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

2014 ◽  
Vol 54 (5) ◽  
pp. 557 ◽  
Author(s):  
Sakura Maeda ◽  
Joe Grose ◽  
Keisuke Kato ◽  
Keigo Kuchida
Keyword(s):  
Image Analysis ◽  
Least Square ◽  
Meat Industry ◽  
Strongly Correlated ◽  
Analysis Method ◽  
Japanese Black Cattle ◽  
Marbling Score ◽  
Beef Breed ◽  
Range Of Values ◽  
Calculated Image

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.

scholarly journals Influence of digitization input device on calculation of print (non)uniformity value of prints using ISO 13660 method

2020 ◽  
Author(s):  
Ivana Jurič ◽  
◽  
Dragoljub Novaković ◽  
Nemanja Kašiković ◽  
Sandra Dedijer ◽  
...  
Keyword(s):  
Image Analysis ◽  
Light Source ◽  
Mobile Phones ◽  
Quality Attributes ◽  
Input Device ◽  
Strongly Correlated ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Input Devices ◽  
Matlab Code

This paper examines the influence of the digitization input device on the print nonuniformity value when using the ISO 13660 method. This method belongs to the group of techniques called Image Analysis Method (IAM), so the basis for calculating the quality attributes is a digitized print. We selected six different devices: three flatbed scanners and three mobile phones. All settings were constant, such as the scan resolution (600 spi) and light source (D50). To have controlled prints, they were simulated using the MATLAB code - Macro Uniformity Toolbox and printed using the Epson Stylus PRO 7800 InkJet machine. We simulated random print nonuniformity know as small-scaled (graininess) and large-scaled (mottle). The calculated values differ drastically by changing the digitization device, while the values within the same group of devices are strongly correlated. The obtained results indicate the need to expand the standard and define more precise settings for input devices.

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽  
2021 ◽  
pp. 101447
Author(s):  
Fabio Valoppi ◽  
Petri Lassila ◽  
Ari Salmi ◽  
Edward Haeggström
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Release Test

An automatic analysis method for in situ hybridization using high-resolution image analysis

1989 ◽  
Vol 281 (5) ◽  
pp. 336-341 ◽  
Author(s):  
W. Stolz ◽  
K. Scharffetter ◽  
W. Abmayr ◽  
W. K�ditz ◽  
T. Krieg
Keyword(s):  
Image Analysis ◽  
In Situ Hybridization ◽  
High Resolution ◽  
Automatic Analysis ◽  
Analysis Method ◽  
Resolution Image ◽  
High Resolution Image

A Computerized Image Analysis Method for Measuring Elastic Tissue.

1989 ◽  
Vol 93 (3) ◽  
pp. 358-362 ◽  
Author(s):  
Thomas J. Flotte ◽  
Johanna M. Seddon ◽  
Yuqing Zhang ◽  
Robert J. Glynn ◽  
Kathleen M. Egan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Elastic Tissue ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Computerized Image Analysis

Collision-Free Tool Path Generation for Five-Axis High Speed Machining

2011 ◽  
Vol 474-476 ◽  
pp. 961-966 ◽  
Author(s):  
Li Qiang Zhang ◽  
Min Yue
Keyword(s):  
Image Analysis ◽  
Collision Detection ◽  
High Speed ◽  
Tool Path ◽  
Geometric Model ◽  
High Speed Machining ◽  
Analysis Method ◽  
Geometric Information ◽  
Detection Approach ◽  
Five Axis

Collision detection is a critical problem in five-axis high speed machining. Using a combination of process simulation and collision detection based on image analysis, a rapid detection approach is developed. The geometric model provides the cut geometry for the collision detection and records a dynamic geometric information for in-process workpiece. For the precise collision detection, a strategy of image analysis method is developed in order to make the approach efficient and maintian a high detection precision. An example of five-axis machining propeller is studied to demonstrate the proposed approach. It has shown that the collision detection task can be achieved with a near real-time performance.

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