卷烟辅材与烟气指标和感官质量的相关性研究

为研究卷烟辅材与烟气指标和感官质量的相关性,对不同厂家、规格和批次的卷烟纸、接装纸、成型纸、滤棒等辅材组合下对应的卷烟进行烟气CO、烟气烟碱、焦油量的测定,并进行感官评吸。通过对结果的分析,分别得到以烟气CO、烟气烟碱、焦油量以及感官质量得分为指标,以辅材参数为自变量的多元线性回归模型。根据回归模型,以感官质量总得分为主要衡量标准,辅以卷烟烟气指标,期望感官质量总得分高,主要卷烟烟气指标与盒标值的残差接近于0,得出上述辅材的最优组合为JYZ1-KF卷烟纸、C2-MDJ成型纸、JZZ-2接装纸、LBDS-3滤棒、LBDS-2滤棒旦数。     

浅谈烟气含水率与卷烟感官质量相关性

梯度筛选不同的烟气含水率的卷烟样品,评价与分析样品感官质量的细腻性、刺激性、舒适性等各单项质量的指标变化情况,分析研究影响烟气含水率的主要因素。     

基于PLSR分析常规化学成分对市售卷烟感官品质的影响

为研究常规化学成分对市售卷烟感官品质特征的影响,采用偏最小二乘回归法(partial least square regression,PLSR)分析常规化学指标总糖、还原糖、烟碱、总氮等与卷烟感官品质的相关性。结果表明:总糖、还原糖、糖碱比与舒适感所有指标呈正相关;烟碱、总氮、钾与卷烟的舒适感特性呈负相关;钾氯比与口腔刺激/舌部灼烧和口腔残留/干燥感呈显著正相关。在卷烟的烟气特性中,总糖、还原糖、糖碱比与大部分烟气特性指标呈正相关;烟碱与丰富性呈显著负相关,与劲头呈显著正相关;钾氯比与杂气呈显著正相关。     

爆珠对细支卷烟物理指标及烟气舒适性的影响

为明确爆珠对细支卷烟物理指标和卷烟抽吸舒适性的影响,将香精滴制成细支卷烟用爆珠,并加入到滤棒中,进一步卷制成细支卷烟。分析爆珠对滤棒和细支卷烟物理指标的影响,进一步分析爆珠对细支卷烟的主流烟气成分和感官舒适性影响。结果表明,爆珠明显增大滤棒和烟支的吸阻,爆珠捏破后吸阻下降;爆珠成分进入烟气后会导致烟气焦油量上升,其他成分不受影响;爆珠对细支卷烟的感官舒适性有很好的提升效果,特别是天然提取物类的香料成分提升效果更好。     

基于遗传算法的卷烟主流烟气粒相物pH值影响因素研究

为研究影响烟气pH值的关键性烟丝化学成分,以国内代表性卷烟为研究对象,分别对样品的烟丝生物碱、糖、氨基酸、有机酸等化学成分含量及主流烟气粒相物pH值进行了测定。采用遗传算法结合偏最小二乘法,筛选出8个对烟气总粒相物pH值影响最大的化学指标,建立了烟气pH值与烟丝化学成分之间的定量关系模型。结果表明,烟丝丁酸、异戊酸、乙酰丙酸、苹果酸、葡萄糖和精氨酸可以降低卷烟烟气pH值,烟碱和异亮氨酸可以增加卷烟烟气pH值。本研究可为卷烟产品研发提供科学依据。      

基于感官符合度及卷烟纸参数的卷烟包灰性能改进研究

【目的】探究在保证感官品质稳定的前提下改进卷烟包灰性能的方法。【方法】以卷烟纸灰分含量等5个参数为因子,卷烟香气等4项感官指标、包灰值等3项包灰性能指标为变量,通过构建指标与参数间的回归模型、制定感官符合度控制限方法进行了包灰性能改进研究。【结果】（1）5个卷烟纸参数均为影响感官品质和包灰性能的重要因子,所建回归模型的决定系数介于0.944～0.999;(2)为保持感官品质稳定,总分及单项指标平均符合度应大于99.3%;(3)卷烟纸灰分含量、透气度、定量、助燃剂添加量和钾钠比分别21.5%、60 CU、33 g/m2、2.1%和2.0时,卷烟感官品质的总分及单项指标平均符合度均为99.88%,包灰性能3项指标显著改善。【结论】实现改进目标的关键是回归模型构建及感官符合度控制限的制定。     

卷烟主流烟气pH和粒相物pH的测定及与感官质量的关系

为比较卷烟主流烟气pH及主流烟气粒相物pH与卷烟感官质量间的相关程度,检测了20个卷烟感官标准样品的两种pH以及烟丝烟碱、总糖、还原糖、总氮、钾、氯等常规化学成分的质量分数;根据20个样品的标准评吸得分,采用简单相关分析、逐步回归分析等方法研究了两种pH以及常规化学成分与感官质量间的关系。结果表明:①主流烟气pH与卷烟感官质量的相关性大于主流烟气粒相物pH,且大于除还原糖外的其他常规化学成分。②20个卷烟感官标准样品的主流烟气pH在5.615~6.055之间变化,且表现出随感官质量得分升高而增大的变化规律。      

两段式滚筒烘丝机工艺参数优化研究

为了更好地利用两段式烘丝机,充分发挥其对卷烟感官质量的有利作用,选择"泰山"品牌中某一类卷烟,试验不同的工艺参数组合对烘后叶丝感官质量、理化指标等方面影响,优化两段式滚筒烘丝机的工艺参数,提升卷烟产品的感官质量。结果表明,在试验范围内,滚筒采用分区式烘丝,筒壁一区、二区温度相差12℃样品时,感官质量优于不分区感官质量,采用低强度分区干燥可以使泰山品牌的烟气细腻、柔和,舒适程度提高,香气较透发,余味改善,突出了产品风格和口味特征;主流烟气CO、焦油量释放量也略有降低。两段烘丝参数在生产应用后,卷烟感官质量明显提升。     

卷烟纸麻浆含量对卷烟感官质量的影响

通过感官评析分析不同麻浆含量的卷烟纸对卷烟感官质量的影响,基于主成分分析法筛选出影响度较大的感官指标,并进行相关的机理分析。研究结果发现,随着卷烟纸麻浆含量的上升,卷烟总体感官质量呈现先上升后下降的趋势;卷烟纸产生的香味物质或气味物质进入到主流烟气中,影响烟气的香气和余味;卷烟纸麻浆含量变化对烟气水分有影响,进而影响卷烟烟气的干燥感。     

卷烟烟气的毒理学指标与其重要有害成分之间的相关性

对22个牌号卷烟烟气的5项毒理学指标(MR值、SCE率、微核率、细胞死亡率和被动吸烟小鼠死亡率)和5项化学指标(焦油、烟碱、CO、TSNA和BaP)进行了相关分析和多元线性回归分析。结果表明:卷烟烟气生物效应与烟气中重要有害化学成分之间存在一定的相关性,其中TSNA是影响MR值、SCE率和细胞死亡率最重要的因素(P<0.01),而微核率和被动吸烟小鼠急性死亡率与焦油、烟碱、CO、TSNA、BaP均无相关性(P>0.05)。因此,大幅度降低卷烟烟气中的TSNA将有可能大大减少吸烟对健康的危害。     

Variable Selection in Visible and Near-Infrared Spectral Analysis for Noninvasive Determination of Soluble Solids Content of ‘Ya’ Pear

Informative variable selection or wavelength selection plays an important role in the quantitative analysis of near-infrared (NIR) spectra because the modern spectroscopy instrumentations usually have a high resolution and the obtained spectral data sets may have thousands of variables and hundreds or thousands of samples. In this study, a new combination of Monte Carlo–uninformative variable elimination (MC-UVE) and successive projections algorithm (SPA; MC-UVE-SPA) was proposed to select the most effective variables. MC-UVE was firstly used to eliminate the uninformative variables in the raw spectra data. Then, SPA was applied to determine the variables with the least collinearity. A case study was done based on the NIR spectroscopy for the non-destructive determination of soluble solids content (SSC) in ‘Ya’ pear. A total of 160 samples were prepared for the calibration (n?=?120) and prediction (n?=?40) sets. Three calibration algorithms including linear regressions of partial least square regression (PLS) and multiple linear regression (MLR), and nonlinear regression of least-square support vector machine (LS-SVM) were used for model establishment by using the selected variables by SPA, UVE, MC-UVE, UVE-SPA, and MC-UVE-SPA, respectively. The results indicated that linear models such as PLS and MLR were more effective than nonlinear model such as LS-SVM in the prediction of SSC of ‘Ya’ pear. In terms of linear models, different variable selection methods can obtain a similar result with the RMSEP values range from 0.2437 to 0.2830. However, combination of MC-UVE and SPA was helpful for obtaining a more parsimonious and efficient model for predicting the SSC values in ‘Ya’ pear. Twenty-two effective variables selected by MC-UVE-SPA achieved the optimal linear MC-UVE-SPA-MLR model compared with other all developed models by balancing between model accuracy and model complexity. The coefficients of determination (r ²), root mean square error of prediction, and residual predictive deviation by MC-UVE-SPA-MLR were 0.9271, 0.2522, and 3.7037, respectively.     

Development and interpretation of disinfection byproduct formation models using the Information Collection Rule database

Multiple linear regression models were used to examine relationships between water quality, treatment, and disinfection byproduct (DBP) formation in Information Collection Rule field data. Finished water models were specified using a cross-validation approach based on data for 225 free chlorine treatment plants. Turbidity, bromide, temperature, alkalinity, total organic carbon, ultraviolet absorbance at 254 nm, pH, chlorine residual, chlorine consumed, and chlorine contact time were employed as independent variables. Important trends within the trihalomethane, dihaloacetic acid, and trihaloacetic acid classes were observed. Bromide was a significant predictor for all DBP species and its influence changed in sign and magnitude with the extent of bromine substitution. A similar pattern followed by alkalinity suggested it plays an important role as an indicator of natural organic matter hydrophobicity and reactivity. Chlorine consumed and organic precursor variables were significant predictors in almost all DBP species models, exhibiting trends opposite to those for alkalinity and bromide. Temperature was the most significant variable in chloroform and chloral hydrate models and its significance declined with increasing bromine substitution within the trihalomethane class. pH had a strong positive influence on chloroform formation, a negative influence on trihaloacetic acid formation, and no influence on dihaloacetic acid formation.     

烤烟主要化学指标与感官舒适度的相关性分析

为了分析烤烟主要化学指标对其感官舒适度的影响,利用复相关系数分析方法对50个涵盖国内主要烟叶产区及进口烟叶原料的35个主要化学指标检测数据与感官舒适度评价数据进行分析与验证。结果表明,烤烟烟碱、氮碱比和糖碱比与感官舒适度整体上呈极显著相关(P<0.01),石油醚提取物含量与感官舒适度整体上呈显著相关(P<0.05),其余化学指标与感官舒适度10个指标得分的相关性统计上不显著(P>0.05);根据复相关系数的大小及显著性水平,烤烟主要化学成分对其感官舒适度的影响程度为:烟碱>氮碱比>糖碱比>石油醚提取物。     

基于PLSR分析酚类物质对市售卷烟感官品质的影响

为探究多酚物质对卷烟感官品质的影响,采用偏最小二乘回归分析法(PLSR)分析绿原酸、莨菪亭和芸香苷与卷烟感官品质的相关性。结果表明,绿原酸与口腔刺激/舌部灼烧、口腔残留/干燥感呈显著正相关;莨菪亭与收敛、喉部刺激呈显著负相关;芸香苷对卷烟的舒适感没有显著影响;在卷烟的烟气特性中,绿原酸与杂气呈显著正相关,绿原酸和莨菪亭与劲头呈显著负相关,芸香苷对烟气特征没有显著影响。     

利用图像分析仪评价馒头品质的研究

以我国小麦主产区的222份小麦制成的馒头为研究对象,进行了感官评价和图像分析仪C-Cell测试。以此为基础进行C-Cell参数聚类分析,将C-Cell的34个特征参数聚为4类,筛选出了11个代表性特征参数。初步探索了馒头仪器评价和感官评价之间的关系,结果表明：C-Cell特征参数与感官评价指标存在一定的相关性,切片面积、周长和切片亮度与内部结构、感官总分的相关性较好,都呈极显著正相关;而气孔对比度、气孔密度、粗糙气孔体积及粗细气孔比都与馒头感官总分呈显著或极显著负相关。回归分析得到了以C-Cell特征参数为自变量的馒头感官评分的回归方程,为客观评价馒头品质提供了参考。     

两种新型多羟基类保润化合物的合成及应用

以D-甘露糖（Ⅰ）为原料,成功合成了两种新型多羟基类保润产品分别是1-O-羧甲基-D-呋喃甘露糖（Ⅴ）和1-O-羟乙基-D-吡喃甘露糖（Ⅶ）,利用IR,1H-NMR和13C-NMR证实了每步产物的结构。以D-甘露糖、丙二醇、甘油和山梨醇为对照,以烟丝含水率为指标对Ⅴ和Ⅶ的物理保润性能进行评价,并以卷烟感官舒适度验证其在卷烟中的应用效果。结果表明:①目标产物Ⅴ和Ⅶ最终总产率分别是56.2%和50.6%;②Ⅴ的保湿性能优于丙二醇、甘油和山梨醇传统保润剂,Ⅶ的保湿能力略差于丙二醇,但优于甘油和山梨醇;③Ⅴ和Ⅶ具有使卷烟烟气圆润、柔和,减少刺激性和杂气,提升口感舒适性的作用。      

Influence of sensory characteristics on the acceptability of dry-cured ham

The influence of different sensory attributes on the acceptability of dry-cured Iberian ham was studied. Partial least squares regression analysis showed that juiciness and several flavour traits were the major attributes positively influencing acceptability of dry-cured Iberian ham, whereas yellowness of the fat, dryness and fibrousness showed a negative influence. Using stepwise multivariate regression, juiciness and flavour intensity were the two traits that better explained the acceptability of dry-cured ham, the linear model obtained showing a regression coefficient of 0.526. The regression coefficient of acceptability with juiciness and flavour intensity was higher using a piecewise linear regression model (R²=0.759) showing, therefore, a discontinuous relationship between these variables. However, results on product acceptability have been obtained using trained panellists and it might be possible that the use of a consumer panel would change these conclusions.     

A Novel Technique on Determining Water Content in Milk Using Radio-Frequency/Microwave Dielectric Spectroscopy and Chemometrics

Water is the major component of milk. More water means less total solids concentration. Therefore, routine analysis on water content is very important in milk factory. To offer a new method for determining water content of milk in situ and in-line quality monitoring, dielectric spectroscopy, an instrumental method used to obtain spectra describing dielectric properties of materials, was used to determine the water content of milk in this study. The dielectric spectra of 161 milk samples were obtained at 201 discrete frequencies on a logarithmic scale from 20 to 4500 MHz at 25 °C. Ten, 34, and 14 optimal dielectric variables (ODVs) were extracted from the full dielectric spectra (FDS) with 402 dielectric variables by using successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and combination of CARS and SPA (CARS + SPA), respectively. Four models, including two linear models, i.e., multiple linear regression (MLR) and partial least squares regression (PLSR), and another two artificial neural network models, i.e., extreme learning machine (ELM) and least squares-support vector machine (LSSVM), were established. The artificial neural network models had better prediction performance than the linear models at the same ODV selection methods. Moreover, the ODVs extracted by CARS could give better prediction performance than SPA and CARS + SPA. Among all developed models, the FDS-LSSVM model had the lowest root mean squares error of prediction set (0.054%), followed by CARS-LSSVM with 0.094%. Few variables and high prediction precision of CARS-LSSVM have great potential in developing portable milk water detector used in situ and in-line inspection. This study indicated that dielectric spectroscopy is a promising approach for accurately determining the water content of milk.