Publications (8)16.29 Total impact
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Article: Effects of post-processing treatments on sensory quality and Shiga toxigenic Escherichia coli reductions in dry-fermented sausages.
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ABSTRACT: The effects of post-processing treatments on sensory quality and reduction of Shiga toxigenic Escherichia coli (STEC) in three formulations of two types of dry-fermented sausage (DFS; salami and morr) were evaluated. Tested interventions provided only marginal changes in sensory preference and characteristics. Total STEC reductions in heat treated DFS (32°C, 6days or 43°C, 24h) were from 3.5 to >5.5 log from production start. Storing of sausages (20°C, 1month) gave >1 log additional STEC reduction. Freezing and thawing of sausages in combination with storage (4°C, 1month) gave an additional 0.7 to 3.0 log reduction in STEC. Overall >5.5 log STEC reductions were obtained after storage and freezing/thawing of DFS with increased levels of glucose and salt. This study suggests that combined formulation optimisation and post-process strategies should be applicable for implementation in DFS production to obtain DFS with enhanced microbial safety and high sensory acceptance and quality.Meat Science 01/2013; 94(1):47-54. · 2.28 Impact Factor -
Article: Changes in protein abundance between tender and tough meat from bovine longissimus thoracis muscle assessed by isobaric Tag for Relative and Absolute Quantitation (iTRAQ) and 2-dimensional gel electrophoresis analysis.
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ABSTRACT: The aim of this study was to find potential biomarkers for meat tenderness in bovine Longissimus thoracis muscle and to compare results from isobaric Tag for Relative and Absolute Quantitation (iTRAQ) and 2-dimensional gel electrophoresis (2-DE) analysis. The experiment included 4 tender and 4 tough samples, based on shear force measurements at 7 d postmortem, from young Norwegian red (NRF) bulls, taken at 1 h postmortem. A number of the proteins which have previously been related to tenderness were found to change in abundance between tender and tough samples, both in iTRAQ (P < 0.1) and 2-DE analysis (P < 0.05). Furthermore, 3 proteins that have not previously been related to tenderness were found to change significantly in abundance between tender and tough meat samples in the present study. These include proteins related to control of flux through the tricarboxylate cycle [2-oxoglutarate dehydrogenase complex component E2 (OGDC-E2)], apoptosis (galectin-1) and regulatory role in the release of Ca(2+) from intracellular stores (annexin A6). Even though the overlap in significantly changing proteins was relatively low between iTRAQ and 2-DE analysis, certain proteins predicted to have the same function were found in both analyses and showed similar changes between the groups, such as structural proteins and proteins related to apoptosis and energy metabolism.Journal of Animal Science 12/2011; 90(6):2035-43. · 2.10 Impact Factor -
Article: On-line determination and control of fat content in batches of beef trimmings by NIR imaging spectroscopy.
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ABSTRACT: An NIR imaging scanner was calibrated for on-line determination of the fat content of beef trimmings. A good calibration model was obtained for fat in intact beef (R=0.98, RMSECV=3.0%). The developed model could be used on single pixels to get an image of the fat distribution, or on the average spectrum from each trimming/portion of trimmings passing under the scanner. The fat model gave a rather high prediction error (RMSEP=8.7%) and a correlation of 0.84 when applied to 45 single trimmings with average fat content ranging from 1.6 to 49.3% fat. Test measurements on streams of trimmings making up batches varying from 10 to 24 kg gave a much lower prediction error (RMSEP=1.33%). Simulations based on true measurements indicate that the RMSEP decreases with increasing batch size and, for the present case, reached about 0.6% for 100 kg batches. The NIR scanner was tested on six batches of intact trimmings varying from 145 to 210 kg and gave similar fat estimates as an established microwave system obtained on the ground batches. The proven concept should be applicable to on-line estimation of fat in trimmings in order to determine the batch fat content and also to control the production of batches to different target fat levels. A possible requirement for the concept to work properly is that the trimming or layer of trimmings on the belt is not too thick. In this study maximum thickness was about 8 cm. Thicker trimmings might be measured, but careful hardware adjustments are then required.Meat Science 05/2011; 89(3):317-24. · 2.28 Impact Factor -
Article: Reduction of verotoxigenic Escherichia coli by process and recipe optimisation in dry-fermented sausages.
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ABSTRACT: Outbreaks of verotoxigenic Escherichia coli (VTEC) linked to dry-fermented sausages (DFSs) have emphasized the need for DFS manufacturers to introduce measures to obtain enhanced safety and still maintain the sensory qualities of their products. To our knowledge no data have yet been reported on non-O157:H7 VTEC survival in DFS. Here, the importance of recipe and process variables on VTEC (O157:H7 and O103:H25) reductions in two types of DFS, morr and salami, was determined through three statistically designed experiments. Linear regression and ANOVA analyses showed that no single variable had a dominant effect on VTEC reductions. High levels of NaCl, NaNO(2), glucose (low pH) and fermentation temperature gave enhanced VTEC reduction, while high fat and large casing diameter (a(w)) gave the opposite effect. Interaction effects were small. The process and recipe variables showed similar effects in morr and salami. In general, recipes combining high batter levels of salt (NaCl and NaNO(2)) and glucose along with high fermentation temperature that gave DFS with low final pH and a(w), provided approximately 3 log(10) reductions compared to approximately 1.5 log(10) reductions obtained for standard recipe DFS. Storage at 4°C for 2months provided log(10) 0.33-0.95 additional VTEC reductions and were only marginally affected by recipe type. Sensory tests revealed only small differences between the various recipes of morr and salami. By optimisation of recipe and process parameters, it is possible to obtain increased microbial safety of DFS while maintaining the sensory qualities of the sausages.International journal of food microbiology 05/2010; · 3.01 Impact Factor -
Article: Nondestructive analysis of salt, water, and protein in dried salted cod using computed tomography.
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ABSTRACT: Computed X-ray tomography (CT) was used to determine NaCl, water, and protein levels in dried salted cod. Cod fillets were salted and dried, and CT was conducted several times during the process. Also, homogenized cod samples with a chemical composition covering the typical composition of cod during salting and drying were produced, and CT scanned. Chemical composition of fillet and model samples was predicted from CT images acquired at 80, 110, and 130 kV. The best average prediction errors (RMSECV) obtained for homogenized samples were 0.6% NaCl, 1.3% water, and 1.5% protein; all explained variances were R2= 0.99 or above. The best RMSECVs and explained variances for cod fillet samples were 0.9% NaCl (R2= 0.96), 0.8% water (R2= 0.99), and 1.4% protein (R2= 0.79). Combining CT values from 2 or 3 voltages gave the best predictions except when predicting salt in cod fillet, where 1 voltage was sufficient.Journal of Food Science 05/2009; 74(3):E147-53. · 1.66 Impact Factor -
Article: Nondestructive Analysis of Salt, Water, and Protein in Dried Salted Cod using Computed Tomography
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ABSTRACT: Computed X-ray tomography (CT) was used to determine NaCl, water, and protein levels in dried salted cod. Cod fillets were salted and dried, and CT was conducted several times during the process. Also, homogenized cod samples with a chemical composition covering the typical composition of cod during salting and drying were produced, and CT scanned. Chemical composition of fillet and model samples was predicted from CT images acquired at 80, 110, and 130 kV. The best average prediction errors (RMSECV) obtained for homogenized samples were 0.6% NaCl, 1.3% water, and 1.5% protein; all explained variances were R2= 0.99 or above. The best RMSECVs and explained variances for cod fillet samples were 0.9% NaCl (R2= 0.96), 0.8% water (R2= 0.99), and 1.4% protein (R2= 0.79). Combining CT values from 2 or 3 voltages gave the best predictions except when predicting salt in cod fillet, where 1 voltage was sufficient.Journal of Food Science 03/2009; 74(3):E147 - E153. · 1.66 Impact Factor -
Article: Determination of sodium chloride in pork meat by computed tomography at different voltages.
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ABSTRACT: Ground pork samples simulating the widely different chemical composition of hams during dry-cured ham production were produced and scanned by x-ray computed tomography (CT). Chemical composition accounted for most of the variation in CT values (97%). Tube voltage (80, 110, and 130 kV) affected CT value and the effect varied between different types of tissue. Sodium chloride (NaCl) was predicted in the ground samples with average prediction errors (RMSEP) as low as 0.2% to 1.0% NaCl. NaCl was also predicted in small samples of raw to dry-cured ham. When dry and fat ham samples were left out of the models, NaCl was predicted with a high precision (RMSEP 0.2% to 0.4% NaCl, R(2) > 0.99). CT can be used as a valuable, nondestructive tool to analyze distribution of and quantify NaCl in ham during dry-curing.Journal of Food Science 10/2008; 73(7):E333-9. · 1.66 Impact Factor -
Article: Determination of Sodium Chloride in Pork Meat by Computed Tomography at Different Voltages
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ABSTRACT: Ground pork samples simulating the widely different chemical composition of hams during dry-cured ham production were produced and scanned by x-ray computed tomography (CT). Chemical composition accounted for most of the variation in CT values (97%). Tube voltage (80, 110, and 130 kV) affected CT value and the effect varied between different types of tissue. Sodium chloride (NaCl) was predicted in the ground samples with average prediction errors (RMSEP) as low as 0.2% to 1.0% NaCl. NaCl was also predicted in small samples of raw to dry-cured ham. When dry and fat ham samples were left out of the models, NaCl was predicted with a high precision (RMSEP 0.2% to 0.4% NaCl, R2 > 0.99). CT can be used as a valuable, nondestructive tool to analyze distribution of and quantify NaCl in ham during dry-curing.Journal of Food Science 08/2008; 73(7):E333 - E339. · 1.66 Impact Factor
