Comparing AUS-MEAT marbling scores using image analysis traits to estimate genetic parameters for marbling of Japanese Black cattle in Australia

The aim of the present study was to evaluate the application of image analysis for Japanese Black cattle in Australia (Australian JB). Therefore, we assessed meat quality using an image analysis method to estimate the heritability of this trait in Australian JB. We photographed the cross-section of the 5th–6th ribs and calculated image analysis traits of 473 and 539 head of Australian JB and Australian JB sire crosses with other breeds (F1), respectively. Least square means of grading and image analysis traits were calculated. We further estimated the heritability of grading and image analysis traits of 414 head of Australian JB. The Australian Meat Industry Classification System (AUS-MEAT) marbling score (6.8) and percentage marbling area (29.2%) for Australian JB were significantly (P < 0.01) higher than those for F1 (4.7% and 19.3%, respectively). Percentage marbling area strongly correlated with the AUS-MEAT marbling score (r = 0.88), indicating that marbling can be improved using percentage marbling area as a substitute for AUS-MEAT marbling score. The head counts of AUS-MEAT marbling score increased in the Australian JB (mode value = 9). The result indicated that the AUS-MEAT marbling score lacks a sufficient range of values to evaluate a high marbling beef breed such as the Australian JB. Further, the heritability of percentage marbling area was 0.54, which is higher than the heritability of AUS-MEAT marbling score (0.23). Therefore, we conclude that determining percentage marbling area using image analysis may prove to be an effective method for improving the marbling of the Australian JB.

Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy

X-Ray absorption spectromicroscopy provides rich information on the chemical organization of materials down to the nanoscale. However, interpretation of this information in studies of “natural” materials such as biological or environmental science specimens can be complicated by the complex mixtures of spectroscopically complicated materials present. We describe here the shortcomings that sometimes arise in previously-employed approaches such as cluster analysis, and we present a new approach based on non-negative matrix approximation (NNMA) analysis with both sparseness and cluster-similarity regularizations. In a preliminary study of the large-scale biochemical organization of human spermatozoa, NNMA analysis delivers results that nicely show the major features of spermatozoa with no physically erroneous negative weightings or thicknesses in the calculated image.

3D SHAPE RECONSTRUCTION OF HYBRID REFLECTANCE USING THE LMS ALGORITHM

In this paper, we present a new approach for determining the reflectance properties of surface and recovering 3D shapes from intensity images. We determine reflectance parameters which minimize the sum squared difference of the intensity distribution between the image of a sample sphere and the calculated image. The estimated reflectance parameters provide the range data with intensity distributions. Therefore, we generate three reference images of a range sphere, which has the same diameter as that of the sample, from the same viewpoint but with different light directions. Direct matching of the object images to the references can precisely reconstruct the shape of the object. This paper uses a plate diffuse illumination to alleviate the effects of specular spike and highlights. The simulation results show that the proposed method can estimate reflectance properties of the hybrid surface, and also recover the object shape.

ESTIMATION OF HYBRID REFLECTANCE PROPERTIES AND SHAPE RECONSTRUCTION USING THE LMS METHOD

This paper presents a new method to estimate reflectance properties of non–Lambertian surface by the least-mean-square (LMS) algorithm. In this paper, hybrid reflectance of an object is represented by the Torrance–Sparrow model. We determine reflectance parameters which minimize the sum squared difference of the intensity distribution between the image of a sample sphere and the calculated image. The estimated reflectance parameters provide the range data with intensity distributions. Therefore, we generate three reference images of a range sphere, which has the same diameter as that of the sample, from the same viewpoint with different light directions. Direct matching of the object images to the references can precisely reconstruct the shape of the object. This paper uses a plate diffuse illumination to alleviate the effects of specular spike and highlights. The simulation results show that the proposed method can estimate reflectance properties of the hybrid surface, and also recover the object shape.

Quantitative χn analysis of HREM images with applications to planar defects

A number of different methods have been suggested in the literature for using HREM in a quantitative fashion, including R factors and cross-correlation analyses. The problem with many of these is that it is difficult to realistically gauge the errors involved when they are applied to real systems. For instance, R-factors defined by:(1)(where n=1 or 2 and Ic is the calculated image, Ie the experimental data) assume a signal independent error. Furthermore, the absolute value of R is strongly dependent upon background levels which is misleading.

Calculated image contrast of vacancies in silicon crystal and representation of their contrast anomalies

Images of small lattice defects have been observed as a contrast anomaly recently by HREM. However, the observed images are generally mixed with the contrast anomalies which come from the quantum noise, contamination etc. Therefore, it seems to be useful to know the calculated image and to compare with the observed ones. In this paper, calculated image contrast of Si containing vacancies is studied.The stress field due to a stacking fault tetrahedron (SFT) proposed by Yoffe has been extrapolated to that of a vacancy. Since the atomic structure around the vacancies is not yet clearly known, it is assumed that a pair of vacancies in Si behaves like single vacancy in f.c.c. crystals. Figure 1 shows a pair of vacancies position (®-®) in a large unit cell with 0.38nm thickness of Si crystal projected to [110]. It is necessary for this calculation to have the large unit cell because the stress field effects on the atom positions at an infinite distance.