Investigation of an in-line prototype fluorescence and infrared backscatter sensor to monitor rennet-induced coagulation of skim milk at different protein concentrations

Coagulation of milk is one of the most important steps in cheese manufacture. Cutting the coagulum at optimum firmness is important to optimise the yield and quality of the cheese produced. The aim of this study was to investigate a prototype sensor to monitor rennet-induced coagulation of skim milk at different protein concentrations (3.3%, 4.0% and 4.7%) and to develop a model to predict the coagulum cutting time at a desired storage modulus (G′). Fluorescence and infrared backscatter profiles were recorded at wavelengths of 350 and 880 nm, respectively. Rheological measurements were used as a reference method to determine the times required for the coagulum to reach G′ values of 0.5, 5 and 20 Pa. Time parameters extracted from the optical profiles generated during the coagulation process were used to develop a model to predict the cutting time at which the coagulum reaches selected G′ values. This study demonstrated that the investigated prototype sensor, combined with the developed prediction model, can be used as an in-line PAT tool for real-time monitoring of milk coagulation and prediction of cutting time in cheese manufacturing.     

The influence of diet and breed of cow on the efficiency of conversion of milk constituents to curd in cheese manufacture

The influence of diet on the efficiency of conversion of milk solids to cheese in two breeds of cow, viz. Jersey and Friesian, was examined. An increase in the efficiency of conversion of milk solids to cheese in Jersey milks produced from cows on winter diets as compared with a typical summer diet was shown to be associated with an improvement in the level of fat retention in curd. The difference in fat retention could to some extent be related to the overall fat content of the milk, the casein to fat ratio and the distribution in the size of the fat globules but these factors when considered collectively or independently could not adequately explain the differences in fat retention observed in these experiments. The level of fat retention in curd was not influenced by the thermal properties of the mik fat.     

Composition and aptitude for cheese-making of milk from cows,buffaloes, goats,sheep, dromedary camels,and donkeys

Bovines produce about 83% of the milk and dairy products consumed by humans worldwide, the rest represented by bubaline, caprine, ovine, camelid, and equine species, which are particularly important in areas of extensive pastoralism. Although milk is increasingly used for cheese production, the cheese-making efficiency of milk from the different species is not well known. This study compares the cheese-making ability of milk sampled from lactating females of the 6 dairy species in terms of milk composition, coagulation properties (using lactodynamography), curd-firming modeling, nutrients recovered in the curd, and cheese yield (through laboratory model-cheese production). Equine (donkey) milk had the lowest fat and protein content and did not coagulate after rennet addition. Buffalo and ewe milk yielded more fresh cheese (25.5 and 22.9%, respectively) than cow, goat, and dromedary milk (15.4, 11.9, and 13.8%, respectively). This was due to the greater fat and protein contents of the former species with respect to the latter, but also to the greater recovery of fat in the curd of bubaline (88.2%) than in the curd of camelid milk (55.0%) and consequent differences in the recoveries of milk total solids and energy in the curd; protein recovery, however, was much more similar across species (from 74.7% in dromedaries to 83.7% in bovine milk). Compared with bovine milk, the milk from the other Artiodactyla species coagulated more rapidly, reached curd firmness more quickly (especially ovine milk), had a more pronounced syneresis (especially caprine milk), had a greater potential asymptotical curd firmness (except dromedary and goat milk), and reached earlier maximum curd firmness (especially caprine and ovine milk). The maximum measured curd firmness was greater for bubaline and ovine milk, intermediate for bovine and caprine milk, and lower for camelid milk. The milk of all ruminant species can be used to make cheese, but, to improve efficiency, cheese-making procedures need to be optimized to take into account the large differences in their coagulation, curd-firming, and syneresis properties.     

近红外光谱分析技术在粮油品质评价中的研究应用进展

近红外光谱分析技术于20世纪60年代率先应用于美国农业领域,随着计算机技术的普及和化学计量学的发展,近年来国内也广泛应用到各个领域,在粮油收购过程中对质量的检控就应用了近红外光谱分析技术。简述近红外光谱分析技术的基本原理和操作流程,重点综述近年来近红外光谱分析技术在粮油品质评价方面的具体应用,分析其存在的不足,并展望其在粮油领域中的应用前景。     

发酵乳酸度近红外光谱快速检测方法的研究

利用近红外光谱技术对发酵乳酸度进行快速分析检测。采用电位滴定仪法测定71批次含活乳酸菌发酵乳样品的酸度实测值,并同时扫描得到近红外光谱数据。以校正集均方根误差(RMSEC)、预测集均方根误差(RMSEP)、交互验证均方根误差(RMSECV)及其相关系数R_c、R_p、R_cv为评价指标建立最优的酸度定量模型。利用模型对10批次含活乳酸菌发酵乳样品的酸度进行预测。结果表明,优化后的模型,其RMSEC、RMSEP、RMSECV及其相关系数R_c、R_p、R_cv分别为3.27、4.39、4.84,0.946 2、0.922 5、0.877 8。经外部验证后,该模型酸度预测值和实测值的最大相对误差为6.76%,满足不超过10%的要求。说明模型具有良好的预测性能,可用于发酵乳中酸度的快速检测。     

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.     

工艺过程对干酪品质及产率的影响

探讨了干酪制作过程中工艺过程、发酵剂、凝乳酶及CaCl2的添加量等对干酪产率及品质的影响,从而确定最佳工艺参数。实验结果表明:在干酪生产过程中,为了使产品的凝乳时间短、状态好、产率高,采用72℃、15s的杀菌条件,发酵剂的添加量为1.2%,预酸pH为6.1,CaCl2添加量为0.015%,凝乳酶添加量为4g/L,干酪切割时间为100min,切割大小为5mm,干酪浸渍在6℃16%的食盐水中放置24h。     

近红外光谱分析技术在动物源性食品检测中的应用进展

近年来动物源性食品的消费量日益增大,关于动物源性食品的质量安全也受到人们的高度重视。近红外光谱(NIR)分析技术具有分析速度快、非破坏性、所需样品量小、多组分同时测定,且可对生产过程进行实时监控等优点。本文对NIR分析技术进行了简介,并列举了常用的光谱预处理方法;综述了该技术在动物源性食品检测中的研究进展,包括品质评价和安全评价;并对该技术在动物源性食品检测中的发展趋势进行了阐述。表明NIR分析技术适合评价动物源性食品的品质和安全。      

近红外光谱技术在粮食工业中的应用

近红外光谱技术是一种无损、快速、高效的检测技术,综述介绍近年来近红外光谱技术在粮食行业中的应用,从粮食收获到储藏、加工过程中的质量控制,涉及粮食的营养成分、储存指标以及卫生安全指标的检测模型的建立等方面看,近红外光谱技术在粮食安全在线检测方面具备可行性,可为我国\"粮安\"工程实时在线检测提供支持。     

Seasonal changes in the fat composition of Lacha sheep's milk used for Idiazabal cheese manufacture

 The effect of the seasonality of lacha sheep's milk production on the milk-fat composition was studied. This raw milk is used to manufacture Idiazabal cheese, a typical product of the Basque Country of northern Spain. Milk samples were taken, prior to cheesemaking, from a refrigerated tank of mixed milk from different flocks in a cheese factory in February, April and June. The triglyceride and fatty acid composition of the milk were analysed. The results showed that the molecular characteristics of the milk-fat components, the degree of unsaturation and the chain length changed with the time of the year. The June milk had a higher content of unsaturated and long-chain fatty acids and triglycerides. The April and February milks were very similar, with a higher content of saturated and short-chain fatty acids and triglycerides. The differences in animal feeding are probably the most important factor affecting milk composition because in June flocks are fed mainly in natural pastures while in April and February the ewes are also fed additional commercial feeds. Idiazabal cheeses were considerably different from February to June, suggesting a relationship between the free fatty acid composition of the cheese, its sensorial properties and the fat composition of the raw milk used in cheesemaking. Received: 18 June 1999     

Near-Infrared Reflectance Spectroscopy for Rapid Analysis of Curds during Cheddar Cheese Making

Near-infrared reflectance spectroscopy (NIRS) equations were developed for rapid analysis of curds during Cheddar cheese making. The coefficients of determination (R²) for NIRS and chemical analysis were: moisture (0.982), protein (0.965), fat (0.951), and lactose (0.909). When validation samples were compared by NIRS and chemical analysis, the R²s were moisture (0.984), protein (0.964), fat (0.957), and lactose (0.982). These results suggest that NIRS is applicable for rapidly monitoring chemical changes in curds.     

Technical note: Near infrared reflectance spectroscopy to predict fecal indigestible neutral detergent fiber for dairy cows

In vitro and in situ procedures performed to estimate indigestible neutral detergent fiber (iNDF) in forage or fecal samples are time consuming, costly, and limited by intrinsic factors. In contrast, near infrared reflectance spectroscopy (NIRS) has become widely recognized as a valuable tool for accurately determining chemical composition and digestibility parameters of forages. The aim of this study was to build NIRS calibrations and equations for fecal iNDF. In total, 1,281 fecal samples were collected to build a calibration data set, but only 301 were used to develop equations. Once dried, samples were ground and chemically analyzed for crude protein, ash, amylase and sodium sulfite–treated NDF corrected for ash residue (aNDFom), acid detergent fiber, acid detergent lignin, and in vitro digestion at 240 h to estimate iNDF (uNDF240). Each fecal sample was scanned using a NIRSystem 6500 instrument (Perstorp Analytical Inc., Silver Spring, MD). Spectra selection was performed, resulting in 301 sample spectra used to develop regression equations with good accuracy and low standard error of prediction. The standard error of calibration (SEC), cross validation (SECV), and coefficients of determination for calibration (R²) and for cross validation (1 ? VR, where VR = variance ratio) were used to evaluate calibration and validation results. Moreover, the ratio performance deviation (RPD) and ratio of the range of the original data to SECV (range/SECV; range error ratio, RER) were also used to evaluate calibration and equation performance. Calibration data obtained on fiber fractions aNDFom (R² = 0.92, 1 ? VR = 0.87, SEC = 1.48, SECV = 1.89, RPD = 2.80, and RER = 20.19), uNDF240 (R² = 0.92, 1 ? VR = 0.86, SEC = 1.65, SECV = 2.24, RPD = 2.57, and RER = 14.30), and in vitro rumen aNDFom digestibility at 240 h (R² = 0.90, 1 ? VR = 0.85, SEC = 2.68, SECV = 3.43, RPD = 2.53, and RER = 14.0) indicated the predictive equations had good predictive value.     

乳扇加工新工艺及品质的研究

在乳扇传统加工工艺基础上,结合意大利干酪加工技术,研究乳扇新加工工艺和产品质量。筛选的最佳工艺为:生鲜乳→质检→净乳→巴氏杀菌→冷却→接种发酵→加酶凝乳→凝乳、切割→乳清成熟→堆叠后熟→热烫拉伸→成型→干燥→包装→检验→成品。水牛奶乳扇的蛋白质平均质量分数29.25%,脂肪平均质量分数为51.14%,水分10.14%;霉菌≤50g-1,酵母菌≤50g-1,大肠菌群(最近似值)≤0.30 g-1,致病菌未检出。产品质量符合相关规定。     

基于近红外光谱技术的桃品质指标快速检测方法研究

采用傅里叶变化近红外光谱技术建立桃的甜度、酸度和硬度品质参数快速检测方法.采集1 000～2 500nm范围的近红外光谱,选取1 110～2 325nm为分析区域,描述谱峰的归属.以常规分析测定值作建模数据,采用偏最小二乘(PLS)回归法建立桃的品质参数定量分析模型,并考察近红外光谱预处理方法对模型的影响.分别用验证集和校正集样本分析模型预测的准确性.结果显示预测集均方差(RMSEP)分别为0.98、0.309、2.81,校正集均方差(RMSEC)分别为0.258、0.1、1.83,相关系数分别为0.9766、0.8918、0.9497.样本的预测值与真实测定值之间没有显著性差异(P＞0.05).本研究结果表明,采用近红外光谱法可同时测定桃的甜度、酸度和硬度等品质参数.与传统的化学分析方法相比,该方法具有快速、无损、简单等特点.     

近红外光谱技术在酿酒葡萄品质检测中的应用现状及展望

文章介绍了近红外光谱技术的基本原理、测定程序以及该分析方法中的定量分析法和定性判别法,综述了国内外采用该技术评价酿酒葡萄品质指标,鉴定酿酒葡萄品种以及检测酿酒葡萄成熟度等方面的应用进展情况,分析了该技术在检测酿酒葡萄品质时存在的问题以及应用前景。     

The application of near infrared spectroscopy technology and a remote reflectance fibre-optic probe for the determination of peptides in cheeses (cow’s,ewe’s and goat’s) with different ripening times

The use of near infrared spectroscopy (NIRS) technology employing a remote reflectance fibre-optic probe (with a 5 cm × 5 cm quartz window) for the analysis of the hydrophilic (HI) and hydrophobic (HO) peptides and the ratio HO/HI was assayed. To do so, cheeses with known and varying percentages of cow’s, ewe’s and goat’s milk were elaborated (112 samples). Ripening controls were performed over 6 months, and the chemical data obtained by reversed-phase high performance liquid chromatography used as reference. The regression method employed was modified partial least squares (MPLS). The multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP (C)) obtained 0.879 and 1.83% for hydrophilic (HI) and 0.879 and 1.83% for hydrophobic (HO) peptides, respectively, and 0.890 and 0.03% for the ratio HO/HI. The method allows immediate control by direct application of the fibre-optic probe to the cheese without prior sample treatment or destruction.     

Model based optimization of transflection near infrared spectroscopy as a process analytical tool in a continuous flash pasteurizer

Near infrared spectroscopy in combination with a transflection probe was investigated as inline measurement in a continuous flash pasteurizer system with a sugar–water model solution. Robustness and reproducibility of fluctuations of recorded spectra as well as trueness of the chemometric analysis were compared under different process parameter settings. Variable parameters were the flow rate (from laminar flow at 30 L/h to turbulent flow at 90 L/h), temperature (20 to 100 °C) and the path length of the transflection probe (2 and 4 mm) while the pressure was kept constant at 2.5 bar. Temperature and path length were identified as the most affecting parameters, in case of homogenous test medium. In case of particle containing systems, the flow rate could have an impact as well. However, the application of a PLS model, which includes a broad temperature range, and the correction of prediction results by applying a polynomial regression function for prediction errors, was able to compensate these effects. Also, a path length of 2 mm leads to a higher accuracy. The applied strategy shows that by the identification of relevant process parameters and settings as well as the establishment of a compensation strategy, near infrared spectroscopy is a powerful process analytical tool for continuous flash pasteurization systems.     

近红外光谱法检测山茱萸中莫诺苷和马钱苷的含量

目的 建立近红外光谱法快速检测山茱萸中莫诺苷和马钱苷含量的分析方法.方法 利用近红外光谱仪扫描粉碎后的山茱萸药材样品,对其光谱进行预处理和波段选择,并结合偏最小二乘法(partial least squares,PLS)建立莫诺苷和马钱苷含量快速无损检测方法.结果 所建立的模型的决定系数R分别为0.9668、0.906...     

基于近红外光谱特性分析的花生含水率检测

以花生检测国家标准GB/T 5497为基础,采用近红外光谱检测技术对花生含水率是否达标进行检测. 实验配制了30个不同含水率的花生样本,其中18个样本含水率达到国家标准,12个未达标,将样本分为训练集和测试集,通过近红外实验获取不同含水率的花生对不同波长光的吸收情况,将采集的数据作为BP神经网络的输入参数,在训练集对神经网络进行学习和训练,然后采用该模型,对测试集花生含水率是否达标进行测试. 实验表明,基于近红外光谱技术和神经网络的识别方法可全部正确识别测试集样本.     

测试部位、温度对苹果品质近红外分析准确度的影响

本实验以苹果为试材建立常温近红外光谱无损检测模型,研究测试部位和样品温度对分析模型精度的影响,并探讨温度补偿模型最少用果量。结果表明,阳面2 点和阴面2 点光谱混合后平均所得光谱建立模型的预测精度最高,水分和颜色模型交互验证相关系数分别达0.8274 和0.8005;当不同温度样品添加量达到校正集样品数的20% 时基本可以消除温度波动对定量分析模型的影响;温度补偿验证结果表明,可溶性固形物、水分和颜色温度混合校正模型预测标准误差分别比常温模型低15.52%～29.77%、13.68%～31.68% 和45.9%～88.46%。