ANALYSIS OF CONDITIONALITY OF SENSORY QUALITY LONGISSIMUS LUMBORUM MUSCLE AFTER HEAT TREATMENT

Wiesław Przybylski, Danuta Jaworska, Ewa Czarniecka-Skubina, Andrzej Półtorak, Stanisław Niemyjski
Department of Engineering and Catering Technology, Faculty of Human Nutrition and Consumer Science, Warsaw Agricultural University, SGGW, Poland

ABSTRACT

The aim of this study was to estimate the relations between slaughter values of fatteners and technological value of meat and sensory quality evaluated in Longissimus lumborum muscle after thermal treatment. The studies were executed on a group of 50 fatteners derived from the crossing of Polish Landrace and Polish Large White sows with hybrid boars P-76 PenArLan. In the animals slaughtered at 100 kg live weight the following features were estimated: the percent of meat in carcass, technological value and sensory quality of meat in 96 h post mortem after heat treatment. The meat tenderness was also estimated instrumentally on the basis of the cutting test, using an Instron Company device, type 4301. Additionally, a photograph of microstructure of muscle was taken. Sensory quality of meat after thermal treatment depended on its tenderness, juiciness and tastiness. The correlations between meatiness and fatness of fatteners with tastiness were obtained. Overall quality of cooked meat, tenderness, juiciness and tastiness was correlated with pH, drip loss, cooking yield and TY indicator. Simultaneous effect of technological meat quality on its sensory quality was analyzed by using canonical analysis. Calculated ratio of canonical correlation R_C = 0.97 showed that sensory meat quality is significantly determined by its technological value.

Key words: pork meat, technological quality, sensory quality.

INTRODUCTION

Pork is still the most popular type of meat and takes a dominant position on the Polish meat market. However, intensification of breeding by using high meatiness breads in crossbreeding resulted in considerably different quality of the raw material. Therefore improvement as well as formation of the valuable slaughter and quality of pork meat should conducted taking into consideration aspects from selection to reproduction. Environmental factors also play the important role (breeding, transport, slaughtering procedures and the procedures after the slaughter). From the consumers` point of view progressive evolution of the technology of pork meat production and particularly the growth of the meatiness after slaughtering should not have negative effects on the quality of gained meat. Improving technological quality should be also connected with sensory quality improvement. Considering the above mentioned issues, the real problem becomes the estimation of conditionality of sensory and technological quality as well as a possibility of quality diagnosis, especially in the condition of strong competition and the surplus of meat.

AIM, MATERIAL AND METHODS

The aim of this study was to estimate the relations between slaughter values of fatteners and technological value of meat and sensory quality evaluated in Longissimus lumborum muscle after thermal treatment.

The research was executed on the material taken from 50 hogs originated from crossing Polish breeds (Polish Landrance and Polish Large White) and Naïma sows with hybrids P76-PenArLan boars. The fatteners were kept in the same environmental conditions and fed ad libitum on the same complete compound feed. The animals had a free access to water. After fattening completion and reaching the weight of 100 kg, the animals were slaughtered in the “ZM Mróz” at “Borzęciczki” slaughterhouse in accordance with the legally binding procedures (the distance from the farm to the slaughterhouse was 200 km, a rest of about 2 h, automatic electric stunning, and exsanguinations in a horizontal position).

Following the slaughter, on the technological line, the content of meat in carcass was determined on warm, hanging carcasses with a CGM apparatus, the back fat thickness was measured as the length of the longest back muscle at the height of the last rib, 7 cm off the carcass mid-line [4]. Meat quality parameters were examined (directly on the technological line or in the meat plant laboratory) in samples of the Longissimus muscle taken behind the last rib. The pH value was measured with pH-meter PM-600 after 45 min, 1, 3, 24 and 48 h after slaughtering directly in the muscle tissue. The colour brightness was determined after 24 h post mortem using a CR310 Minolta apparatus in the CIE Lab system (L-lightness, a-reference to the red, b-saturation towards the yellow colour).

The natural drip (DL) was determined according to Prange [18] methods. A 50 g sample of the meat (a slice of meat cut perpendicularly to muscle fibres, with sides of equal lengths) was taken after 24 h post mortem and put in a plastic bag and next kept at the temperature of 4°C. After 24 h the sample was taken out, dried on an absorbent paper and weighed again. The drip amount was expressed as percentage.

The technological yield index (TY – Technological Yield), characterizing the meat efficiency in the processes of curing and cooking while making ham, was determined according to Naveau at al. [13], as modified by Koćwin-Podsiadła et al. [10].

24 h post mortem a 100 g muscle sample was cut into 1 cm x 1cm x 1 cm cubes and put in a can. Next the meat was covered by 20 ml of salt brine composed of components as those used when curing ham and kept for 24 h at the temperature of 4°C. After this period the closed can was put into boiling water for 10 min to ensure homogenic heat treatment conditions for the meat up to temperature of 72°C in the sample epicenter.

After cooling, the sample was weighed and the technological yield was measured as the ratio between the cooked and raw meat sample weight and expressed as a percentage. The meat cooking yield (CY) was determined by subjecting 500 g meat samples to heat treatment by cooking in salt solution (0.8%) until reaching the temperature of 72°C in the sample epicenter. The yield index was expressed as a percentage, as the ratio of the cooked to the raw meat sample weight.

A sensory quality of meat (96 h after slaughtering) was determined after heat treatment by using sensory scaling method [15], with the use of an unstructured graphical scale; a 100 mm (0-10 conventional units) with precisely determined edge definitions.

The raw meat samples (weighing about 600 g) were being subjected to the heat treatment - cooking in salt solution (0.8% NaCl) according to Baryłko-Pikielna et al. [2] method. The heat treatment process was conducted to achieve the temperature of 72°C inside the meat, and then samples were covered and kept until reaching the temperature of 75°C.

After cooling the meat samples were cut into portions of approximately equal size and weight (around 25 g) and placed in plastic odorless, disposable boxes covered with lids. Following the thermal treatment the meat was evaluated in terms of odour, intensity and homogenity of colour, tenderness, juiciness, sensory fat sensitivity and meat flavour. On the basis of the above mentioned quality characteristics, the assessing sensory panel indicated an overall sensory quality for each sample on a separate scale.

The cooked meat sensory quality was evaluated by a 10-person assessing panel. All samples were separately coded for assessment with three digit codes and were passed in random order to avoid the so called carry-over effect (i.e. the impact of a previous sample on the subsequent one). The cooked meat was estimated directly after the thermal treatment within three hours. The estimation was repeated twice so each average result was based on minimum of 18 individual results. The testing was conducted in rooms with daily light, at room temperature. Between the subsequent evaluations each person received hot tea without sugar to neutralize the taste. All samples were determined with the use of individual cards including the instruction of estimation. Estimated attributes were determined on separated scales placed on the card.

The testing was carried out in the Catering Technology and Food Hygiene Department of the Faculty of Human Nutrition and Consumer Sciences of the Warsaw Agricultural University. Condition and the assessment mode were determined in accordance with Meilgaard et al. [12].

In addition, for samples which differentiated in tenderness, photos of microstructure cross-section were taken using scanning microscope XL 30 type, ESEM. The photos were taken with enlargement of 300 x.

The testing results were elaborated statistically with the Statistica 6.0 PL software packet, a general characteristic of the material under testing was presented. Relationships between studied characteristics were given by calculation at simple correlation coefficients and by using canonical correlation. This analysis makes it possible to estimate the correlation degree of two variable sets, explanatory variable collection X (parameters of usefulness to preservation - technology quality, pH, drip loss, TY and cooking yield or colour parameters) with explanation variable sets (quality meat characters after thermal treatment). The degree of correlation of these variable sets explained canonical correlation coefficient C_R and compound determination coefficient C_R². It made it possible to estimate what part of total variance of Y collection is explained as effected X collection [11].

RESULTS AND DISCUSSION

The results indicated that the fatteners studied were characterized by quite high meatiness and low fattiness (Table 1).

In an experimental group of fatteners PSE type meat or acid meat was not confirmed because the common character analyses used to diagnostic faults of meat (colour, TY, pH₁, pH₂₄) did not indicate quality deviation (Table 1). The meat of the studied animals characterized profitable value of pH₁ and pH₂₄, sufficiently high technological yield in curing and cooking processes estimated by TY index and a little thermal drip and profitable colour parameters.

Table 1. Characteristics of carcass slaughter value: technological value parameters and sensory quality features of meat of studied group of fatteners

Traits	Mean	S. d.
Carcass slaughter value
Hot carcass weight (HCW)[kg]	81.35	5.54
Meat in carcass [%]	56.61	2.21
Loin thickness [mm]	56.09	3.09
Back fat thickness [mm]	13.84	3.49
Technological parameters
pH1	6.34	0.19
pH3	6.11	0.14
pH24	5.50	0.08
pH48	5.42	0.06
Colour parameters of raw meat in 96 h: L a b	56.20 13.78 6.18	1.51 0.93 1.02
Drip loss (DL) [%]	6.95	2.46
Technological yield (TY) [%]	97.36	6.36
Cooking yield (CYI) [%]	76.11	4.34
Colour parameters of cooked meat 96 h: L a b	73.20 5.31 8.53	1.65 0.68 0.55
Sensory descriptors of cooked meat in 96 h post mortem [0-10 j.u.]
Odour (ODU)	4.94	1.09
Colour intensity (CIN)	6.74	0.74
Colour homogeneity (CHG)	6.60	0.80
Tenderness (TEN)	6.97	0.73
Juiciness (JUI)	5.88	1.25
Fat perception (FPE)	3.07	0.29
Meat flavour (MFL)	6.57	0.61
Overall quality (OSQ)	6.50	0.56

The collection of the calculated simple correlation coefficient between parameters and characters studied in the experiment was presented in Table 2. This data analysis allows to confirm that post mortem pH₂₄ value and pH₄₈ value were significantly connected with the meat tastiness.

Results of several studies [3,14] showed that tastiness was a feature which determined the overall sensory quality estimation to the largest extent (attributes are highly correlated with each other) and for that reason similar correlations were observed for overall sensory quality of cooked meat.

Overall sensory quality of meat was statistically significantly connected with the amount of drip loss (Table 2). High significant dependence of technological meat yield coefficient in model process of ham production with tenderness, juiciness and sensory overall quality was worthy noticing. Similar dependence between cooking quality and taste and overall sensory quality of meat was observed.

To compare the effect of technological quality parameters on the sensory quality of cooked meat a microstructure photos of chosen meat samples differing in technological and sensory quality characters of range were taken.

Table 2. Simple correlation coefficient value between carcass slaughter value: technological value and descriptors of sensory quality of determined cooked meat samples

Variable	Calculated correlations coefficients*
Parameters	TEN- instrum.	ODU**	CIN	CHG	TEN	JUI	FPE	MFL	OSQ
pH1	-0.19	-0.01	-0.20	-0.30	-0.35	-0.16	0.50*	0.13	0.17
pH3	-0.10	0.00	-0.18	-0.17	-0.29	-0.05	0.26	0.31	0.22
pH24	0.05	0.14	0.02	-0.06	0.37	0.41	-0.13	0.56	0.55
pH48	0.09	-0.14	-0.24	-0.19	0.31	0.43	0.20	0.55	0.64
L	-0.32	-0.25	0.15	0.08	-0.12	0.11	-0.14	-0.29	-0.28
a	0.32	0.15	-0.61	-0.02	0.08	0.12	-0.03	0.18	0.07
b	-0.10	-0.22	0.19	-0.02	-0.25	-0.09	-0.29	-0.63	-0.66
DL	-0.18	0.12	0.08	0.44	-0.23	-0.27	-0.11	-0.47	-0.50
TY	-0.51	-0.34	0.11	0.50	0.80	0.75	0.17	0.48	0.59
HCW	-0.44	0.12	0.13	0.08	0.08	0.27	-0.24	0.28	0.29
Meat in carcass	-0.02	-0.25	0.33	-0.07	-0.02	-0.30	-0.28	-0.20	-0.25
Loin thickness	-0.45	0.10	0.26	0.13	0.08	-0.06	-0.08	0.24	0.32
Back fat thickness	-0.17	0.32	-0.25	0.14	0.06	0.30	0.27	0.33	0.41
Cooking yield	-0.13	-0.17	-0.05	0.03	0.24	0.23	-0.18	0.55	0.53

* Indicated factors significant p<0.05. ** Explanation in Table 1.

Sample A was characterized by low final pH (5.48), increased drip loss – 6.73% and at the same time determined low juiciness (5.06 conventional units) and tenderness on the medium value level – 6.86 conventional units. B and C samples characterized by higher tenderness (8.26 and 7.71 conventional units, respectively) and higher juiciness (7.75 and 7.35 conventional units) or lower drip loss value (4.43 and 3.01 %). Simultaneously, B and C samples characterized higher final pH value – 5.66 in comparison to A sample (Fig. 1).

To estimate simultaneous and total effect of these factors such as carcass slaughter value and technological parameters (technological meat usefulness) on sensory quality of cooked meat characters a canonical analysis was applied. Using this type of statistical analysis is suitable to determine dependence between variable sets and was used by other authors [11, 19, 25].

Fig. 1. Microstructure photos of chosen meat samples differing in the range of technological and sensory quality characteristic

Sample A	Sample B	Sample C

The results of statistical analysis were convergent with the results determined on presented results with using other, multidimensional statistic analysis (principal component and aggregation analysis by Ward method [9, 21].

Taking into account the complexity of the interpretation of canonical analysis results, it Has been decided to present only a part of the results which enable to accomplish the aim of his work.

Analysis of the obtained results presented in Tables 3, 4, 5 makes it possible to determine the input of certain variables into the distinct canonical variables. On the hand, canonical variables, which are the weighted average of the variables from the first and second set, are new implicit variables (u and v) which are a synthetic index (rate) defining the correlation between both sets.

Table 3. Results of canonical analysis obtained on studied 50 fatteners: canonical factors structure presented relation of technological meat quality parameters and sensory descriptors with both canonical variables

Traits		Canonical variables
Variables explaining other variables		u 1	u 2	u 3	u 4	u 5	u 6	u 7
pH1	x 1	-0.30	-0.51	0.35	0.04	-0.40	0.08	-0.60
pH3	x 2	-0.23	-0.50	0.18	-0.21	0.35	0.05	-0.71
pH24	x 3	0.38	-0.09	0.16	-0.72	-0.41	-0.35	0.04
pH48	x 4	0.46	-0.39	0.45	-0.39	-0.20	-0.49	-0.03
Drip loss	x 5	-0.24	0.20	-0.59	0.60	0.40	0.10	-0.16
Technological yield	x 6	0.86	-0.41	-0.19	0.02	0.05	0.20	-0.07
Cooking yield	x 7	0.77	0.43	0.21	0.10	-0.27	-0.21	-0.24
Explained variables		v1	v2	v3	v4	v5	v6	v7
Odour	y 1	-0.41	0.05	-0.52	-0.34	-0.25	-0.59	-0.12
Colour intensity	y 2	0.10	0.21	-0.32	-0.19	-0.13	0.73	0.16
Colour homogenity	y 3	0.35	-0.11	-0.89	0.14	-0.00	-0.05	-0.19
Tenderness	y 4	0.87	-0.01	-0.33	-0.11	-0.14	0.08	0.18
Juiciness	y 5	0.82	-0.07	-0.04	-0.21	-0.02	0.13	-0.42
Fat perception	y 6	-0.09	-0.71	0.25	0.37	-0.21	0.15	0.17
Meat flavour	y 7	0.41	-0.58	-0.06	-0.66	0.05	-0.26	0.16
Overall quality	y 8	0.52	-0.67	-0.01	-0.42	-0.14	-0.05	0.11

At the beginning there are pairs of canonical variables of the maximum correlation of two weighted averages, which enable to explain a part of variability. Then the subsequent averages are calculated. They maximize the second canonical correlation explaining the next additional part of variability in the examined sets.

Canonical factors loads presented in Tables 3, 4 and 5 may be interpreted as correlation coefficient separate variable with canonical variable, on this basis it is possible to estimate to which extent they determined estimated canonical variable.

Variables which are significantly correlated with the canonical variable have higher values and therefore they have a considerable input into the distinct canonical variables.

Table 4. Results of canonical analysis on studied 50 fatteners: canonical loads factors described the degree of relation between pH and colour parameters and meat sensory descriptors after heat treatment adequate canonical variables

Traits		Canonical variables
Variables explaining other variables		u 1	u 2	u 3	u 4	u 5	u 6	u 7
pH1	x 1	-0.07	0.40	-0.59	0.01	0.57	0.40	0.10
pH3	x 2	-0.18	0.00	-0.45	0.36	0.75	-0.02	-0.27
pH24	x 3	-0.62	-0.31	-0.19	-0.40	-0.22	0.47	-0.23
pH48	x 4	-0.76	0.07	-0.27	0.03	-0.23	0.45	-0.29
L	x 5	0.46	-0.18	-0.27	0.72	0.00	0.28	0.29
a	x 6	-0.60	-0.29	0.46	-0.50	0.25	0.01	0.17
b	x 7	0.39	0.05	-0.68	0.39	-0.05	-0.16	0.45
Explained variables		v1	v2	v3	v4	v5	v6	v7
Odour	y 1	0.00	-0.20	-0.17	-0.67	0.27	-0.48	-0.11
Colour intensity	y 2	0.21	-0.35	0.34	-0.22	0.14	0.23	0.62
Colour homogenity	y 3	0.00	-0.15	-0.00	-0.24	-0.24	-0.78	0.37
Tenderness	y 4	-0.41	-0.20	0.14	-0.15	-0.65	-0.14	0.01
Juiciness	y 5	-0.40	-0.34	-0.33	0.18	-0.69	-0.00	0.19
Fat perception	y 6	-0.05	0.65	-0.42	0.17	0.10	0.11	-0.33
Meat flavour	y 7	-0.85	-0.20	-0.10	-0.18	0.41	-0.11	0.07
Overall quality	y 8	-0.86	0.01	-0.16	-0.13	0.12	-0.02	0.26

Table 5. Results of canonical analysis of 50 fatteners: canonical load factors described the relation between principal variables characterized by slaughter value of carcass weight and meat sensory descriptors after heat treatment and adequate canonical variables

Traits
Variables explaining other variables		u 1	u 2	u 3	u 4
HCW	x 1	-0.29	0.40	0.02	-0.87
The percentage of meat	x 2	0.36	-0.71	-0.30	-0.53
Loin thickness	x 3	0.08	0.27	-0.70	-0.66
Back fat thickness	x 4	0.35	0.89	0.03	0.29
Explained variables		v1	v2	v3	v4
Odour	y 1	0.01	0.41	-0.03	0.02
Colour intensity	y 2	-0.15	-0.28	-0.40	-0.54
Colour homogenity	y 3	0.30	0.34	0.07	-0.24
Tenderness	y 4	-0.26	-0.00	-0.12	-0.15
Juiciness	y 5	-0.46	0.24	0.33	-0.27
Fat perception	y 6	0.08	0.26	-0.12	0.72
Meat flavour	y 7	-0.17	0.41	-0.10	-0.38
Overall quality	y 8	-0.18	0.52	-0.23	-0.36

The analysis of obtained experimental results indicated that canonical variable u1 and u2 were connected with TY index to high extent, cooking yield or tenderness and juiciness of meat, and in consequence with overall sensory quality (Table 3). Variables u2 and v2 were connected with pH1 and pH3 or sensory fat sensitivity, tastiness as well as overall quality. Successively characters, as well as natural drip loss and pH₂₄ were connected with u3 and u4 variable and explained to high extent v3 and v4 variable, connected with typical aroma, brightness of colour and flavour.

The results are in agreement with the data obtained by Jaworska et al. [9] using other multidimensional statistic analysis. Similar correlations between water-holding capacity, technological yield in cooking and processing, the degree of its acidification measured by final pH and its sensory quality of meat, mainly tenderness and juiciness, were found by numerous authors [1, 5, 6, 17, 23]. Large variability in this regard is often observed in high meatiness fatteners, both in individuals and inside a single muscle [24].

Additional effects of the rate of the decrease and range of pH, drip loss and cooked meat yield on the studied meat quality descriptors after heat treatment were statistically highly related to each other, which is indicated by the level of estimated canonical correlation coefficient C_R = 0.98 found between both group of variables (Table 6).

Table 6. Canonical correlation (CR) and determination (CR2) coefficient obtained in 50 studied fatteners

Variables explaining other variables	Explained variables	CR	CR2x100%
pH1. pH3. pH24. pH48. DL.. TY. CYI	All tested sensory descriptors (ODU. CIN. CHG. TEN. JUI. FPE. MFL. OSQ)	0.98***	96.5
pH1. pH3. pH24. pH48. Colour parameters L a b	All tested sensory descriptors (ODU. CIN. CHG. TEN. JUI. FPE. MFL. OSQ)	0.97***	94.1
HCW, the precentage of meat. loin and back fat thickness	All tested sensory descriptors (ODU. CIN. CHG. TEN. JUI. FPE. MFL. OSQ)	0.88***	78.5

Lower, but statistically significant, relationship of pH effects measured in different time was obtained by Przybylski et al. [20].

Similar correlations were observed in the case of comparison parameters characterizing meat quality and possible to diagnose its quality (pH value and colour parameters).

The meat colour constituents were significant statistically related to variable u1, u3 and u4, similarly as for pH₁ and pH₂₄, pH₄₈ and highly explained meat aroma, meat flavour and its overall quality (Table 4). The canonical correlation coefficient obtained was C_R = 0.97 (Table 6).

Lower, but statistically significant, relationships between features characterizing slaughter value and sensory quality attributes (C_R = 0.88, tab.6) were also observed. Variable u2, u3 and u4, were related to weight carcasses, meat content, loin thickness and highly explained meat colour, sensory fat sensitivity, meat tastiness and in consequence its overall quality after heat treatment (Table 5).

The results of the research of other authors showed that pork quality after heat treatment is a result of its tastiness, texture (tenderness and juiciness) and low intensity of off-flavour [5, 7, 22]. Literature data indicate that overall pork quality after heat treatment to the largest estent is affected by flavour, texture (tenderness and juiciness) but decreased by sour odour and off-flavour, and also hardness and fibrous [7,16].

Grzes et al. [8] showed a significant effect of slaughter value and weight of carcass on their sensory quality of cooked meat (especially tenderness).

Summarizing, on the basis of the obtained results it is possible to confirm that formation of adequate technological usefulness of fatteners meat, derived from crossbreeding of high meatiness, may be a significant factor in improving sensory quality of meat after heat treatment. With regards to the above the issue of improving pork meat quality is very important and simultaneously it is possible to satisfy the consumers culinary expectation regarding meat quality (as indicated by statistical data, 56% of total pork meat is purchased as culinary meat) and also its technological usefulness.

CONCLUSIONS

1. Studied fatteners originated from crossing of Polish Landrace sows with Naïma sows with hybrids P76-PenArLan boars were characterized by high meatiness and satisfactory technological and sensory meat quality.

2. The overall sensory quality of meat following heat treatment was significantly statistically related to final meat pH (pH₂₄, pH₄₈), amount of drip loss and cooking yield and laboratory model of ham production (TY).

3. Application of canonical analysis provides an opportunity to estimate simultaneous effect of slaughter and also technological value of meat on its sensory quality of Longissimus lumborum after heat treatment.

4. The obtained amount of canonical correlation coefficient was highly statistically significant and the value ranged from C_R= 0.88 (slaughter value) to C_R= 0.98 (technological quality).

5. The obtained results indicated the simultaneous possibility of improving technological quality of meat (technological usefulness) and its sensory quality.

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Accepted for print: 5.10.2007

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Wiesław Przybylski
Department of Engineering and Catering Technology,
Faculty of Human Nutrition and Consumer Science,
Warsaw Agricultural University, SGGW, Poland
Nowoursynowska 159 C, 02-766 Warszawa, Poland
email: wieslaw_przybylski@sggw.pl

Danuta Jaworska
Department of Engineering and Catering Technology,
Faculty of Human Nutrition and Consumer Science,
Warsaw Agricultural University, SGGW, Poland
Nowoursynowska 159 C, 02-766 Warszawa, Poland

Ewa Czarniecka-Skubina
Department of Engineering and Catering Technology,
Faculty of Human Nutrition and Consumer Science,
Warsaw Agricultural University, SGGW, Poland
Nowoursynowska 159 C, 02-766 Warszawa, Poland

Andrzej Półtorak
Department of Engineering and Catering Technology,
Faculty of Human Nutrition and Consumer Science,
Warsaw Agricultural University, SGGW, Poland
Nowoursynowska 159 C, 02-766 Warszawa, Poland

Stanisław Niemyjski
Department of Engineering and Catering Technology,
Faculty of Human Nutrition and Consumer Science,
Warsaw Agricultural University, SGGW, Poland
Nowoursynowska 159 C, 02-766 Warszawa, Poland

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Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.

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