Use of linear regression and partial least square regression to predict intramuscular fat of pig loin computed tomography images

Font-i-Furnols, Maria; Brun, A.; Tous, Núria; Gispert, M.

doi:10.1016/j.chemolab.2013.01.005

Cited by 33 publications

(24 citation statements)

References 23 publications

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“…The best prediction model was achieved by scaling with an RMSEP of 0.48 and a R squared of 0.18. The prediction errors had the same level as found by Font-i-Furnols et al [1] in prediction of IMF in post mortem pork loins, but the explained variance (R squared) was significantly lower. This might be due to the variation in the sample, our sample set had a lower variance (std.…”

Section: Resultssupporting

confidence: 68%

“…Since its introduction to animal sciences in the early eighties [5], computed tomography (CT) has been used to estimate and predict the body composition of farmed animals. In recent years, several studies have examined the use of CT to predict intramuscular fat and fatty acid composition using CT [1,6]. Both studies concluded that CT could be used to predict the IMF content post mortem in carcasses or meat samples.…”

Section: Introductionmentioning

confidence: 99%

“…Intramuscular fat (IMF) in meat is an important trait due to the impact on sensory quality and acceptance of pork meat [1]. IMF is generally determined by extracting IMF from muscle [2] or by spectroscopic methods [3].…”

Section: Introductionmentioning

confidence: 99%

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<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography

Kongsro¹,

Gjerlaug-Enger²

2013

OJAS

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One hundred and four pure-bred Norwegian Duroc boars were CT (computed tomography) scanned to predict the in vivo intramuscular fat percentage in the loin. The animals were slaughtered and the loin was cut commercially. A muscle sample of the m. Longissimus dorsi was sampled and analyzed by the use of near-infrared spectroscopy. Data from CT images were collected using an in-house MATLAB script. Calibration models were made using PLS (partial least square) regression, containing independent data from CT images and dependent data from near-infrared spectroscopy. The data set used for calibration was a subset of 72 animals. The calibration models were validated using a subset of 32 animals. Scaling of independent data and filtering using median filtering were tested to improve predictions. The results showed that CT is not a feasible method for in vivo prediction of intramuscular content in swine.

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Section: Resultssupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

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<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography

Kongsro¹,

Gjerlaug-Enger²

2013

OJAS

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“…Given the pixel resolution of the CT images (1 × 1 mm), the increased cell size in cattle may result in better tissue/density differentiation between pixels, potentially amplifying the density differences between high and low IMF samples. However in contrast to this, the IMF% of pork (Font-i-Furnols et al, 2013) and lamb (Clelland et al, 2014) has been predicted using CT, indicating cell size alone does not account for the relatively poor prediction of IMF% in our study.…”

Section: Discussioncontrasting

confidence: 99%

The correlation of intramuscular fat content between muscles of the lamb carcass and the use of computed tomography to predict intramuscular fat percentage in lambs

Anderson

Pethick

Gardner

2015

Animal

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Intramuscular fat (IMF) % contributes positively to the juiciness and flavour of lamb and is therefore a useful indicator of eating quality. A rapid, non-destructive method of IMF determination like computed tomography (CT) would enable pre-sorting of carcasses based on IMF% and potential eating quality. Given the loin muscle (longissimus lumborum) is easy to sample, a single measurement at this site would be useful, providing is correlates well to other muscles. To determine the ability of CT to predict IMF%, this study used 400 animals and examined 5 muscles from three sections of the carcass: from the fore-section the m. supraspinatus and m. infraspinatus, from the saddle-section the m. longissimus lumborum and from the hind-section the m. semimembranosus and m. semitendinosus. The average CT pixel density of muscle was negatively associated with IMF% and can be used to predict IMF% although precision in this study was poor. The ability of CT to predict IMF% was greatest in the m. longissimus lumborum (slope −0.07) and smallest in the m. infraspinatus (slope −0.02). The correlation coefficients of IMF% between the five muscles were variable, with the highest correlation coefficients evident between muscles of the fore section (0.67 between the m. supraspinatus and the m. infraspinatus) and the weakest correlations were between the muscle of the fore and hind section. The correlation between the m. longissimus lumborum to the other muscles was fairly consistent with values ranging between 0.34 and 0.40 (partial correlation coefficient). The correlation between the proportion of carcass fat and the IMF % of the five muscles varied and was greatest in the m. longissimus lumborum (0.41).Keywords: intramuscular fat, computed tomography, lamb, lean meat yield, fatness ImplicationsThe intramuscular fat% (IMF%) of lamb is linked to eating quality. Currently in Australia, IMF% is determined in lamb for experimental purposes only, mainly in the longissimus. The use of technologies such as computed tomography (CT) to predict IMF% in muscle would allow for the rapid and non-destructive determination of IMF% before carcass sorting. There is information regarding the use of CT to determine the IMF% of the M. longissimus but little data to assess the success of this technique in other muscles in the lamb carcass. Additionally, the correlation of IMF% between muscles from different regions of the carcass is currently unknown, with this information required to determine if a single muscle is appropriate to determine the IMF% of other muscles. The potential to utilise CT to estimate the intramuscular fat% of lamb is currently limited by the precision of the technique and the lack of their installation in abattoirs. CT has the potential for non-invasive point measurement in the loin for rapid prediction of intramuscular fat, and therefore eating quality, of multiple muscles in the carcass. If individual lamb and on farm data is concurrently available then the ability to predict intramuscular fat from CT scanning would be improv...

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“…30 According to the standard of cumulative contribution to x more than 75%, the Table 5 shows that the first potential factors can preferable explain the original independent variables, the values of cumulative contribution TVB-N value, TBA value, POV value, TAM-N value based on the developed PLSR models were 79.0%, 79.1%, 79.0%, 79.1%, respectively which indicated the regression equation regression effect is very good. Meanwhile, the textural properties parameters was more powerful in predicting TVB-N values, TBA values, POV value, TMA-N value, which also demonstrated that PLSR was suitable and competent for selecting the informative variables in this study.…”

Section: The Correlation Between Freshness and Tpa Parametersmentioning

confidence: 99%

The Correlation Research on Yak Meat Texture Profile Analysis (Tpa) And Freshness Parameters During Refrigerated Storage

Li¹

2015

MOJFPT

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Abbreviations: TPA, texture profile analysis; TVB-N, total volatile basic nitrogen; TBA, thiobarbituric acid; POV, peroxide value; TMA-N, trimethylamine nitrogen; MDA, malondialdehyde IntroductionYak (Bos grunniens) is the large ruminant species in the high altitude Qinghai-Tibetan Plateau, China, which is characterized by year-round low temperatures and hypoxic atmosphere. There is the most yaks in China, and yak meat is an natural green food.1 The protein content of yak meat is about 22%, fat content is lower than 3%, 2 it's a kind of high protein, low fat animal foods. A chemical change of yak meat by the endogenous enzymes and the pathogenic microorganisms, and also the sensory properties and the composition changed, nutritional value reduce, and there are some toxic or harmful substances the same time, it's harmful to the consumers, 3 it is a comprehensive evaluation index that freshness of yak meat could be used as a judgment during cold storage, it is largely reflects the meat quality, nutritional value and safety coefficient.4 So measuring the freshness of yak meat during cold storage, which can effectively prevent food health security problem occurs, how to accurately and objective measure of yak meat freshness using rapid methods, it's a subject of intense interest in recent years.At present, the methods of evaluation the yak meat freshness is mainly measuring the freshness parameters (TVB-N value, TBA value, POV value, TMA-N value).5 Proteins come into being the alkaline nitrogenous substances due to microorganism and endogenous enzymes during storage, One of the most main is volatile base nitrogen, TVB-N value is one of the important indicators to evaluate meat freshness, it is can be evaluate the meat freshness by measuring the value of TVB-N, and it is used as a national standard of measuring meat freshness.6 Fat occur different degree oxidation in the during storage, and TBA value show lipid secondary oxidation products or the number of the final products.7 However, there is a disadvantages that needs complicated sample preparation work and trival test operation, complex Procedure, consuming too much time.It is not convenient to frequently and widely implement, it cannot satisfy far from rapid and large quantities measurement, 8 it is a urgent request that find a method of rapid measurement. In recent years, many scholars have studied the relationship between sensory evaluation and instrumental determination values. It is observed that three is a significant or extremely significant correlation between the textural properties and the sensory evaluation value of pork.9 The correlations between the textural properties and volume water content of date palm.10 It was observed that hardness and springiness decreased linearly with the increase of water content, whereas increased linearly with the increase of fat content. 11Despite the above investigations, there is no study reported yet about the determination of textural properties parameters for evaluation of yak meat freshness using PLSR. Therefore, ...

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Use of linear regression and partial least square regression to predict intramuscular fat of pig loin computed tomography images

Cited by 33 publications

References 23 publications

<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography

<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography

The correlation of intramuscular fat content between muscles of the lamb carcass and the use of computed tomography to predict intramuscular fat percentage in lambs

The Correlation Research on Yak Meat Texture Profile Analysis (Tpa) And Freshness Parameters During Refrigerated Storage

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Use of linear regression and partial least square regression to predict intramuscular fat of pig loin computed tomography images

Cited by 33 publications

References 23 publications

&lt;i&gt;In vivo&lt;/i&gt; prediction of intramuscular fat in pigs using computed tomography

&lt;i&gt;In vivo&lt;/i&gt; prediction of intramuscular fat in pigs using computed tomography

The correlation of intramuscular fat content between muscles of the lamb carcass and the use of computed tomography to predict intramuscular fat percentage in lambs

The Correlation Research on Yak Meat Texture Profile Analysis (Tpa) And Freshness Parameters During Refrigerated Storage

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<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography

<i>In vivo</i> prediction of intramuscular fat in pigs using computed tomography