On-line, proximate analysis of ground beef directly at a meat grinder outlet

The fat, moisture and protein contents of ground beef were determined on-line by a diffuse reflectance near infrared (NIR) spectroscopy instrument at the outlet of a meat grinder. Beef samples in the range of 6.2–21.7% fat, 59.6–72.9% moisture and 18.1–20.7% protein were studied. Calibrations from samples ground with hole diameters of 4, 8, 13 or 19 mm in the grinder plate were validated. In addition, calibrations of combinations of these samples from the different hole diameters were validated. Prediction errors, expressed as root mean square error of cross validation of the beef samples, were 0.73–1.50% for fat, 0.75–1.33% for moisture and 0.23–0.32% for protein, depending on the hole diameter of the grinder plate. Calibrations from samples ground with the smallest hole diameters gave lowest prediction errors. The present prediction error results are only slightly higher compared to reported prediction error results using conventional at- and off-line NIR instruments.

It is concluded that the on-line NIR prediction results were acceptable for samples ground with grinder plates of 4, 8 or 13 mm hole diameter.     

On-line determination and control of fat content in batches of beef trimmings by NIR imaging spectroscopy

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.     

在线近红外分析仪在豆粕质量控制中的应用

通过在生产线安装近红外分析仪在线测定豆粕的水分、粗蛋白质含量和粗脂肪含量,对比研究了近红外分析仪安装位置、豆粕流速和流量稳定性对在线近红外分析仪测定结果与传统国标法测定结果之间误差的影响,确定了生产线的改造方案,并对改造效果进行了考察。结果表明：通过对下料口进行技术改造,加装限料挡板和流量调节手柄,可使豆粕流速和流量稳定,从而减小测定误差;将近红外分析仪安装在成品粕下料溜槽处后方,在线近红外分析仪与国标法测定打包线及发货车辆豆粕的水分、粗蛋白质含量、粗脂肪含量结果的绝对误差分别小于0.20%、0.30%和010%,测定结果稳定可靠。在线近红外分析仪可以用于豆粕生产过程的质量控制。     

On-line NIR analysis of fat, water and protein in industrial scale ground meat batches

Fat, water and protein contents in industrial scale meat batches were determined on-line by near infrared (NIR) reflectance spectroscopy. The NIR instrument was mounted at the outlet of a large meat grinder, and the measurements were performed in an industrial environment. Beef and pork samples, with chemical compositions of 7-26% fat, 58-75% water and 15-21% protein, were processed with hole diameters of 13mm in the grinder plate. Calibrations were made both for a combined set of beef and pork samples, and for separate sets of beef and pork samples. Validations were either done by full cross validation of the calibration set, or by bias corrected prediction of a test set. Prediction errors for the two sample sets, expressed as root mean square errors of cross validation or standard error of prediction, were in the ranges 0.82-1.49% fat, 0.94-1.33% water and 0.35-0.70% protein, depending of sample set and species of animal. The presented application is an improvement to the existing manual meat standardisation procedure, and has been implemented for regular use in a Norwegian meat manufacturing plant.     

Determination of Moisture, Fat and Protein in Spray-Dried Whole Egg by Near Infrared Reflectance Spectroscopy

Near infrared reflectance (NIR) spectroscopy was used to measure moisture, protein, and fat in spray-dried whole egg. Calibrations were developed for a commercial, filter monochromator NIR instrument and tested against standard methods. A standard error of performance (SEP) of 0.15% was obtained for moisture using a calibration based on three wavelengths. Protein and fat determinations by NIR were susceptible to variability due to sample particle size differences. Calibrations employing three wavelengths were used to measure protein and fat in samples of uniform particle size (SEP = 0.20% and 0.28%, respectively), but it was necessary to utilize additional wavelengths to adequately measure these constituents in samples having particle size variability (SEP = 0.38% for both protein and fat).     

Determination of Moisture, Protein, Fat, and Calories in Raw Pork and Beef By Near Infrared Spectroscopy

The near infrared (NIR) (1100–2500 nanometers) of raw pork and raw beef samples was determined on a Neotec Model 6350 Scanning Spectrocomputer. Spectral curves were correlated with moisture, protein, fat, and calorie data determined by standard methods. A stepwise multiple regression technique was used to determine the optimum wavelengths for predicting each constituent. Correlation coefficients were ? 0.987 for moisture, fat, and calories and 0.885 for protein. The coefficients of variation for each of the nutrients were ? 3.46%.     

Composition assessment of raw meat mixtures using ultrasonics

The use of ultrasonic velocity measurements to determine the composition of dry fermented sausages was assessed. Mixtures of ground lean and fatty tissues were prepared to cover a wide range of fat (2–90 wt.%), moisture (7–76 wt.%), and protein (2–21 wt.%) contents. The ultrasonic velocity in fat decreased on average 5.6 ms⁻¹ per °C increase in temperature, due to the negative temperature coefficient for fat and the fat melting, which is observed in (DSC) differential scanning calorimetry analysis. The ultrasonic velocity temperature dependence allowed the determining of the fat, moisture and protein+others content, by measuring the ultrasonic velocity in the mixtures at 4 and 25°C and using a semi-empirical equation. The explained variance was 99.6% for fat, 98.7% for moisture and 85.4% for protein+others. The results obtained show the feasibility of using ultrasonic velocity measurement to assess the composition of meat products such as dry fermented sausages, rapidly and non-destructively.     

Effects of protein and fat levels in milk on Cheddar cheese yield

Over a 14-month period, bulk tank milk was collected twice a week and was adjusted with cream and skim milk powder to provide six levels each of fat and protein varying from 3·0 to 4·0%. Milk samples were analyzed for total solids, fat, protein, casein, lactose and somatic cell count and were used for laboratory-scale cheesemaking. Data obtained from the milk input and the cheese output were used to determine actual, moisture adjusted, theoretical yield, and efficiency of yield. Least squares analyses of data indicated that higher cheese yields were obtained from higher fat and protein contents in milk. Higher yield efficiency was associated with higher ratios of protein to fat and casein to fat. Regression analysis indicated that a percentage increase in fat content in milk resulted in an increase of 1·23–1·37% in moisture adjusted yield in the different protein levels. For a similar increase of protein in milk, there were 1·80–2·04% increase in moisture adjusted yields in different fat levels.     

Moisture sorption isotherm of fresh lean beef and external beef fat

The moisture sorption isotherm (MSI) of lean beef and fat beef was experimentally determined. The experimental procedure used was that of the COST 90 project with some modifications to accelerate equilibration. The procedure was validated with the standard reference material microcrystalline cellulose. The MSI of the beef at the highest humidity range was obtained by accelerating equilibration with changes of salts, using a low water activity salt for some time. This procedure was reliable for beef samples but not for the fat samples. No significant changes were found for lean beef in the temperature range 5–40 °C. Three models, GAB, Peleg and Lewicki, were used to fit the experimental data. The best fit was obtained with the GAB equation. The fat MSI was determined at 5, 15 and 25 °C and it was best fitted with the Lewicki model.     

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.     

普通公牛肉和淘汰母牛肉的近红外光谱鉴别方法

选取来自内蒙同一品种普通公牛和淘汰母牛各部位肉各224个肉样,新疆同一品种普通公牛和淘汰母牛各部位肉130个肉样,分别经冷冻解冻和冷鲜状态下,应用便携式近红外光谱仪在1000～1799nm波长内对绞碎后的肉糜进行光谱扫描,并且测定了内蒙肉样的蛋白质、脂肪、水分和剪切力值(WBSF)。从中分别选择来自两个产地的154和91个肉样作为建模集,采用偏最小二乘判别分析法(PLS-DA)建立了两个产地普通公牛肉和淘汰母牛肉的鉴别模型。所建的两个模型对校正集和验证集样本的鉴别准确率均达100%,对剩余预测集的70和39个肉样进行鉴别分析的鉴别准确率分别为96%和90%。     

Enhancement of the nutritional status of beef patties by adding flaxseed flour

Flaxseed flour was used as a functional ingredient in the production of beef patties. Beef patties were produced with five different formulations; the addition of 3%, 6%, 9%, 12% and 15% flaxseed flour. Control samples were formulated with 10% and 20% fat addition. Raw and cooked beef patties were analyzed for moisture, protein, fat, ash, pH, color parameters and fatty acid profiles. Beef patties were evaluated for cooking loss and sensory properties. Fat and ash content of raw patties increased, while moisture and protein content decreased with increased flaxseed flour. The same trend (except fat content) was also observed after cooking. The addition of flaxseed flour did not affect pH values of raw and cooked beef patties. The addition of flaxseed flour improved the cooking loss but, increased the energy value (as kcal/100 g). L and a values of raw beef patties containing flaxseed flour were close to controls with 10% fat. α-linolenic acid content of raw and cooked beef patties increased as the level of flaxseed flour increased. The PUFA/SFA ratio increased from 0.04 in the control with 10% fat to 0.62 in the raw beef patties with 15% flaxseed flour. The n-6/n-3 ratio decreased from 5.76 in the control with 10% fat to 0.36 in the raw beef patties with 15% flaxseed flour. The nutritional status of beef patties was enhanced with minimal composition and sensory changes with 3% or 6% flaxseed flour addition.     

Effect of replacing beef fat with hazelnut oil on quality characteristics of sucuk - A Turkish fermented sausage

Turkish fermented sausages (sucuk) were produced by replacing 15, 30 and 50% of beef fat with hazelnut oil incorporated as pre-emulsified with simplesse^® 100 (whey protein powder) Each treatment was formulated to contain 20% total fat and beef fat was the only fat material used in the control (C) group. After 12 days of fermentation and ripening, all sucuk samples had TBA values within acceptable limits (<1.0). Increasing levels of hazelnut oil in sucuk formulation increased penetrometer values (softer texture) and moisture content. Hazelnut oil replacement had a significant effect on redness values of the samples. Cholesterol content decreased progressively as the percentage of hazelnut oil increased in the formulation. Replacement of 50% beef fat with 50% hazelnut oil significantly increased MUFA, PUFA and MUFA + PUFA/SFA ratios. The use of hazelnut oil resulted in significant decreases in the slice appearance, texture and taste scores. However there was no significant difference in the overall acceptability score of samples, except those in which hazelnut oil replaced 15% beef fat, which had the highest score.     

Challenges in Model Development for Meat Composition Using Multipoint NIR Spectroscopy from At‐Line to In‐Line Monitoring

This study evaluates the efficiency of multipoint near‐infrared spectroscopy (NIRS) to predict the fat and moisture content of minced beef samples both in at‐line and on‐line modes. Additionally, it aims at identifying the obstacles that can be encountered in the path of performing in‐line monitoring. Near‐infrared (NIR) reflectance spectra of minced beef samples were collected using an NIR spectrophotometer, employing a Fabry‐Perot interferometer. Partial least squares regression (PLSR) models based on reference values from proximate analysis yielded calibration coefficients of determination of 0.96 for both fat and moisture. For an independent batch of samples, fat was estimated with a prediction coefficient of determination of 0.87 and 0.82 for the samples in at‐line and on‐line modes, respectively. All the models were found to have good prediction accuracy; however, a higher bias was observed for predictions under on‐line mode. Overall results from this study illustrate that multipoint NIR systems combined with multivariate analysis has potential as a process analytical technology (PAT) tool for monitoring process parameters such as fat and moisture in the meat industry, providing real‐time spectral and spatial information.     

Grinding Time and Pressure Developed in Beef and Pork: Effects of Temperature and Fat

Pressure on the inside face of grinder plates was measured during meat grinder operation using four transducers mounted at various distances from the center to the periphery of the plate face. Pressure during grinding of 11.4 kg batches of beef or pork was increased significantly (P<0.05) with low temperature and high fat content. The pressure increase was about 25% (409.5 kPa to 512.3 kPa) when temperature was decreased from 4°C to - 2°C and about 500% (from 177.2 kPa to 875.6 kPa) when fat content was increased from 10.1% to 44.6%. Pressure also increased (P<0.05) by about 30% from the center (344.7 kPa) to the periphery (448.5 kPa) of the plate. Overall, beef resulted in 61% greater pressure than pork.     

Feeding interruption and quality of cultured gilthead sea bream

Proximate composition, fatty acid and amino acid profiles and sensory attributes of semi-intensive cultured gilthead sea bream were determined without feeding interruption and with feeding interruption from 1 to 13 days. Average proximate composition was protein: 19.4–19.9%, fat 14.1–15.4%, moisture: 64.1–65.3%, and ash: 1.3%. The monounsaturated fatty acids (MUFA) were dominant: 43%, followed by polyunsaturated fatty acids (PUFA): 32% and saturated fatty acids (SFA) 25%. For each fatty acid class the major compounds were palmitic acid (SFA), vaccenic and oleic acid (MUFA) and docosahexaenoic acid (PUFA). Regarding the feeding interruption, it appears that the perivisceral fat can supply the required energy for up to 13 days of starvation.     

Near-Infrared Spectroscopy Determination of Physical and Chemical Characteristics in Beef Cuts

The qualities of beef cuts were compared with near-infrared (NIR) spectroscopy readings using reflectance, transmittance and a fiber optic probe. Multiple linear regression analyses were used to select the optimum wavelengths for estimating beef properties. High multiple correlation coefficients (R) were obtained for Warner-Bratzler shear value (R = 0.798?0.826), protein (R = 0.822?0.904), moisture (R = 0.895?0.941), fat (R = 0.890?0.965) and energy content (R = 0.899?0.961) with each reflectance, transmittance and using the fiber optic probe. Total pigment content also highly correlated with optical densities using transmittance (R = 0.946) and the fiber optic probe (R = 0.893). NIR with a fiber optic probe is a useful tool for determining physical and chemical characteristics of beef.     

Non-destructive determination of fat,moisture and protein in salmon fillets by use of near-infrared diffuse spectroscopy

Near infrared (NIR) diffuse spectroscopy was used to determine the fat, moisture and protein contents in whole and ground farmed atlantic salmon fillets. A remote fibre-optic probe was used for NIR measurements on 50 whole salmon fillets. The constituent ranges were: 91-205 g kg^?1 fat, 599-709g kg^?1 moisture and 186-209 g kg^?1 protein. Principal component regression resulted in the following prediction errors for ground salmon fillets, expressed as root mean square error of cross validation: 6.6 g kg-1 fat, 3.8 g kg^?1 moisture and 2.0 g kg^?1 protein. The corresponding prediction errors for non-destructive measurements on whole salmon fillets were 10.8 g kg^?1 fat, 8.5 g kg^?1 moisture and 3.7 g kg^?1 protein. Regression models using the 760-1100 m range gave lower prediction errors than models using the 1100-2500 mm or 760-2500 nm ranges. The results show that fibre-optic probe NIR instruments are suited to determine fat and moisture in whole salmon fillets non-destructively.     

True and Apparent Retention of Nutrients in Hamburger Patties Made from Beef or Beef Extended with Three Different Soy Proteins

Hamburger patties containing all beef or beef extended (20% reconstituted soy product, 80% beef) with soy isolate, soy concentrate or textured soy flour, or beef extended with one of the three soy products fortified with iron (60 mg/100g soy protein) and zinc (25 mg/100g soy protein), were analyzed in both the raw and cooked states for moisture, protein, fat, Ca, P, Mg, Na, Fe, Cu, Zn, and Mn. The percent true nutrient retentions (% TR) and percent apparent nutrient retentions (% AR) were calculated. The % TR was not significantly different for any of the patties for protein, fat, total ash, Ca, or Cu. The % TR of moisture decreased as the refinement of the soy added to the patties increased. The % AR was higher than the % TR for all nutrients examined.     

Indirect measurement of the fat content of beef mince using the Infra-Tester

A technique for the indirect estimation of the fat content of beef mince by the direct measurement of moisture content was evaluated. Samples of commercially produced beef mince ranging from 7 to 25% fat were analysed for moisture content using infra-red heating, and for fat and moisture content by standard laboratory procedures. Moisture content measured by infra-red heating using the Infra-Tester was highly correlated with fat content measured by the standard method and could be used as a rapid and inexpensive method of predicting the fat content of beef mince.