Assessing and predicting the softness of hygiene tissue containing alternative fibers

Abstract

Softness, a key attribute in hygiene tissue, has traditionally been determined via consumer panel tests. These collective tests involve trained judges (panelists) who express their subjective judgments of softness to rank and compare hygiene tissue products, which become time and resource-intensive measurements. The tissue softness analyzer (TSA, Emtec, Germany) has been utilized to measure softness in uncreped handsheets with conventional fibers, but it fails to assess products with alternative fibers accurately. As a single-frequency parameter, the so-called TS7 value from the TSA does not capture the full range of acoustic properties that contribute to the perceived softness of uncreped hygiene tissue containing alternative fibers. In this work, we developed and validated a rigorous statistical model capable of quantitatively, accurately, and reproducibly predict softness for uncreped tissue paper containing non-wood fibers, including agricultural residues (e.g., wheat straw) and dedicated fiber crops (e.g., miscanthus, switchgrass, sorghum and bamboo). Softness panel test scores were collected using a novel technique for sensory assessment, the Optimized Sensory Panel Test (O-SPT), which employs Thurstone’s Law of Comparative Judgement. The model was built by integrating softness values (handfeel scores) from panel tests, along with the physical and morphological properties of both wood-derived and non-wood fibers. The model demonstrated 98% accuracy in predicting softness compared to panel tests scores. The results will provide valuable tools for softness prediction that will be beneficial for product development in the hygiene tissue industry.

Graphical abstract

Methodology to develop and validate a rigorous statistical model that can quantitatively accurately, and reproducibly predict softness for hygiene tissue containing alternative fibers