Production and characterization of bio lubricating base oil from non-edible castor seed oil has been studied. Castor oil was extracted from castor seed by solvent extraction method. KOH catalyzed transesterification process was used to produce bio-lubricating oil. Ethanol was used as alcohol in the transesterification process. Optimum condition for bio-lubricating base oil production was 40% ethanol, 0.45% KOH at 75oC for reaction time of 90 min. and the yield was 98%. Important properties of produced bio-lubricating oil like acid value (0.58 mg KOH/g), flash point (235oC), density (0.890 g/cc), pour point (-15oC) and viscosity (131.90 and 16.5 cSt at 40 and 100 oC respectively) etc. were analyzed. The properties were found to be analogues to conventional commercial lubricating oil. This renewable base oil from castor seed could be an attractive and environment friendly alternative to base oil from petroleum sources. Bangladesh J. Sci. Ind. Res. 57(1), 7-14, 2022

Production of biodiesel using leather industry solid wastes (leather lime fleshing) containing high fats and proteins was developed, which benefitted both the ways to manage waste along with generation of renewable energy. Oil from this waste was obtained using solvent extraction process. Acid catalyzed esterification followed by transesterification using KOH was used in this biodiesel production process. Extracted oil containing high free fatty acid of 11.19 % was subjected to acid catalyzed esterification using 80% methanol, 2.5 % H2SO4 at 70 °C for 60 min. The esterified oil than trans esterified into biodiesel using 60% methanol and 0.8% KOH at 60 °C for 120 min. Biodiesel yield was 95.81%. Characteristics of produced biodiesel like flash point (145 oC), acid value (2.7 mg KOH/g), density (0.870 g/cc), pour point (-12 oC) and viscosity (5.79 and 1.2 cSt at 40 and 100 oC respectively) etc. were determined. These characteristics were very close to the commercial biodiesel standards. The renewable leather industry waste could be a potential sources of biodiesel production and would protect environment and contribute to energy demand. Bangladesh J. Sci. Ind. Res. 57(3), 131-138, 2022

Consumption of diversified pigmented whole grain maize is encouraged to combat hidden hunger. The present research was conducted to evaluate physico-functional and nutritional properties of pigmented and non-pigmented maize in Bangladesh. Results revealed that white maize had the highest brightness value while purple, and deep red maize showed the lowest brightness value. The lowest bulk density (0.565 ± 0.005 g/ml) and percentage change (15.05 ± 0.31%) in sedimentation was in purple maize flour. White maize flour showed the highest change (35.43 ± 0.59%) in sedimentation value. Red and purple maize contained the highest amount of ash (2.27 ± 0.059 and 2.27 ± 0.05%, respectively) and mixed maize contained the highest crude fibre (4.17 ± 0.049%). Purple, deep red, and mixed colored maize had the highest (72 to 73%) carbohydrate whereas indigenous deep red and mixed colored maize had the lowest (6%) protein content. All most all samples had similar Mg and S content. Purple, deep red and mixed maize were found to be promising for Ca. White maize had the highest amount (19.79 ± 0.1 mg/100 g) of Zn. Yellow maize showed to contain the highest amount (4.99 ± 0.37 mg/100 g) of Fe. Overall, whole grain pigmented and nonpigmented hybrid and indigenous maize were comparable for physico-functional and nutritional properties. Bangladesh J. Bot. 51(3): 589-596, 2022 (September)

The study has attempted to develop chemometric modeling based method to quantify compositions of textile fabrics by FT-NIR spectroscopic data. Three calibration techniques such as: Principal Component Regression (PCR), Partial Least Square Regression (PLSR) and Artificial Neural Network (ANN) were assessed, and PLSR showed the best result. Several pretreatment techniques of spectral data have been evaluated, and Multiplicative Scatter Correction (MSC) performed the best. Results also shows that performance of PLSR was satisfactory for quantification of cotton (R2 ≈0.99), elastine (R2 ≈0.97) and polyester (R2≈0.94) when FT-NIR spectral data were pretreated with MSC. But for quantification of viscose in mixture fabric, efficiency of developed model was not upto the mark (R2≈0.75). Finally, the developed PLSR model with FT-NIR spectroscopic data pretreated with MSC could be used for quantification of cotton, elastine and polyester in textile fabrics rapidly and with comparatively low cost. Bangladesh J. Sci. Ind. Res. 57(4), 229-238, 2022