There is a substantial loss of value in bovine leather every year due to a leather quality defect known as “looseness”. Data show that 7% of domestic hide production is affected to some degree, with a loss of $35 m in export returns. This investigation is devoted to gaining a better understanding of tight and loose wet blue leather based on vibrational spectroscopy observations of its structural variations caused by physical and chemical changes that also affect the tensile and tear strength. Several regions from the wet blue leather were selected for analysis. Samples of wet blue bovine leather were collected and studied in the sliced form using Raman spectroscopy (using 532 nm excitation laser) and Attenuated Total Reflectance - Fourier Transform InfraRed (ATR-FTIR) spectroscopy. The purpose of this study was to use ATR-FTIR and Raman spectra to classify distal axilla (DA) and official sampling position (OSP) leather samples and then employ univariate or multivariate analysis or both. For univariate analysis, the 1448 cm− 1 (CH2 deformation) band and the 1669 cm− 1 (Amide I) band were used for evaluating the lipid-to-protein ratio from OSP and DA Raman and IR spectra as indicators of leather quality. Curve-fitting by the sums-of-Gaussians method was used to calculate the peak area ratios of 1448 and 1669 cm− 1 band. The ratio values obtained for DA and OSP are 0.57 ± 0.099, 0.73 ± 0.063 for Raman and 0.40 ± 0.06 and 0.50 ± 0.09 for ATR-FTIR. The results provide significant insight into how these regions can be classified. Further, to identify the spectral changes in the secondary structures of collagen, the Amide I region (1600–1700 cm− 1) was investigated and curve-fitted-area ratios were calculated. The 1648:1681 cm− 1 (non-reducing: reducing collagen types) band area ratios were used for Raman and 1632:1650 cm− 1 (triple helix: α-like helix collagen) for IR. The ratios show a significant difference between the two classes. To support this qualitative analysis, logistic regression was performed on the univariate data to classify the samples quantitatively into one of the two groups. Accuracy for Raman data was 90% and for ATR-FTIR data 100%. Both Raman and ATR-FTIR complemented each other very well in differentiating the two groups. As a comparison, and to reconfirm the classification, multivariate analysis was performed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The results obtained indicate good classification between the two leather groups based on protein and lipid content. Principal component score 2 (PC2) distinguishes OSP and DA by symmetrically grouping samples at positive and negative extremes. The study demonstrates an excellent model for wider research on vibrational spectroscopy for early and rapid diagnosis of leather quality.

中文翻译：

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用比色法和化学分析法对湿蓝色牛皮革的拉曼光谱和ATR-FTIR光谱分类

由于称为“松散度”的皮革质量缺陷，每年牛皮革的价值都会大量减少。数据显示，国内生皮产量的7％受到一定程度的影响，出口回报损失了3500万美元。这项研究致力于通过振动光谱学观察，了解由物理和化学变化引起的结构变化（也影响拉伸强度和撕裂强度），从而更好地理解紧绷和松散的湿蓝色皮革。从湿蓝色皮革中选择了几个区域进行分析。收集湿的蓝色牛皮革样品，并使用拉曼光谱（使用532 nm激发激光）和衰减全反射-傅立叶变换红外（ATR-FTIR）光谱以切片的形式进行研究。这项研究的目的是使用ATR-FTIR和拉曼光谱对腋下（DA）和官方采样位置（OSP）皮革样品进行分类，然后进行单变量或多变量分析或同时使用这两种方法。对于单变量分析，使用1448 cm-1（CH2变形）带和1669cm-1（Amide I）带评估OSP和DA拉曼光谱中的脂蛋白比，并使用IR光谱评估皮革质量。使用高斯和方法进行曲线拟合来计算1448和1669 cm-1谱带的峰面积比。对于DA和OSP，获得的比率值为0.57±0.099，对于拉曼来说为0.73±0.063，对于ATR-FTIR为0.40±0.06和0.50±0.09。结果为如何分类这些区域提供了重要的见识。此外，要确定胶原蛋白二级结构的光谱变化，研究了酰胺I区域（1600-1700 cm-1），并计算了曲线拟合面积比。拉曼光谱使用1648：1681 cm-1（非还原性：还原性胶原蛋白类型）的带面积比，红外光谱使用1632：1650 cm-1（三重螺旋：α样螺旋胶原）的条带面积比。比率显示出这两个类别之间的显着差异。为了支持这种定性分析，对单变量数据进行了逻辑回归，以将样本定量地分为两组之一。拉曼数据的准确度为90％，ATR-FTIR数据的准确度为100％。拉曼光谱和ATR-FTIR两者在区分这两个族群方面非常互补。作为比较并再次确认分类，使用主成分分析（PCA）和线性判别分析（LDA）进行了多变量分析。获得的结果表明，基于蛋白质和脂质含量，两个皮革组之间的分类良好。主成分评分2（PC2）通过在正极端和负极端处对样本进行对称分组来区分OSP和DA。该研究表明了一个极好的模型，可用于振动光谱的广泛研究，以早期和快速诊断皮革质量。