilk was 1.83%, 48.19%, 30.9 mg/g, 8.24 mg/g, and 4.21 mg/g GAE, respectively. Based on the results obtained, it was concluded that cultured buttermilk with a high nutritional value and functional health benefits can be developed by fortification with 0.25% Spirulina as a natural ingredient. © 2023 by the authors.
Effect of Storage Temperature on Microbiological Quality of Optimized Almond Supplemented Paneer Kheer
(Agricultural Research Communication Centre, 2024) Pankaj Kumar Gupta; Rajendra Kumar Pandey; Rajendra Panta; Aman Rathaur; Lokesh Kumar Tinde
Background: The present research entitled Effect of Storage Temperature on Microbiological Quality of Optimized Almond Supplemented Paneer Kheer was conducted to detect the relationship between storage temperature and storage period. Methods: The research took place in the laboratory of Department of Animal Husbandry and Dairying, Banaras Hindu University, Varanasi from October 2019 to December 2019. Three different aspects of Microbiological Parameters were studied viz. Standard Plate Count (SPC), Coliform Count (CFC) and Yeast and Mold Count (YMC) from the sample taken under study as control and optimized. All the samples were studied at distinguish storage temperatures like. 5ºC, 25ºC and 37ºC. The CRD was used to find out the appropriate data obtained from research work. Result: Microbiological parameters have been the major influencer in determination of shelf life of any product. Milk possesses the characteristics to be refrigerated soon otherwise it starts degrading in its quality which is true also for milk products. It has been found that maximum mean scores of SPC of control sample (5.54) and of optimized sample (5.42) were obtained on 3rd day of storage at 37ºC. But for YMC maximum mean score of control (1.32) and of optimized (1.25) were obtained on 18th days of storage at 5ºC whereas CFC remained nil at every count regardless of storage temperature and period. Thus, the result revealed that with the elevation in the storage temperature along with storage period the life of product deteriorates at a faster rate showing directly proportional relation. © 2024 Agricultural Research Communication Centre. All rights reserved.
Heavy metals in sludge produced from UASB treatment plant at Mirzapur, India
(University of Tehran, 2021) Vijai Krishna; Anil Kumar Pandey; Pankaj Kumar Gupta
In Mirzapur (U.P.), a power-starved district, the UASB (Upflow Anaerobic Sludge Blanket) technique was adopted. Almost all of the available technologies do not treat heavy metals, so, is the case with the UASB also. The present study is to assess how much heavy metal can get accumulated in plant tissues in different species. The result of the present study was that the concentration of Pb(1106.31)>Zn(221.45)>Cd(49.26)>Hg(23.37) mg/Kg in the sludge while the concentration of Zn(93.35)>Pb(52.00)>Hg(16.93)>Cd(1.53) mg/Kg in the soil. When the sludge was mixed with the soil the trend got changed and the trend was Pb(596.36)>Zn(219.86)>Cd(24.70)>Hg(22.63) mg/Kg. Three different species that were chosen for the study were Basella Alba (Spinach), Solanum Lycopersicum (Tomato) & Brassica Juncea (Mustard). The trend of accumulation of studied heavy metals in the Brassica Juncea (Mustard) was Zn(85.33)>Pb(25.88)>Hg(11.23)>Cd(0.99) mg/Kg. In Solanum lycopersicum (Tomato) the trend was Pb(231.11)>Zn(108.72)>Hg(12.43)>Cd(9.41) mg/Kg and in Basella alba (Spinach) was Zn(103.81)>Pb(83.90)>Hg(10.78)>Cd(4.18) mg/Kg. Overall the study reveals that the accumulation of heavy metals takes place in plants grown in soil mixed with sewage sludge. The reduction in the concentration of Pb, Cd, Hg and Zn in sludge mixed with soil after the harvesting of plant in case of Solanum lycopersicum were 39.38%, 47.93%, 6.18% and 49.89% respectively; while in case of Basella alba these were 25.23%, 57.53%, 71.58% and 49.16% respectively; and in case of Brassica Juncea these reduction were 25.86%, 60.80%, 70.96% and 49.04% respectively. © University of Tehran
Preventing Microplastic Pollution in Surface Waters: Legal Frameworks and Strategic Actions
(John Wiley and Sons Inc, 2025) Monika Mahajan; Ajay Kumar Singh; Rajeev Pratap Singh; Pankaj Kumar Gupta; Sonu Singh; Mayank Pratap
Microplastic contamination of surface water is another looming environmental issue driven by fast industrialization, urbanization, and the rampant use of plastics. Microplastics are plastic particles smaller than 5 mm in size, and there are a variety of origins, including broken pieces of plastic waste, synthetic fibers, or industrial effluents. They are one of the pollutants that pose significant threats to aquatic ecosystems and human well-being because they carry toxic substances, disrupt aquatic food webs, and degrade water quality. This situation led India to formulate a series of regulatory frameworks for the reduction of plastic pollution. Other important policies are the 2016 Plastic Waste Management Rules, with a focus on recyclability and reduction of plastic waste at the source level, and the 2022 countrywide single-use plastic ban, which targets the spread of high-volume plastics that lead to microplastic pollution. India also works with international groups like the Global Partnership on Marine Litter and has integrated EPR into its plastic waste management to make it more long-lasting. In some states, incomplete or nonexistent waste management infrastructure and a lack of specific legislation on microplastics combine to raise concerns about enforcement. This review discusses the source and implications of microplastic contamination in the surface water, evaluates the effectiveness of the current legal regime, and highlights what could be done to strengthen the legislation and reduce microplastic contamination. Strengthened surveillance, state-of-the-art wastewater treatment technology, and awareness programs are essential before such elements can prevent the entry of microplastic contaminants and protect water bodies. © 2025 Wiley Periodicals LLC.
Process optimization through value addition for the manufacture of almond supplemented paneer kheer
(Plant Archives, 2020) Pankaj Kumar Gupta; Rajendra Kumar Pandey; Rajendra Panta
Research was conducted to optimize the process of manufacturing almond supplemented Paneer kheer by evaluating it’s Textural (Chewiness, Gumminess and Springiness), Physico-Chemical (Titratable Acidity and pH) and Sensory attributes (Colour and Appearance, Sweetness, Flavor, Consistency and Overall Acceptability). The research was performed in the laboratory of Dairy Science and Food Technology Department in Banaras Hindu University under CRD. The result revealed that maximum mean score of flavour (8.80), sweetness (8.75), colour and appearance (8.55), chewiness (326.158), gumminess (332.566), springiness (0.978), pH (6.31) was obtained when almond supplemented Paneer kheer was prepared with 6% almond while with same percent of almond the minimum mean score of TA was obtained. Mean score of overall acceptability at control condition was found to be lower (8.22) as compared to 8.63 under optimized condition. © 2020 Plant Archives. All rights reserved.
Quantitative assessment of irrigation water and organic/inorganic amendment on biometric growth profiles of Abelmoschus esculentus and Solanum lycopersicum and their varieties
(IWA Publishing, 2024) Monika Mahajan; Rajeev Pratap Singh; Pankaj Kumar Gupta; Shreeshivadasan Chelliapan
In recent decades, the use of chemical fertilizers has been recklessly provoked to meet the increased food needs of the rapidly growing population. However, there is some disagreement about the use of chemical fertilizers in agriculture. Hence, the appropriate nitrogen, phosphate, and potassium ratios must be determined before their application in agricultural practices. This study explored three distinct sources of nutrients to support healthy seed germination and reduce nutrient loss: chemical fertilizers, vermicompost, and nutrient-laden irrigation water supply. A sustainable, affordable, and green petri plate seed germination experiment was used to analyze the biometric growth patterns of two plant species (Abelmoschus esculentus and Solanum lycopersicum). To quantify the effects of different irrigation water sources (groundwater, river water), their combinations with chemical fertilizers and vermicompost (3 ton/ha), multivariate statistical methods such as correlation, principal component analysis, and deep neural networks were used. The purpose of this research was to find the optimal nutrient delivery technique for encouraging healthy plant growth while minimizing the environmental stress of excessive nutrient application. © 2024 The Authors.
Study on Physico-Chemical and Microbial Quality of Raw Milk Collected from Different Places of Assi Region in Varanasi City, Varanasi
(Agricultural Research Communication Centre, 2020) Pankaj Kumar Gupta; Dinesh Chandra Rai; Vinod Kumar Paswan; Rajendra Panta; Ashok Kumar Yadav
The present study was conducted to evaluate the physico-chemical characteristics including Adulteration and Microbiological quality of cow raw milk collected from four different places of ASSI region in Varanasi. Samples were analysed to know the chemical composition, the results showed that the statistically average percentage of Moisture (87.46), Fat (3.87), Protein (3.15), Lactose (4.42), Ash (.712), pH (6.43) and acidity (0.147). The keeping quality of milk was evaluated by Methylene Blue Reduction Test (MBRT). This phenomenon testified that milk sample 1 is fair quality and remained sample were found good and excellent. The microbiological conclusion confirmed the presence (less or more) of microbial load in all the raw milk samples. The highest level of microbial quality in standard plate count (SPC) was 19.1×106 cfu/ml. in sample 1 and in logarithm value is 7.28 cfu/ml at the same time, the highest coliform bacteria 2.3×102 in logarithm value is 2.36 was found in the sample 2. The adulterations in raw milk were checked by the standard procedure. In cow’s raw milk the different mixed adulterant were found in two samples contaminated with detergent and pulverized soap. Besides different hazardous chemical adulterant, raw milk from sample 1 was detected with presence of hydrogen peroxide and sample 2 was contaminated formalin whereas urea was present in sample 2 and 4. Milk adulteration is a global concern and social problem. Increased demand, growth in competition in dairy industry and financial gain makes some producers to adulterate the milk thereby decreasing milk quality. © Agricultural Research Communication Centre. All Rights Reserved.
Understanding the benefits and implications of irrigation water and fertilizer use on plant health
(Springer Science and Business Media B.V., 2024) Monika Mahajan; Anita Singh; Rajeev Pratap Singh; Pankaj Kumar Gupta; Richa Kothari; Vaibhav Srivastava
Shrinking agricultural land sizes and multiplied food demand have prompted overuse of fertilizers in agriculture, leading to a series of environmental repercussions worsening day after day. In the contemporary scenario, concerns over the magnitude of soil destruction and plant health have shifted the scientific community's attention toward sustainable agricultural practices, including organic farming and the use of organic fertilizers like vermicompost (VC), animal manure, etc. A factorial study using a randomized block design was conducted in the field to appraise the potential of fertilizer and irrigation water on the biochemical and growth responses of Abelmoschus esculentus using different doses of VCs along with and without recommended doses of NPK. All the biochemical analyses were performed at 45 and 65 DAG (days after germination). At both ages, combination of 3-ton ha−1 vermicompost + recommended dose of inorganic fertilizer (120:60:60 kg ha−1) + irrigation water treatments (T5) had the highest protein, chlorophyll, carotenoid, and phenol content and less lipid peroxidation as compared to control (144.28%, 84.21%, 83%, 224.2% and -60.43%, respectively). Also, T5 treatment showed a noticeable increase in the photosynthetic pigments level and reduced heavy metal content in fruits of the test plant at maturity. Statistical analyses, including PCA, Pearson correlation matrix, and MANOVA (p < 0.05), showed that appropriate dosing of VC together with inorganic fertilizer not only augments plant growth and yield, but also helps in reducing the transport of metals to different plant parts, mitigating food chain contamination. However, overdosing on fertilizers could negatively impact the plant’s growth and yield. Overall, the research highlights the value of organic agricultural supplements and irrigation water quality, fostering sustainable agriculture in multifaceted ways. Graphical abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer Nature B.V. 2023.