{'fraction_non_alphanumeric': 0.0269694819020582, 'fraction_numerical': 0.0191625266146203, 'mean_word_length': 5.238938053097345, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evaluating Weavability in Flax Yarn Using near Infrared Spectroscopy

The manufacture of linen fabrics depends on maintaining quality whilst maximising weaving efficiency. Problems often arise due to loom stoppages which are brought about by breaks in the warp yarns. For years researchers have attempted to bring about a full understanding of the mechanisms responsible. It is clear that weavability in flax yarn is primarily affected by chemical composition and structure, this is turn is affected by various steps in the production chain. In the search for objective methods for assessing flax yarn properties, instrumental techniques such as derivative thermogravimetric analysis (DTG), tensile testing and regularity have been developed. This investigation describes an attempt to construct relationships between these instrumental parameters taken from a range of flax yarns and near infrared (NIR) spectroscopy using partial least squares (PLS) regression analyses. Calibrations with DTG peak 1 weight loss (r2 0.83), regularity of thin and thick spots (r2 0.82, 0.81), nep counts (r2 0.82) and weaving breaks (r2 0.79) have all been produced. Using these relationships prediction equations for evaluating DTG peak 1 and 2 weight loss, regularity of thin spots on yarn and weaving performance (breaks per 10,000 picks) have been developed. These equations were validated using a blind set of flax yarn.