154 Acta argiculturae Slovenica, Supplement 5, 154–159, Ljubljana 2016 24th Int. Symp. “Animal Science Days”, Ptuj, Slovenia, Sept. 21st−23rd, 2016. COBISS: 1.08 Agris category code: E16 ECONOMIC IMPORTANCE OF MILK TRAITS IN CZECH HOLSTEIN CATTLE UNDER VARIOUS MILK PAYMENT SYSTEMS 1 Zuzana KRUPOVÁ 2, Jiří MOTYČKA 3, Emil KRUPA 4, Monika MICHALIČKOVÁ 5 Economic importance of milk traits in Czech Holstein cattle under various milk payment systems 1 The work was supported by project MZERO0714 of the Ministry of Agriculture of the Czech Republic 2 Institute of Animal Science, Přátelství 815, 104 00 Prague 10, Czech Republic, e-mail: krupova.zuzana@vuzv.cz 3 Holstein Cattle Breeders Association, Hradištko 123, 252 09 Hradištko, e-mail: motycka@holstein.cz 4 Same address as 2, e-mail: krupa.emil@vuzv.cz 5 Same address as 2, e-mail: michalickova.monika@vuzv.cz ABSTRACT The impact of various pricing systems on the economic values of milk traits in Czech Holstein cattle was com- prehensively evaluated. Milk yield, milk components, somatic cells score (SCS) and clinical mastitis incidences were evaluated under the average production and economic conditions of the year 2015. The flexible bio-economic model of the program package ECOWEIGHT 6.0.4 was used for calculation. Under the evaluated pricing systems marginal economic values of milk components ranged from 37.92 to 253.05 € and from 126.46 to 461.71 € per % of fat and pro- teins per cow per year, respectively. High variability was also found for economic importance of SCS (from −14.71 to 800.94 € pre score pre cow and per year). Marginal economic values for milk yield (0.103 € per kg) and clinical mastitis (83.86 € per incidence), both per cow and per year remained without the change over all pricing systems. To standardize the marginal economic values and to calculate the actual relative economic values of traits the actual genetic standard deviations are needed. Key words: cattle, breeds, Czech Holstein, economic values, payment systems, milk traits, milk yield, milk com- ponents, SCS, clinical mastitis 1 INTRODUCTION The abolition of milk quotas in 2015 has been caused stronger pressure on dairy sector in Europe. Eu- ropean Union supplies at a time when China has started to reduce its purchases and Russia has introduced an im- port ban have been resulted to the low prices for milk and dairy commodities (EC, 2015). For example, average milk price decreased by 17 % in the Czech Republic over the last year (MA CR, 2016). The bonuses defined in the milk pricing systems seem to be one solution to influence the milk price by farmers. Selection for milk production traits has traditionally received most emphasis in nation- al breeding programs of dairy cattle in many countries (e. g. Hietala et al., 2014; Komlósi et al., 2010). Consider- ing the actual selection strategy, breeding values and eco- nomic values for milk fat and milk proteins (expressed both, in kg and in %) and somatic cell score (SCS) are the key breeding parameters for Czech Holstein cattle. Selec- tion for reduced clinical mastitis incidence has not been yet included there in spite of the generally positive effect on animal welfare, product quality and economically sus- tainable farming (Krupová et al., 2016). The absolute economic values of milk production traits differed notably in the literature due to differences in pricing systems. The impact of various milk pricing systems on the economic weights for milk yield and fat and protein content in Holstein were investigated in the past (Wolfová et al., 2007). In the Czech conditions, the milk pricing system has been still varied in high exten- sion among the farms however the production and eco- nomic conditions of the breed have been changed from Acta agriculturae Slovenica, Supplement 5 – 2016 155 ECONOMIC IMPORTANCE OF MILK TRAITS IN CZECH HOLSTEIN CATTLE UNDER VARIOUS MILK PAYMENT SYSTEMS this time. Therefore, the impact of various pricing sys- tems applied in 2015 on the economic values of milk traits in Czech Holstein dairy cattle population using the bio-economic approach were comprehensively investi- gated in the study. 2 MATERIALS AND METHODS 2.1 PRODUCTION SYSTEM Economic values of milk traits were calculated for purebred Holstein breed. Production system was treat- ed as self-reproducing (breeding and commercial herds together). A classical indoor farming system with loose for dairy herd presented in Table 1 corresponded to the population average obtained from own investigations on farms (unpublished data) and from the official resources (CMBC, 2015, 2016) for the year 2015. 2.2 PROFIT FUNCTION AND ECONOMIC VALUES Economic efficiency of the production system was expressed as the present value of total profit per cow and per year entering a reproductive cycle (Wolfová et al., 2007). Revenues were derived from milk, from sold animals (breeding heifers, calves, slaughtered cows and heifers), manure, and direct subsidies (0.007 € per kg of milk). Revenues from milk were a function of milk amount, fat and protein content, and somatic cell count. Marginal economic value (economic importance) of trait l (evl) was calculated as the partial derivative of the profit function with respect to the trait: avll TVTV lev     lTV TP where TP was total profit per cow and year, TVl was the value of trait l, and TVlav was the trait mean within the population. Relative economic value of trait l (in %) was calculated as proportion of absolute value of the standardized mar- ginal economic value (i.e., marginal economic value multiplied by the genetic standard deviation) of trait l on the sum of the standardized marginal economic values of all evaluated traits. It was calculated to compare the Trait (unit) Mean Genetic standard deviation Milk yield (kg) 1 9 546 870 Milk fat percentage (%) 3.80 0.210 Milk protein percentage (%) 3.34 0.150 SCS (score) 2 4.387 0.083 Clinical mastitis (cases per cow and year) 3 0.98 0.080 1 Milk yield defined as 305-day milk yield with constant fat and protein content averaged over all lactations 2 Somatic cell score expressed as log2 (somatic cell count/100 000) + 3. 3 Clinical mastitis incidence expressed as the number of cases per cow and year at risk, averaged over all lactations. Table 1: The main input traits for Czech Holstein in 2015 PS Base milk price (€ kg−1) Fat content Protein content SCC 1 Intervals (%) − / + 2 (€ %−1) Intervals (%) − / + 2 (€ %−1) Intervals (1000 cells) − / + 2 (€ kg−1) A 0.022 - 0.027 - 0.041 < 250 / ≥ 400 +0.049 / −0.20 B 0.058 - 0.022 - 0.040 ≥ 400 −0.037 C 0.256 < 3.5 / ≥ 3.5 −0.007 / +0.014 < 3.0 / ≥ 3.0 −0.048 / +0.055 ≥ 400 −0.037 D 0.273 < 3.6 / ≥ 3.8 −0.029 / +0.029 < 3.9 / ≥ 3.9 −0.062 / +0.044 ≥ 400 −0.139 E 0.028 - 0.029 - 0.040 ≤ 300 +0.004 F 0.304 < 3.4 / ≥ 3.7 −0.007 / +0.026 < 3.2 / ≥ 3.4 −0.007 / +0.044 ≥ 240 −0.044 G 0.034 - 0.027 - 0.042 ≥ 400 −0.044 1 Somatic cell count measured in thousand of somatic cells per ml of milk as geometric average over the last 3 months period. 2 − / + are penalties and bonuses for milk components intervals and for SCC. Value is not placed (-) in the Table when no interval was mentioned in the given PS (milk price linearly depended over the whole range of the milk components content). 1€ was set to 27.28 Czech Crowns. Table 2: Characteristics of milk pricing systems (PS) for milk, fat and protein content and SCC 1 housing of cows, selling (exporting) of surplus calves at weaning and selling of surplus pregnant breeding heifers was assumed. Markov chain approach was used to gener- ate steady state of the dairy herd structure as described by Wolfová et al. (2007). The main input parameters Acta agriculturae Slovenica, Supplement 5 – 2016156 Z. KRUPOVÁ et al. economic importance of different traits. Considering the main aim of the study, only the traits related to milk price and milk payment system are presented here. Due to abolition of milk quota in April 2015 all calculations were done for the situations without quotas on milk yield and fat content. Detailed description of principles ap- plied to calculate revenues, cost and economic values of the traits can be found in previous studies (e.g. Wolfová et al., 2007; Krupová et al., 2016) and in manual of the program package ECOWEIGHT (Wolf et al., 2013). 2.4 MILK PAYMENT SYSTEMS The actual milk payment systems provided by seven Czech dairies in the year 2015 were investigated in the study (Table 2). Two main indicators were considered as the inputs of the bio-economic model to simulate pay- ment systems: 1. volume and system of penalties and/or bonuses for fat and protein content and for somatic cell count (SCC), 2. base price for milk plasma or base price for milk volume with the average components content In the most of payment systems, average fat and protein content specified in the statistical statement of the Ministry of Agriculture of the Czech Republic (MA CR) for the given time period were referred to calculate average milk price. Therefore, when modelling the ap- propriate payment systems the content of milk compo- nents (3.84 % and 3.39 % for milk fat and proteins, re- spectively; MA CR, 2016) averaged over the year 2015 was taken into account. Regarding the basic milk price it has not been di- rectly defined in most of the payment systems except of the “C”, “D” and “F” where base milk price have been mentioned and it referred to the milk with the given fat and protein content and SCC. In other payment systems, base milk price has depended on the statistical statement (MA CR, 2016) and it referred to milk plasma. These specifics were set in the program to correspond to the average price of milk in the Czech Republic in 2015 (MA CR, 2016) and to consider milk price difference in Czech Holstein breed (Wolfová et al., 2007). In all variants of payment systems, average price per unit of milk finally calculated in the bio-economic model fully correspond to the value 0.276 € l–1. The payment systems (listed in Table 2) were applied to the bio-economic model while other inputs for the breed remained constant. Name of dairies included into the evaluation remained anony- mous due to confidentiality of data and without any im- pact on the main aim of the study. The program EWDC (version 3.0.4) from the pro- gram package ECOWEIGHT 6.0.4 (Wolf et al., 2013) was used to model production system and to calculate the economic values of traits. The model includes both deterministic and stochastic components. Most perfor- mances of animals are modelled as herd averages, but phenotypic variation in in milk production, weight of heifers at mating (described by mean and standard de- viation) and other traits are included. The model is non- integer (fractions of animals are allowed) and the cow herd size is given by a fixed number of cows calving per year in the dairy system. 3 RESULTS AND DISCUSSION Marginal and relative economic values of milk traits calculated under the evaluated payment systems are shown in the Table 3 and Figure 1, respectively. Looking at the marginal economic values of milk traits over all of the pricing systems (shown in Table 3), variability of limits for milk components and SCC and associated pen- alties and bonuses for milk quality traits can be shown. These values varied between dairies from 0.007 € 1 %–1 (payment system “C”) to 0.062 € 1 %–1 (payment system “D”) for fat and protein content, respectively. The price corrections (+ / – in Table 2) were mostly linear and over the whole range of milk components content. The high- est marginal importance of milk fat (253.05 € 1 %–1) and proteins (461.71 € 1 %–1) both expressed per cow and Trait (unit) Pricing system A B C D E F G Median Milk yield (kg) 0.103 0.103 0.103 0.103 0.103 0.103 0.103 0.103 Milk fat percentage (%) 137.46 98.92 37.92 253.05 159.92 77.89 143.63 137.47 Milk protein percentage (%) 288.69 287.78 348.77 461.71 287.80 126.46 298.06 288.69 SCS (score) −800.94 −14.71 −14.71 −541.51 −36.59 −551.00 −17.71 −36.59 Clinical mastitis (cases per cow and year) −83.86 −83.86 −83.86 −83.86 −83.86 −83.86 −83.86 −83.86 1 Detailed description of evaluated traits and pricing systems is given in Table 1 and 2 and in Material and Methods section. Table 3: Marginal economic values (€ per unit of the trait per cow and year) of milk traits in pricing systems 1 Acta agriculturae Slovenica, Supplement 5 – 2016 157 ECONOMIC IMPORTANCE OF MILK TRAITS IN CZECH HOLSTEIN CATTLE UNDER VARIOUS MILK PAYMENT SYSTEMS year was found in PS “D”. Contrary, the lowest economic values of milk components were calculated under the payment system “C” (37.92 € 1 %–1 of fat) and “F” (37.92 € 1 %–1 of protein). Similar variation in the marginal economic values of milk components under the various pricing systems was found by Wolfová et al. (2007). Re- lation of the marginal economic values for milk fat and protein content obtained in our study ranged from 1:9.2 to 1:1.62 which is comparable to those published for oth- er European cattle breeds (from 1:2.2 to 1:3.7; Wolfová et al., 2007; Komlósi et al., 2010; Hietala et al., 2016). Proportion favourable for milk protein content founded in our study in payment system “C” was based on the fact, that the upper threshold for milk fat content (3.5 %) was lying out from the Czech Holstein population aver- age (3.8 %) and bonuses (0.014 € 1 %–1 of fat) paid for ad- ditional increase of the trait mean would not be so profit- able compared to bonuses for this trait in other payment systems (e.g. 0.029 € 1 %–1 of fat). Therefore, next to the differences in pricing systems, also the trait definitions and its average population value were found as impor- tant factor for marginal economic value of milk traits in presented study and under the literature (Wolfová et al., 2007; Hietala et al., 2016). Marginal economic importance for SCS was, simi- larly as for milk components, influenced by the variabil- ity in correction coefficients in individual payment sys- tems. Penalties and bonuses oscillated there from –0.037 € per kg of non-standard milk (PE “B” and “C”) to 0.049 € per kg of Q-quality of milk (PA “A”). Based on the pro- duction system of Czech Holstein breed in 2015 the ap- propriate marginal economic values for SCS ranked from –14.71 to –800.94 € per score per cow and year in the payment system “B” and “C”, and “A”, respectively. It is comparable with the literature resources (–241.05 € and –158.30 per score per cow and year; Komlósi et al., 2010; Krupová et al., 2016). Marginal economic values for milk yield and clini- cal mastitis incidence remained without the change over the all pricing systems tested. It was due to the main aim of the study where impact of pricing system under the average economic (e.g. average milk price) and produc- tion (e.g. average milk yield of cows) conditions of Czech Holstein breed in the year 2015 was analysed. If the fluc- tuation of the milk price over the year (e.g. 0.258 € in August and 0.312 € in January per kg of milk in Czech Republic; MA CR, 2016) is considered the appropriate changes in marginal economic value of these traits are found. Similarly, as it was published by Wolfová et al. (2007) when individual purchased contracts for Hol- stein breed were modelled. Average milk price for Czech Holstein breed varied in this study from 0.238 to 0.290 € kg of milk and marginal economic value from 0.101 to 0.163 € per kg of milk per cow and year. In our current study, a slightly lover economic value of milk yield (0.103 € per kg of milk per cow and year) compared to previous analyse was found in spite of the fact that average milk price over the years increased (0.276 € per kg in 2015) and milk subsidies (0.007 € per kg of milk) incorporated into the calculation in 2015 strengthened the economic importance of milk trait. We suppose that it can be as- sociated to cost needed for additional milk production which increased much more intensive compared to ad- ditional revenues in the year 2015. When deriving marginal economic importance of clinical mastitis incidence next to the depreciations, veterinary and farmers costs directly connected to mas- titis incidence also the losses of discarded milk within Figure 1: Relative economic values (%) of milk traits in pricing systems (Detailed description of evaluated traits and pricing systems is given in Table 2 and Material and Methods section.) Acta agriculturae Slovenica, Supplement 5 – 2016158 Z. KRUPOVÁ et al. the clinical mastitis incidence were taking into account. Based on the main aim of the study, except of the pay- ment system, all inputs of the bio-economic model for Czech Holstein breed remained constant. Therefore, average milk price and milk yield per lactation were as the main factors in our study. Total losses accounted for 83.86 € per clinical mastitis case per cow and per year for Czech Holstein cattle (9546 kg of milk per lactation and 0.276 € per kg of milk). For comparison, slightly lover economic losses (70.65 € per mastitis case per cow and year) calculated for local breed farmed in marginal areas was based on the lover milk yield (4473 kg per lactation) partially compensated with higher milk price (0.310 € per kg; Krupová et al., 2016). Taking into account the negative relationship between clinical mastitis and milk yield in the rest of lactation and reproduction parameters the relative importance of this health trait (ranged from 3 to 5 % form economic importance all of the evaluated traits) could be increased considerably in the constructed selection index. The next important result of this study is that eco- nomic values for milk and milk components were posi- tive under all of the pricing systems. In another words, the additional costs related to the increase of individual traits by one unit (kg; %) was fully compensated by bo- nuses (defined in Table 2) and finally has positive effect on profitability of the production system. Negative eco- nomic value for fat content (–30 € 1 %–1 of fat per cow and year) was calculated in literature (Wolfová et al., 2007) when only the penalties (–0.107 € 1 %–1 of fat) and no bonuses were applied in the given payment sys- tem. Moreover, it should be mentioned that relationship among evaluated traits has not been taken into account when their marginal and relative economic values were calculated to avoid double counting. Genetic standard deviations were used to stand- ardize the marginal economic values and to calculate the relative economic values of traits (Fig. 1). All inputs data were set on the production and economic condi- tions of Czech Holstein breed in 2015. However, actual genetic parameters of the evaluated traits have not been nowadays available. Therefore, approximation of genetic parameters of traits from the previous study (Wolfová et al., 2007) was applied here. Due to this fact, relative proportion of the traits can be slightly influenced by such assumption. In spite of this fact, economic values of the traits were influenced by our assumption in the same way/direction and therefore, some general statement could be still made. Next to the milk yield (ranged from 28 to 50 %) also the milk components (from 6 % to 39 % for fat and protein content, respectively both in payment system “B”) remained as the most important milk traits. To calculate the relative economic values of traits and finally to provide the selection strategy in the popu- lation more precisely genetic parameters should be recal- culated. The main reason is that population genetic and economic parameters substantially influence the con- structed selection indexes (Šafus et al., 2005). Moreover, application of index weights based on a ‘wrong’ pricing system as well as inappropriate genetic parameters of the population can reduce the total economic selection response in the future (Šafus et al., 2005; Wolfová et al., 2007). Optionally, taking into account the appropriate genetic parameters and the weights of traits makes possi- ble to construct customised index according to economic conditions of individual herd (Přibyl et al., 2004). Indeed for farmers it creates the room to consider the economic conditions (e.g. milk payment system) individually. Cus- tomized subindices for milk production traits would increase farmers’ profit from sire selection when selling milk on the basis of different pricing systems (Wolfová et al., 2007). For example, next to the genetic predispo- sition of selected animal for milk yield also the protein content and SCS should be adequately considered in payment system “C” and “A”, respectively. The payment system “E” and “G” seems to be the most suitable when deriving economic values for the whole population due to the median of the marginal and relative economic val- ues of the milk traits (Table 3, Fig. 1) and participation of these dairies on the overall dairy industry (7 % and 20 %, respectively) in the Czech Republic. Nevertheless, the actual marginal economic values can be fully implicated to define the economically important traits in Holstein cattle immediately the actual genetic parameters of traits are available. 4 CONCLUSIONS Milk yield and milk components remained as the most important milk traits over all of the pricing systems analysed in our study. The pricing system confirmed as an important factor of economic values of milk traits cre- ates the space to consider the economic conditions by individual farmer. This finding should be widely applied also in other breeds and production conditions. Marginal economic values of traits calculated in this study can be fully implicated for defining economically important traits in Holstein cattle immediately the actual genetic parameters of traits are available. Moreover, it should be mentioned that relationship among evaluated traits has not been taken into account when their economic val- ues were calculated to avoid double counting. A further study therefore should be valuable to estimate responses in traits potentially included in the breeding goal for Hol- stein breed in the Czech Republic. Acta agriculturae Slovenica, Supplement 5 – 2016 159 ECONOMIC IMPORTANCE OF MILK TRAITS IN CZECH HOLSTEIN CATTLE UNDER VARIOUS MILK PAYMENT SYSTEMS 5 REFERENCES CMBC (2015). 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