Preliminary evaluation of endogenous milk fluorophores as tracer molecules for curd syneresis

A front-face fluorescence spectroscopy probe was installed in the wall of a laboratory-scale cheese vat. Excitation and emission filters were chosen for the selective detection of vitamin A, tryptophan, and riboflavin fluorescence. The evolution of the fluorescence of each fluorophore during milk coagulation and syneresis was monitored to determine if they had the potential to act as intrinsic tracers of syneresis and also coagulation. The fluorescence profiles for 2 of the fluorophores during coagulation could be divided into 3 sections relating to enzymatic hydrolysis of κ-casein, aggregation of casein micelles, and crosslinking. A parameter relating to coagulation kinetics was derived from the tryptophan and riboflavin profiles but this was not possible for the vitamin A response. The study also indicated that tryptophan and riboflavin may act as tracer molecules for syneresis, but this was not shown for vitamin A. The evolution of tryptophan and riboflavin fluorescence during syneresis followed a first-order reaction and had strong relationships with curd moisture and whey total solids content (r = 0.86-0.96). Simple 1- and 2-parameter models were developed to predict curd moisture content, curd yield, and whey total solids using parameters derived from the sensor profiles (standard error of prediction = 0.0005-0.394%; R² = 0.963-0.999). The results of this study highlight the potential of tryptophan and riboflavin to act as intrinsic tracer molecules for noninvasive inline monitoring of milk coagulation and curd syneresis. Further work is required to validate these findings under a wider range of processing conditions.     

Effects of cutting intensity and stirring speed on syneresis and curd losses during cheese manufacture

Recombined whole milk was renneted under constant conditions of pH, temperature, and added calcium, and the gel was cut at a constant firmness. The effects of cutting and stirring on syneresis and curd losses to whey were investigated during cheese making using a factorial design with 3 cutting modes designed to provide 3 different cutting intensity levels (i.e., total cutting revolutions), 3 levels of stirring speed, and 3 replications. These cutting intensities and stirring speeds were selected to give a wide range of curd grain sizes and curd shattering, respectively. Both factors affected curd losses, and correct selection of these factors is important in the cheesemaking industry. Decreased cutting intensity and increased stirring speed significantly increased the losses of fines and fat from the curd to the whey. Cutting intensities and stirring speeds in this study did not show significant effects on curd moisture content over the course of syneresis. Levels of total solids, fines, and fat in whey were shown to change significantly during syneresis. It is believed that larger curd particles resulting from low cutting intensities coupled with faster stirring speeds resulted in a higher degree of curd shattering during stirring, which caused significant curd losses.     

Comparison between red-green-blue imaging and visible-near infrared reflectance as potential process analytical tools for monitoring syneresis

The current work focuses on the comparison of 2 on-line optical sensing systems; namely red-green-blue imaging and visible-near infrared reflectance, for monitoring syneresis during cheese manufacture. The experimental design consisted of 3 temperature treatments carried out in an 11-L cheese vat in triplicate. Both systems were shown to predict syneresis without significant differences in prediction accuracy. However, a single-wavelength near infrared model was the most parsimonious (standard error of prediction = 4.35 g/100 g) for predicting syneresis. This technique was also the simplest in terms of parameters in the model (standard error of prediction = 4.15 g/100 g with 2 parameters), when time after gel cutting and process parameters (temperature and cutting time) were included in the models. The study showed that either system could be employed to control syneresis in cheese manufacture and improve the control of moisture content in cheese.     

涤纶筒子纱染花成因及解决措施

讨论涤纶筒子纱染色色花的影响因素及其控制方案,并介绍色花的回修方法。     

基于计算机视觉的午餐肉颜色测定系统研究

目的建立一种对午餐肉样品物理特性要求较少,能对物料表面整体颜色进行准确测量的无损检测方法。方法采用计算机视觉系统对24色色彩测试板测定得L,a,b值,使用色彩色差计对24色色彩测试板测得L~*,a~*,b~*值,对两组数据进行线性回归;计算机视觉系统测定午餐肉的L,a,b值,带入回归方程得到标准的L,a,b值,色彩色差计对午餐肉测定得L~*,a~*,b~*值,用SPSS软件对得到的标准L,a,b值和L~*,a~*,b~*值进行成对样本检验。结果 L,a,b值回归方程的相关系数r~2分别为0.9900、0.9707和0.9801,有高度相关性;午餐肉标准L,a,b值和L~*,a~*,b~*值成对样本检验得到的P值分别为0.146、0.087、0.109,大于显著性水平0.05,回归方程转换值与色差计测定结果无显著差异。结论本文建立的基于计算机视觉的午餐肉颜色测定方法可以准确测定午餐肉颜色,其效果可以代替色差计。     

Technical note: Improving modeling of coagulation,curd firming,and syneresis of sheep milk

The importance of milk coagulation properties for milk processing, cheese yield, and quality is widely recognized. The use of traditional coagulation traits presents several limitations for testing bovine milk and even more for sheep milk, due to its rapid coagulation and curd firming, and early syneresis of coagulum. The aim of this technical note is to test and improve model fitting for assessing coagulation, curd firming, and syneresis of sheep milk. Using milk samples from 87 Sarda ewes, we performed in duplicate lactodynamographic testing. On each of the 174 analyzed milk aliquots, using 180 observations from each aliquot (one every 15 s for 45 min after rennet addition), we compared 4 different curd firming models as a function of time (CF_t, mm) using a nonlinear procedure. The most accurate and informative results were observed using a modified 4-parameter model, structured as follows: ${\text{CF}}_t={\text{CF}}_{\text{P}}\times \left(1?{\text{e}}^{?{\text{k}}_{\text{CF}}\left({\text{RCT}}_{\text{eq}}\right)}\right)\times {\text{e}}^{{\text{k}}_{\text{SR}}\times \left({\text{t-RCT}}_{\text{eq}}\right)}$ where t is time, RCT_eq (min) is the gelation time, CF_P (mm) is the potential asymptotical CF at an infinite time, k_CF (%/min) is the curd firming rate constant, and k_SR (%/min) is the curd syneresis rate constant. To avoid nonconvergence and computational problems due to interrelations among the equation parameters, CF_P was preliminarily defined as a function of maximum observed curd firmness (CF_max, mm) recorded during the analysis. For this model, all the modeling equations of individual sheep milk aliquots were converging, with a negligible standard error of the estimates (coefficient of determination >0.99 for all individual sample equations). Repeatability of the modeled parameters was acceptable, also in the presence of curd syneresis during the lactodynamographic analysis.     

Manipulation of Dhaka cheese curd and effects on cheese quality

Dhaka cheese is a semihard artisanal variety originating from Bangladesh where manual curd kneading is a normal stage in its manufacture. Dhaka cheeses were produced with different degrees of curd kneading to quantify the curd manipulation process in terms of pressure and to standardise the length of operation. The effect of manipulation on the composition, rheology, texture and microstructure of fresh cheese was also studied. Manipulation had significant effects (P < 0.05–0.001) on most of the parameters studied. One minute of curd manipulation was found to be sufficient for Dhaka cheesemaking.     

Evaluation of on-line optical sensing techniques for monitoring curd moisture content and solids in whey during syneresis

This study focuses on the prediction ability of several optical sensing techniques, namely single wavelength (980 nm), broad spectrum and colour coordinates, for monitoring key syneresis indices during cheese manufacture. Three series of trials were undertaken in which milk gel was cut and stirred in an 11 L cheese vat. Three full factorial designs were employed with experimental variables consisting of: (i) three curd stirring speeds and three cutting programmes; (ii) three milk fat levels and three gel firmness levels at cutting; and (iii) two milk protein levels and three fat:protein ratio levels in the respective experiments. Models developed using the range of techniques investigated demonstrated that an on-line visible–NIR sensor was able to predict curd moisture content. However, the broad spectrum technique was the only one capable of predicting whey solids. The findings show that on-line sensing techniques can significantly improve the control of curd moisture content in cheese factories, across the range of experimental variables used in this study.     

基于机器视觉的筒子纱密度在线检测系统

为提高筒子纱密度检测自动化程度,解决传统筒子纱密度测量方法效率低、操作复杂等问题,设计了一种基于机器视觉的筒子纱密度在线检测系统。该系统由质量传感器、光电传感器、蓝色面光源、工业摄像机、传送装置和工控机组成。研究了筒子纱图像校正算法,根据透视投影理论建立了筒子纱校正模型,还原了筒子纱上下边界的直线特性,得到了理想的筒子纱侧面图像,用积分法得到筒子纱的精确体积。150个筒子纱密度检测结果表明:通过像素当量折算出筒子纱实际最大直径和体积参数,再结合高精度质量传感器的数据,最终可计算出筒子纱密度,基于机器视觉的筒子纱密度在线检测系统的检测精度和稳定性能可满足生产要求。     

Multispectral vision for monitoring peach ripeness

The main objective of this research was to develop an automatic procedure able to classify Rich Lady commercial peaches according to their ripeness stage through multispectral imaging techniques. A classification procedure was applied to the ratio images calculated as red (R, 680 nm) divided by infrared (IR, 800 nm), that is, R/IR images. Four image-based ripeness reference classes (A: unripe to D: overripe) were generated from 380 fruit images (season 1: 2006) by a nonsupervised classification method and evaluated according to reference measurements of the ripeness of the same samples: Magness-Taylor penetrometry firmness, low-mass impact firmness, reflectance at 680 nm (R680, and soluble solids content. The assignment of unknown sample images from those season 1 images (internal validation, n = 380) and of 240 images from the 2nd season (season 2: 2007) to the ripeness reference classes (external validation) was carried out by computing the minimum Euclidean distance (classification distance, C(d)) between each unknown image histogram and the average histogram of each ripeness reference class. For both validation phases, firmness values decreased and R680 increased for increasing alphabetical order of image-based class letter, reflecting the ripening process. Moreover, 70% (season 1) and 80% (season 2) of the samples below bruise susceptibility firmness were classified into class D. PRACTICAL APPLICATION: This work proposes and validates a procedure for assessing peach ripeness through spectral imaging. The control of ripeness in this fruit is crucial for ensuring its quality and the measurement of optimum peach ripeness at harvest and postharvest is a controversial issue, which needs to be balanced between a minimum ripeness, acceptable for the consumer, and a maximum ripeness, to minimize fruit losses during the postharvest process. The proposed method is nondestructive and quick, showing thus, a good perspective for its application in fresh fruit packing lines, either for peach ripeness assessment or for other fruits (providing adequate calibration).     

Breed of cow and herd productivity affect milk composition and modeling of coagulation,curd firming,and syneresis

Milk coagulation properties (MCP) have been widely investigated in the past using milk collected from different cattle breeds and herds. However, to our knowledge, no previous studies have assessed MCP in individual milk samples from several multi-breed herds characterized by either high or low milk productivity, thereby allowing the effects of herd and cow breed to be evaluated independently. Multi-breed herds (n = 41) were classified into 2 categories based on milk productivity (high vs. low), defined according to the average milk net energy yielded daily by lactating cows. Milk samples were taken from 1,508 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, Jersey) and 3 dual-purpose (Simmental, Rendena, Alpine Grey) breeds, and analyzed in duplicate (3,016 tests) using 2 lactodynamographs to obtain 240 curd firming (CF) measurements over 60 min (1 every 15 s) for each duplicate. The 5 traditional single-point MCP (RCT, k₂₀, a₃₀, a₄₅, and a₆₀) were yielded directly by the instrument from the available CF measures. All 240 CF measures of each replicate were also used to estimate 4 individual equation parameters: RCT estimated according to curd firm change over time modeling (RCT_eq), asymptotic potential curd firmness (CF_P), curd firming instant rate constant (k_CF), and syneresis instant rate constant (k_SR) and 2 derived traits: maximum curd firmness achieved within 45 min (CF_max) and time at achievement of CF_max (t_max) by curvilinear regression using a nonlinear procedure. Results showed that the effect of herd-date on traditional and modeled MCP was modest, ranging from 6.1% of total variance for k₂₀ to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for t_max to 82.5% for RCT_eq. The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a₆₀, k_SR, k_CF, and t_max: 57 to 71%). Reproducibility, taking into account the effect of instrument, was equal to or slightly lower than repeatability. Milk samples collected in farms characterized by high productivity exhibited delayed coagulation (RCT_eq: 18.6 vs. 16.3 min) but greater potential curd firmness (CF_P: 76.8 vs. 71.9 mm) compared with milk samples collected from low-productivity herds. Parity and days in milk influenced almost all MCP. Large differences in all MCP traits were observed among breeds, both between specialized and dual-purpose breeds and within these 2 groups of breeds, even after adjusting for milk quality and yield. Milk quality and MCP of samples from Jersey cows, and coagulation time of samples from Rendena cows were better than in milk from Holstein-Friesian cows, and intermediate results were found with the other breeds of Alpine origin. The results of this study, taking into account the intrinsic limitation of this technique, show that the effects of breed on traditional and modeled MCP are much greater than the effects of herd productivity class, parity, and DIM. Moreover, the variance in individual animals is much greater than the variance in individual herds within herd productivity class. It seems that improvement in MCP depends more on genetics (e.g., breed, selection) than on environmental and management factors.     

High-pressure effects on the microstructure, texture, and color of white-brined cheese

Abstract: White‐brined cheeses were subjected to high‐pressure processing (HPP) at 50, 100, 200, and 400 MPa at 22 °C for 5 and 15 min and ripened in brine for 60 d. The effects of pressure treatment on the chemical, textural, microstructural, and color were determined. HPP did not affect moisture, protein, and fat contents of cheeses. Similar microstructures were obtained for unpressurized cheese and pressurized cheeses at 50 and 100 MPa, whereas a denser and continuous structure was obtained for pressurized cheeses at 200 and 400 MPa. These microstructural changes exhibited a good correlation with textural changes. The 200 and 400 MPa treatments resulted in significantly softer, less springy, less gummy, and less chewy cheese. Finally, marked differences were obtained in a* and b* values at higher pressure levels for longer pressure‐holding time and were also supported by ΔE* values. The cheese became more greenish and yellowish with the increase in pressure level. Practical Application: The quality of cheese is the very important to the consumers. This study documented the pressure‐induced changes in selected quality attributes of semisoft and brine‐salted cheese. The results can help the food processors to have knowledge of the process parameters resulting in quality changes and to identify optimal process parameters for preserving pressure‐treated cheeses.     

一种测定羊绒颜色纯度的计算机视觉系统

传统测定羊绒纯度的手工方法受主观因素影响,精度和速度不能满足生产需要.文章提出了一种由纤维分匀器、图像获取系统和图像处理计算机组成的、能客观测定羊绒颜色纯度的计算机视觉系统.由实验结果的对比可以看出本系统的研究成果是可行的.文章还对系统采用的检测样品的预处理、羊绒中杂色毛的识别与评定算法等关键技术进行了重点介绍.     

The potential for carbon dioxide formation during ripening of acid curd cheese

Inspired by recent reports on high concentrations of carbon dioxide in the atmosphere of ripening chambers used in acid curd cheese production, small-scale experiments were performed to systematically investigate sources of CO₂ formation. In a closed system with a ratio of cheese mass to air volume close to that in industrial scale, up to approximately 16% (v/v) CO₂ were observed within 3 d of maturation at 24 °C. Without addition of ripening salts (CaCO₃, NaHCO₃) the initial carbon dioxide formation was delayed, but maximum CO₂ levels were still much higher than admissible workplace concentrations. Control experiments with quarg, which was pasteurized for yeast inactivation, revealed that growth and activity of yeasts has to be considered as the most important source for carbon dioxide formation. The results of the study strongly point on the necessity of preventive measures for ensuring the safety of employees.     

嗜酸乳杆菌发酵生产低脂干酪凝乳工艺的优化

以脱脂乳为原料,采用嗜酸乳杆菌发酵进行预酸化,对其生产的低脂干酪凝乳工艺条件进行了研究。实验选取凝乳pH、氯化钙添加量、凝乳酶添加量、凝乳温度4个影响因素,以干酪产率、乳清中非脂乳固体物质残留量、嗜酸乳杆菌活菌数为指标,采用L₉（3⁴）正交实验进行优化。结果表明,凝乳的最佳工艺参数为凝乳pH6.0,氯化钙添加量0.02%（w/w）,凝乳酶添加量0.01%（w/w,酶活20000u/g）,凝乳温度35℃,以此条件生产的低脂干酪脂肪含量小于5%,干酪产率29.41%,乳清中非脂乳固体物质残留量5.66%,嗜酸乳杆菌活菌数在10⁹cfu/mL以上。     

Measurement of meat color using a computer vision system

The limits of the colorimeter and a technique of image analysis in evaluating the color of beef, pork, and chicken were investigated. The Minolta CR-400 colorimeter and a computer vision system (CVS) were employed to measure colorimetric characteristics. To evaluate the chromatic fidelity of the image of the sample displayed on the monitor, a similarity test was carried out using a trained panel. The panelists found the digital images of the samples visualized on the monitor very similar to the actual ones (P < 0.001). During the first similarity test the panelists observed at the same time both the actual meat sample and the sample image on the monitor in order to evaluate the similarity between them (test A). Moreover, the panelists were asked to evaluate the similarity between two colors, both generated by the software Adobe Photoshop CS3 one using the L*, a* and b* values read by the colorimeter and the other obtained using the CVS (test B); which of the two colors was more similar to the sample visualized on the monitor was also assessed (test C). The panelists found the digital images very similar to the actual samples (P < 0.001). As to the similarity (test B) between the CVS- and colorimeter-based colors the panelists found significant differences between them (P < 0.001). Test C showed that the color of the sample on the monitor was more similar to the CVS generated color than to the colorimeter generated color. The differences between the values of the L*, a*, b*, hue angle and chroma obtained with the CVS and the colorimeter were statistically significant (P < 0.05–0.001). These results showed that the colorimeter did not generate coordinates corresponding to the true color of meat. Instead, the CVS method seemed to give valid measurements that reproduced a color very similar to the real one.     

计算机测色配色技术在皮革工业中的应用探讨

详细论述了颜色科学及配色理论 ,介绍了目前计算机技术在颜色测色配色方面的应用 ,着重阐述了现代颜色测量仪器与计算机技术相结合的计算机测色配色技术理论及其在皮革工业中的应用。并结合皮革生产特点 ,对其在皮革工业中应用的局限性及其解决办法进行了探讨     

Computer vision-based sorting of Atlantic salmon (Salmo salar) fillets according to their color level

ABSTRACT:  Computer vision method was used to evaluate the color of Atlantic salmon ( Salmo salar ) fillets. Computer vision-based sorting of fillets according to their color was studied on 2 separate groups of salmon fillets. The images of fillets were captured using a digital camera of high resolution. Images of salmon fillets were then segmented in the regions of interest and analyzed in red, green, and blue (RGB) and CIE Lightness, redness, and yellowness (Lab) color spaces, and classified according to the Roche color card industrial standard. Comparisons of fillet color between visual evaluations were made by a panel of human inspectors, according to the Roche Salmo Fan™ lineal standard, and the color scores generated from computer vision algorithm showed that there were no significant differences between the methods. Overall, computer vision can be used as a powerful tool to sort fillets by color in a fast and nondestructive manner. The low cost of implementing computer vision solutions creates the potential to replace manual labor in fish processing plants with automation.     

干酪及其加工和质量控制新技术

研讨了国外奶酪及其发展、奶酪的品种、分类和质量控制方法，进一步介绍了近年研发出的新型奶酪的特点和加工方法。同时还研讨了乳清及其生物活性物的最新研究进展，以利于充分利用乳清资源和减少排除的乳清对环境的污染。另外，还介绍了奶酪加工新技术和凝乳酶的新型代用酶的种类、特性。     

The color of Brevibacterium linens depends on the yeast used for cheese deacidification

The color of smear cheeses (Muenster) is traditionally thought to be due to the bacterial flora, e.g., Brevibacterium linens. This study was carried out to evaluate indirect effects of yeast on the color of B. linens. A 60% cheese medium was desacidified with Debaryomyces hansenii or Kluyveromyces marxianus until pH 5.8 was reached. After inactivation of the yeast and addition of agar-NaCl, B. linens was inoculated on the medium surface and incubated at 12°C from d 2 to 28. For each bacterial biofilm, color was evaluated by L*C*h° (brightness, chroma, hue angle) spectrocolorimetry. After d 14 (D. hansenii deacidification) and d 21 (K. marxianus desacidification), the color level (as a function of all 3 factors) of B. linens biofilms became maximal and remained so until d 28. Debaryomyces hansenii 304 (LGMPA) was less efficient for deacidification than K. marxianus Laf5. However, color intensity (function of chroma only) was higher when D. hansenii was used. The yeast used had an effect on the composition of the cheese medium in relation to production and consumption of metabolites during deacidification. The results concerning color are discussed with respect to this cheese medium composition.