Prediction of beef quality attributes from early post mortem near infrared reflectance spectra

Rødbotten, Rune; Nilsen, B.N.; Hildrum, Kjell Ivar

doi:10.1016/s0308-8146(00)00059-5

Cited by 112 publications

(55 citation statements)

References 25 publications

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“…Typically, the two spectra show broad absorbance bands. The characteristics of the water bands are observed at different regions of the wavelengths of the spectrum, typically around 1400-1450 nm [16,21]. When the signal reaches higher harmonics (third and fourth harmonic (see Fig.2)), the signal reflection becomes weaker, so the spectrum absorbance is stronger at 1400-1500 nm.…”

Section: Spectral Study (Materials and Method)mentioning

confidence: 99%

“…Moreover, in a spectroscopic study carried out on pure fat in mammals [24], it was shown that the fat (marbling) has a strong absorbance signal at 930 nm. Also, according to [21,25], in this area, marbling contributes more to light absorbance. Thus, the distribution and architecture (shape) of the marbling present within the meat sample affect the path of light penetration into the muscles.…”

Section: Spectral Study (Materials and Method)mentioning

confidence: 99%

“…NIR light analysis provides valuable quantitative information for applications in several fields. For meat, several research projects have demonstrated that it can be used to measure moisture and marbling [21,22,23].…”

Section: Fig1 Light Spectrum (Schematic Representation)mentioning

confidence: 99%

See 2 more Smart Citations

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Ziadi

Maldague

Saucier

et al. 2012

Infrared Physics & Technology

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Section: Spectral Study (Materials and Method)mentioning

confidence: 99%

Section: Spectral Study (Materials and Method)mentioning

confidence: 99%

See 1 more Smart Citation

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Ziadi

Maldague

Saucier

et al. 2012

Infrared Physics & Technology

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“…A homomorphic filtering technique [6] significantly improves target recognition performance on images with difficult illumination conditions.Homomorphic Filter approach for image processing is very well known as a way for image dynamic range and increasing contrast. According to this approach, input is assumed to have2 multiplicative elements: background and details.…”

Section: Homomorphic Filtermentioning

confidence: 99%

Object Recognition based on Template Matching and Correlation Method in Hyperspectral Images

Gupta¹,

Goswami²

2017

IJCA

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In past recent years, image processing of hyperspectral images have become more popular than earlier. New methods, techniques and logics are being evolved for extracting more information from a digital image, as the existing techniques of image processing and analyzing techniques are not quenching the thirst of today's demand. The research of image processing based on traditional low resolution image has already not satisfied the need for people to get more accurate information from high resolution hyperspectral images. The today's demand is, to get more information about some particular things and modify about a particular region from a digital hyperspectral image, this is particularly central to the urban plan and disaster observation. On the basis of analysis of the conventional techniques for information extracting from a digital image, a method of extraction particular object in hyperspectral image based on feature template correlation is proposed. There are three different pars in this technique: building the template, image match and template correlations, and object recognition. The methods are applied to several high-resolution example images, and vehicles as example object in the image are extracted and recognized. Those examples illuminate that the method proposed in this paper is very effective and accurate.

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“…SLAUGHTER et al (1989) used near infrared reflectance to measure the fat and protein content of samples of ground hog carcasses. There has been considerable interest in the application of NIR spectroscopy for evaluating the quality of beef (PARK et al, 1998;BYRNE et al, 1998;RØDBOTTEN et al, 2000) and pork (BRØNDUM et al, 2000;GEESINK et al, 2003;HOVING-BOLINK et al, 2005). IRIE (1999) evaluated different types of fiber optic probes (surface, contact, insertion or transmittance) for NIR spectroscopic evaluation of pork fat quality.…”

Section: Introductionmentioning

confidence: 99%

Estimation of body composition of pigs by a near-infrared interactance probe technique

Mitchell

Scholz²,

Solomon

2005

Arch. Anim. Breed.

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Near-infrared (NIR) interactance was evaluated as a potentially new method for estimating live body and carcass composition of pigs. Using a surface placed fiber optic probe, measurements of the live animal and carcass were made on a total of 120 pigs. These measurements were compared with lipid and protein content of soft tissue dissected from the pig carcass. NIR results were evaluated using multiple regression equations containing NIR readings at various locations on the body, combinations of wavelengths and with or without ultrasonic fat depth readings and body weight. NIR measurements made on the carcass predicted percent carcass fat (R = 0.71) better than did measurements made on the live animal (R = 0.66), however, both could be improved substantially by including live body weight in the prediction equation (R = 0.93 and 0.91). Spectral information indicated that the depth of tissue penetration and reflectance may be the primary limitation in this application of the current technology. IntroductionCompositional analysis by near-infrared (NIR) spectroscopy is based on the detection of definitive transmission or reflectance characteristics of radiation in the 850 to 2600 nm region by the major components (i.e., water, fat or protein) of the sample in question. NIR is widely used to predict the composition or quality of various plant materials (NORRIS, 1983). This technique has also been studied as a method for compositional analysis of homogeneous samples of animal tissues (KRUGGEL et al., 1981;LANZA, 1983) or whole-carcass composition of homogeneously prepared *Mention of a trade name does not constitute a guarantee or warranty by the USDA and does not imply its approval to the exclusion of other products that may be suitable.Arch. Tierz. 48 (2005) 6

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Prediction of beef quality attributes from early post mortem near infrared reflectance spectra

Cited by 112 publications

References 25 publications

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Object Recognition based on Template Matching and Correlation Method in Hyperspectral Images

Estimation of body composition of pigs by a near-infrared interactance probe technique

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