scholarly journals Prediction of beef quality traits through mini NIR spectrophotometer and multivariate analyses

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
MA Hashem ◽  
SA Tule ◽  
M Khan ◽  
MM Rahman ◽  
MAK Azad ◽  
...  
Keyword(s):  
Cross Validation ◽  
Predictive Ability ◽  
Cooking Loss ◽  
Coefficient Of Determination ◽  
Quality Trait ◽  
Drip Loss ◽  
Quality Traits ◽  
Beef Quality ◽  
Nir Reflectance Spectroscopy ◽  
Range Error

The aim of this study was to test the ability of mini NIR reflectance spectroscopy to predict beef quality traits. Sixty M. longissimus thoracis were collected and spectra were obtained prior to beef quality trait analysis. Calibration equations were developed from reference data (n=60) of pH, color traits (lightness, redness and yellowness), drip loss (%), cooking loss (%), CP (%), EE (%), moisture (%), DM (%), and Ash (%) using partial least squares regressions. Predictive ability of the models was assessed by coefficient of determination of cross-validation (R2CV) and root mean square error of cross-validation. Predictions models were satisfactory (R2CV = 0.95) for pH, (R2CV = 0.96) for lightness (L*), (R2CV = 0.96) for redness (a*), (R2CV = 0.97) for yellowness (b*), (R2CV = 0.95) for drip loss, (R2CV = 0.95) for cooking loss, (R2CV = 0.94) for CP, (R2CV = 0.95) for EE, (R2CV = 0.91) for moisture, (R2CV = 0.91) for DM and (R2CV = 0.91) for ash. The ratio performance deviation is 5.35, 5.34, 5.87, 5.16, 4.64, 4.81, 4.45, 4.95, 3.36, 4.73 and 4.47 for L*, a*, b*, pH, drip loss, cooking loss, CP, EE, moisture, DM and Ash respectively which indicates that all values are adequate for analytical purposes. Range error ratio are 20.69, 22.97, 27.11, 18.92, 20.74, 16.20, 17.80, 17.52, 14.96, 17.89 and 17.87 for L*, a*, b*, pH, drip loss, cooking loss, CP, EE, moisture, DM and ash respectively. From the findings of this study it can be concluded that mini NIRS is a suitable tool for a rapid, non-destructive and reliable prediction of beef quality.

scholarly journals Determination of the alterations in quality parameters and consumer preference of dry-aged beef based on different periods of ageing using a purposive incubator

2021 ◽  
Vol 72 (1) ◽  
pp. 2669
Author(s):  
H USTUNER ◽  
S ARDICLI ◽  
O ARSLAN
Keyword(s):  
Shear Force ◽  
Ageing Time ◽  
Quality Parameters ◽  
Cooking Loss ◽  
Water Holding Capacity ◽  
Quality Traits ◽  
Beef Quality ◽  
Significant Difference ◽  
Meat Colour ◽  
Water Holding

The aim of this study was to evaluate beef quality traits including pH, water holding capacity, cooking loss, meat colour, and Warner-Bratzler shear force in dry-aged beef and to determine the most favorable ageing time based on beef quality parameters and consumer acceptability. In this respect, longissimus dorsi samples were obtained from Simmental bulls and stored for an ageing period up to 21-days, and thus, the beef quality evaluation was performed at 0-day, 7-day, 14-day, and 21-day of the experimental period. Results revealed that the lowest shear force value was observed in beef samples on day-14 whereas the lowest pH value was determined in samples on day 21. Moreover, water holding capacity and beef colour values were significantly differentiated based on dry-ageing (P<0.05). In sensory panel evaluation, a significant difference is found only in meat colour rating (P<0.05). There was no significant difference between ageing periods and cooking loss. The most important technical point is that increasing dry-ageing time from 14 to 21 days did not desirably affect quality traits and sensory scores. Hence, dry-ageing for 14 days seemed to be the most economically efficient application. Taken altogether, the present results suggest that the potential for use of dry-ageing should be considered as an alternative method to produce high-quality beef with respect to the optimum ageing process.

Use of near Infrared Reflectance Spectroscopy to Analyse Bovine Faecal Samples

2002 ◽  
Vol 10 (4) ◽  
pp. 309-314 ◽  
Author(s):  
D. Cozzolino ◽  
A. La Manna ◽  
D. Vaz Martins
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Dry Weight ◽  
Reflectance Spectroscopy ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Faecal Samples ◽  
Acid Detergent Fibre ◽  
Nir Reflectance Spectroscopy ◽  
Calibration Equations

Near infrared (NIR) reflectance spectroscopy was used to predict nitrogen (N), acid detergent fibre (ADF), neutral detergent fibre (NDF) and chromium (Cr) in beef faecal samples. One hundred and twenty faecal samples were scanned in a NIRSystems 6500 monochromator instrument over the wavelength range of 400–2500 nm in reflectance. Calibration equations were developed using modified partial least squares (MPLS) with internal cross validation to avoid overfitting. The coefficient of determination in calibration ( R2cal) and the standard error in cross validation ( SECV) were 0.80 (0.74) for N, 0.92 (12.04) for ADF, 0.86 (13.5) for NDF and 0.56 (0.07) for Cr in g kg−1 dry weight, respectively. Results for validation were 0.78 ( SEP: 0.1) for N, 0.74 ( SEP: 7.5) for ADF, 0.85 ( SEP: 8.5) for NDF and 0.10 (0.09) for Cr in g kg−1 dry weight, respectively.

The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples

2005 ◽  
Vol 80 (3) ◽  
pp. 333-337 ◽  
Author(s):  
D. Cozzolino ◽  
F. Montossi ◽  
R. San Julian
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Model Development ◽  
Fibre Diameter ◽  
Reflectance Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Calibration Models ◽  
Nir Reflectance Spectroscopy

AbstractAbstract Visible (VIS) and near infrared (NIR) reflectance spectroscopy combined with multivariate data analysis were explored to predict fibre diameter in both clean and greasy Merino wool samples. Fifty clean and 400 greasy wool samples were analysed. Samples were scanned in a large cuvette using a NIRSystems 6500 monochromator instrument by reflectance in the VIS and NIR regions (400 to 2500 nm). Partial least square (PLS) regression was used to develop a number of calibration models between the spectral and reference data. Different mathematical treatments were used during model development. Cross validation was used to assess the performance and avoid overfitting of the models. The NIR calibration models gave a coefficient of determination in calibration (R2) > 0·90 for clean wool samples and a R2 < 0·50 for greasy wool samples. The values for the residual predictive value, RPD (ratio of standard deviation (s. d.) to the root mean square of the standard error of cross validation (RMSECV)) were 3 for clean and 0·6 for greasy wool samples, respectively. The results indicated that fibre diameter in greasy wool samples was poorly predicted with NIR, while clean wool showed good relationships.More research is required to improve the calibration on greasy wool samples if the technology is to be used for rapid analysis to assist in the selection of animals in breeding programmes.

scholarly journals Bayesian Statistical Analyses for Presence of Single Genes Affecting Meat Quality Traits in a Crossed Pig Population

Genetics ◽  
1997 ◽  
Vol 145 (2) ◽  
pp. 395-408 ◽  
Author(s):  
L L G Janss ◽  
J A M Van Arendonk ◽  
E W Brascamp
Keyword(s):  
Meat Quality ◽  
Mixed Model ◽  
Single Gene ◽  
Genetic Research ◽  
Intramuscular Fat ◽  
Cooking Loss ◽  
Drip Loss ◽  
Quality Traits ◽  
Ph Measurements ◽  
Meat Quality Traits

Presence of single genes affecting meat quality traits was investigated in F2 individuals of a cross between Chinese Meishan and Western pig lines using phenotypic measurements on 11 traits. A Bayesian approach was used for inference about a mixed model of inheritance, postulating effects of polygenic background genes, action of a biallelic autosomal single gene and various nongenetic effects. Cooking loss, drip loss, two pH measurements, intramuscular fat, shearforce and back-fat thickness were traits found to be likely influenced by a single gene. In all cases, a recessive allele was found, which likely originates from the Meishan breed and is absent in the Western founder lines. By studying associations between genotypes assigned to individuals based on phenotypic measurements for various traits, it was concluded that cooking loss, two pH measurements and possibly backfat thickness are influenced by one gene, and that a second gene influences intramuscular fat and possibly shearforce and drip loss. Statistical findings were supported by demonstrating marked differences in variances of families of fathers inferred as carriers and those inferred as noncarriers. It is concluded that further molecular genetic research effort to map single genes affecting these traits based on the same experimental data has a high probability of success.

scholarly journals Online Prediction of Physico-Chemical Quality Attributes of Beef Using Visible—Near-Infrared Spectroscopy and Chemometrics

Foods ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 525 ◽  
Author(s):  
Amna Sahar ◽  
Paul Allen ◽  
Torres Sweeney ◽  
Jamie Cafferky ◽  
Gerard Downey ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Coefficient Of Determination ◽  
Drip Loss ◽  
Chemical Quality ◽  
Post Mortem ◽  
Physico Chemical ◽  
Online Prediction

The potential of visible–near-infrared (Vis–NIR) spectroscopy to predict physico-chemical quality traits in 368 samples of bovine musculus longissimus thoracis et lumborum (LTL) was evaluated. A fibre-optic probe was applied on the exposed surface of the bovine carcass for the collection of spectra, including the neck and rump (1 h and 2 h post-mortem and after quartering, i.e., 24 h and 25 h post-mortem) and the boned-out LTL muscle (48 h and 49 h post-mortem). In parallel, reference analysis for physico-chemical parameters of beef quality including ultimate pH, colour (L, a*, b*), cook loss and drip loss was conducted using standard laboratory methods. Partial least-squares (PLS) regression models were used to correlate the spectral information with reference quality parameters of beef muscle. Different mathematical pre-treatments and their combinations were applied to improve the model accuracy, which was evaluated on the basis of the coefficient of determination of calibration (R2C) and cross-validation (R2CV) and root-mean-square error of calibration (RMSEC) and cross-validation (RMSECV). Reliable cross-validation models were achieved for ultimate pH (R2CV: 0.91 (quartering, 24 h) and R2CV: 0.96 (LTL muscle, 48 h)) and drip loss (R2CV: 0.82 (quartering, 24 h) and R2CV: 0.99 (LTL muscle, 48 h)) with lower RMSECV values. The results show the potential of Vis–NIR spectroscopy for online prediction of certain quality parameters of beef over different time periods.

scholarly journals Relationship between objective measurements and taste panel assessment of beef quality

2001 ◽  
Vol 41 (7) ◽  
pp. 981 ◽  
Author(s):  
D. Perry ◽  
J. M. Thompson ◽  
I. H. Hwang ◽  
A. Butchers ◽  
A. F. Egan
Keyword(s):  
Electrical Stimulation ◽  
Shear Force ◽  
Predictive Ability ◽  
Objective Measurement ◽  
Cooking Loss ◽  
Taste Panel ◽  
Objective Measures ◽  
Drip Loss ◽  
Objective Measurements ◽  
The Relationship

The relationship between objective measurements (shear force, compression, drip loss, cooking loss) and sensory evaluation of tenderness and juiciness of samples of M. longissimus thoracis et lumborum was examined using data from 2 experiments which imposed different electrical stimulation and aging treatments post mortem, with resultant differences in sensory and objective measures of tenderness. The relationships were tested first in separate models for each objective measurement, and then in multiple regressions containing all measurements. These models were then repeated with the inclusion of stimulation and aging treatments and their interactions with each objective measurement. Shear force by itself was a useful predictor of sensory tenderness score, with which it had a quadratic relationship. Compression and cooking loss, when used by themselves, accounted for substantially less variation in sensory tenderness scores than did shear force, with larger residual standard deviations (r.s.d.). Drip loss had no significant relationship with sensory tenderness scores. Inclusion of post-slaughter treatment in the analyses increased the amount of variation in sensory tenderness scores accounted for by only a small amount in the case of shear force, with a substantial increase in the case of compression and cooking loss. Use of all objective measurements in the 1 model had a similar predictive ability (r2 , r.s.d.) as the use of shear force plus treatment variables. Aging affected the sensory tenderness scores given by taste panellists, in that they gave 14-day aged meat higher tenderness scores (more tender) than they gave 1-day aged meat with the same shear force, compression or cooking loss values. Electrical stimulation did not affect the relationship between sensory tenderness scores and shear force, but did affect that between sensory scores and compression. The effect was similar to that seen for aged meat, with stimulated meat being scored as more tender by a taste panel than non-stimulated meat, at the same compression values. Post-slaughter treatment did not affect the slope of these relationships. When all objective measurements were analysed together, aging period affected the relationship between tenderness scores and objective measures, with tenderness scores being lower in 1-day aged samples than 14-day aged samples at the same combination of objective measures. There was only a poor relationship between shear force, compression, drip loss, cooking loss and sensory juiciness scores.

scholarly journals Meat quality traits of Vietnamese indigenous Noi chicken at 91 days old

2020 ◽  
Vol 36 (2) ◽  
pp. 191-203
Author(s):  
Nguyen Tuoi ◽  
Nguyen Giang ◽  
Huynh Loan ◽  
Phan Phuc ◽  
Dai Van ◽  
...  
Keyword(s):  
Meat Quality ◽  
Dry Matter ◽  
Storage Time ◽  
Cooking Loss ◽  
Drip Loss ◽  
Quality Traits ◽  
Breast Meat ◽  
Indigenous Chicken ◽  
Chicken Breeds ◽  
Meat Samples

Indigenous chicken breeds have showed slower growth rate and yield lower meat production, compared to commercial broilers. However, their meat quality is valued by modern consumers. The present study aimed at analyzing the quality traits of breast meat samples of Noi broilers, one of the famous indigenous chicken breeds in Vietnam. A total of 355 breast fillet samples were collected to evaluate quality meat traits such as pH, surface color, drip loss, and cooking loss at different time points of 3, 24, and 48 hours after slaughtering as well as to analyze chemical compositions such as dry matter, crude protein and ether extract. As result, sex and cold-storage time significant affect some of quality traits of breast meat, whereas their interaction did not associate among the observed properties. After 3 hour-storage, the pH value was determined at 5.63, then decrease to 5.56 and 5.55 after 24 and 48 hours, respectively. The color values (L*, a*, and b*) were in the normal range reported from previous studies. Meat samples of two sexes did not vary in the cooking loss and drip loss values, whereas it was significantly different due to cold-storage time. The ether extract content of the meat was found negatively correlated with the cooking loss. The higher dry matter content of breast meat resulted in the lower drip loss value after 3h coldstorage (r=-0.12, P<0.05). There is a negative relationship between L* and a*. The variation demonstrated in this study can be used in breeding schemes in order to improve meat quality of Noi chicken lines.

scholarly journals Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Delphine M. Pott ◽  
Sara Durán-Soria ◽  
Sonia Osorio ◽  
José G. Vallarino
Keyword(s):  
Quality Trait ◽  
Quality Traits ◽  
Crop Species ◽  
Breeding Programs ◽  
Crop Quality ◽  
Crop Varieties ◽  
New Genes ◽  
Technical Advances ◽  
Health Promoting ◽  
Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

scholarly journals Hourly Ground-Level PM2.5 Estimation Using Geostationary Satellite and Reanalysis Data via Deep Learning

2021 ◽  
Vol 13 (11) ◽  
pp. 2121
Author(s):  
Changsuk Lee ◽  
Kyunghwa Lee ◽  
Sangmin Kim ◽  
Jinhyeok Yu ◽  
Seungtaek Jeong ◽  
...  
Keyword(s):  
Cross Validation ◽  
Ground Level ◽  
Reanalysis Data ◽  
Training Dataset ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface

This study proposes an improved approach for monitoring the spatial concentrations of hourly particulate matter less than 2.5 μm in diameter (PM2.5) via a deep neural network (DNN) using geostationary ocean color imager (GOCI) images and unified model (UM) reanalysis data over the Korean Peninsula. The DNN performance was optimized to determine the appropriate training model structures, incorporating hyperparameter tuning, regularization, early stopping, and input and output variable normalization to prevent training dataset overfitting. Near-surface atmospheric information from the UM was also used as an input variable to spatially generalize the DNN model. The retrieved PM2.5 from the DNN was compared with estimates from random forest, multiple linear regression, and the Community Multiscale Air Quality model. The DNN demonstrated the highest accuracy compared to that of the conventional methods for the hold-out validation (root mean square error (RMSE) = 7.042 μg/m3, mean bias error (MBE) = −0.340 μg/m3, and coefficient of determination (R2) = 0.698) and the cross-validation (RMSE = 9.166 μg/m3, MBE = 0.293 μg/m3, and R2 = 0.49). Although the R2 was low due to underestimated high PM2.5 concentration patterns, the RMSE and MBE demonstrated reliable accuracy values (<10 μg/m3 and 1 μg/m3, respectively) for the hold-out validation and cross-validation.

scholarly journals 41 Estimating the heritability of meat quality traits in turkeys

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 18-19
Author(s):  
Ryley J Vanderhout ◽  
Michelle Yahiro ◽  
Benjamin Wood ◽  
Shai Barbut ◽  
Jeff S Mohr ◽  
...  
Keyword(s):  
Meat Quality ◽  
Shear Force ◽  
Live Weight ◽  
Drip Loss ◽  
Quality Traits ◽  
Breast Meat ◽  
Meat Yield ◽  
Meat Quality Traits ◽  
White Striping ◽  
Breast Meat Yield

Abstract Genetic selection for improved meat quality traits has been successfully implemented in many livestock species. The objective of this study was to estimate the heritability of several meat quality traits to assess their selection potential in turkeys. Pedigree toms (n = 1,033) were processed at a commercial facility and live weight, breast meat yield (as a percentage of live weight), ultimate pH, color (CIELAB values), drip loss, cooking loss, and shear force were recorded on M. pectoralis superficialis (fillet). White striping was also rated on a 1–4 scale. Heritabilities were estimated using univariate animal models in ASReml version 4.1. Hatch week and age at slaughter were included as fixed effects in the mode,l and 32 generations of pedigree records were used. Breast meat yield (h2 = 0.62; SE = 0.090) showed the highest heritability and was higher compared to previous estimates, probably due to the smaller sample size. Live weight (h2 = 0.31; SE = 0.078), ultimate pH (h2 = 0.36; SE = 0.087), lightness (h2 = 0.28; SE = 0.086), redness (h2 = 0.22; SE = 0.075), and white striping score (h2 = 0.27; SE = 0.085) all had moderate heritabilities. The estimate for ultimate pH was similar to previous studies in broilers but was high compared to previous studies in turkeys. Estimates for color were similar to those found in previous studies involving turkeys. Drip loss and cooking loss had similar heritability estimates of 0.13 (SE = 0.071) and 0.10 (SE = 0.064), respectively, which were akin to previous estimates in pork. Shear force (h2 = 0.02; SE = 0.056) was found to have a very low heritability. In conclusion, the heritability estimates provided in this study show great potential for the inclusion of meat quality traits in selection programs of turkeys. This study is part of a larger project working towards the implementation of genomic information in the selection of turkeys for improved meat quality.

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