Study area: A total of 100 rice samples were collected from ten selected upazila of Tangail district, Bangladesh, while one upazila was considered as the sampling site. Tangail district covers an area of 3375 km2 and is situated at the central part of Bangladesh. Tangail district is a densely populated area in Bangladesh and the population density is 975/km2 (Banglapedia 2014). Agriculture is the principal land-use type in Tangail district and about 2800 km2 of cultivatable lands are available in the district. About 50% of the populations of Tangail district are involved with agricultural activities, and paddy is the main agricultural product (Rahman and Mian 2015). In Tangail, there are about 1200 industries (BBS 2013) including textile and garments industries, dyeing industries, battery manufacturing industries, packaging industry, glass industries, tanneries, metal workshops, pesticide and fertilizer industries, and food processing industries which collectively produce large volumes of effluents containing toxic metals (Tusher et al. 2017; Proshad et al. 2019a). These industries discharge their untreated effluents randomly onto the surrounding agricultural lands (Tusher et al.2017), rivers and/or canals for waste dumping (Proshad et al.2019a). Those waste-waters, containing different toxic heavy metals, get mixed with soils and thus the soil of the area is continuously being polluted by toxic elements. From the soil, toxic metals may transfer to cropplants resulting in serious health problems to both humans and animals alike. Rice sample collection and preparation for laboratory analysis: Rice grain (Oryza sativa L.; rice variety: BRRI dhan28) samples were collected from ten selected sampling sites of agricultural fields in the vicinity of the industrial areas. BRRI dhan28, one of the modern and high-yielding rice varieties developed by Bangladesh Rice Research Institute (BRRI), was selected for the present study since this rice variety is highly popular and predominantly cultivated during all growing seasons in Bangladesh. One hundred rice samples were collected by hand from the selected agricultural fields at the beginning of May 2018. Ten samples were collected from each sampling site. For each sample, rice grains were collected from three places in the same field as sub-samples and were thoroughly mixed to form a composite sample. The rice samples collected for chemical analysis were kept in polythene zip-bags with appropriate markings and labeling and brought to the laboratory on the same day of sampling. Samples were then washed with distilled water and were kept in an oven at 70–80°C to attain a constant weight (Tiwari et al. 2011).Toxic metal analysis: All the chemicals used were of analytical grade reagents, while the Milli-Q water (Elix UV5 and Milli-Q, Millipore, Boston, MA, USA) was used for the preparation of solutions. The digestion and analysis of the collected samples were performed following the procedures described by Proshadet al. (2019b). Briefly, about 0.3–0.5 g of the rice sample was treated with 6 mL of 69% HNO3 (Kanto Chemical Co., Inc., Tokyo, Japan) and 2 mL of 30% H2O2 (Wako Pure Chemical Industries, Ltd.,Osaka, Japan) in a closed Teflon vessel and was digested in a Microwave Digestion System (Berghofspeed wave, Eningen, Germany). The digested samples were then transferred to a Teflon beaker, and the total volume was increased to 50 mL with Milli-Q water. The digested solution was then filtered by using a syringe filter (DISMIC1–25HP PTFE, pore size = 0.45 mm; Toyo Roshi Kaisha, Ltd., Tokyo, Japan) and stored in 50 mL polypropylene tubes (Nalgene, New York, NY, USA). Prior to its use, the Teflon vessel and polypropylene containers were properly cleaned, soaked in 5% HNO3 for more than 24 hours, then rinsed with Milli-Q water and dried. The digestion tubes were then cleaned using a blank digestion procedure following similar procedure of samples. Afterwards, the samples were analyzed using an inductively coupled plasma mass spectrometer (ICP-MS, Agilent7700 series, Santa Clara, CA, USA) to measure the concentrations of toxic metals. The detection limits of ICP-MS were 0.7, 0.6, 0.8, 0.4, 0.06, and 0.09 ng/L for Cr, Ni, Cu, As, Cd, and Pb, respectively. Multi-element Standard XSTC-13 (Spex Certi Prep®, Metuchen, NJ, USA) solutions were used to prepare the calibration curves. Internal calibration standard solutions containing1.0 mg/L of indium, yttrium, beryllium, tellurium, cobalt and thallium were purchased from SpexCerti Prep® (Metuchen, NJ, USA). During the procedure, a 10 mg/L internal standard solution was prepared from the primary standard and added to the digested samples. A multi-element solution(Agilent Technologies, Japan) was used as the tuning solution covering a wide range of masses of elements. All test batches were evaluated using an internal quality approach and validated to see if they satisfied the defined Internal Quality Controls (IQCs). Before starting the analysis, the relative standard deviation (RSD, <5%) was checked by using tuning solution purchased from Agilent Technologies. The certified reference materials INCT-CF-3 (cornflour) bought from the National Research Council (Canada), were analyzed to confirm analytical performance and good precision (relative standard deviation bellow 20%) of the applied method. Transfer factor (TF) of heavy metals: The transfer factor (TF) of metals from soil to plant parts was defined as the ratio of the metal concentration in the plant’s tissues to the metal concentration in soil. The transfer factor was calculated for each plant sample separately. A transfer factor can be used to evaluate the potential capability of plants to transfer metals from soil to plant tissues. Statistical analysis: The data were statistically analyzed using the statistical package SPSS 20.0 (International Business Machines Corporation [IBM] Armonk, NY, USA), and calculations of means, standard deviations and health risk indices were done using Microsoft Excel 2013. Multivariate methods in terms of Pearson’s bivariate correlation matrix and principal component analysis (PCA) were used to evaluate the inter-element relationship and also to interpret the potential sources of toxic metals in rice (Islam et al. 2016; Proshad et al. 2019a). The extraction method was performed to find out the principal components (PC) in PCA analysis that was Eigen values. For dividing the toxic metals into several groups, cluster analysis (CA) with dendrogram using Ward’s method was adopted by using the overall metals concentrations in rice samples (Islam et al. 2016; Proshad et al. 2019a). The CA was also used to obtain the detailed information of the data set and to gain insight into the distribution of toxic metals by detecting similarities or differences in toxic metals in rice samples.