To improve the ability of the rice husk to purify colored wastewater, effluent from the alkaline scouring of cotton yarn was used immediately after the scouring (without cooling and additionally added chemicals) in order to remove the non-cellulosic silicon-lignin shield from the rice husk’s surface. This rice husk, with 93.8 mg/g adsorption capacity, behaves similarly as the rice husk treated with an optimized alkaline scouring recipe consisting of 20 g/L NaOH, 2 mL/L Cotoblanc HTD-N and 1 mL/L Kemonecer NI at 70 °C for 30 min with an adsorption capacity of 88.9 mg/g of direct Congo red dye. Treating one form of waste (rice husk) with another (effluent from the alkaline scouring of cellulosic plant fibers), in an effort to produce a material able to purify colored effluent, is an elegant environment-friendly concept based on the circular economy strategy. This will result in a closed-loop energy-efficient process of the pre-treatment of cotton (alkaline scouring), modification of rice husk using effluent from the alkaline scouring, dyeing cotton fabrics and cleaning its colored effluents with modified rice husk without adding chemicals and energy for heating.

Using the exhaustion-pad-dry-rinse method, chitosan was applied to alkaline-scoured and bleached cotton yarns in a solution with concentrations ranging from 0.2–1% to achieve good antimicrobial activity against the bacteria Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive). Studied samples were also assessed by measuring the amount of introduced chitosan, amount of accessible amino groups, mechanical properties, whiteness index and the b* colour coordinate. Alkaline-scoured and bleached cotton yarns treated with all concentrations of the chitosan solution showed good antimicrobial activity against Escherichia coli and Staphylococcus aureus. Better antimicrobial activity was achieved against Escherichia coli. Increasing the concentration of chitosan solution deteriorated the mechanical properties of chitosan-treated cotton yarns. The optimal concentration of chitosan solution incorporated in the exhaustion phase to obtain chitosan-treated yarns with good antimicrobial activity and mechanical properties was 0.6%. The best antimicrobial treatment should minimise potential economic costs while providing functionality.

The different sublimation transfer paper was printed in black color with total ink limiting levels, from 100 % to 400 %, using an ink jet printing system with the CMYK color system. Then the test image was transferred to fabric using the sublimation printing process. The ink jet printer was installed with sublimation dye. Color strength, CIELab color coordinate, color difference ΔE*, and GLCM (grey level co-occurrence matrix) image processing method were used for analyzing print quality. The significant change in print quality is caused by the sublimation transfer paper, resulting in a medium color difference noticeable to the human eye, while the total ink limiting level for printing sublimation transfer paper did not cause a significant change in print quality. The print with the maximum color strength is obtained with the 270 % total ink limiting level. The color difference between prints obtained with lighter sublimation transfer paper with a higher transfer rate printed with 100 % and 270 % total ink limiting levels was less than 1, suggesting a color difference undetectable to the human eye. Considering the importance of ink in terms of costs in businesses, the optimal total ink limiting level for printing sublimation transfer paper and achieving good print quality was 100 %. The total ink limiting level for printing sublimation transfer paper is useful for saving money on ink, so good print quality will be reached at a lower total ink limiting level.

The white fabric was printed with different printing temperatures and pressing times using the sublimation printing process in solid-tone black color with a 100 % total ink limiting level. Non-uniformity of the print was examined through print mottle determined by grey level co-occurrence matrix (GLCM) image processing method. Color strength of print was also determined by reflectance spectrophotometry. The print with the lower print mottle was obtained at a printing temperature of 190 °C at a longer pressing time of 120 s or at an increased printing temperature of up to 210 °C at the reduced pressing time of 60 s. The print with the lower print mottle had the lowest entropy, contrast, and correlation and the highest energy and homogeneity. The print with a higher color strength was accompanied by decreased print mottle. Choosing a suitable printing temperature and pressing time for sublimation printing is helpful in achieving print with low print mottle and high color strength and balancing cost, price, and price.

Fabric drape characterization is vital for textile performance and aesthetics, but the conventional Cusick method is labor-intensive and incompatible with digital workflows. This study assesses a smartphone-enabled digital image processing (DIP) method for fabric drape coefficient (DC) measurement, providing an accessible, low-cost alternative to the Cusick method. Draped specimens of light, medium, and heavy fabrics were imaged at three diameters (24, 30, and 36 cm) using a smartphone positioned at three vertical distances (22, 32, and 42 cm). DCs were determined through pixel-based analysis in Adobe Photoshop^®, ImageJ^®, and MATLAB^®. Statistical comparison against the Cusick method employed F-tests for variance, two-sample t-tests for mean differences, and skewness analysis. No statistically significant differences were found between smartphone DIP (with either the iPhone or Samsung device) and Cusick measurements (p > 0.05). Neither imaging height nor software platform significantly influenced outcomes, though a 22 cm height consistently provided the most stable conditions. ImageJ^® was identified as an effective open-source option for reliable analysis. The findings establish a reliable, cost-effective, and portable method for drape evaluation, reducing technical and economic barriers while aligning with Industry 4.0 digitalization. This approach enables broader adoption of reliable textile characterization across research, industry, and domains.