Piotr Ślósarz

The effect of sex on the dressing percentage, carcass, and organ quality in the fallow deer (Dama dama)

Abstract Basic carcass characteristics, the quality traits of meat and internal organs from 10 fallow deer bucks and 10 does aged from 31 to 32 months were investigated. No sex effects on the bled body weight, meat yield and carcass composition were found. A significantly higher weight of mesenteric and omental fat (by 0.44 kg) was found for does. The combined share of muscle and fat in the carcass parts ranged from 77.9 to 78.5%, and the share of bones from 21.5 to 22.1%. No sex effects were found for the pH and water holding capacity measurements. Venison from males was characterized by a significantly higher thermal drip value (P=0.043) and higher L* (P=0.026), a* (P=0.010) and b* (P=0.036) values compared to does. The extracted fat content was significantly higher for females compared to males (P=0.009). The chemical analysis of deer edible by-products indicated the highest level of protein for the liver (17%), and the highest level of dry matter and fat for the tongue (33-34% and 15-18%, respectively).

Quality of meat from three muscles of farmed fallow deer (Dama dama)

The quality of three muscles (supraspinatus, longissimus, semimembranosus) were studied in a group of 12 farmed fallow deer bucks (Dama dama) aged 28 months. The aim was to compare the selected quality traits of these muscles and to assess the extent to which these traits change after 14 days of being stored in vacuum packaging. Both the pH and the temperature were significantly affected by the muscle (P < 0.0001) and the time of storage (P < 0.0001). The supraspinatus muscle had the highest initial and final pH (pH0.5 h = 6.95; pH15d = 5.93), while m. semimembranosus showed the greatest drop in temperature (by 37.5°C) 24 h postmortem. The colour parameters differed among muscles. Only lightness (L*) was not influenced by the duration of storage (P = 0.081). The 14-day storage in a vacuum bag caused a decrease in the drip loss (P = 0.002), free water (%; P = 0.001), free water (cm2; P < 0.0001) and a cooking loss (P = 0.050). The duration of time in storage caused an increase in the dry-matter (P = 0.049) and crude-protein (P = 0.044) contents and a decrease of the water to protein ratio (W : CP; P = 0.014). There was a significant effect of muscle on the dry-matter (P < 0.0001) and crude-protein (P < 0.001) contents and W : CP (P < 0.0001). The highest contents of dry matter (P ≤ 0.01) and crude protein (P ≤ 0.01) were found in m. longissimus. The highest W : CP was observed in m. supraspinatus (W : CP24 h = 4.02; W/CP15d = 3.92). The results indicated a different technological quality of the analysed muscles, and, thus, a need to further explore the background of these differences in the early postmortem period and after meat maturation.

Marbling classification of lambs carcasses with the artificial neural image analysis

This paper describes a part of research, whose goal was to develop an effective method to determine marbling classes of lamb carcasses, with the neural image analysis techniques. Current methods for identifying the degree of intramuscular fat level content are time consuming, require specialized expertise and often rely on subjective assessment based on predefined patterns. In this paper, authors proposes the use of neural model developed as a tool to assist evaluation of marbling.

Methodology of data processing in the process of neural image analysis of pork half carcasses

This article describes data processing in neural analysis of the images of pork half carcass. Parameters of pork halfcarcass obtained from three-dimensional analysis, was processed into form of 130 files. These files has been used as learning sets for the artificial neural network simulator - STATISTICA. Next, we obtained the set of neural models from which the best was chosen. For all data processing activities in this research process were used applications developed in C # in the Visual Studio 2015 development environment.

Unsupervised neural classification of six chosen apple pests using learned vector quantization agorithm

The aim of this work was a neural identification of selected apple tree orchard pests in Poland. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning files acquired on the basis of information contained in digital photographs of pests. There has been identified 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the chosen agrofags, neural networks type Self-Organizing Feature Map (SOFM) methods supported Learned Vector Quantization (LVQ) algorithm were utilized, using by digital analysis of image techniques.

Novel ultrasound approach for measuring marbling in pork

An ultrasound examination was done on the m. longissimus lumborum, between the 10th and the 11th thoracic vertebra, on two sides (inside and outside the thoracic cavity) of the left half-carcasses of 162 fatteners. The carcasses were classified for lean meat percentage using the SEUROP system. The R pig carcasses (47.7% lean) had the thickest backfat (30.6mm; P≤0.01) and the highest content of intramuscular fat (IMF=2.28%; P≤0.01). More artifacts-free images were collected from the inside compared to the outside of the pig carcasses (90.1% vs. 58.6%; P≤0.01). The percent of bright pixels (PBP) was the highest for the inside, for all the lean-meat-content classes (P≤0.01). The correlation between the PBP and the IMF was higher for the images of the inside compared to the outside (r=0.811; P=0.001 vs. r=0.523; P=0.009). The ultrasound images of the inside of the carcasses proved to be the most useful for making an assessment of the marbling.

A computer method to analyse the impact of ultrasound frequency on the brightness of USG images of muscle cross-sections

A total number of 270 ultrasound images of m. longissimus behind the 13th thoracic vertebrae were obtained on 90 lamb carcasses. Three different scanning frequencies were used (5.0, 7.5 and 10.0 MHz) in order to analyse how the frequency of the ultrasound wave affects the changes of pixel brightness in the ultrasound image. In the images obtained with 10 MHz probe the brightness of the 1st region was higher by 27% and 25% (P≤0.01) compared to the same region of images obtained with 5 MHz and 7.5 MHz frequency probe. The 3rd region of muscle cross-sections obtained with 10 MHz frequency was very dark, with the brightness lower by 22,5% and 28,3% compared to the same region of images obtained with 5 MHz and 7.5 MHz frequency. In the images obtained with 10 MHz scanning frequency, the decrease of brightness from the 1st to the 3rd region of the image was very sharp. While in the images obtained by means of 5 and 7.5 MHz ultrasound frequency, the brightness changes between the regions were very fluent. To conclude, the results of the presented research reveal that high ultrasound frequency has a negative impact on ultrasound image brightness and may reduce the information value of the image.

Possibilities for the use of edge detection algorithms in the analysis of images of oilseed rape leaves

A study was carried out to analyse the quality and usefulness of methods of edge identification in the case of images of winter rape leaves. For this purpose a five available methods that are implemented in Matlab were used. The methods such as: Sobel, Robert, Prewitt, Cannys algorithms and on the other hand Laplacian of Gaussian were compared. The study focused on the image characteristics extraction and based on the results select those methods that will best respond on the research problem, which was to found the relationship between the detected edges, and incidence spots of fungal diseases in the oilseed rape cultivation. The aim of the article was to present the possibilities of using Matlab function to compare two approaches to edge detection. The first approach was the transformation of the images into gray-scale and create a histogram. The second one focused on dividing the image into three RGB components palette and then proceed with thresholding. On such prepared samples was conducted edge detection by used the above-mentioned methods.

Different methods of image segmentation in the process of meat marbling evaluation

The level of marbling in meat assessment based on digital images is very popular, as computer vision tools are becoming more and more advanced. However considering muscle cross sections as the data source for marbling level evaluation, there are still a few problems to cope with. There is a need for an accurate method which would facilitate this evaluation procedure and increase its accuracy. The presented research was conducted in order to compare the effect of different image segmentation tools considering their usefulness in meat marbling evaluation on the muscle anatomical cross – sections. However this study is considered to be an initial trial in the presented field of research and an introduction to ultrasonic images processing and analysis.