Kamil Duziński

A new simple method for estimating the pork carcass mass of primal cuts and lean meat content of the carcass

The aim of this study was to develop regression equations for estimating lean meat content and the mass of primal cuts (ham, loin, shoulder, belly) based on selected linear measurements. The experiment involved a classification of 141 pigs from the Polish commercial pig population, with hot carcass weight ranging between 60 and 120 kg. The study population was characterised by high variability in terms of analysed measurements. Eight measurements were made including: mass of half-carcass, backfat thickness at different points (over shoulder, over last rib, over the middle of M. gluteus medius), width and thickness of the M. longissimus dorsi measured over the last rib, thickness of the lumbar and the gluteal muscle layer located between the spinal cord and beginning of the M. gluteus medius and waist width – the width of the carcass measured at the narrowest point of the lumbar. A subjective five-point scale was used to score difficulties in obtaining linear measurements (workload rate). The lean meat percentage and mass of cuts were determined by dissection. The study enabled equations to be devised for estimating lean meat content with an accuracy greater than most devices used for carcass classification (estimation error 1.67). Regression coefficients for the mass of primal cuts were: 0.92 for ham, 0.87 for loin, 0.87 for shoulder, and 0.74 for belly. The error of equations used to estimate the mass of primal cuts were: 391 g for ham, 447 g for loin, 263 g for shoulder and 257 g for belly. The workload rate for all the developed regression equations ranged from 1.3 to 1.6 points. The outcome of this study was the development of equations to predict carcass value without the need to use expensive classification equipment.

The effect of parity and date of service on the reproductive performance of Polish Large White × Polish landrace (PLW × PL) crossbred sows.

Abstract The aim of this study was to demonstrate the influence of the month of insemination on the reproductive performance of crossbred sows in moderate climates. The research material consisted of 309 primiparous and 625 multiparous (PLW×PL) sows kept on an industrial-scale farm. Analysis included 2457 litters obtained during a five-year period from 2006 to 2011. Statistically, the lowest number of piglets born alive and weaned was observed as a result of summer month insemination (July, August, September) compared to the winter months (February, March) (P≤0.01 and P≤0.05). Inseminations in the first four months of the year resulted in a higher number of piglets born alive in second and following parities (P≤0.01). Statistically significant differences in litter size due to the month of insemination were observed for sows in parities 4 and 5-11 (P≤0.01 and P≤0.05). The shortest farrowing interval was demonstrated for sows inseminated in November, the longest in January, March (P≤0.01) and April, July (P≤0.05). The results indicate that the insemination month of the sow may affect some reproductive parameters.

Does a Boar's Season of Birth Determine Semen Parameters and Reproductive Performance?

This article studies the effect of a boars birth season and breed on semen parameters and its further reproductive performance. Research material consisted of 72 boars from three breeds (24 Polish Large White PLW, 24 Polish Landrace PL, 24 Duroc × Pietrain D × P). During the whole period of the study, selected semen parameters were analysed: semen volume, spermatozoa concentration, total number of spermatozoa, total number of motile spermatozoa, number of insemination doses and also reproductive indicators: farrowing rate, total born litter size, total number of piglets born live and still, and average piglet weight. Boars born in the winter and summer months demonstrated the highest spermatozoa concentrations (383.25 and 392.37 × 10(6)/ml), total number of spermatozoa (91.75 and 93.21 × 10(9)), total number of motile spermatozoa (76.10 and 77.99 × 10(9)) and number of insemination doses (24.53 and 24.89; p ≤ 0.01). Statistically lower values for these parameters were observed for boars born in the spring and especially in autumn (p ≤ 0.01). The significant impact of birth season on farrowing rate (p ≤ 0.05) and average piglet weight (p ≤ 0.05) was confirmed for PLW boars. For the PL breed, only the total number of piglets born live was proven to be significantly affected (p ≤ 0.05). No impact of birth season was shown on semen quality or reproductive performance for D × P boars. In our study, we showed that the birth season of a boar had a more impact on the level of semen parameters, and less on the reproductive performance indicators. The results indicated that both the quality of semen and reproductive performance varied in terms of the study factors, as well as between individual breeds of boars involved in the experiment.

Factors affecting the tissues composition of pork belly.

Bellies derived from the commercial population of pig carcasses are diverse in terms of tissue composition. Knowledge of the factors influencing it and the expected results, permits quick and easy evaluation of raw material. The study was designed to determine the factors affecting the tissues composition of pork bellies and to estimate their lean meat content. The research population (n=140 pig carcasses) was divided into groups according to sex (gilts, barrows), half-carcass mass (<40, 40 to 43.9, 44 to 46.9, ⩾47 kg) and lean meat content class: S (⩾60%), E (55% to 60%), U (50% to 55%), R (<50%). Bellies were subjected to a detailed dissection. Half-carcass mass affected the levels of all the analysed parameters. The only exception was the mass of the fat with the skin in the 40 to 43.9 kg group, for which the value did not differ statistically between the two groups <40 and 44 to 46.9 kg. Decrease in lean meat content affected the growth of the fat and skin mass in a linear way. No differences were observed between class S and E in terms of belly muscle mass. A 0.37% higher share of belly in the half-carcass was found for barrows (P<0.001), although bellies issued from barrows were characterized by a higher proportion of fat with skin compared with gilts (P=0.02). Interactions were observed between sex and half-carcass mass, so the sex of heavy half-carcasses becomes an important determinant for conditioning the muscle content. Equations were calculated and allow a fast and highly accurate determination of the lean meat content in bellies, suggesting they may be used directly in the production line.

The estimation of pork carcass primal cuts value based on backfat thickness

The aim of the present study was to determine the effect of pork carcass backfat thickness on the dissection efficiency of four primal cuts (ham, loin, shoulder, belly), including correlation coefficients. The research material consisted of 80 pork carcasses. Backfat thickness (mm) was measured on cold half-carcasses using a vernier caliper at 6 points: at the first cervical vertebra (atlas), over shoulder at the thickest point, on the back, at the beginning, center, end of the gluteus medius muscle (CI, CII, CIII). On the basis of the average backfat thickness, measurements from 6 points were separated into two experimental groups: I (<25 mm); II (≥25 mm). Detailed dissection of the elements was performed to define mass (g): total, intermuscular fat, bones and lean meat. The significant effect of fat thickness on intermuscular fat content regardless of the cut was noted. Correlations between the average backfat thickness of 6 points and the total weight of the four main elements were calculated. In addition, the correlation coefficients were compared between the dissection elements and the average backfat thickness of 6 and 5 points. Higher backfat thickness determined the increase in the total mass of loin, shoulder and belly. A statistically proven correlation was shown between the average backfat thickness and the total mass of the analysed elements (r=0.293). When comparing the correlation coefficients of a different number of measurements a specific tendency was observed. Positive correlation coefficients were slightly higher for an average of 5 points of backfat thickness and negative correlation coefficients were slightly higher for an average of 6 points. Statistical differences between groups were recorded at the same level for the same parameters (P≤0.001 and 0.01

Does the activity of producer group organizations improve the production of pigs

Abstract There are many works dealing with the activities of small farms, however there is a lack of papers about production and economic performance of small farms associated in producer group organizations. The aim of the study was to compare the production parameters of selected pig producer groups over two years (2010-2011). The basis for the analysis were the results of surveys carried out in 174 individual farms, which were members of 4 groups of pig producers. The study was conducted through direct interviews using a personal questionnaire. The average herd size of sows increased in the next year by 18.5% and the average annual production volume of fatteners by 9.3%. Average meatiness increased from 53.8% to 54.5%. In order to estimate the revenues a model of factors dependent on the farmer was created, expressed as the production of 1 kg of raw material. Three independent variables were introduced into the model: meatiness of fatteners (X1), the size of produced fatteners (X2), weight of fatteners (X3). The model developed in the study was proposed to groups as a tool to measure the efficiency of production and is currently being used by them. The results indicate that the activities of pig producers have a positive effect on production effectiveness and confirms the validity of horizontal integration in agriculture. Managing production in accordance with the statute imposed on the producer group showed a similar quality of produced raw materials, while the average annual sales of fatteners increased, which may contribute to the ability to negotiate purchase prices.

The dependence of the growth rate and meat content of young boars on semen parameters and conception rate.

Boars have a decisive impact on the progress in pig production, however, there is no recent information about the optimal growth parameters during the rearing period for modern breed later used in artificial insemination (AI) stations. Therefore, the objective of the research was to conduct semen parameter and conception rate analyses on the basis of growth rate and meat content assessments made during the rearing of AI boars of different genotypes. The study was carried out between 2010 and 2014 and included 184 boars in five breed combinations: 46 Polish Large White, 50 Polish Landrace, 27 Pietrain, 36 Duroc×Pietrain and 25 Hampshire×Pietrain. Boars were qualified by daily gains and meat content assessment (between 170 and 210 days of life). A total number of 38 272 ejaculates were examined (semen volume (ml), spermatozoa concentration (×106 ml-1), total number of spermatozoa (×109) and number of insemination doses from one ejaculate (n)). The fertility was determined by the conception rate (%). Semen volume, spermatozoa concentration and conception rate (P<0.01), followed by the total number of spermatozoa and insemination doses (P<0.05) were characterized by the highest variability in relation to breed of boars. The effect of daily gains was reported for spermatozoa concentration, number of insemination doses, conception rate (all P<0.01) and total number of spermatozoa (P<0.05). The peak of growth for spermatozoa concentration, total number of spermatozoa, insemination doses and conception rate was achieved for 800 to 850 g gains. Meat content affected semen volume, number of insemination doses and conception rate (P<0.05). Rearing boars while maintaining daily gains at the 800 to 850 g level and 62.5% to 65% meat content helps AI stations to increase the efficiency and economic profitability, and the number of insemination doses to increase by up to 300 doses/boar within a year. The analyses of growth parameters may help increase the efficiency and economic viability of AI stations.

Pork ham and belly quality can be estimated from loin quality measurements

The aim of the study was to determine the relationships between the quality evaluation of loin and the quality evaluation of ham and belly from the same carcasses for trying to predict the quality parameters of ham and belly based on measurements made on the loin. The research material consisted of 105 pork carcasses, from which three elements were cut and marked: loin, ham and belly. Quality evaluation included: pH, color, water holding capacity (WHC), cooking loss (CL), and sensory analysis. All designated quadratic equations were characterized by low R2 values from 0.06 to 0.43 for ham and from 0.00 to 0.28 for belly. However, it is possible to predict the quality parameters of ham or belly with different levels of accuracy (R2 from 0.50 to 0.92 - depending on the measurement and the element), using measurements selected from all those tested on the loin. Those loin quality measurements most frequently used in equations were chewiness and CL.

Variability of Fresh Pork Belly Quality Evaluation Results Depends on Measurement Locations

The increase in pork demand has led to an especially high increase in demand for precisely quality-defined bellies. The aim of the study was to determine the influence of quality measurement location on the pork belly on the results of qualitative evaluation and then to recommend the main measurement locations required to determine the precise quality evaluation of the whole cut. The research material consisted of 92 fresh pork belly samples, each divided on 12 testing locations. The highest pH values were noted for M2 (5.74), M1 (5.70), and D3 (5.69) locations, as well as A4 (5.53; P ≤ 0.05) generating the most outliers. Location D2 was distinguished by generally obtaining the highest values for parameters L*, b*, C*, and H* and the lowest for a*; this was independent of the measurement side. The highest water holding capacity values were reported for D4 and D3 locations, and the lowest (about 7% lower than the maximal values) were obtained for A4 and A2 locations. The highest values for the cooking loss parameter were noted for D4, D1, and M4 (about 33%) locations, and the lowest values were observed for location M2 (only 22%). In the case of sensory evaluation between the analyzed locations, differences (P ≤ 0.05) were recorded for all parameters. It is recommended to evaluate belly quality using one location: A1 and M3 are most accurate. The highest position in the ranking for processing quality parameters was occupied by the middle locations: M4, M1, and M3. However, when consumers ranked important quality parameters, the highest positions were given to location A1 and then D3 and M2. From a practical point of view, it is highly recommended to take quality parameters from location A1, which is much easier to obtain, and obtaining samples from this location leads to the least damage to the structure of the whole commercial cut.

The influence of housing and feeding systems on selected fattening and slaughter parameters of finishing pigs with different genotypes

The aim of the present study was to demonstrate the influence of housing and feeding systems on selected fattening and slaughter parameters of finishers with different genotypes. The experimental population consisted of 1200 finishers in three genetic variants from the Landrace (L), Large White (LW), Duroc (D) and Pietrain (P) breeds: 400 finishers L × [D × P] genotype, 400 finishers LW × [D × P] genotype and 400 finishers [L × LW] × [D × P] genotype. Subgroups were isolated for each genetic variant with the experimental factors: housing system (slatted floor or deep litter) and feeding system (dry or liquid). Selected fattening parameters were analysed: final liveweight (kg), mortality (%), average daily gain (g/day) and feed conversion ratio (kg/kg gain). Additionally, slaughter parameters were analysed: carcass weight (kg), height of longissimus dorsi (LD) muscle (mm), backfat thickness (mm) and lean meat content (%). The housing system strongly affected the final liveweight, average daily gain and carcass weight. To a lesser degree, this factor determined the mortality, feed conversion ratio, height of LD muscle, backfat thickness and lean meat content. The feeding system substantially affected almost all fattening parameters, except for the mortality. Statistical analysis of slaughter parameters showed that the impact of the feeding system was confirmed statistically only in terms of carcass weight. Genotype largely determined the final liveweight, average daily gain, carcass weight and lean meat content. Taking into account interactions of all factors, the most favourable effect in terms of production was to fattening four-way crossbreeds [L × LW] × [D × P] on slatted floors and fed by liquid feeding.