A waveguide technique for non-destructive determination of egg quality parameters

The input of a waveguide probe for shell eggs was connected to a sinewave sweeper oscillator and the signal at the output was captured by a spectrum analyser. A first analysis was carried out in the range from 3 to 20 GHz with a span of 1 GHz to investigate which 1 GHz frequency range contains most information for predicting the main quality indices of eggs during 15 days of storage. Simple linear regression models were therefore set up and the coefficient of determination was calculated. The absorbance spectra in the range thus identified (from 10.5 to 11.5 GHz) were used to predict the quality indices by means of an artificial neural network (ANN). The R² values of the obtained ANN in validation mode were 0.918, 0.854 and 0.912 for the air cell, the thick albumen height and the yolk index, respectively. The correlations between the quality parameters and tests carried out on albumen, yolk and plastic eggs for simulating the air cell showed how one index can be indirectly predicted through another one.     

Real-time monitoring of alcalase hydrolysis of egg white protein using near infrared spectroscopy technique combined with efficient modeling algorithm

The degree of hydrolysis is one of the most important indexes for process control and quality assessment in proteins enzymatic hydrolysis. This article proposed a simple and rapid near infrared spectroscopy method for real-time quantifying the degree of hydrolysis in alcalase hydrolysis process. Efficient variables selection algorithms were systemically studied in multivariate calibrations; the partial least squares coupled with uninformative variables elimination and ant colony optimization were proposed for modeling with results yielding Rp = 0.9525. Additionally, 10 independent samples with the relative error less than 10% further confirmed the stability and reliability of this method. This work demonstrated that the near infrared spectroscopy technique with a selected multivariate calibration has a high potential for in situ monitoring of alcalase hydrolysis process in protein industry.     

Determination of egg content in egg pasta by an indirect elisa procedure

Polyclonal antibodies have been raised against a highly purified egg yolk protein, which appears to be unaffected by thermal treatments and whose content is constant in eggs of different origin. The antibodies are able to bind specifically to the egg yolk protein and can be used for the quantification of the egg content in egg pasta. For this purpose an indirect ELISA procedure has been developed.     

生鲜猪肉水分含量的快速无损检测

目的 研究生鲜猪肉水分含量与1000~1680 nm范围内近红外吸收光谱之间的关系, 对生鲜肉的水分含量进行快速无损检测。方法 将原始光谱经中值平滑、多元散射校正和一阶导数复合预处理, 结合多元线性回归和偏最小二乘回归两种建模方法建立生鲜肉水分含量的预测模型。结果 应用所建立的模型对111个实际生鲜猪肉样品的水分含量进行预测, 得到较为满意的预测结果, 两种模型的预测相关系数分别为0.839和0.810。结论 所建模型适合于生鲜猪肉水分的无损快速检测。     

近红外光谱法测定混合汁中还原糖含量

采用近红外光谱法测定混合汁中还原糖含量 ,获得良好效果 ,所建模型标准误差小而决定系数高。定标决定系数 R2 、交互定标标准误差 (SECV)、交互定标决定系数 (1-VR)分别为 0 .95 1,0 .0 74 ,0 .85 0 ,具有较好的相关性。用 5 2个随机混合汁样品检验该模型 ,近红外法预测结果与传统滴定法测定结果的检验工作标准误差 (SEP(C) )为 0 .0 75 ,检验决定系数 RSQ为 0 .85 0 ,证明测定所建近红外法定标模型具有较好的稳定性。     

Variable selection for partial least squares analysis of soluble solids content in watermelon using near-infrared diffuse transmission technique

This work is focused on the variable selection in building the partial least squares (PLS) regression model of soluble solids content (SSC) that is used to evaluate quality grading of watermelon. The spectra were obtained by the near infrared (NIR) spectrometer with the device designed for on-line quality grading of watermelon and the spectra of 680–950 nm were adopted to analysis. The variable selection was based on Monte-Carlo uninformative variable elimination (MC-UVE) and genetic algorithm (GA). In comparison of the performances of the full-spectra (680–950 nm) PLS regression model and the feature wavelengths PLS regression model showed that the MC-UVE–GA–PLS model with baseline offset correction combined multiplicative scatter correction (MSC) pretreatment was much better and 14 variables in total were selected. The correlation coefficients between the predicted and actual SSC were 0.885 and 0.845, the root mean square errors were 0.562 °Brix and 0.574 °Brix for calibration and prediction set, respectively. This work can make a great contribution to the research of on-line quality grading for watermelon nondestructively.     

Growth of Listeria monocytogenes in egg salad and pasta salad formulated with mayonnaise of various pH and stored at refrigerated and abuse temperatures

This study investigated and modeled the behavior of Listeria monocytogenes in egg salad and pasta salad as affected by mayonnaise pH (3.8, 4.2, 4.6, and 5.0) and storage temperature (4, 8, and 12 degrees C). At each storage temperature, L. monocytogenes was able to grow in both salads regardless of the mayonnaise pH. The lag-phase durations (LPD) of L. monocytogenes in egg salad ranged from 33 to 85, 15 to 50, and 0 to 19 h, and the growth rates (GR) ranged from 0.0187 to 0.0318, 0.0387 to 0.0512, and 0.0694 to 0.1003 log(10)cfu/h at 4, 8, and 12 degrees C, respectively. The LPD of L. monocytogenes in pasta salad ranged from 210 to 430, 49 to 131, and 21 to 103 h, and GR ranged from 0.0118 to 0.0350, 0.0153 to 0.0418, and 0.0453 to 0.0718 log(10)cfu/h at 4, 8, and 12 degrees C, respectively. The growth of L. monocytogenes was more rapid in egg salad than in pasta salad, indicating that a better growth environment for L. monocytogenes existed in egg salad. In both salads, the LPD decreased and the GR increased as the storage temperature increased. Mathematical models and response surface plots describing the LPD and GR of L. monocytogenes in both salads as affected by the mayonnaise pH and storage temperature were developed. The models confirmed that the growth of L. monocytogenes in egg salad and pasta salad was primarily promoted by higher storage temperatures and, secondarily, by higher mayonnaise pH. The conditions under which the models may be applied to estimate the growth of L. monocytogenes in both salads were identified.     

用混合线性分析法建立苹果糖度近红外光谱预测模型

用混合线性分析法的一种变形算法建立了苹果糖度近红外光谱预测模型，并与偏最小二乘模型进行比较。结果表明：虽然最佳的混合线性分析法模型（18个主因子）比最佳偏最小二乘模型（11个主因子）复杂．但其精度却明显优于偏最小二乘模型：利用梗正集的28个苹果样本建立的糖度混合线性分析法校正模型，其相关系数r^2和标准偏差SEC分别为0．92509和0．40618；该校正模型经预测集的11个样本验证，相关系数r^2和标准偏差SEP分别达到0.87611和0．48480。混合线性分析法建立的糖度模型对苹果光谱的校正标准偏差SEC和预测标准偏差SEP分别比PLS法的SEC（0．41473）和SEP（0．50473）减小了2％和3．9％。结果表明：在诸如苹果糖度这一类农产品品质综合指标（非纯组分含量指标）的光谱检测中，应用混合线性分析法进行定量分析是完全可行的。并且其结果可与偏最小二乘法（PLS）的结果相媲美。     

Rapid measurement of total acid content (TAC) in vinegar using near infrared spectroscopy based on efficient variables selection algorithm and nonlinear regression tools

Total acid content (TAC) is an important index in assessing vinegar quality. This work attempted to determine TAC in vinegar using near infrared spectroscopy. We systematically studied variable selection and nonlinear regression in calibrating regression models. First, the efficient spectra intervals were selected by synergy interval PLS (Si-PLS); then, two nonlinear regression tools, which were extreme learning machine (ELM) and back propagation artificial neural network (BP-ANN), were attempted. Experiments showed that the model based on ELM and Si-PLS (Si-ELM) was superior to others, and the optimum results were achieved as follows: the root mean square error of prediction (RMSEP) was 0.2486 g/100mL, and the correlation coefficient (R(p)) was 0.9712 in the prediction set. This work demonstrated that the TAC in vinegar could be rapidly measured by NIR spectroscopy and Si-ELM algorithm showed its superiority in model calibration.     

The effect of varying fat content on the microstructure of Oaxaca cheese,a typical pasta filata cheese

The effect of varying fat content in Oaxaca cheese, a typical pasta filata, on microstructure was described. Microstructure of cheeses was analysed by scanning electron microscopy (SEM) and light microscopy (LM) in nondehydrated and dehydrated samples. In nondehydrated samples, protein fibres were wide and compact in fat‐free cheese, and big serum channels were approximately 100 μm in width. Width of protein fibres and size of channels decreased as fat content increased. Small channels seemed to be occupied only by fat, while in big channels, water and fat were observed. LM both confirmed and supplemented the observations made by SEM, particularly the presence and distribution of fat in channels.     

FT-NIR spectroscopy for caffeine estimation in instant green tea powder and granules

The feasibility of measuring caffeine content in instant green tea and granules was investigated by Fourier Transform Near-Infrared (FT-NIR) spectroscopic technique. A calibration model was developed using pure caffeine standards of varying concentrations in the near-infrared region (4000-12000 cm⁻¹). The developed model was validated using test validation technique. FT-NIR spectroscopy with chemometrics, using the PLS-first derivative plus straight line subtraction method could predict the caffeine content in tea samples accurately up to an R² value greater than 0.98 and a standard error of prediction (SEP) value less than 2.0 with 6 factors in the prediction model. The developed model was applied to predict caffeine content in tea samples within 2-5 min. The developed procedure was further validated by recovery studies by comparing with UV spectroscopic method of caffeine determination.     

Direct determination of polymerised triacylglycerides in deep-frying vegetable oil by near infrared spectroscopy using Partial Least Squares regression

A green method for the determination of polymerised triacylglyceride (PTG) in deep-frying vegetable oils of different botanic origin has been developed employing near infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression. Four different types of oil were heated during several hours, with and without the addition of foodstuff. NIR transmission spectra were obtained directly from sample aliquots stored in glass vials, thus avoiding the consumption of solvents and minimising waste generation. Variables employed for building the PLS models were selected applying interval PLS (iPLS) as well as Uninformative Variable Elimination-PLS (UVE-PLS). A global PLS model using spectra of all four types of oils was compared to PLS models established for each oil type. Due to the small differences observed in the NIR spectra that can be related to the different botanic origin and results obtained from the PLS model comparison, the use of a global PLS model is recommended leading to prediction errors of 2.28% (w/w) for the determination of PTG in oils employed for frying different kinds of foods.     

基于数字光处理技术的梨可溶性固形物含量的无损速测研究

目的为降低近红外光谱仪器制造成本,将近红外技术推广到农业生产一线,检验自主集成水果品质无损快速分析仪实验样机性能。方法以北京大兴产黄金梨、园黄梨为例,利用基于数字光处理技术内核的实验样机采集数据,采用偏最小二乘回归结合全交互验证算法分别建立黄金梨、园黄梨以及两种梨的可溶性固形物含量定量校正模型,并采用外部验证集对模型预测性能做进一步验证。结果黄金梨、园黄梨以及两种梨的可溶性固形物含量模型的测定系数R~2分别为0.6136、0.6576、0.5105,RMSEC分别为0.71、0.79、0.87:交互验证测定系数R~2_(CV)分别为0.5332、0.5076、0.4193,RMSECV分别为0.78、0.96、0.95;外部验证集相关系数r分别为0.7239、0.6825、0.6550,RMSEP分别为0.83、1.03、0.94。结论基于数字光处理技术内核自主集成的水果品质无损快速分析仪器在梨可溶性固形物含量的无损速测以及降低仪器制造成本方面具有一定的应用潜力。     

On-line monitoring of fat,dry matter and acrylamide contents in potato chips using near infrared interactance and visual reflectance imaging

The contents of dry matter, oil and acrylamide are some of the most relevant parameters in the quality control of potato chips. Near infrared spectroscopy (NIR) is a common technique for routine analysis of bulk chemistry in different raw materials and products because it allows a fast and non-destructive analysis of samples. The objective of this research was to investigate the possibilities of using on-line NIR monitoring of acrylamide, moisture and oil content in potato chips. Sixty samples of potato chips from individual frying runs were measured on-line using a VIS/NIR interactance line scanner. The same samples were analysed in the laboratory to determine their corresponding moisture, acrylamide and oil contents. The mean VIS and NIR spectra for the 60 samples were modelled against the reference values for acrylamide, fat and dry matter using partial least squares regression (PLSR), and the regression models were validated using full cross-validation. On-line NIR interactance was found to predict fat and dry matter of potato chips with high accuracy, i.e. prediction errors of 0.99 and 0.86% (w/w), respectively. The corresponding correlations between predicted values and reference values were 0.99 and 0.97 for fat and dry matter. For acrylamide an average prediction error of 266 μg/kg was achieved using NIR and VIS signals in combination. The correlation between predicted values and reference values was 0.83 for this model. The system may be used to separate samples with very high acrylamide contents from samples with average to low contents.     

谈谈茶叶中茶多酚的药理保健功效

茶多酚作为茶叶品质检测的重要指标之一,利用近红外光谱分析技术对茶多酚含量进行快速检测具有重要意义。本文以144个红茶样品作为研究对象,采取近红外光谱法结合偏最小二乘法（Partial Least Squares, PLS）,分别建立粉末状茶叶样品和完整茶叶样品的茶多酚含量的近红外快速分析模型。结果表明,选用SNV+一阶导数+Savitzky-Golay平滑的预处理方法结合PLS建立的预测模型效果最佳,粉末状茶叶样品所建立模型训练集相关系数（Correlation Coefficient,r）为0.9990,训练集均方根误差（Root Mean Square Error of Calibration, RMSEC）为0.165%,预测集的r为0.9243,预测集均方根误差（Root Mean Square Error of Prediction, RMSEP）为0.972%;完整茶叶样品训练集r为0.9967,RMSEC为0.310%,预测集的r为0.9541,RMSEP为0.870%。结果表明,完整茶叶样品所建立的PLS定量分析模型要优于粉末状茶叶所建立的模型。因此,利用近红外光谱技术可实现对红茶中茶多酚含量的快速、无损检测。     

快速酒精仪在黄酒酒精度分析中的应用

通过与GB/13662—2008《黄酒》中的酒精度检测方法相比较,研究了近红外酒精分析仪法的准确性和稳定性,并且研究了总糖、浊度和色度对该方法的影响。结果表明,与国标检测方法相比,近红外酒精分析仪法操作简单、快速,并且重复性和准确性都更高。     

京郊鲜食杏白利糖度的便携式光谱快速无损检测方法研究

目的建立京郊鲜食杏白利糖度的定量分析预测模型,实现对京郊鲜食杏品质的快速无损检测。方法使用便携式近红外光谱仪采集900～1700 nm下鲜食杏的漫反射光谱信息,使用多元散射校正(multiplicative scatter correction,MSC)、标准正态变量变换(standard normal variable transformation,SNV)和Savitzky-Golay卷积平滑(Savitzky-Golay smooth,S-G)对原始光谱数据进行预处理,使用Kennard-Stone (K-S)算法以3:1比例将样本集划分成校正集和预测集,利用竞争自适应重加权采样(competitive adaptive reweighted sampling,CARS)算法和连续投影算法(successive projections algorithm,SPA)对光谱进行特征波长筛选,使用偏最小二乘回归(partial least squares regression,PLSR)算法建立京郊鲜食杏白利糖度的预测模型。结果以MSC+S-G+CARS+PLSR算法建立的北京鲜食杏的...     

一种乳中钙含量的快速检测方法

目的建立血液中钙离子临床快速检测方法检测乳中钙含量的方法。方法样品采用盐酸+TX-100稀释,依据碱性(酸性)条件下钙与偶氮胂Ⅲ作用生成的蓝色复合物颜色与钙浓度正比的正比关系,在650nm波长处测定吸光度变化,经与钙校准液比较,计算出样品中钙含量。方法的准确度、精密度、稳定性等用乳中钙含量检测国标方法进行验证。结果建立的乳中钙含量快速测定方法与国标方法比较,准确度(偏差≤10%的符合率达到100%)和精密度(相对标准偏差为10%)方面均符合要求,且操作简单、成本低、安全性高,单个样品检测时间由原来国标方法的24h缩短至8min。结论该方法可应用于乳中钙含量快速检测,对生乳采购和液态奶市场筛查检测具有重要的应用价值。     

氯仿-甲醇法和酸水解法测定禽蛋中脂肪的方法比较

目的 对比富含磷脂等结合态脂肪的蛋制品中脂肪含量测定的方法,弥补目前国标中规定的酸水解检测方法无法准确地测定富含磷脂等结合态脂肪样品的不足。方法 采用氯仿－甲醇提取法对比国标中规定的蛋制品脂肪测定方法-酸水解法,测定蛋制品中的脂肪含量, 考察了两种方法测定不同蛋制品的提取结果、提取时间、精密度和重复性。结果 采用氯仿－甲醇法对比酸水解法提取蛋制品中的脂肪含量,结果表明,氯仿-甲醇提取法可以有效的提取蛋制品的磷脂等结合态脂肪,对蛋制品脂肪的测定具有较高的精密度和较好的重复性,相对标准偏差在0.91%-1.62%之间,且测定周期短,测定次数少。结论 氯仿－甲醇法弥补了酸水解法水解磷脂的不足且测定快速、准确,适合测定蛋制品中的脂肪含量。