Near Infrared Reflectance Spectroscopy as a Tool for the Determination of Dichloromethane Extractable Matter and Moisture Content in Combed Wool Slivers
Notice bibliographique
Résumé
In the wool textile field the quantitative determination of solvent extractable matter and moisture content is a crucial analysis for the evaluation of combed sliver quality. The test carried out includes the acquisition of a series of data about dichloromethane soluble matter (according to the International Wool Textile Organisation—IWTO 10–01 specification), and moisture content in combed wool slivers and the search for a correlation between these data and the near infrared spectra of samples. Combed wool slivers tested were of different origins and variable mean diameters and were obtained from different combing mills in the industrial district of Biella, the principal wool textile region of Italy. The spectrophotometer used was a FT-NIR system (Perkin-Elmer Spectrum IdentiCheck). Spectra were collected in the region from 3700 to 10,000 cm −1 in reflection mode. The extraction of greasy matter from wool tops was carried out with a continuous extraction technique on a 10 g wool sample with a total extraction time of about 3 hours in a soxhlet apparatus. The results express the weight (obtained by the mean of two determinations) of the dichloromethane soluble extract as a percentage of the dry weight of the de-greased sample. For the determination of dichloromethane extractable matter, 103 samples were used for calibration. Some wool samples were deliberately under-scoured and others were re-scoured in a combing mill in order to obtain a wide range of data, ranging from 1.15% to 0.21%. Spectra were analysed using Quant+ (Perkin-Elmer Software). The best results were obtained with the PLS1 (Partial Least Square) algorithm when considering the spectral region 9000–3800 cm −1 [Standard Error of Prediction ( SEP) = 0.1042, mean value ( M) = 0.6963%, Coefficient of Determination ( R 2 ) = 0.85]. A cross-validation was used. The determination of moisture content in combed wool sliver was performed by drying wool (80 g for a single determination) in an oven to constant weight using forced air at 105 ± 2°C. 85 samples were used for the calibration. Deliberate variations in regain were induced by exposing the wool to a dry or moist atmosphere. In this way moisture contents ranging from 9% to 15% were obtained. NIR spectra were analysed using Quant+ Software. A cross-validation was used. The best results were obtained with the Principal Component Regression algorithm when considering the spectral region 9000–3800 cm −1 . A SEP of 0.4954 ( M = 11.76%) and a R 2 of 0.90 were found. A limited number of determinations of grease and moisture content were carried out using the models obtained and compared with values determined manually.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».