




































In ternationa l
Scholars
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African Journal of Pig Farming ISSN 2375-0731 Vol. 6 (3), pp. 001-007, March, 2018. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 

 

Full Length Research Paper 

 

Factorial analysis of slaughter characteristics of 
fattening pigs fed different additives–Enzyme and 

probiotic in mixtures 

 
Blazenka Popovic1*, Branislav Zivkovic2, Radojka Maletic1, Zoran Rajic1 and 

Svjetlana Jankovic-Soja1
 

 
1
University of Belgrade, Faculty of Agriculture, Nemanjina 6, 11080 Belgrade - Zemun, Serbia. 

2
Institute for Animal Husbandry, Autoput 16, 11080 Belgrade - Zemun, Serbia. 

 
Accepted 09 October, 2017 

 
To successfully investigate slaughter characteristics of fattening pigs fed in different ways, this experiment was 
carried out on Experimental Farm of the Institute for Animal Husbandry, Belgrade-Zemun. Investigation of correlation 
between slaughter traits of pigs fed with different additives in their nutrition was done by factorial analysis. Slaughter 
characteristics in three groups of fattening pigs fed in different ways were observed. The first group (variant 1) 
consisted of fatteners fed diets without any special additives. The second group (variant 2) consisted of pigs fed diets 
containing enzyme Rovabio, and the third group (variant 3) probiotic Lacture + Microbond. This study was aimed at 
coming to conclusion based on the results of factorial analysis of the observed traits to the greatest extent which 
determined slaughter traits of pigs fed diets containing different additives. The results obtained in general, that is, the 
structure of separated factors showed that different slaughter characteristics are realized with different nutrition. 

 
Key words: Fattening pigs, slaughter characteristics, enzyme Rovabio, probiotic Lacture + Microbond, factorial  
analysis. 
 
 
INTRODUCTION 

 
Probiotic preparations are used as food additives 
containing live micro organisms, used to replace or 
supplement micro flora of the digestive tract and 
protection of the animal health. The aim of their use is to 
reduce the utilization of antibiotics in animal nutrition, as 
much as possible, and that products are free of harmful 
residues. As a result, the following is realized: Increase of 
milk performance and of body mass, animal resistance, 
better use of nutrients, products of higher quality are 
obtained and environment is protected. Enzyme prepa-
rations are used in animal nutrition in order to improve the 
digestibility of food that is, increase the nutritional value of 
animal food. Multi-applicative solutions contri-bute to 
improvement of animal performances, enable use of 
more raw materials in nutrition and reduce phosphorus  
 
 

 
*Corresponding  author.  E-mail:  blazenka@agrif.bg.ac.rs.  Tel: 
+381112615315. Fax: +381113161730. 

 
 
 
 
 

 
emission on the farm (Gardzińska et al., 2003; Fililz et al., 
2008; Nortey et al., 2007; Kosovac et al., 2006).  

The influence of different genetic characteristic, as well 
as of food additions, is a topic of numerous researches  
(Collins et al., 2007 Ostrowska et al., 2005; Zivkovic et 
al., 2003c, 2006c) that are very important for improving 
slaughter characteristics of fattening pigs. Considering 
our positive experiences with the use of probiotics in 
nutrition of sows and piglets (Zivkovic et al., 2003a, b, 
2004a, b, 2006b, d; Radovic et al., 2007), as well as layer 
hens in production of table. The objective of this study 
was to investigate the effects of introduction of enzyme 
Rovabio and probiotic Lacture, based on yeast cultures 
Saccharmoyces cerevisiae and bacteria of lactic acid, 
enzymes and manane oligosaccharides, as well as 
Microbond, based on D-glucanes, in nutrition of fattening 
pigs (Xin et al., 2007; Angelov et al., 2010; Winiarska-
Mieczan and Kwiecien, 2010). Complete, clear and 
profound understanding of correlation between observed 
slaughter traits of fattening pigs can be achieved through 



 
 
 

 

the application of the method of factorial analysis, 
representing a set of mathematical-statistical procedures 
which enable that based on numerous mutually 
dependent and correlated variables less latent variables 
are determined which explain existing correlation. These 
fundamental variables which can elicit great number of 
mutually related variables are called factors. In this way, 
important task of factorial analysis is achieved as well as 
determination of homogeneity of observed characteristics 
(Fulgosi, 1979). At the same time, this means reduction 
of the number of properties, which is also a significant 
contribution of the application of this method. If inter-
correlation of traits is higher, factorization is more expres-
sed, that is, number of factors is lower, and amount of 
information which they contain on initial traits is greater 
(Ivanovic, 1977; Maletic, 2000). 
 

 
MATERIALS AND METHODS 
 
Investigations were carried out on Experimental Pig Farm of the 
Institute for Animal Husbandry, Belgrade-Zemun. Trial included total 
of 30 heads divided into three groups. According to present 
technology on the farm, and based on standard criteria of origin, 
sex and initial mass, animals were divided into three groups of 10, 
that is, three nutrition treatments.  

First, control group received diet of standard composition used on 
the pig farm. Secondly, trial group of animals was fed the same diet 
supplemented with enzyme Rovabio, and thirdly, trial group was fed 
standard diet supplemented with probiotic Lacture and Microbond. 
Pigs received food ad libitum during entire trial period and received 
water from automatic waterers. All analyzes were done with 
software Stat Soft STATISTICA 8.0 for Windows.  

Analyzed data relate to slaughter traits of pigs fed in three ways, 
that is, with different feed additives. 46 slaughter traits were 
observed for each of three nutrition methods, viz: x1- body mass of 
pigs prior to slaughtering (kg); x2– mass of warm carcass sides (kg); 
x3– fat thickness, withers (mm); x4– fat thickness, back (mm); x5– fat 
thickness, rump (mm); x6– carcass length, atlas– pubis (cm); x7– 

carcass length, 1
st

 rib– pubis (cm); x8– dressing percentage (%); 

x9– meat yield (% ); x10- leg (g); x11- shoulder (g); x12- back + fat 
tissue (g); x13 – rib fat (g); x14 – butt shoulder with neck (g); x15 – 
belly fat (g); x16– fore thigh (g); x17- kidney (g); x18- shank (g); x19- 
feet (g); x20– kidney fat (g); x21– head (g); x22– tender loin (g); x23– 
Jowl (g); x24– front ribs in butt shoulder with neck (g); x25– meat for 
smoking in butt shoulder with neck (g); x26– cut meat in butt 
shoulder with neck (g); x27– fat tissue in butt shoulder with neck (g); 
x28- skin in butt shoulder with neck ( g); x29– bones with 30% of 
meat in butt shoulder with neck, (g); x30- MLD loin part of the back 
(g); x31- cut meat in loin part of the back (g); x32– fat tissue in loin 
part of the back (g); x33– skin in loin part of the back (g); x34– bones 
in loin part of the back (g); x35– meat in the leg (g); x36– fat tissue in 
the leg (g); x37– skin in the leg (g); x38– bones in the leg (g); x39– 
meat in the shoulder (g); x40– fat in the shoulder (g); x41– skin in the 
shoulder (g); x42– bones in the shoulder (g); x43– meat in rib fat 
tissue (g); x44– fat in rib fat tissue (g); x45– skin in rib fat tissue (g); 
x46– bones in rib fat tissue (g). 
 

 
Statistical analysis 

 
For the obtained experimental data, descriptive statistics 
parameters have been defined first, and then the Pearson's 
correlation coefficients, in order to detect the correlation in 

 
 
 
 

 
slaughter characteristics by using different feeding methods 
(Popovic, 2001).  

The objective of the factorial analysis is to explain the mutual 
correlation between large number of variables with fewer 
fundamental variables (Lakic, 1984; Stankovic et al., 1985; Popovic, 
2005; Ralevic et al., 2006). Main task of the factorial analysis is to 
extract from initial set of indicators (x1,x2, ... xn) fewer (p<n) latent 
(hidden) factors (F1, F2 ... Fp), so the model of factorial analysis can 
be written down in the following form 

 
p 

X j ∑ajkFkεj j = 1,2,  n 
k −1 

 
Where, ajk represent factorial load of k latent factor on j indicator, 
and εj so called specific factors, that is, residual random 
components.  

Factorial analysis was carried out using the method of main 
factors where analysis of main components is applied on complete 
correlation matrix. Based on established characteristic equations 
and their square roots by Kaiser criteria, the number of factors 
which are maintained as relevant for further analysis is determined 
(only common factors with characteristic square root greater than 1 
(one) are maintained). After that orthogonal rotation of primary 
factorial solution using Kaiser varimax method was performed. By 
rotation, a factorial matrix was obtained whose elements are 
factorial ponders, and ponders of value above 0.7 are considered 
significant and based on their correlation with certain factor a factor 
interpretation was carried out. Methodology reveals that in the first 
factor the highest proportional share of total variation of all 46 traits 
is located, and in subsequent factors this proportion decreases. 
 

 

RESULTS AND DISCUSSION 
 
Average level and variability of observed slaughter 
characteristics for all three nutrition methods are 
presented in Table 1.  

Variability of observed traits was expressed by variation 
coefficient and it is almost low and below 30%, which 
indicated that these are homogenous series of data. 
 

 

Correlation analysis 
 
According to results of correlation analysis, correlation 
between slaughter properties realized in different nutrition 
treatments is similar.  

In case of first nutrition treatment, a very high negative 
correlation between the following indicators is observed: 
Fat thickness at withers and rump fat thickness; belly fat 
and butt shoulder with neck; head and shank; jowl and 
body mass of pigs prior to slaughtering; kidney fat and 
front ribs in butt shoulder with neck; fat in rib fat tissue 
and fat thickness (withers) etc. Very high positive 
correlation exists between the following characteristics: 
leg mass and body mass prior to slaughtering and mass 
of warm carcass sides; jowl and body mass of pigs prior 
to slaughtering; back fat and rump fat thickness; fat of the 
leg and carcass length (atlas-pubis); kidney fat and fat of 
the leg, etc.  

In case of t he second nutrition treatment, very high 



  
 
 

 
Table 1. Indicators of the average level and variability of slaughter characteristics.  
 

Indicator 
   Variant 1      Variant 2      Variant 3  

 

                 
 

 x S Cv (%)   x  S Cv (%)  x S Cv (%) 
 

x1 97.4 1.96 2.012 98.4 3.72 3.781 98.5 2.1679 2.201 
 

x2 76.3 1.503 1.97 74.6 2.82 3.777 75.33 2.5232 3.349 
 

x3 32.6 3.72 11.41 29.2 2.79 9.54 34.83 4.2622 12.24 
 

x4 19.6 1.625 8.29 17.6 2.5 14.19 16.67 2.582 15.49 
 

x5 20.6 3.382 16.42 20.8 3.43 16.49 16.67 3.6148 21.69 
 

x6 97.0 1.789 1.844 95.6 3.61 3.777 96 1.7607 1.834 
 

x7 80.7 2.088 2.587 79 5.4 6.84 80.5 0.8367 1.039 
 

x8 78.342 0.876 1.118 75.826 1.52 2.009 76.49 2.1707 2.838 
 

x9 41.706 0.888 2.13 42.668 1.2 2.821 43.57 1.0939 2.511 
 

x10 8208 220.9 2.691 8055 346 4.291 8147 426.22 5.232 
 

x11 4576 444.6 9.716 4704 323 6.859 4676 417.28 8.924 
 

x12 5688 428.3 7.53 5729 333 5.812 5493 576.11 10.49 
 

x13 4084 181.3 4.439 3984 341 8.553 3838 260.61 6.791 
 

x14 5018 822 16.38 5159 146 2.835 5132 716.56 13.96 
 

x15 2364 209.2 8.851 2227 142 6.381 2265 201.67 8.904 
 

x16 729 26.91 3.691 772 62.4 8.085 765 38.859 5.08 
 

x17 160 23.66 14.79 157 26.2 16.68 175.8 29.055 16.52 
 

x18 1360 88.99 6.544 1445 155 10.73 1422 135.08 9.502 
 

x19 684 37.2 5.439 707 47.9 6.777 702.5 36.021 5.128 
 

x20 750 178.1 23.75 583 149 25.54 657.5 186.19 28.32 
 

x21 1970 40.99 2.081 1840 201 10.91 2032 203.9 10.04 
 

x22 337 41.9 12.43 349 35 10.02 345.8 30.069 8.695 
 

x23 726 133.2 18.35 686 99.3 14.47 727.5 164.67 22.64 
 

x24 537 70.11 13.06 589 65 11.03 511.7 42.151 8.238 
 

x25 1412 168.9 11.96 1708 156 9.135 1632 200.44 12.28 
 

x26 1068 77.05 7.214 1315 57.3 4.355 1240 262.81 21.19 
 

x27 773 215.4 27.87 591 169 28.66 854.2 426.95 49.98 
 

x28 193 51.34 26.6 141 25 17.72 238.3 127.97 53.69 
 

x29 651 135.9 20.87 801 55.4 6.911 709.2 138.36 19.51 
 

x30 2284 367.7 16.1 2262 269 11.89 2180 151.33 6.942 
 

x31 939 68.29 7.273 1024 249 24.34 885 354.1 40.01 
 

x32 1190 263 22.1 1024 249 24.34 1123 339.33 30.21 
 

x33 234 42.12 18 251 44.3 17.66 256.7 68.093 26.53 
 

x34 1019 114.8 11.27 1127 132 11.72 1028 174.64 17 
 

x35 5951 367.9 6.182 5912 332 5.614 5955 417.65 7.013 
 

x36 1315 281.1 21.38 1009 189 18.7 1108 161.54 14.58 
 

x37 346 29.39 8.495 355 37.9 10.69 351.7 60.553 17.22 
 

x38 708 39.19 5.536 752 52.7 7.006 702.5 30.943 4.405 
 

x39 2909 325.7 11.2 2814 314 11.15 2937 262.42 8.936 
 

x40 1133 339.6 29.97 1067 76.4 7.16 944.2 136.62 14.47 
 

x41 289 36.8 12.73 285 44.3 15.53 301.7 134.19 44.48 
 

x42 478 29.93 6.262 525 21.4 4.085 515 36.056 7.001 
 

x43 2186 108.6 4.966 2275 231 10.17 2188 157.28 7.187 
 

x44 1320 163.3 12.37 1073 214 19.94 1127 226.77 20.13 
 

x45 304 28.71 9.443 335 40.2 12.01 285 70.64 24.79 
 

x46 242 27.31 11.29 256 58.2 22.72 230.8 30.727 13.31 
 



 
 
 

 

negative correlation was observed between the following 
characteristics: Fat thickness (back) and meat yield; fat 
thickness (back) and leg; fat thickness (back) and meat in 
the leg; dressing percentage and fat in the shoulder; leg 
and bones in loin part of the back; dressing percentage 
and fat in shoulder, etc. High positive correlation was 
recorded between the following characteristics: body 
mass of pigs prior to slaughter and meat yield; body mass 
of pigs prior to slaughtering and leg meat; mass of warm 
carcass sides and leg; mass of warm carcass sides and 
shoulder; carcass length (atlas-pubis) and leg; meat yield 
and meat in the leg; shoulder and cut meat of butt 
shoulder with neck; shoulder and meat in the shoulder, 
etc.  

Inter correlation of slaughter characteristics in case of 
third nutrition treatment is somewhat lower than in two 
previous cases, and very high negative correlation is 
recorded for: fat thickness (back) and meat yield; fat 
thickness (back) and leg; butt shoulder with neck and fat 
in shoulder. High positive correlation was recorded 
between the following characteristics: body mass of pigs 
prior to slaughtering and kidney fat; carcass length (rib-
pubis) and dressing percentage; dressing percentage and 
leg; meat yield and leg; shoulder and meat in shoulder, 
etc. 
 

 

Factorial analysis 

 

Factorization in the first and second variants of nutrition 
was finalized by the fourth factor, and in the third variant 
by fifth factor (since only common factors with 
characteristic square root over 1 are maintained) which 
include 100% of total variation of observed traits.  

Distribution of total variability of slaughter properties per 
individual factors is presented in Table 2.  

In regard to dispersion distribution per individual 
factors, it is obvious that most were included in the first 
factor, over 30%; the second factor included somewhat 
lower percentage of total variation varying from 25.78% in 
the third nutrition treatment, 27.54% in the first variant 
and 28.26% in the second nutrition variant. Proportional 
share of remaining factors in total variation is increasingly 
lower, so that in the third factor it is approximately 20%, 
and in the fourth factor it varied from 10.34 to 14.38%.  

Subsequent to rotation of initial factorial matrix, factors 
were obtained which were adequate for interpretation; 
and considering their correlation with initial indicators, 
they were interpreted.  

Slaughter traits in the first nutrition treatment (variant 1) 
distributed themselves in four factors, where the first 
factor included 38.22% of total variability. In the structure 
of this factor, the following traits were dominant: Fat 
thickness, withers; fat thickness, rump; belly fat; fat tissue 
in butt shoulder with neck; fat in loin part of the back; fat 
in rib fat tissue; so it can be concluded that the first factor 
was the one defining the fat. The second factor explained 

 
 
 
 

 

27.54% of total variability, and in the structure of this 
factor the following traits are dominant: meat yield; tender 
loin; meat in the rib fat tissue; so the second factor can be 
defined as meat yield. The third factor explained 19.85% 
of total variability, and considering the correlation with the 
initial traits it can be defined as factor skin (skin in loin 
part of the back, skin in the shoulder, skin in the rib fat 
tissue). Traits which were related with fourth factor mainly 
related to shoulder and butt shoulder traits, therefore this 
factor explained 14.38% of total variability.  

In the second nutrition treatment (variant 2), traits were 
distributed also within four factors, where the first factor 
explained 39.65% of total variability. This factor can be 
defined as meat yield since the following traits were 
related to this factor: meat yield; leg; shoulder; tender 
loin; leg meat; shoulder meat; rib fat tissue meat. The 
second factor could be defined as the fat factor since 
most of the traits related to this factor related also to fat 
(kidney fat; jowl; fat tissue in the leg). This factor 
explained 28.26% of total variability. The third factor was 
dominated by traits relating to skin and bones, and this 
factor explained 21.75% of total variability. The fourth 
factor explained 10.34% of total data dispersion and was 
mainly defined by traits relating to loin part of the back.  

The third nutrition treatment (variant 3), contrary to 
previous two, resulted in the separation of five factors. 
The first factor explained 31.53% of total variation, and 
most traits connected to this factor related to meat yield 
(meat yield; leg; butt shoulder with neck; meat in the leg; 
meat for drying in butt shoulder with neck). The second 
factor was dominated by traits related to fat tissue (fat 
thickness, withers; rib fat tissue; kidney fat; fat tissue in 
butt shoulder with neck; fat tissue in loin part of the back), 
and this factor explained 25.78% of total variability. Traits 
connected to shoulder defined the third factor and this 
factor explained 18.91% of total variation. The fourth 
factor explained 12.97%, and the fifth 10.81% of total 
variability. Traits related to these factors are very 
heterogeneous so it was not possible to define their 
names.  

Part of total variance explained by separated factors for 
each observed slaughter characteristic and each nutrition 
treatment is presented in Table 3. 
 

 

Conclusion 

 

Investigation of correlation between 46 slaughter charac-
teristics of pigs fed diets containing different additives 
showed that observed traits do not present uniform set. 
By correlation analysis, it was determined that between 
observed traits there was expressed inter-correlation 
which resulted from extraction of fewer factors. In case of 
first and second nutrition treatment, four factors per each 
treatment were separated, and in the third treatment, due 
to somewhat lower correlation between indicators, five 
factors were separated. Structure of formed factors 



                          
 

 Table 2. Distribution of variability of properties per individual factors               
 

                            
 

      Variant 1          Variant 2        Variant 3    
 

   Factor Characteristic % of total Cumulant Characteristic % of total Cumulant  Characteristic % of total Cumulant 
 

    square root  variation (%)      square root variation (%)     square root variation (%)   
 

   1 17.58  38.22  38.22     18.24 39.65 39.65     14.50 31.53 31.53   
 

   2 12.67  27.54  65.76     13.00 28.26 67.91     11.86 25.78 57.31   
 

   3 9.13  19.85  85.62     10.00 21.75 89.66     8.70 18.91 76.22   
 

   4 6.61  14.38  100.00     4.75 10.34 100.00     5.97 12.97 89.19   
 

   5 /  /  /      / / /      4.97 10.81 100.00   
 

Table 3. Communalities (%) of slaughter characteristics for different nutrition treatments             
 

                         
 

    Variant 1         Variant 2        Variant 3    
 

 
Trait For first For two For three For four For first For two For three For four 

For  
For two For three For four For first  

 first  
 

   factor factor  factor  factor factor  factor factor factor  factor factor factor factor  

      factor  

                         
 

 x1 66.9 92.2  95.4  100   74.4  84.7 85.3 100   0.1  96.0 99.2 99.2 100 
 

 x2 33.7 86.1  94.0  100   91.1  91.4 96.2 100   60.4  86.2 91.1 91.1 100 
 

 x3 66.1 66.2  73.6  100   25.5  71.9 96.4 100   8.1  88.7 88.8 88.8 100 
 

 x4 0.0 72.8  94.1  100   53.6  57.2 62.8 100   92.2  93.0 98.1 98.1 100 
 

 x5 49.7 59.5  59.5  100   33.3  55.1 55.2 100   2.8  39.9 49.9 49.9 100 
 

 x6 0.0 0.4  0.7  100   86.7  87.9 95.3 100   34.8  50.0 51.5 51.5 100 
 

 x7 0.5 1.4  26.6  100   56.7  56.8 83.6 100   57.3  58.9 59.4 59.4 100 
 

 x8 19.4 33.2  99.7  100   3.6  54.7 87.3 100   79.2  81.8 83.5 83.5 100 
 

 x9 21.9 84.0  86.5  100   59.6  61.2 65.2 100   86.5  90.9 95.8 95.8 100 
 

 x10 49.2 80.2  80.4  100   81.9  88.1 88.1 100   87.0  92.4 95.5 95.5 100 
 

 x11 6.1 19.7  26.6  100   79.6  89.6 96.5 100   8.1  8.7 92.0 92.0 100 
 

 x12 0.9 77.4  91.9  100   14.6  16.6 99.8 100   1.1  47.7 53.9 53.9 100 
 

 x13 10.5 55.8  59.6  100   71.4  98.3 98.8 100   4.4  63.2 63.8 63.8 100 
 

 x14 45.4 62.4  88.2  100   6.8  63.9 88.5 100   60.6  72.1 74.1 74.1 100 
 

 x15 51.6 52.9  98.8  100   47.5  55.3 99.3 100   0.2  7.3 8.4 8.4 100 
 

 x16 95.5 97.6  99.5  100   19.8  91.0 93.8 100   15.2  17.9 18.9 18.9 100 
 

 x17 83.3 87.1  98.2  100   0.6  35.7 55.4 100   6.6  30.3 54.3 54.3 100 
 

 x18 0.1 90.5  91.1  100   35.3  44.6 90.5 100   4.4  8.5 77.3 77.3 100 
 

 x19 6.3 69.6  96.2  100   14.6  54.0 96.0 100   2.4  12.7 12.9 12.9 100 
 

 x20 2.9 3.6  4.4  100   3.1  92.1 99.1 100   2.0  98.1 99.0 99.0 100 
 

 x21 5.2 90.0  95.6  100   4.7  89.8 99.4 100   86.0  86.1 95.0 95.0 100 
 



 
            

Table 3.continues.             
              

x22 0.3 90.5 100.0 100 54.2 98.9 98.9 100 34.7 38.6 42.9 42.9 100 

x23 86.2 99.2 99.9 100 8.7 59.1 79.2 100 4.2 5.6 15.5 15.5 100 

x24 16.0 26.8 33.8 100 2.8 5.9 17.5 100 19.3 23.4 99.5 99.5 100 

x25 16.8 17.3 99.9 100 21.8 24.5 93.0 100 90.1 91.2 97.0 97.0 100 

x26 12.0 49.8 50.6 100 70.9 98.4 100.0 100 12.8 63.7 82.1 82.1 100 

x27 56.2 65.3 71.1 100 0.4 1.4 94.4 100 20.3 70.9 80.2 80.2 100 

x28 37.3 40.2 44.1 100 24.1 96.0 97.6 100 0.0 50.5 81.1 81.1 100 

x29 5.0 6.6 100.0 100 0.4 25.7 97.5 100 17.2 25.1 68.6 68.6 100 

x30 13.2 80.0 96.7 100 76.7 78.2 95.8 100 1.5 18.8 99.9 99.9 100 

x31 87.8 97.1 97.3 100 11.2 11.9 12.1 100 28.7 31.4 54.3 54.3 100 

x32 65.2 65.3 65.4 100 11.2 11.9 12.1 100 13.4 81.5 84.2 84.2 100 

x33 6.0 15.8 94.5 100 3.9 37.4 87.2 100 4.8 70.3 78.0 78.0 100 

x34 3.4 75.1 75.5 100 64.1 70.5 70.5 100 1.1 4.3 8.3 8.3 100 

x35 88.55 89.4 92.7 100 58.7 59.1 59.5 100 70.1 83.3 88.2 88.2 100 

x36 1.0 4.2 8.7 100 1.4 65.0 65.1 100 0.7 3.0 7.1 7.1 100 

x37 80.1 80.2 90.9 100 43.0 44.0 60.5 100 0.3 0.9 37.2 37.2 100 

x38 69.3 87.2 93.0 100 0.5 90.6 92.2 100 13.2 17.2 25.3 25.3 100 

x39 59.5 91.9 97.6 100 82.1 82.1 99.5 100 1.3 1.7 87.5 87.5 100 

x40 1.8 22.2 71.5 100 1.6 43.4 89.6 100 68.5 69.7 87.6 87.6 100 

x41 8.9 13.6 99.9 100 12.4 80.4 88.9 100 0.5 4.9 94.5 94.5 100 

x42 73.7 75.8 98.2 100 0.1 89.2 98.8 100 6.6 9.4 10.7 10.7 100 

x43 0.7 85.7 99.8 100 51.3 54.8 87.8 100 48.4 63.9 72.4 72.4 100 

x44 59.5 64.2 65.6 100 26.2 63.7 68.9 100 63.3 87.3 97.1 97.1 100 

x45 0.3 24.9 99.8 100 3.7 9.6 62.7 100 3.1 42.0 42.1 42.1 100 

x46 89.9 89.9 95.0 100 18.7 20.6 97.4 100 48.1 70.0 71.6 71.6 100 
              

 

 

showed that in the first nutrition treatment, traits 
relating to fat tissue were more associated than 
those relating to meat yield, whereas in the two 
remaining treatments the situation is reverse. The 

 

 

third singled out factor in the first and second 
treatment were very similar and related to traits 
connected to skin and bones, whereas in the third 
treatment this factor related to traits connected 

 

 

with shoulder. Fourth singled out factor was 
different for all three nutrition treatments which 
confirmed the fact that these additives in nutrition 
result in different slaughter characteristics of 



 
 
 

 

fattening pigs. 
 

 

ACKNOWLEDGEMENTS 

 

This work is made possible with the help of previous 
researches funded by the Ministry of Science and 
Technological Development: “Development and 
application of new and traditional technologies in the 
production of competitive food products with added value 
for domestic and world markets – Create wealth from the 
wealth of Serbia” and “Rural Labour Market and Rural 
Economy of Serbia - Income Diversification as a Toll to 
Overcome Rural Poverty.” 
 

 
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