Classification accuracy of different pork quality evaluation methods in assessment of meat with lowered drip loss

ABSTRACT: This study compared the diagnostic value of pork quality evaluation methods using different pH threshold values and time-points with muscle metabolites concentration threshold values measured 45 min. post mortem in assessment of meat with lowered drip loss. Samples of 100 longissimus dorsi (LD) (Landrace × Yorkshire) × Duroc fatteners were examined after slaughter for following parameters: muscle acidity in 35 min, 2 h, 3 h, 24 h and 48 h (pH1, pH2, pH3, pH24 and pH48), colour lightness (L*, a*, b*), meat yield after curing and thermal processing in 72 °C (technological yield), water-holding capacity (WHC) and drip loss in 48, 96 and 144 h (DL48, DL96, DL144). To verify the accuracy of analysed methods two groups were distinguished according to DL48, e.g. Low DL (DL48≤4%) and High DL (DL48>4%). In High DL pH1 to pH48 were statistically lower while L*, WHC, DL48, DL96, DL144 were statistically higher (P≤0.05). On the basis of pH-dependent methods classification to RFN (red, firm, normal), PSE (pale, soft, exudative), DFD (dark, firm, dry) and AM (acid meat) was performed and then the percentage share of Low DL and High DL among meat classified as RFN was evaluated. Despite most samples were classified as RFN Low DL share among them did not exceed 50%. If meat sample shows metabolites concentration below threshold value and was assigned to Low DL (or was assigned to High DL above threshold value) it was regarded as correctly classified. The most promising cut-off point (correct classification of 73%) was 45 µmol both for glycogen and lactate.

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A Simplified Approach for the Annual and Spatial Evaluation of the Comfort Classes of Daylight Glare Using Vertical Illuminances

Buildings ◽

10.3390/buildings8120171 ◽

2018 ◽

Vol 8 (12) ◽

pp. 171 ◽

Cited By ~ 5

Author(s):

Luigi Giovannini ◽

Fabio Favoino ◽

Valerio Lo Verso ◽

Anna Pellegrino ◽

Valentina Serra

Keyword(s):

Case Studies ◽

Grid Point ◽

Threshold Value ◽

Average Error ◽

Threshold Values ◽

Simplified Approach ◽

Annual Basis ◽

Venetian Blinds ◽

Simplified Method

A simplified approach to calculate the daylight glare comfort class (imperceptible, perceptible, disturbing, or intolerable glare) on annual basis and for a grid of points in a space is presented. This method relies on the calculation of the vertical illuminance (Ev) for each grid point only, which is compared to an Ev threshold value for each daylight glare comfort class. These Ev threshold values are determined through a comparison with the Daylight Glare Probability (DGP) values on an annual basis through a fault-detection technique, for a reduced number of points. Compared to an annual calculation of exact DGP values on a certain grid, this approach is able to evaluate the daylight glare comfort classes only, but it is less time consuming. The paper presents and critically discusses this simplified method by means of its application to different case-studies: south and west oriented office in Turin (Lat 45.1° N), in which the DGP is assessed for three points in the space, considering glazing with different transmission properties (specular or scattering) and visible transmittances, as well as three operable internal shading systems (one venetian blinds and two roller blinds, for solar or glare control). For the presented case studies, the average error in the classification of the space according to daylight glare comfort classes is below 5% when comparing this simplified approach to related DGP values.

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Relationship of glycogen and lactate concentrations as a pork quality indicator

South African Journal of Animal Science ◽

10.4314/sajas.v50i1.4 ◽

2020 ◽

Vol 50 (1) ◽

pp. 26-37

Author(s):

A Zybert ◽

K Tarczyński ◽

H Sieczkowska ◽

E Krzęcio-Nieczyporuk ◽

K Antosik

Keyword(s):

Lactate Concentration ◽

Muscle Metabolism ◽

Pork Quality ◽

Drip Loss ◽

Post Mortem ◽

Threshold Values ◽

B Values ◽

Muscle Ph ◽

Longissimus Lumborum ◽

Relationship Of

Muscle metabolites greatly determine pork quality. However, precise threshold values which indicate its deterioration or improvement are not fully known. This study aimed to determine the influences of pork Longissimus lumborum (LL) glycogen and lactate concentrations measured at 45 min post mortem on pH, colour (L*a*b*) and drip loss (DL) measured during 144 hours post mortem in order to prescribe appropriate threshold values. The investigation used 30 gilts and 30 barrows being fattened for slaughter. After slaughter, the carcasses were assigned to groups based on the observed levels of glycogen and lactate: low GlyL with glycogen ≤35 μmol/g, GlyM with glycogen between 35 and 55 μmol/g, GlyH with glycogen >55 μmol/g; LacL with lactate ≤40 μmol/g and LacH with lactate >40 μmol/g. Lower muscle pH was noted up to 24 h post mortem in the LacH group compared to LacL (P ≤0.01). 24 h post mortem higher pH was found in GlyL than in GlyM and GlyH (P ≤0.01), which were similar. Similarly no statistical differences were noted between The GlyM and GlyH groups were also similar in L*, DL96 and DL144, with lower values found for GlyL (P ≤0.01). Compared to LacH, LacL had lower L*, DL48, DL96 and DL144 (P ≤0.01) and higher a* and b* values. Muscle pH, drip loss, L* and a* values were more affected by lactate concentration if the glycogen concentration ≥35 μmol/g muscle tissue. Thus, metabolite concentration may be a useful and valuable indicator of pork quality. Keywords: drip loss, glycolytic resources, pork colour, post-mortem muscle metabolism

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Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100068096 ◽

1970 ◽

Vol 28 ◽

pp. 220-221

Author(s):

Gerald Fine ◽

Azorides R. Morales

Keyword(s):

Cardiac Myxoma ◽

Osteogenic Sarcoma ◽

Diagnostic Value ◽

Soft Tissue Tumors ◽

Amelanotic Melanoma ◽

Growth Patterns ◽

Light Microscopic Level ◽

Mesenchymal Tumors ◽

Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

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Graphic technology. Image quality evaluation methods for printed matter

10.3403/30349149 ◽

2020 ◽

Keyword(s):

Image Quality ◽

Quality Evaluation ◽

Evaluation Methods ◽

Image Quality Evaluation

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Image quality evaluation methods for printed matter

10.3403/30379074 ◽

2020 ◽

Keyword(s):

Image Quality ◽

Quality Evaluation ◽

Evaluation Methods ◽

Image Quality Evaluation

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Graphic technology � Image quality evaluation methods for printed matter

10.3403/30397804u ◽

2020 ◽

Keyword(s):

Image Quality ◽

Quality Evaluation ◽

Evaluation Methods ◽

Image Quality Evaluation

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Monotonic Functions Method and Its Application to Staging of Patients with Prostate Cancer According to Pretreatment Data

Applied Sciences ◽

10.3390/app11093836 ◽

2021 ◽

Vol 11 (9) ◽

pp. 3836

Author(s):

Valeri Gitis ◽

Alexander Derendyaev ◽

Konstantin Petrov ◽

Eugene Yurkov ◽

Sergey Pirogov ◽

...

Keyword(s):

Prostate Cancer ◽

Learning Algorithm ◽

Binary Classification ◽

Preoperative Staging ◽

Threshold Value ◽

Logical Function ◽

Adequate Treatment ◽

Monotonic Functions ◽

Selection Of

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.

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Classification of extinction profiles for a one-dimensional diffusive Hamilton–Jacobi equation with critical absorption

Proceedings of the Royal Society of Edinburgh Section A Mathematics ◽

10.1017/s030821051700049x ◽

2018 ◽

Vol 148 (3) ◽

pp. 559-574

Author(s):

Razvan Gabriel Iagar ◽

Philippe Laurençot

Keyword(s):

Differential Equation ◽

Ordinary Differential Equation ◽

Jacobi Equation ◽

Threshold Value ◽

Monotonicity Property ◽

Fast Diffusion ◽

Extinction Time ◽

One Step ◽

Hamilton Jacobi Equation

A classification of the behaviour of the solutions f(·, a) to the ordinary differential equation (|f′|p-2f′)′ + f - |f′|p-1 = 0 in (0,∞) with initial condition f(0, a) = a and f′(0, a) = 0 is provided, according to the value of the parameter a > 0 when the exponent p takes values in (1, 2). There is a threshold value a* that separates different behaviours of f(·, a): if a > a*, then f(·, a) vanishes at least once in (0,∞) and takes negative values, while f(·, a) is positive in (0,∞) and decays algebraically to zero as r→∞ if a ∊ (0, a*). At the threshold value, f(·, a*) is also positive in (0,∞) but decays exponentially fast to zero as r→∞. The proof of these results relies on a transformation to a first-order ordinary differential equation and a monotonicity property with respect to a > 0. This classification is one step in the description of the dynamics near the extinction time of a diffusive Hamilton–Jacobi equation with critical gradient absorption and fast diffusion.

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