CG TG LG TLG
P7 10,98 ± 0,07
A9,61 ± 0,18
B9,54 ± 0,09
B9,60 ± 0,19
BP21 20,44 ± 0,35
A22,23 ± 0,30
B22,20 ± 0,25
B22,35 ± 0,67
BP42 50,36 ± 1,45
A52,50 ± 0,64
B52,29 ± 0,22
B52,66 ± 0,94
BAge (days) Leg muscle cells diameter
CG TG LG TLG
P7 11,59 ± 0,09
A10,23 ± 0,04
B10,20 ± 0,05
B10,23 ± 0,08
BP21 20,90 ± 0,26
A22,73 ± 0,32
B22,69 ± 0,24
B22,82 ± 0,65
BP42 50,72 ± 1,45
A52,84 ± 0,64
B52,63 ± 0,24
B53,03 ± 0,97
B Groups: CG (control group), TG (thermal treated group), LG (light treated group), TLG (simultaneous thermal and light treated group)Age (days): P (postnatal)
Means in a row without a common superscript capital letter differ significantly (P < 0.01)
It can be expected that in accordance with pattern of development of muscle cells (Junqueira and Carneiro, 2003), muscle cells of treated groups, which have greater diameter compared to control group on 21
stand 42
ndday of embryonic development, have the greater amount of cytoplasm while the nucleus takes up a smaller part of the cell. That was confirmed by Stojanović (2011) who found the smaller nucleo-cytoplasmic ratio of muscle cells of thermal treated groups during the late postnatal development compared to control groups, as a consequence of described relation between nucleus and cytoplasm inside muscle cell.
Stojanović (2011) also detected that there were no significant differences between volume density of connective tissue in muscles between control group and thermal treated groups, which could be due to the equal quantity of muscle tissue per unit area within the muscle.
For example, during the late postnatal development, applied treatments caused the formation of smaller number of muscles cells of greater diameter per unit area, while in control group, the higher number of muscle cells of smaller diameter was formed per the same unit area. These findings are related to distribution of muscle and connective tissue inside muscles (Eurell and Frappier, 2006).
Relying on the results of previously described studies, where thermal manipulations during incubation caused prolonged proliferation of myoblasts and increased diameter of muscle cells in late postnatal period of development (Halevy et al., 2006c; Stojanović, 2011; Žikić et al., 2013), it can be assumed that these treatments could have influence of carcass characteristics of broiler chickens, and that great number of muscle cells in treated groups could cause greater muscle mass in later stages of postnatal development. Stojanović et al.
(2011) showed that thermal treated group had significant higher body weight, weight of
drumsticks and thighs, and toes. These production parameters of broilers of thermal treated
group could also be explained by stimulatory effect of thermal manipulation on the
proliferation of satellite cells which are responsible for postnatal growth and development
of muscle cells (Schultz and McCormik, 1994; Ušćebrka et al., 2010a).
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Kanački et al. (2011) examined the effects of temperature manipulations on the quality of broiler meat. It was shown that treated group had higher dry matter content in meat, due to increased percentage of total protein in meat. The progressive loss of moisture is an important indicator of meat quality, since the weight loss increases during the technological processes of cooling. In thermal treated group less progressive loss of moisture (drip loss) was determined, which was related to high capacity of proteins for binding the water.
Conclusion
Temperature manipulation during incubation could greatly affect on development of muscle cells. Increased temperature of narrow temperature interval (temperature increasing from 37.8ºC to 39 ºC) stimulates the proliferation of myoblast. Also, these temperature changes accelerate growth of muscle cells after the completing the process of proliferation.
It was shown that temperature manipulations during incubation have positive effect on proliferation of satellite cells too. Increased myoblast and satellite cell proliferation leads to greater diameter of skeletal muscle cells in treated groups in late postnatal period. This could have positive effect on body weight of broilers and quality of broiler meat. It can be concluded that temperature manipulation during incubation should be further examined as the factor which leads to postnatal growth of skeletal muscle tissue.
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Invited paper UDC: 551.525:551.571
VARIABILITY OF TEMPERATURE-HUMIDITY INDEX ON SIMMENTAL DAIRY FARMS
Bogdanović V.1, Đedović R.1, Stanojević D.1
Abstract: The aim of this study has been to analyze the variability of temperature-humidity index (THI) values, depending on the influences of various factors associated with the housing conditions on Simmental cattle farms with different capacities. A systematic measurement of the T°C and RH% was carried out in the facilities for cattle housing, in the period from March to December 2014. A total of 18076 individual values of THI were analyzed. To analyze the variability of THI, a fixed model with the effects of the farm, altitude, day and month of the measurement was used. In addition, single effect associated with the size of farm and type of cowshed for housing the cattle were tested, i.e. influences regarding the method of construction, type of standing and type of ceiling in the cowshed.
The most farms had an average value of the TH index below the critical value of 72, but also that all farms recorded extremely high maximum values which indicate that the potential for occurrence of heat stress existed in all analyzed farms. High determination of the model (63%), with high significance of all the factors included in the model, indicates that the farm with all its determined and undetermined effects, together with the location and microclimate factors, represents very important sources of variation that may affect the occurrence of heat stress in cattle. All of this suggests that when designing the facilities for cattle housing, special attention should be paid to technological solutions for proper maintenance of the microclimate in them, especially taking into account present changes taking place and the increasing occurrence of short-term, but extreme, weather conditions.
Keywords: source of variation, temperature, relative humidity, THI, heat stress
Introduction
The production of cow’s milk in Serbia is organized on farms with very different capacities, which mutually differ in relation to agro-ecological, zoo-technical and socio- economic conditions. The production is dominated by two breeds of cattle, the Simmental and Holstein-Friesian. These two breeds, in addition to differences in genetic potential for milk production, also differ in relation to the farm conditions in which they are grown. The Simmental breed is more often grown on small and medium-sized family farms whose farming production conditions can be classified as widely ranging from semi-extensive to intensive, while the Holstein-Friesian breed is more typical for medium and large family farms where production conditions are much more intensive (Bogdanović et al. 2014).
1Bogdanović Vladan, PhD, professor; Đedović Radica, PhD, professor; Stanojević Dragan, BSc, assistant, University of Belgrade, Faculty of Agriculture, Belgrade, Serbia;
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Given the fact that the Simmental breed is grown in heterogeneous farm conditions, the impact of different housing and microclimate factors will be more pronounced on both the livestock and milk production. In regards to the microclimate factors those that particularly stand out are air temperature and relative air humidity. This is because these two parameters are involved in the formation of the so-called “temperature-humidity index”
(THI), which is the most common indicator for the assessment of heat (thermal) stress, as well as for assessment of the impact of heat stress on production and reproduction features of the livestock (Kučević et al 2013). It is well known that heat stress has a very negative influence on the expression of productive and reproductive traits in cattle and that high air temperature plays a key role in the initiation of heat stress. Cows with a higher milk production are particularly sensitive to high air temperatures and heat stress. The decrease in milk production in relation to outside air temperature can be in the range between 3-10%
and even up to 50% in conditions of extreme temperatures exceeding 40°C (Kučević et al, 2013). The negative temperature effect is even more pronounced in conditions where the relative air humidity is not appropriate in the cattle housing facility, given the fact that the thermoregulatory mechanisms of cattle function with difficulties in conditions of high relative humidity.
The combined effect of temperature and relative air humidity is used to calculate the temperature-humidity index and in relation to established values provides a satisfactory assessment of potential heat stress (Akyuz et al., 2010). It is considered that milk production is endangered if the THI values exceeds 72, which corresponds to an air temperature of 22°C and relative air humidity of 100%, air temperature of 25°C and relative humidity of 50% or air temperature of 28°C and relative humidity of 20% (Gantner et al., 2011).
Previous researches have been more focused on identifying the relationship between the THI value and milk production than with the variability of this index. Therefore, the aim of this study has been to analyze the variability of TH index values, depending on the influences of various factors associated with the housing conditions on Simmental cattle farms with different capacities.
Material and Methods
A systematic measurement of the temperature and relative humidity was carried out in the facilities for housing cattle, in the period from March to December 2014, in order to determine the variability of the temperature-humidity index (THI) on Simmental cattle farms. This study included five farms of different capacities which are primarily engaged in milk production and are located in the vicinity of Velika Plana, Čačak and Loznica.
The measurement of the temperature and relative air humidity in cowsheds for housing cattle was carried out using the device for automatic registration of microclimate parameters, Data logger AMTAST, AMT-116.The measurements were performed continuously every 60 minutes during all the months included in the research period.
Included farms differed in relation to size, altitude and type of building. Within the type of building category, several subcategories were defined which included the method of building the facility, type of standing and the ceiling in the cowshed.
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In terms of size, all the farms included in the analysis were classified as small (SMALL, up to 20 cattle, n=8259) and medium (MEDIUM, from 21-50 cattle, n=9817). The altitude of the farm was divided into heights up to 100 m (ALT1, n=1800), from 101-200 m (ALT2, n=3845) and from 201-300 m (ALT3, n=12431). In terms of the method of building the facility for housing the cattle, all the cowsheds are divided into cowsheds built from concrete (TYPE1, n=1800), from brick (TYPE2, n=10060) and combined concrete-wood (TYPE3, n=6216). In relation to the type of standing, the cowsheds are divided into sheds with tied housing system, short standing and grid floor (STAND1, n=6215), tied housing system and short standing (STAND2, n=1800) and tied housing system and medium standing (STAND3, n=10061). The type of ceiling in the cows had included cowsheds with a flat concrete slab as the ceiling (ROOF1, n=8016), a sloping roof and partly a flat slab as the ceiling (ROOF2, n=1800) and a sloping roof without ceiling (ROOF3, n=8260).
The temperature-humidity index (THI) is calculated as follows:
THI =(1.8T + 32) – ((0.55−0.0055RH) × (T − 26.8))(Dunn et al., 2014)
where: T = temperature of the air expressed in °C, RH = relative humidity of the air expressed in %.
A total of 18076 individual values of THI were analyzed. To analyze the variability of THI, a fixed model with the effects of the farm, altitude, day and month of the measurement was used. This model was chosen because it had the highest coefficient of determination by keeping the significance of all the included factors. In addition, single effects associated with the size and type of cowshed for housing the cattle were tested, i.e.
influences regarding the method of construction, type of standing and type of ceiling in the cowshed. The variability of TH index was analyzed using statistical procedures PROC FREQ and PROC GLM of the SAS statistical package (SAS9.1.3, 2007).
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Results and Discussion
Table 1 shows the descriptive statistic parameters for the values of the temperature- humidity index in relation to the fixed factors of the basic statistic model.
Table 1.Descriptive statistics for THI
Levels of effects Mean SD Min Max
Farm 1 68.24 7.88 50.52 88.53
Farm 2 72.39 5.53 59.84 97.54
Farm 3 67.19 8.13 45.17 87.27
Farm 4 65.83 8.98 41.01 87.83
Farm 5 66.25 6.79 50.52 84.26
Altitude up to100 m 68.24 7.88 50.52 88.53
Altitude from 101 to 200 m 69.12 6.94 50.52 97.54
Altitude from 201 to 300 m 66.51 8.59 41.01 87.83
March 61.43 4.62 52.20 76.83
April 63.64 6.01 50.52 97.54
May 67.99 6.54 51.24 85.81
June 73.14 5.60 59.18 88.53
July 75.48 3.89 66.17 86.37
August 74.39 4.46 61.27 87.84
September 67.57 4.44 55.82 78.16
October 61.75 6.85 44.93 73.56
November 55.43 5.25 42.80 68.40
December 46.95 3.78 41.01 66.30
It can be noticed from Table 1 that most farms had an average value of the TH index below the critical value of 72, but also that all farms recorded extremely high maximum values which indicates that the potential for occurrence of heat stress existed in all analyzed farms. The same can be observed for TH index values in relation to altitude. Somewhat different, but still expected values were observed in relation to the month of measurement.
Three critical months, when the occurrence of heat stress is not only highly probable, but represents a real danger, are June, July and August. During all of these three months, the average values of the TH index were above 72. However, potentially dangerous months are also May and September in which recorded values of the TH index were very close to critical, but also April when exceptionally high maximum TH index values were recorded.
This kind of unexpected extreme, but short-term weather effects can be expected in the future, so it is extremely important that farmers pay attention not only to the summer season, but also the middle of the spring season. The results of this study coincide with results published by Bouraoui et al. (2002), Akyuz et al. (2010) and Gantner et al. (2011).
The impact of all analyzed factors involved in the fixed model, and the impact of individual factors associated with farm size, type of facility and cowshed conditions, were statistically highly significant (Tables 2 and 3).
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Table 2. Analysis of variance for THI
Effect df R2 p
Model 45 0.63 ***
Farm 4 --- ***
Altitude 2 --- ***
Day of measurement 30 --- ***
Month of measurement 9 --- ***
High determination of the model (63%), with high significance of all the factors included in the model, indicates that the farm with all its determined and undetermined effects, together with the location and microclimate factors, represents very important sources of variation that may affect the occurrence of heat stress in cattle. All of this suggests that when designing the facilities for housing cattle, special attention should be paid to technological solutions for proper maintenance of the microclimate in them, especially taking into account present changes taking place and the increasing occurrence of short- term, but extreme, weather conditions.
Table 3 shows the significance and descriptive parameters for factors associated with farm size, type of building and cowshed conditions.
Table 3. Descriptive statistics for THI according to single farm or stall effect
Source of variation and significance Mean SD Min Max
Farm size effect ***
SMALL-size farm 65.93 8.49 41.01 87.83
MEDIUM-size farm 68.33 7.92 45.17 97.54
Type of building effect ***
TYPE 1 68.24 7.89 50.52 88.53
TYPE 2 67.09 8.42 41.01 97.54
TYPE 3 67.17 8.13 45.17 87.27
Type of standing effect ***
STAND 1 65.83 8.99 41.01 87.83
STAND 2 68.24 7.88 50.52 88.53
STAND 3 67.93 7.77 45.17 97.54
Type of ceiling effect ***
ROOF 1 67.30 8.77 41.01 97.54
ROOF 2 68.24 7.88 50.52 88.53
ROOF 3 66.95 7.83 45.17 87.27
Observed throughout the year, the impact of individual factors related to farm size, type of building and cowshed conditions, i.e. the type of standing and the type of roof, were highly significant. The average values of TH index observed in relation to every single factor did not exceed the critical value of 72. However, the potential for occurrence of heat stress should also be viewed through measured threshold THI values. In this regard, the potential for occurrence of heat stress is particularly expressed in medium sized farms which have not adjusted the number of animals to the size of the object. It often happens that farmers intensify milk production by increasing the number of cattle, but this expansion of