傅里叶变换在纳米纤维取向测量中的应用

取向的纳米纤维具有良好的力学性能、尺寸稳定性,并有利于细胞的黏附和增殖,其性能随纤维取向程度的提高而改善。而纳米纤维的取向特征可过电镜图像FFT变换的频谱图来反映[1-2]。本文采用此方法以FFT频谱图一定半径的圆区域为对象,分不同的方向角沿半径对灰度求和,描绘出FFT频谱图谱强度随方向角的分布曲线。再通过曲线拟合获取峰值曲线特征,描述纳米纤维的取向效果。     

应用一维傅里叶变换的剖幅区自动识别与定位

针对纺织行业布匹剖幅机工作过程中,剖幅区的识别定位仍由人工完成的现状,提出一种可行的剖幅区自动识别定位方法,以降低工人劳动强度,提高布匹剖幅速率和准确率。这种方法基于成像式自动检测技术,应用一维傅里叶变换提取剖幅区频域特征来对其进行识别与定位,并利用VC++编写定位软件对该方法进行测试。结果表明,应用一维傅里叶变换的成像式定位方法可快速、准确地实现剖幅区自动识别与定位,提高剖幅机的工作效率和可靠性。     

图像检测非织造材料纤维取向的主因素探讨

为研究图像处理过程中影响纤维取向检测结果的因素,以模拟的非织造纤网为研究对象,采用二维离散傅里叶变换技术(DFT),提取纤网中的纤维取向分布形态,重点探讨图像处理过程中阈值选取和形态处理对纤维取向检测结果的影响.结果表明:图像灰度分布均匀性不理想时,采用Otsu法选取的阈值分割效果最佳,能够较准确地分析纤维取向,当目标...     

织造对不同结构光纤织物侧发光性能的影响

利用织造对光纤的损伤,制备结构简单、手感柔软的发光面料。通过探讨织造过程中光纤的损伤机理,比较不同组织结构光纤织物的侧发光强度,结果表明：织造对光纤的损伤主要发生在卷取过程中,光纤的侧发光主要是由于卷取轴的挤压和摩擦产生的破坏;不同组织织物的侧发光强度存在明显差异,其中平纹织物侧发光强度最小,纬缎织物最大;随着缎纹组织循环的增大,侧发光强度有增大趋势,但当增大到16枚纬缎时,与卷轴接触的光纤增加不明显,对发光的影响较小,这时光纤的弯曲起主导作用,因此从发光效果来看,16枚纬缎是较佳的选择。     

织物傅里叶变换衰减全反射红外光谱库的建立及应用

针对常规方法鉴别纯纺织物及预测混纺织物组分含量工序多、耗时长且污染环境的问题,采用傅里叶变换红外光谱仪,结合衰减全反射(ATR)附件测试各纯纺及二组分混纺织物的傅里叶变换衰减全反射红外光谱(ATR-IR)图,并从已测的753个样品中筛选出正反经纬组分一致的纯纺及混纺织物样品205个,建立了涤纶/棉、涤纶/羊毛、涤纶/锦纶、蚕丝/棉和涤纶/粘胶等纯纺及混纺织物的ATR-IR谱库。并利用自建谱库的检索功能,对20个未知纤维织物样品进行快速无损鉴别及含量预测。研究表明:对于纯纺织物,识别准确率为100%;对于混纺织物,当误差≤3% 时,通过T检验,其定量预测结果与国标法测定值无显著差异,方便了样品的快速检验与含量预测。     

利用模糊C-均值聚类分析法实现织物组织结构自动识别

文章提出了一种新的有效的织物组织结构识别算法.用彩色扫描仪输入紧密织物组织的灰度图像并将其转换为数字文件,然后通过灰度图像形态学处理获得增强图像.基于纱线间隙和经纬纱交叉区的存在,通过一阶和二阶的统计量可获取4种区域结构特征.利用模糊C-均值聚类分析法得出识别经纬浮点的非监督的判别准则.实验材料包括平纹、斜纹和缎纹织物,实验结果表明这3种基础组织结构模式可以得到有效识别.     

Selection for milk coagulation properties predicted by Fourier transform infrared spectroscopy in the Italian Holstein-Friesian breed

Milk coagulation is based on a series of physicochemical changes at the casein micelle level, resulting in formation of a gel. Milk coagulation properties (MCP) are relevant for cheese quality and yield, important factors for the dairy industry. They are also evaluated in herd bulk milk to reward or penalize producers of Protected Designation of Origin cheeses. The economic importance of improving MCP justifies the need to account for this trait in the selection process. A pilot study was carried out to determine the feasibility of including MCP in the selection schemes of the Italian Holstein. The MCP were predicted in 1,055 individual milk samples collected in 16 herds (66 ± 24 cows per herd) located in Brescia province (northeastern Italy) by means of Fourier transform infrared (FTIR) spectroscopy. The coefficient of determination of prediction models indicated moderate predictions for milk rennet coagulation time (RCT = 0.65) and curd firmness (a₃₀ = 0.68), and poor predictions for curd-firming time (k₂₀ = 0.49), whereas the range error ratio (8.9, 6.9, and 9.5 for RCT, k₂₀, and a₃₀, respectively) indicated good practical utility of the predictive models for all parameters. Milk proteins were genotyped and casein haplotypes (α_S1-, β-, α_S2-, and κ-casein) were reconstructed. Data from 51 half-sib families (19.9 ± 16.4 daughters per sire) were analyzed by an animal model to estimate (1) the genetic parameters of predicted RCT, k₂₀, and a₃₀; (2) the breeding values for these predicted clotting variables; and (3) the effect of milk protein genotypes and casein haplotypes on predicted MCP (pMCP). This is the first study to estimate both genetic parameters and breeding values of pMCP, together with the effects of milk protein genotypes and casein haplotypes, that also considered k₂₀, probably the most important parameter for the dairy industry (because it indicates the time for the beginning of curd-cutting). Heritability of predicted RCT (0.26) and k₂₀ (0.31) were close to the average heritability described in literature, whereas the heritability of a₃₀ was higher (0.52 vs. 0.27). The effects of milk proteins were statistically significant and similar to those obtained on measured MCP. In particular, haplotypes including uncommon variants showed positive (B-I-A-B) or negative (B-A¹-A-E) effects. Based on these findings, FTIR spectroscopy-pMCP is proposed as a potential selection criterion for the Italian Holstein.     

Determination of degree of substitution of carboxymethyl starch by Fourier transform mid-infrared spectroscopy coupled with partial least squares

The degree of substitution (DS) markedly affects the properties of carboxymethyl starch (CMS). The conventional methods for the DS determination are time-consuming and not environment friendly. Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with partial least squares (PLS) regression is applied to determine the DS of CMS in the present study. Calibration models with direct titration as the reference method were optimised by cross validation. A PLS regression model with a coefficient of determination (R²) of 0.9593 and root-mean-square error of cross validation (RMSECV) of 0.0141 was obtained in the spectral range from 500 to 4000 cm⁻¹. The prediction set gave a coefficient of determination (R²) and root-mean-square error of prediction (RMSEP) of 0.9368 and 0.0228, respectively. The results obtained in this study indicate that FT-MIR spectroscopy can be used as an easy, rapid, and novel tool to quantitatively predict the DS of CMS.     

GC-MS结合模式识别评价鱼新鲜度的研究

目的 对鱼新鲜度进行客观评价。方法 用顶空固相微萃取气相色谱质谱联用(HS-SPME-GC-MS)检测不同储藏时间下鱼的挥发性成分, 建立鱼肉挥发性物质的特性指纹图谱, 利用模糊C均值聚类法(FCM)分析特征共有峰。为验证聚类分析的结果, 建立鱼新鲜度神经网络判别模型。结果 FCM能较好地将贮藏9 d的鱼可分成3类(新鲜、次新鲜和腐败), 建立的RBF神经网络模型能很好鉴别鱼的新鲜度, 其训练集和测试集的正确分类率都达到100%。结论 此方法效果好, 为分析和检验鱼新鲜度提供了一种新的方法。     

纤维组分与针织组织对半精纺针织物服用性能的影响

针对半精纺纱的纤维组成复杂,针织组织结构各异,选用4种典型的多组分配比的半精纺纱和4种常规的针织组织,利用正交试验法分析纤维组分与针织组织对半精纺针织物服用性能的影响.研究结果表明:纤维组分与针织组织对半精纺针织物服用性能的各项指标有不同程度的影响,在设计针织服装时应该有针对性地选用半精纺纱和针织组织,以实现理想效果.     

Caprine CSN1S1 haplotype effect on gene expression and milk composition measured by Fourier transform infrared spectroscopy

The Norwegian dairy goat population has a high frequency of a CSN1S1 (α_S1-casein) haplotype with negative effects on protein and fat content. It is characterized by a single point deletion in exon 12 of CSN1S1, leading to a truncated protein and hence a low content of α_S1-casein in the milk. This haplotype together with another haplotype with a deletion in exon 9 are called “weak” haplotypes. “Strong” haplotypes, on the other hand, have positive effects on important milk production traits. We show that expression of CSN1S1 in the mammary gland of lactating goats is significantly lower in animals with 2 weak haplotypes. Moreover, the effects of defective alleles were not detected in animals having 1 strong and 1 weak haplotype. Expression levels of other genes in the casein cluster were not affected by the CSN1S1 haplotypes investigated. Milk samples from goats with 2 weak haplotypes could be distinguished from the other milk samples using Fourier transform infrared (FTIR) spectroscopy and partial least squares discriminant analysis (PLS-DA). The PLS-DA components were related to spectra of pure caseins and whey proteins, hence FTIR has a potential for identifying milk samples with low α_S1-casein content and different protein composition. The results indicate that FTIR-based measurements can be incorporated into breeding plans, or for selection of milk samples with high casein content, which in turn may improve cheese-making properties of the milk.     

Discrimination between immature and mature green coffees by attenuated total reflectance and diffuse reflectance Fourier transform infrared spectroscopy

The objective of this work was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) in the characterization and discrimination between immature and mature or ripe coffee beans. Arabica coffee beans were submitted to FTIR analysis by reflectance readings employing attenuated total reflectance (ATR) and diffuse reflectance (DR) accessories. The obtained spectra were similar, but in general higher absorbance values were observed for nondefective beans in comparison to immature ones. Multivariate statistical analysis (principal component analysis, PCA, and agglomerative hierarchical clustering, AHC) was performed in order to verify the possibility of discrimination between immature and mature coffee samples. A clear separation between immature and mature coffees was observed based on AHC and PCA analyses of the normalized spectra obtained by employing both ATR and DR accessories. Linear discriminant analysis was employed for developing classification models, with recognition and prediction abilities of 100%. Such results showed that FTIR analysis presents potential for the development of a simple routine methodology for separation of immature and mature coffee beans. Practical Application: The ultimate goal of this research is to be able to propose improvements in the way immature coffee beans are separated from graded mature beans in coffee facilities (cooperatives and other coffee producer's associations). The results obtained herein point toward FTIR as a potential tool for the aimed improvements.     

Authentication of pure camellia oil by using near infrared spectroscopy and pattern recognition techniques

Abstract: Total of 4 pattern recognition methods for the authentication of pure camellia oil applying near infrared (NIR) spectroscopy were evaluated in this study. Total of 115 samples were collected and their authenticities were confirmed by gas chromatography (GC) in according to China Natl. Standard (GB). A preliminary study of NIR spectral data was analyzed by unsupervised methods including principal component analysis (PCA) and hierarchical cluster analysis (HCA). Total of 2 supervised classification techniques based on discriminant analysis (DA) and radical basis function neural network (RBFNN) were utilized to build calibration model and predict unknown samples. In the wavenumber range of 6000 to 5750 cm^?1, correct classification rate of both supervised and unsupervised solutions all can reach 98.3% when smoothing, first derivative, and autoscaling were used. The good performance showed that NIR spectroscopy with multivariate calibration models could be successfully used as a rapid, simple, and nondestructive method to discriminate pure camellia oil.