11 resultados para Cheese Analysis

em CentAUR: Central Archive University of Reading - UK


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The meltabilities of 14 process cheese samples were determined at 2 and 4 weeks after manufacture using sensory analysis, a computer vision method, and the Olson and Price test. Sensory analysis meltability correlated with both computer vision meltability (R-2 = 0.71, P < 0.001) and Olson and Price meltability (R-2 = 0.69, P < 0.001). There was a marked lack of correlation between the computer vision method and the Olson and Price test. This study showed that the Olson and Price test gave greater repeatability than the computer vision method. Results showed process cheese meltability decreased with increasing inorganic salt content and with lower moisture/fat ratios. There was very little evidence in this study to show that process cheese meltability changed between 2 and 4 weeks after manufacture..

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In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

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Why it is easier to cut with even the sharpest knife when 'pressing down and sliding' than when merely 'pressing down alone' is explained. A variety of cases of cutting where the blade and workpiece have different relative motions is analysed and it is shown that the greater the 'slice/push ratio' xi given by ( blade speed parallel to the cutting edge/blade speed perpendicular to the cutting edge), the lower the cutting forces. However, friction limits the reductions attainable at the highest.. The analysis is applied to the geometry of a wheel cutting device (delicatessan slicer) and experiments with a cheddar cheese and a salami using such an instrumented device confirm the general predictions. (C) 2004 Kluwer Academic Publishers.

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The influence of adjunct brine cultures on the volatile compounds in Feta-type cheeses made from bovine milk was studied. Four batches of brine were produced: one with no added adjuncts, a second containing Lactobacillus paracasei subsp. paracasei, a third containing Lb. paracasei subsp. paracasei plus Debaryomyces hansenii and a fourth with Lb. paracasei subsp. paracasei plus Yarrowia lipolytica. All the cultures were isolated from commercial Feta brines. Aroma compounds were analysed by dynamic headspace analysis, on-line coupled with GC/MS. The most important volatile compounds were quantified in the experimental cheeses; it was concluded that the use of Lb. paracasei subsp. paracasei and D. hansenii as adjuncts in the manufacture of Feta-type cheeses contribute to the formation of a richer pattern of aroma compounds, namely alcohols, aldehydes and esters. The inclusion of Y. lipolytica resulted in the production of undesirable aroma compounds that are not part of the usual volatile profile of high quality Feta cheeses. (C) 2004 Elsevier Ltd. All rights reserved.

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A whey salts mixture was used as a partial substitute for sodium chloride to provide a modified Na:K ratio (1:3.4) in the manufacture of white salted cheese using ultrafiltration. Reduction of chymosin addition from 20 to 8 mu L kg(-1) of cheese was also investigated. Variation of salt and chymosin levels did not result in any significant differences in composition and physicochemical properties. The rates of proteolysis in terms of water-soluble nitrogen (WSN) and nitrogen soluble in 12% trichloroacetic acid (TCA-SN) were affected by chymosin levels but not by salt treatment. Urea-PAGE electrophoretic analysis of caseins from the cheeses manufactured using three levels of chymosin and two salt types showed that the hydrolysis of alpha(s1)-casein was higher than for beta-caseins but the differences between the cheeses were not significant (P > 0.05). The chymosin level did not have a significant effect (P > 0.05) on hardness and fracturability, suggesting that any variation in hardness due to the initial hydrolysis was being confounded by other variables. Cheeses including the whey salts product were harder and more fracturable (P < 0.01) than the cheese treated with NaCl only. Both hardness and fracturability values decreased (P < 0.05) over the maturation period. The scores for bitterness were low; neither the effects of salt nor chymosin levels were significant (P > 0.05). (c) 2005 Elsevier Ltd. All rights reserved.

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This study demonstrated that both chymosin and salt-in-moisture (SM) were important factors for proteolysis in the manufacture of ultrafiltrated white-salted cheese, with significant effects on water-soluble nitrogen and nitrogen soluble in trichloroacetic acid. In contrast, the levels of free amino acids were not significantly affected by chymosin and salt treatments. The cheeses made using high levels of chymosin with low SM had lower levels of residual α(s1)- and β-casein at the end of ripening. On texture profile analysis, the hardness and fracturability of the cheeses significantly increased with SM and decreased during ripening. Increases in chymosin significantly contributed to the overall weakening of the structure throughout ripening. Bitter flavour was detected after 12 weeks in the cheese made with the higher chymosin level and lower SM, which could be the result of accumulation of γ-casein fractions. The sensory data indicated that the hedonic responses for low chymosin with low SM cheeses were good and acceptable in flavour, which may be due to the moderate levels of proteolysis products.

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The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..

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The objective of this study was to determine the potential of mid-infrared spectroscopy coupled with multidimensional statistical analysis for the prediction of processed cheese instrumental texture and meltability attributes. Processed cheeses (n = 32) of varying composition were manufactured in a pilot plant. Following two and four weeks storage at 4 degrees C samples were analysed using texture profile analysis, two meltability tests (computer vision, Olson and Price) and mid-infrared spectroscopy (4000-640 cm(-1)). Partial least squares regression was used to develop predictive models for all measured attributes. Five attributes were successfully modelled with varying degrees of accuracy. The computer vision meltability model allowed for discrimination between high and low melt values (R-2 = 0.64). The hardness and springiness models gave approximate quantitative results (R-2 = 0.77) and the cohesiveness (R-2 = 0.81) and Olson and Price meltability (R-2 = 0.88) models gave good prediction results. (c) 2006 Elsevier Ltd. All rights reserved..

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The objective of this study was to determine the potential of mid-infrared spectroscopy in conjunction with partial least squares (PLS) regression to predict various quality parameters in cheddar cheese. Cheddar cheeses (n = 24) were manufactured and stored at 8 degrees C for 12 mo. Mid-infrared spectra (640 to 4000/cm) were recorded after 4, 6, 9, and 12 mo storage. At 4, 6, and 9 mo, the water-soluble nitrogen (WSN) content of the samples was determined and the samples were also evaluated for 11 sensory texture attributes using descriptive sensory analysis. The mid-infrared spectra were subjected to a number of pretreatments, and predictive models were developed for all parameters. Age was predicted using scatter-corrected, 1st derivative spectra with a root mean square error of cross-validation (RMSECV) of 1 mo, while WSN was predicted using 1st derivative spectra (RMSECV = 2.6%). The sensory texture attributes most successfully predicted were rubbery, crumbly, chewy, and massforming. These attributes were modeled using 2nd derivative spectra and had, corresponding RMSECV values in the range of 2.5 to 4.2 on a scale of 0 to 100. It was concluded that mid-infrared spectroscopy has the potential to predict age, WSN, and several sensory texture attributes of cheddar cheese..

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Partial budgeting was used to estimate the net benefit of blending Jersey milk in Holstein-Friesian milk for Cheddar cheese production. Jersey milk increases Cheddar cheese yield. However, the cost of Jersey milk is also higher; thus, determining the balance of profitability is necessary, including consideration of seasonal effects. Input variables were based on a pilot plant experiment run from 2012 to 2013 and industry milk and cheese prices during this period. When Jersey milk was used at an increasing rate with Holstein-Friesian milk (25, 50, 75, and 100% Jersey milk), it resulted in an increase of average net profit of 3.41, 6.44, 8.57, and 11.18 pence per kilogram of milk, respectively, and this additional profit was constant throughout the year. Sensitivity analysis showed that the most influential input on additional profit was cheese yield, whereas cheese price and milk price had a small effect. The minimum increase in yield, which was necessary for the use of Jersey milk to be profitable, was 2.63, 7.28, 9.95, and 12.37% at 25, 50, 75, and 100% Jersey milk, respectively. Including Jersey milk did not affect the quantity of whey butter and powder produced. Althoug further research is needed to ascertain the amount of additional profit that would be found on a commercial scale, the results indicate that using Jersey milk for Cheddar cheese making would lead to an improvement in profit for the cheese makers, especially at higher inclusion rates.