Search Results (3)

This paper investigates the biodegradation properties of cellulose fibers and PLA biopolymer. For that purpose, hemp, jute, and sisal fibers as lignocellulose fibers; viscose fibers (CV) as regenerated cellulose; and polylactide (PLA) as biopolymer were buried in farmland soil for periods of 2, 4, 7, 9 and 11 days under controlled conditions. The influence of their biodegradation on the fiber mechanical properties, bacteria and fungi population, as well as on the soil quality were investigated. After exposure to microorganisms, analyses of the fibers’ morphological (SEM), chemical (FTIR), and thermal (TGA) properties were conducted to achieve a comprehensive understanding of their biodegradability. The analysis concluded that lignin and pectin content have a greater impact on the biodegradation of hemp, jute, and sisal fibers than factors like crystallinity and degree of polymerization. The viscose fibers showed lower biodegradability despite their lower degree of polymerization, indicating a resistance to biodegradation due to the “skin” formed during the spinning process. PLA fibers experienced chemical hydrolysis and significant microbial attack, resulting in reduced tenacity. The acquired findings yield valuable insights into the biodegradability of the fibers, thereby facilitating the selection of appropriate fibers for the development of environmentally sustainable products. Notably, a literature review revealed a paucity of research on fiber biodegradability, underscoring the significance of the present study’s contributions. Full article

This research aims to analyze the environmental impact of six fibers in the textile industry: conventional and organic cotton, silk, jute, flax, and polyester. The study used a life cycle assessment (LCA) methodology with a cradle-to-gate system boundary and analyzed the stages of agriculture, spinning, weaving, and dyeing. In agriculture production, five impact categories (i.e., fossil resource scarcity, global warming, land use, terrestrial ecotoxicity, and water consumption) have the most significant differences across these fibers. Polyester production significantly impacted the terrestrial ecotoxicity impact category, while stratospheric ozone depletion had a minor impact. In yarn preparation and spinning, silk has the most significant impact in most categories, followed by conventional cotton, while jute had the most minimal impact. In weaving, the most visible differences were in fossil resource scarcity, global warming, land use, terrestrial ecotoxicity, and water consumption. Conventional cotton dyeing showed significant impacts on global warming potential and terrestrial ecotoxicity. This study contributes to the limited literature on existing LCA research in the textile industry. Adding updated information will help increase the comprehension of LCA research and guide stakeholders in transitioning fashion supply chains more sustainably. Full article

Jute is a bio-degradable, agro-renewable, and widely available lingo cellulosic fiber having high tensile strength and initial modulus, moisture regain, good sound, and heat insulation properties. For these unique properties and eco-friendly nature of jute fibers, jute-based products are now widely used in many sectors such as packaging, home textiles, agro textiles, build textiles, and so forth. The diversified applications of jute products create an excellent opportunity to mitigate the negative environmental effect of petroleum-based products. For producing the best quality jute products, the main prerequisite is to ensure the jute yarn quality that can be defined by the load at break (L.B), strain at break (S.B), tenacity at break (T.B), and tensile modulus (T.M). However, good quality yarn production by considering these parameters is quite difficult because these parameters follow a non-linear relationship. Therefore, it is essential to build up a model that can cover this entire inconsistent pattern and forecast the yarn quality accurately. That is why, in this study, a laboratory-based research work was performed to develop a fuzzy model to predict the quality of jute yarn considering L.B, S.B, T.B, and T.M as input parameters. For this purpose, 173 tex (5 lb/spindle) and 241 tex (7 lb/spindle) were produced, and then L.B, S.B, T.B and T.M values were measured. Using this measured value, a fuzzy model was developed to determine the optimum L.B, S.B, T.B, and T.M to produce the best quality jute yarn. In our proposed fuzzy model, for 173 tex and 241 tex yarn count, the mean relative error was found to be 1.46% (Triangular membership) and 1.48% (Gaussian membership), respectively, and the correlation coefficient was 0.93 for both triangular and gaussian membership function. This result validated the effectiveness of the proposed fuzzy model for an industrial application. The developed fuzzy model may help a spinner to produce the best quality jute yarn. Full article