19 research outputs found

    Near-infrared light transmission in beef meat and qualitative marbling evaluation using image analysis

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    Marbling (intramuscular fat tissue) in beef meat is one of the most important criteria for quality, notably juiciness, in meat grading systems. Visual inspection of the meat surface is the common way to assign quality grading level, which is accomplished by authorized experts called graders. In the last years, several works were proposed in order to introduce computer vision on meat quality evaluation. In these works, meat grading was based exclusively on the analysis of meat surface images. In this paper, a new technique using near-infrared light in transmission mode is used to evaluate the beef meat quality based on the marbling detection. It is demonstrated that using near-infrared light in transmission mode, it is possible to detect the fat not only on the surface, as in traditional methods, but also under the surface. Also, in combining the analysis of the two sides of the meat simple, it is possible to estimate the volumetric marbling. We compared results from traditional techniques and those provided by the nearinfrared camera using light transmission. The result of this new study showed that using near-infrared light in transmission mode is a valuable technique to evaluate meat quality, thereby demonstrating the possibility of implementing this approach in a vision syste

    Prediction of beef marbling using Hyperspectral Imaging (HSI) and Partial Least Squares Regression (PLSR)

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    The aim of this study was to build a model to predict the beef marbling using HSI and Partial Least Squares Regression (PLSR). Totally 58 samples of longissmus dorsi muscle were scanned by a HSI system (400 - 1000 nm) in reflectance mode, using 44 samples to build the PLSR model and 14 samples to model validation. The Japanese Beef Marbling Standard (BMS) was used as reference by 15 middle-trained judges for the samples evaluation. The scores were assigned as continuous values and varied from 1.2 to 5.3 BMS. The PLSR model showed a high correlation coefficient in the prediction (r = 0.95), a low Standard Error of Calibration (SEC) of 0.2 BMS score, and a low Standard Error of Prediction (SEP) of 0.3 BMS score

    Prediction of beef marbling using Hyperspectral Imaging (HSI) and Partial Least Squares Regression (PLSR)

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    Vitamin A and marbling attributes: Intramuscular fat hyperplasia effects in cattle

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    © 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Twenty Angus steers were fed a diet low in β-carotene and vitamin A for 10 months. Ten steers were supplemented with vitamin A weekly, while the other ten steers did not receive any additional vitamin A. The results demonstrated that the restriction of vitamin A intake increased intramuscular fat (IMF) by 46%. This was a function of the total number of marbling flecks increasing by 22% and the average marbling fleck size increasing by 14%. Vitamin A restriction resulted in marbling flecks that were less branched (22%) and slightly more round (4%) with an increased minor axis length (7%). However, restricting vitamin A did not affect the size of the intramuscular or subcutaneous adipocyte cells or the subcutaneous fat depth. The results suggest that vitamin A affects the amount of marbling and other attributes of the marbling flecks due to hyperplasia rather than hypertrophy. This may explain why vitamin A restriction specifically affects IMF rather than subcutaneous fat deposition

    Analyse d'image visibles et proche infrarouges : contributions à l'évaluation non-destructive du persillage dans la viande du boeuf

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    Le persillage (gras intramusculaire) dans la viande de boeuf est l'un des critères les plus importants pour l'évaluation de la qualité, notamment sa jutosité, dans les systèmes de classification de la viande. Le processus chimique, méthode destructive, est l'unique moyen officiellement utilisé pour évaluer la proportion du persillage dans la viande. C'est une méthode destructive, complexe et qui n'offre aucune information sur la distribution du persillage dans la viande. Cette thèse porte sur le développement d'une méthode originale destinée à l'évaluation non-destructive de la proportion volumétrique du persillage dans la viande du boeuf. Cette nouvelle méthode, qui pourrait être intégrée dans un système de vision artificielle (machine vision), est une première expérience pour ce genre d'application. À notre meilleure connaissance, aucune méthode semblable n'a été élaborée. De ces travaux de doctorat quatre contributions sont identifiées: la technique proposée, deux méthodes de segmentation d'images et une méthode non-destructive pour estimer la proportion volumétrique du persillage. La technique proposée permet d'avoir deux types d'images : une visible qui illustre la surface de la viande et une proche infrarouge qui est la projection orthogonale de l'échantillon de la viande (3D) en une image d'ombre (2D). Compte tenu de la complexité d'analyse des images, nous avons développé une méthode efficace de segmentation permettant d'identifier les régions homogènes les plus (ou les moins) claires dans une image à niveaux de gris. Cette méthode, qui est relativement générale, est basée sur un modèle mathématique permettant d'évaluer l'homogénéité des régions, qui lui-même a été introduit dans cette thèse. La généralisation de cette méthode pour la segmentation du persillage a démontré des résultats satisfaisants face aux objectifs attendus. Étant donné, que la forme volumétrique du persillage est aléatoire et que celle-ci dépend de la façon dont le persillage est déposé entre les fibres musculaires, ce qui est imprévisible, nous avons combiné les résultats de la segmentation de deux types d'images pour estimer le volume du persillage. L'intégration de l'ensemble des approches précédentes nous a permis de développer une nouvelle méthode non-destructive pour estimer la proportion volumétrique du persillage. Les résultats obtenus par la méthode proposée (non-destructive) ont été comparés aux résultats obtenus par une méthode chimique (destructive) comme étant la vérité-terrain (gold standard). Les résultats expérimentaux confirment les propriétés attendues de la méthode proposée et ils illustrent la qualité des résultats obtenus

    Contemporary cowboy culture and the rise of American postmodern solidarity

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    In this dissertation, I build on contemporary theoretical perspectives to interpret characteristics of contemporary cowboy culture. Specifically, I target the image of the cowboy in relation to solidarity. I assume that contemporary cowboy culture is an illusion or simulacra of something, something maybe once authentic. Now, it is built around language games, illusion, image and many other postmodern phenomena. Even so, in this work I explore how postmodernism is useful, which many are hesitant to do. This is a new twist or at least an interesting study in contrast to the enlightenment project. I rely heavily on theoretical discussion, qualitative analysis, participant observation and interpretive interactionism to accomplish this study and engage this culture. I integrate this approach into the continuing question about progress and the relationship between postmodernism and modernism, which is characterized here by McDonaldization. I find contemporary society provides opportunities to celebrate the benefits and development of postmodern social bonding. As a result, postmodernism, characterized by chaos, contradiction, and especially illusion is found to actually create solidarity and allow for Jungian rebirth of something authentic

    Catalog 1986-87

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    https://openspace.dmacc.edu/catalogs/1013/thumbnail.jp

    On a Fluency Image Coding System for Beef Marbling Evaluation

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    This paper presents a Fluency Image Coding System of beef rib-eye images for Beef Marbling Evaluation. This is the second in a series of cooperative researches with the Japan Livestock Technology Association under an initiative to construct an Automated Online Beef Marbling Grading Support System by image analysis techniques. Our first cooperative research was on a Beef Marbling Grading Method, and was published in this journal in [Pattern Recognition Lett. 21 (12) (2000) 1037–1050]. This second cooperative research focuses on a binary image coding system that supports remote observation of beef marbling structure from a database of coded beef rib-eye images by users including meat graders, livestock producers, and researchers. Image encoding is by a novel automatic contour compression method based on function approximation via interpolation using the Fluency Compactly Supported Sampling Functions of degree 2. Image decoding, based on interpolation of the encoded data by the similar functions, enables the webbrowser based decoder to reconstruct the original fat contours smoothly even on Affine-transformed enlargement.Experimental results showing, respectively, size and image quality comparisons with other formats that support binary images and several enlargement schemes are included for evaluation

    Clemson Newsletter, 1969-1971

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    Information for the faculty and staff of Clemson Universityhttps://tigerprints.clemson.edu/clemson_newsletter/1004/thumbnail.jp
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