SUMMARY OF PhD THESIS UNIVERSITY OF PANNONIA GEORGIKON FACULTY Doctoral School in Animal and Agricultural Environment Sciences Current Head of PhD School: Dr. ANGÉLA ANDA
Former Head of the PhD School and Supervisor: Prof. Dr. FERENC SZABÓ, DSc
Joint-Supervisor: Dr. SZABOLCS BENE
MODEL CALCULATIONS TO DETERMINE THE ECONOMIC WEIGHT OF THE SELECTED TRAITS IN DAIRY BREEDING Written by ZSUZSANNA FEKETE
KESZTHELY 2013
1. Research goals and precedents The dairy cows’ output and the profitability of the same are influence by numerous factors. Among others milk-yield, fat- and protein-yield, loss of calves at birth, conception rate, longevity, mastitis incidence, somatic cell score and not last the feeding. From a breeders perspective these are all very important traits. The aim of this research show the relation between the costs and the revenue of the Hungarian milk production, the status-quo of the dairy cattle stock’s performance traits and their economic weight. 1 To gain new data on the recent costs of domestic milk production, 2 To examine the change in revenue, 3 To evaluate the gross margin and the income, 4 To estimate the most important performance traits in regard to milk production and their marginal and relative economic weight, 5 Furthermore to map the performance and other traits, their economic value and their ranking, of the most common breeds of dairy cattle in Hungary (Holstein-Friesian, Hungarian Simmental, Brown Swiss).
The main topics of the evaluation was as it seen below (Figure 1): Figure 1: The analysed performance and other traits Holstein-Friesian breed milk yield levels
milk price levels Holstein-Friesian
Hungarian Simmental
Brown Swiss
1 loss of calves at birth calculation of the economic weight of these traits on different levels
2 conception rate
calculation of the performance and other traits on the basis of the analysed breeds mean
3 longevity 4 milk yield 5 fat yield 6 protein yield 7 somatic cell score
8 mastitis incidence
2
2. Material and methods The data for the research were collected by using self-made questionnaires on the occasion of farm visits in 2008. The research was conducted in Hungary on 9 Transdanubian cattle farms. Throughout the study the most common dairy cattle breeds for milk production in Hungary were analysed, namely the Holstein-Friesian, the Hungarian Simmental and the Brown Swiss.
The studied performance traits (by cow/year) 1 Loss of calves at birth
%
2 Conception rate
%
3 Longevity
year
4 Milk yield
kg
5 Fat yield
kg
6 Protein yield
kg
7 Somatic cell score
-
8 Mastitis
incidence
The data in the research were analysed with ECOWEIGHT 3.0.2 programme, developed by Wolf et al. (2007) for the ranking of the economic weights of the productive livestock’s performance traits.
2.1. Analysis of the impact of milk yield levels
In this calculation used the data of the Holstein-Friesian stock. Out of the 9 farms included in the study, 4 had purebred or a high percentage of Holstein-Friesian blood in their cattle stock. The calculation was conducted with the average of the farms’ data. The cow milk yield varied between 5000 and 8000 kg/cow/year. Therefore different output levels were determined (5000, 5500, 6000, 6500, 7000, 7500, 8000 kg). The first insemination of the heifers, which are meant for breeding, start at a live weight of 390 kg. Table 2 and Table 3 present the most important data found on the farms. The dairy farms sold the milk during the analysed period for contractually agreed base price of 65 HUF/kg, which applied to 3.7 g/100 g fat content and 3.3 g/100 g protein content. Milk, which differed from the above, was bought with a correction of 3
+/-600 HUF/ fat kg and +/- 900 HUF/ protein kg by the dairy industry. The average of the farms’ was 3.8 % fat content and 3.3 % protein content. The production of the dairy farms was consistent with quota, therefore the subsidy was 8 HUF per litre of milk. In this part of the work examines the impact of the different yield levels on the economic weight of the performance traits. Furthermore the research tried to identify the traits, whose economic importance depend on the milk yield. For the modelling basic data were collected, which are needed for the functioning of the programme package.
2.2. Analysis of the impact of change in milk price
This part of the study evaluated the data of the Holstein-Friesian stock. Out of the 9 farms studied, 4 had purebred or a high percentage of Holstein-Friesian blood in their cattle stock. The farms were not compared separately, but the calculated was done with the average of all farms. The average of the collected data got rounded to a milk yield of 8000 kg/cow/year. The dairy farms sold the milk during the studied period for a hypothetical HUF/kg base price. Similar to the previous study, this base price again applies to 3.7 g/ 100 g fat content and 3.3 g/100 g protein content. The average of the farms’ was 3.8 % fat content and 3.3 % protein content. The production of the dairy farms was consistent with quota; therefore the subsidy was 8 HUF per litre of milk. In the model calculation different base prices got determined for the separate categories (70, 75, 80, 85, 90 HUF/kg). The study aimed to find out, how the change in milk price impacts the economic weight of the different performance traits. Furthermore to determine those traits, whose economic importance is influenced by the change in milk price.
2.3. Economic evaluation of performance and other traits of the different breeds
In this part of the study the Holstein-Friesian, the Hungarian Simmental and the Brown Swiss stock were examined. Out of the 9 farms included in the study, 4 had purebred or a high percentage of Holstein-Friesian blood, 3 Hungarian Simmental blood and 2 Brown Swiss blood, in their cattle stock. Here the economic weight of the performance and other traits was compared in between the different breeds.
4
3. Results and discussion
3.1. Impact of the milk yield levels Table 1 shows the variation in production value, cost of production, gross margin, profit and profitability in connection to the milk yield.
Table 1: Income, cost and profit data of milk production in case of different milk yield Average milk yield, kg/cow (1) Income, thousand HUF/cow (2) Subsidy, thousand HUF/cow (3) Production value, thousand HUF/cow (1+2) (4) Direct cost, thousand HUF/cow (5) Cost of production, thousand HUF/cow (6) Gross margin, thousand HUF/cow (3-4) (7) Profit, thousand HUF/cow (3-5) (8) Profitability, % (7/5*100)
5000
5500
6000
6500
7000
7500
8000
377.21
402.73
428.24
453.76
479.28
504.80
530.32
35.96
39.72
43.48
47.23
50.99
54.75
58.50
413.17
442.45
471.72
501.00
530.27
559.55
588.82
265.24
273.86
282.48
291.10
299.72
308.34
316.96
353.66
365.15
376.65
388.14
399.63
411.12
422.62
147.93
168.58
189.24
209.89
230.55
251.20
271.86
59.51
77.29
95.08
112.86
130.64
148.42
166.20
16.80
21.20
25.20
29.10
32.70
36.10
39.30
The income derived from the realisation of milk, calves, maiden heifers, pregnant heifers, cull cows, as well as manure, logically grows with the milk yield. The difference between the two end values is more than 150 000 HUF. A growth in the costs per cow can been seen in accordance to the growth in milk yield, which can be accounted to the higher quality and therefore price in the nutrition of the cows. It can also be observed that with rising milk yield the profitability grows as well (from 16.8 % to 19.3 %). The gross margin grows in relation to the milk yield, in the studied span of 5000-8000 kg it ranges between 147 930 and 271 860 HUF/cow/year.
Table 2 summarizes the marginal weight of the studied performance traits on the different output levels. With the help of these weights we can compare the same performance traits on the different levels.
5
Table 2: Marginal economic weights of the evaluated traits Milk yield, kg/cow/year
5000
5500
6000
6500
7000
7500
8000
Marginal economic weight, thousand HUF/cow/year Loss of calves at birth, %
-1.35
-1.35
-1.35
-1.35
-1.35
-1.35
-1.35
Conception rate of heifers, %
0.59
0.59
0.59
0.59
0.59
0.59
0.59
Conception rate of cows %
4.61
4.59
4.56
4.53
4.51
4.48
4.46
Longevity, year
38.06
38.42
38.79
39.15
39.54
39.92
40.31
305 days milk production, kg
0.02
0.02
0.02
0.02
0.02
0.02
0.02
305 days fat yield, kg
0.25
0.25
0.25
0.25
0.25
0.25
0.25
305 days protein yield, kg
0.62
0.62
0.62
0.62
0.62
0.62
0.62
Somatic cell score
-0.64
-0.70
-0.76
-0.82
-0.88
-0.95
-1.01
Mastitis, incidence
-0.86
-0.92
-0.98
-1.04
-1.10
-1.16
-1.22
The results shows that some of the performance traits’ economic weight is independent from the milk yield, those are loss of calves at birth, conception rate of heifers, protein and fat yield. On the other hand the milk yield has an impact on the following performance traits: conception rate of cows, longevity, somatic cell score and the mastitis incidence. The conception rate of heifers has a minimal positive growth in correlation with the output levels. If a 1 % rise in conception rate of cows could be attained, this would mean a rise of 4610 HUF on the level of 5000 kg and a 4460 HUF on the level of 8000 kg. If the longevity would grow by a year, it would bring a growth in income of 38060 HUF at a milk yield of 5000 kg and 40310 HUF at a milk yield of 8000 kg. Furthermore the table clearly shows that those traits, which have a positive effect on the profitability (conception rates, longevity, milk and protein yield) have a positive sign and those, which have a negative effect on profitability (loss of calves at birth, somatic cell score, mastitis incidence) show a negative sign. From the results it can be observed that an additional mastitis incidence would cause greater loss with rising milk yield. At a level of 8000 kg this would mean a loss of 1220 HUF/cow/year, which is almost twice the loss of the 5000 kg level (-860 HUF/cow/year). Table 3 displays the relative economic weight of the more important performance traits. The presented data shows the economic importance of the evaluated traits in comparison to the 305 days of milk production, which economic importance set at 100, as well as the ranking in between the different traits. 6
Table 3: Relative economic weight of the evaluated traits Milk yield, kg/cow/year
5000
5500
6000
6500
7000
7500
8000
Relative economic weight % Loss of calves at birth
25.14
25.16
25.16
25.12
25.13
25.14
25.12
Conception rate of heifers
6.54
6.54
6.54
6.54
6.54
6.54
6.54
Conception rate of cows
68.66
68.27
67.90
67.50
67.13
66.74
66.36
Longevity
84.98
85.78
86.62
87.40
88.29
89.14
90.00
305 days milk production
100.00
100.00
100.00
100.00
100.00
100.00
100.00
305 days fat yield
39.11
39.12
39.12
39.12
39.14
39.13
39.14
305 days protein yield
69.04
69.05
69.08
69.07
69.08
69.09
69.08
Somatic cell score
0.40
0.44
0.48
0.52
0.56
0.60
0.64
Mastitis incident
0.51
0.55
0.58
0.62
0.66
0.69
0.73
Due to the results the 305 day milk production has the biggest economic weight (100 %), since it is not out weight by any other trait. It is followed by the longevity (84.98-90.00 %), then protein yield with minimal variation (69.04-69.08 %), conception rate of cows (68.66-66.36 %), fat yield (39.14 %), again with only minor variance the loss of calves at birth (25.14-25.12 %), conception rate of heifers (6.54 %), mastitis incidence (0.51-0.73 %) and finally the somatic cell score (0.40-0.64 %). The ranking does not change with rising milk yield. Conclusionally the milk yield has no impact on the ranking between the traits, but in between the different traits the weight of the relative importance changes through the different levels (conception rate of cows, longevity, somatic cell score, mastitis incident). A minimal variation can also be observed in the case of loss of calves at birth and fat and protein yield. No change can be seen at the importance of conception rate of heifers.
The following ranking can be established on the bases of the retrieved data: 1st 305 days milk production, 2nd longevity, 3rd protein yield, 4th conception rate of cows, 5th fat yield, 6th loss of calves at birth, 7th conception of heifers, 8th mastitis incidence, 9th somatic cell score.
7
3.2. Impact of the purchasing price Based on the data the income per cow logically shows a growing tendency with the rising purchasing price of the milk. The difference between the two established end values is 143 000 HUF. The costs very on the same level in each price category, since the expenditure at a given dimension (8000 kg/cow/year) of production are equal as well. In this case the rise in income can only be contributed to the change in milk price, more precisely the rise in the purchasing price of raw milk. The gross margin (307 610-450 610 HUF/cow/year), the profit (201 950-344 950 HUF/cow/year) and the profitability (from 47.8 % to 81.6 %) grow proportionally with the purchasing price of the milk. The study shows that the economic weight of some performance traits are independent from the milk price, such as the loss of calves at birth, the conception rate of heifers, protein and fat yield and the somatic cell score. At the same time the changes in milk price have an impact on the economic weight of conception rate of cows and the longevity, as well as the milk yield and the mastitis incidence. The study established the milk yield (305 days milk production, 100 %) as the trait with the highest economic weight, followed by the longevity (77.03-51.61 %) and the protein yield (57.18-33.85 %). The somatic cell score as well as the mastitis incidence prove to have the least economic importance at the current Hungarian price level.
The following ranking between the different performance traits got established with the help of the relative economic weights: 1st 305 days milk production, 2nd longevity, 3rd protein yield, 4th conception rate of cows, 5th fat yield, 6th loss of calves at birth, 7th conception of heifers, 8th mastitis incidence, 9th somatic cell score.
The milk yield ranks first, from which can be concluded that the Hungarian price system puts the highest emphasis the litres, that is the quantity of milk and not the quality, meaning the content. This is closely followed by the longevity (77.03-51.61 %).
8
3.3. Comparison of the results from the different breeds Figure 2 shows the changes in costs, gross margin and profit. The costs change proportionally with the production value, which assumes a proximately equal expenditure through all breeds. Due to the model calculation the most profitable breeds of the 3 studied ones is the Holstein-Friesian (36.2 %), with its account for the highest income (531 450 HUF/cow) as well as the highest costs (433 270 HUF/cow) (See Figures 2, 3).
Figure 2: Indicators of costs and income
700 600 500 400
(HUF/cow/year) 300 200 100 0
Holstein-Friesian
Hungarian Simmental
Brown Swiss
Production value
Cost of production
Direct cost
Gross margin
Profitability
Figure 3: Profitability of the studied breeds
40
36,2
35
31,7
30 24
25
(%)
20 15 10 5 0
Holstein-Friesian
Hungarian Simmental Profitability, %
9
Brown Swiss
On the bases of the relative weights the following ranking can be established: 1st 305 days milk production, 2nd longevity, 3rd protein yield, 4th conception rate of cows, 5th fat yield, 6th loss of calves at birth, 7th conception of heifers, 8th mastitis incidence, 9th somatic cell score.
Figure 4: Relation of the relative economic weights within the studied breeds
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Holstein-Friesian Hungarian Simmental
Brown Swiss
milk yield
longevity
protein yield
conception rate of cows
fat yield
loss of calves at birth
conception rate of heifers mastitis incidence somatic cell score
Figure 4 demonstrates the relation between the relative economic weights of the analysed traits within the three breeds. In the example of the Holstein-Friesian the compared traits have the following impact on the final result: milk yield ca. 25 %, longevity ca. 22 %, protein yield ca. 18 %, conception rate of cows ca. 16 %, fat yield ca. 11 %, loss of calves at birth ca. 6 %, conception rate of heifers ca. 2 %. The mastitis incidence and the somatic cell score have a value of under 2 %, which do not show in the diagram.
3.4. Comparison of the three different studies Figure 5 presents the rankings from the three separate studies. All three calculations (milk yield, milk price, breeds) concluded with the same ranking.
10
Figure 5: Ranking of the economic weights of the examined performance traits in the different studies STUDY OF MILK YIELD
STUDY OF MILK PRICE
STUDY OF BREEDS
1
milk yield
1
milk yield
1
milk yield
2
longevity
2
longevity
2
longevity
3
protein yield
3
protein yield
3
protein yield
4
conception rate of cows
4
conception rate of cows
4
conception rate of cows
5
fat yield
5
fat yield
5
fat yield
6
loss of calves at birth
6
loss of calves at birth
6
loss of calves at birth
7
conception rate of heifers
7
conception rate of heifers
7
conception rate of heifers
8
mastitis incidence
8
mastitis incidence
8 mastitis incidence
9
somatic cell score
9
somatic cell score
9 somatic cell score
11
4. New research results 1
The study concluded that with subsidies the gross margin is positive in case of all studied milk yield and price level categories. The gross margin in the sector is increased further by the increase in milk production capacity and in selling price of the milk.
2
From this point of view, the comparison of this three breeds unique in Hungary. showed that the economic importance of the features of quality is in the same order for all breeds.
3
In case of the three studied breeds, the economic weight of conception rate for cows is nearly the same as the relative economic weight of milk protein content of milk. Regarding this result there was no reference in literature examined by me.
4
It was confirmed by economic weights that under the current circumstances, economically the amount of milk is the most important attribute (since this is currently paid the most by the dairy industry). On the basis of the studied relative economic weight of features of the different traits, economically the most important attribute is milk production in 305 days (100 %), followed by longevity (84.98-90 %, 51.61-77.3 %, 86.84 %, 84.62 %, 81.67 %), amount of protein yield (69.04-69.08 %, 33.85-57.18 %, 69.09 %, 68.67 %, 63.67 %), conception rate of cows (66.36-68.66 %, 33.50-55.29 %, 63.87 %, 66.27 %, 62.42 %), amount of fat yield (39.11-39.14 %, 19.18-32.40 %, 39.14 %, 38.89 %, 36.06 %), loss of calves at birth (25.12-25.14 %, 12.33-20.82 %, 25.17 %, 25.03 %, 23.19 %), conception rate of heifers (6.54 %, 3.20-5.41 %, 6.53 %, 6.49 %, 6.02 %), mastitis incidence (0.51-0.73 %, 0.48-0.65 %, 0.73 %, 0.58 %, 0.59 %), somatic cell score (0.40-0.64 %, 0.31-0.53%, 0.67 %, 0.48 %, 0.48 %).
5
On the basis of these, it can be stated that milk production in 305 days has the greatest impact on the gross margin in the industry.
12
5. List of scientific publications 5.1. Scientific publications on the PhD topic
5.1.1. Foreign articles (reviewed) 1) Fekete, Zs.-Baumung, R.-Fürst-Waltl, B.-Keller, K.-Szabó, F. (2012): Einfluss des Milchertrags auf die Betriebsrentabilität und auf die ökonomischen Gewichte von ausgewählten Merkmalen.
Züchtungskunde 84.6.463-473 ISSN 0044.5401.
IF: 0,35 (2012)
5.1.2. Hungarian articles (reviewed) 1) Fekete Zs.-Keller K.-Bene Sz.-Zsuppán Zs.-Szabó F. (2009): Különböző értékmérő tulajdonságok ökonómiai súlyozása a tejtermelő szarvasmarha tenyésztésben. 1. közlemény: A tejhozam hatása a jövedelmezőségre és a fontosabb értékmérő tulajdonságok ökonómiai súlyára. Állattenyésztés és Takarmányozás, 58.6.526-537., ISSN 0230.18.14. 2) Fekete Zs.-Szabó F.-Bene Sz. (2013): A tejár hatása a jövedelmezőségre és néhány tulajdonság ökonómiai súlyára négy holstein fríz tenyészetben. Állattenyésztés és Takarmányozás, 62.3.250-261., ISSN 0230.18.14.
5.1.3. Proceedings in foreign language 1) Szabó, F.-Fekete, Zs.-Wolf, J.-Wolfová, M. (2010): Economic weight of some production and functional traits of dairy cattle. CD of the. 2010 Joint Annual Meeting of the American Dairy Science Association, Canadian Society of Animal Science, American Society of Animal Science, Denver, Colorado, USA, July 12-15, 2010. 2) Szabó, F.-Fekete, Zs.-Wolfová, M. (2010): The effect of milk price on economic weight of some traits of dairy cattle. Book of the abstracts of the 61st Annual Meeting of the European Association for Animal Production. August 23-27, 2010, Heraklion, Greece, 258. p.
13
5.1.4. Proceedings in Hungarian 1) Fekete Zs.-Keller K.-Szabó F. (2008): Értékmérők ökonómiai súlyozása a szarvasmarhatenyésztésben, 50. Georgikon Napok, A magyar állattenyésztés időszerű feladatai szekció, Keszthely, 2008.11.25-26, ISBN 78.963.9639.32.4 2) Pupos T.-Péter Zs.-Fekete Zs. (2008): A szaporulati mutatók hatása a tejtermelő tehenészet forgótőke lekötésére, 50. Georgikon Napok, Keszthely, 2008.11.25-26, ISBN:978.963.9639.32.4 3) Fekete Zs.-Szabó F. (2009): A tejtermelést befolyásoló tulajdonságok ökonómiai súlyozása, XV. Ifjúsági Tudományos Fórum, Állattenyésztési Szekció. 2009.04.16, Keszthely, I.9.1-6., ISBN:978.963.9639.33.1) 4) Fekete Zs.-Bene Sz.-Szabó F. (2009): A tejtermelő tehenek néhány termelési és funkcionális tulajdonságának ökonómiai súlya. 51. Georgikon Napok: Lokalizációmegoldás
a
fenntarthatóságra?
Keszthely,
2009.10.01-2009.10.02
ISBN 978.963 9639.34.8
5.2. Other publications (not related) to the topic of the PhD study 5.2.1. Foreign articles (reviewed) 1) Keller, K.-Fürst-Waltl, B.-Baumung, R.-Fekete, Zs.-Szabó, F. (2009): Einfluss der Länge der Weideperiode auf die Betriebsqualität und auf die ökonomischen gewichte
von
Merkmalen
in
der
Fleischrinderzucht.
Züchtungskunde,
81.4.225-234., ISSN 0044.5401. IF: 0,35 (2009) 2) Keller, K.-Wolfová, M.-Wolf, J.-Fekete, Zs.-Komlósi, I.-Szabó, F. (2009): Der Einfluss des Kuhgewichts auf die Betriebsrentabilität und auf die ökonomischen Gewichte
der
Fleischrindmerkmale.
Archiv
Tierzucht
52.3.255-264,
ISSN 0003.9438. IF: 0,595 (2009)
5.2.2. Hungarian articles (reviewed) 1) Keller K.-Bene Sz.-Fördős A.-Fekete Zs.-Szabó F. (2008): A húsmarhatartás ökonómiai modellezése. 1. Közlemény: A tehenek élősúlyának hatása a jövedelmezőségre és a fontosabb értékmérők ökonómiai súlyára. Állattenyésztés és Takarmányozás, 57.3.201-211., ISSN 0230.18.14. 14
2) Keller K.-Bene Sz.-Fördős A.-Fekete Zs.-Szabó F. (2008): A húsmarhatartás ökonómiai modellezése. 2. Közlemény: A választási súly hatása a jövedelmezőségre és a fontosabb értékmérők ökonómiai súlyára. Állattenyésztés és Takarmányozás, 57.4.305-314., ISSN 0230.18.14. 3) Fekete Zs.-Kovacs J.-Rajnai Cs.-Bene Sz.-Szabó F. (2008): Fedezőkanok direkt hatása a szaporulati eredményekre. Animal Welfare - Etológia és Tartástechnológia, 4.2.614-620., ISSN 17868440. 4) Szabó F.-Fekete Zs.-Fördős A.-Zsuppán Zs.-Kanyar R.-Török M.-Polgár J. P.-Bene Sz. (2008): Azonos körülmények között hizlalt, különböző genotípusú növendék bikák hizlalási és vágási eredménye.
Állattenyésztés és Takarmányozás,
57.6.523-536., ISSN 0230.18.14. 5) Szabó F.-Farkas V.-Fekete Zs.-Fördős A.-Zsuppán Zs.-Kanyar R.-Török M.-Kiss B.-Polgár J. P.-Bene Sz. (2008): Különböző genotípusú növendék bikák hízlalási és vágási eredménye. A hús, 18.3.4.88-92., ISSN 1215.0665. 6) Bene Sz.-Fekete Zs.-Fördős A.-Füller I.-Kiss B.-Rádli A.-Török M.-Wagenhoffer Zs.-Polgár J. P.-Szabó F. (2009): Különböző genotípusú növendék vágómarhák növekedése, vágóértéke és húsminősége. 1. Közlemény: Hízlalási és vágási eredmények. Állattenyésztés és Takarmányozás, 58.1.23-40., ISSN 0230.18.14. 7) Bene Sz.-Fekete Zs.-Fördős A.-Wagenhoffer Zs.-Polgár J. P.-Szabó F. (2009): Különböző
genotípusú
növendék
vágómarhák
növekedése,
vágóértéke
és
húsminősége. 2. közlemény: A vágott test összetétele és minősége. Állattenyésztés és Takarmányozás, 58.2.129-145., ISSN 0230.18.14. 8) Bene Sz.-Fekete Zs.-Zsuppán Zs.-Polgár J. P.-Wagenhoffer Zs.-Husvéth F.-Szabó F. (2009): Különböző genotípusú növendék vágómarhák növekedése, vágóértéke és húsminősége. Állattenyésztés és Takarmányozás, 58.3.193-204., ISSN 0230.18.14. 9) Bene Sz.-Fekete Zs.-Lendvay M.-Rajnai Cs.-Polgár J. P.-Szabó F. (2010): Újabb adatok magyar nagyfehér fedezőkanok reprodukciós teljesítményének értékeléséhez. Animal Welfare - Etológia és Tartástechnológia, 6.2.104-117., ISSN 17868440. 10) Bene Sz.-Fekete Zs.-Lendvay M.-Rajnai Cs.-Polgár J. P.-Szabó F. (2011): Néhány tényező hatása a magyar nagy fehér hússertés szaporasági és malacnevelési tulajdonságaira. Animal Welfare - Etológia és Tartástechnológia, 7.1.15-29., ISSN 17868440.
15
11) Bene Sz.-Fekete Zs.-Lendvay M.-Rajnai Cs.-Polgár J. P.-Szabó F. (2011): A szaporasági és malacnevelési mutatók alapján számított populációgenetikai paraméterek és tenyészértékek egy hazai törzsállományban.
magyar
nagy fehér
hússertés
Animal Welfare - Etológia és Tartástechnológia, 7.1.30-44.,
ISSN 17868440.
5.2.3. Proceedings in foreign language 1) Bene, Sz.-Komlósi, I.-Fekete, Zs.-Lengyel, Z.-Szabó F. (2008): Multibreed beef cattle breeding value estimation based on weaning results. Journal of Animal Science, 86 E-Suppl. 2/J, ISSN 0021-8812. IF: 2,123 (2008) 2) Bene, Sz.-Komlósi, I.-Fekete, Zs.-Lengyel, Z.-Szabó F. (2008): Multibreed beef cattle breeding value estimation based on weaning results, ADSA-ASAS, July 7-11, 2008-Indianapolis, Indiana. ISSN 0021.8812. 3) Fekete, Zs.-Kovacs, J.-Rajnai, Cs.-Bene, Sz.-Szabó, F. (2008): Predicted difference of breeding boars for reproduction: prediction with sire model, 59 th Annual Meeting of the European Association for Animal Production, 24-27 August 2008, Vilnius, Lithuania., 115 p. ISSN 0071.2477. 4) Bene, Sz.-Domokos, Z.-Fekete, Zs.-Fördős, A.-Szabó, F. (2008): Genetic parameters and breeding values on weaning results of Charolais calves. 59 th Annual Meeting of the European Association for Animal Production, Session 35., Poster 16, 27th August 2008, Vilnius, Lithuania. 276.p. ISSN 0071.2477.
5.2.4. Proceedings in Hungarian 1) Fekete Zs. (2005): Lovak sajátteljesítmény vizsgálati rendszerének értékelése Magyarországon. Intézményi Tudományos Diákköri Konferencia, Agrártudományi Szekció, Keszthely 2) Fekete Zs.-Rajnai Cs.-Kovács J. (2007): Tenyészkanok reprodukcióra gyakorolt hatása. XIII. Ifjúsági Tudományos Fórum, Állattenyésztés Szekció, Keszthely, 2007.03.22. 3) Fekete Zs. (2007): Lovak sajátteljesítmény vizsgálati rendszerének értékelése Magyarországon,
XXVIII.
Országos
Tudományos
Diákköri
Agrártudományi szekció, Debrecen, 2007.04.15-18. ISSN 1588.4139
16
Konferencia,
4) Fekete Zs.-Rajnai Cs.-Kovács J. (2007): Apaállatok reprodukcióra gyakorolt hatása a sertéstenyésztésben. XLIX. Georgikon Napok, Állattenyésztés, Állatélettan szekció, Keszthely, 2007.11.20-21. ISBN:978.963.9639.20.1 5) Török M.-Farkas V.-Fördős A.-Fekete Zs.-Polgár J. P.-Szabó F. (2008): A bőr alatti faggyúvastagság
és
a
rostélyos
keresztmetszet
terület
egymást
követő
kiértékelésének kapcsolata hízóbikák esetében. XIV. Ifjúsági Tudományos Fórum, Állattenyésztési Szekció, Keszthely, 2008.04.03, I.9.1-6., ISBN 978.963.9639.24.9. 6) Keller K.-Fekete Zs.-Szabó F. (2008): A jövedelem és a fontosabb értékmérők gazdasági jelentőségének változása a választási súly függvényében, XIV. Ifjúsági Tudományos
Fórum,
Állattenyésztés
szekció,
Keszthely,
2008.04.03.
ISBN 978.963.9639.24.9. 7) Fekete Zs.-Kovács J.-Rajnai Cs.-Bene Sz.-Szabó F. (2008): Fedezőkanok direkt hatása
a
szaporulati
eredményekre.
I.
Gödöllői
Tudományos
Napok,
Sertéstenyésztés Szekció, 119 p. Gödöllő, 2008.04.11-12.
5.2.5. Other publication 1) Fekete Zs. (2006): Mén STV eredmények 2002-2004-ig, avagy a hagyományos fajták összehasonlítása a magyar sportlóval, Lovasélet, 5.31. 2) Fekete Zs. (2006): Lovak sajátteljesítmény vizsgálati rendszerének értékelése Magyarországon, Diplomadolgozat, PE-GK, Keszthely.
17
