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ANIMAL GENETICS |
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* Department of Animal and Dairy Science, University of Georgia, Athens 30602-2771;
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Norsvin, Pb 504, 2304 Hamar, Norway;
and
Departamento de Producción Animal, Universidad de León, León, 24071, Spain; and
Smithfield Premium Genetics Group, PO Box 668, Rose Hill, NC 28458
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Abstract |
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 Top Abstract INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Key Words: carcass weight • heat stress • pig
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INTRODUCTION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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) but also the animals’ welfare and environment (Huynh, 2005). Due to selection for leanness, total heat production of growing pigs has increased during the last decades (Brown-Brandl et al., 2001). The more heat an animal produces internally by its metabolism, the smaller its capacity for tolerating external heat (Bianca, 1976).
Response to heat stress begins with increased respiration rate, continues with decreased feed intake, and leads to increased rectal temperature (Huynh, 2005). Although reduced feed intake can be considered a mechanism of thermoregulation (Bianca, 1976), increased rectal temperature is an indicator of exhaustion of the thermoregulation capacity of pigs (Huynh, 2005). In general, if the magnitude (intensity and duration) of potential stressors exceeds a threshold, animals are unable to cope and are affected adversely (Hahn et al., 2003).
For production in a hot environment, especially in a commercial environment where management conditions are not as good as on nucleus farms, it would be desirable to select pigs resistant to heat stress. Such selection could be for the lowest rectal temperatures during the hot season. However, such data are not readily available. Ravagnolo et al. (2000) used weather records from public weather stations to quantify the change in milk yield in response to the changing temperature-humidity index (THI). They also used the same records to determine genetics of heat tolerance (Ravagnolo and Misztal, 2000). Records from nearby public weather stations were found to be as accurate in capturing the effect of heat stress as records collected on farm (Freitas et al., 2006). As opposed to dairy cattle, where heat stress on 1 d affects milk yield 1 or 2 d later (Fuquay, 1981; Ravagnolo et al., 2000), the effect of daily heat stress on growth is more difficult to measure. The purpose of this study was to quantify the effect of heat stress during the life of a pig on its final BW, as a first step toward a genetic evaluation for heat tolerance.
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MATERIALS AND METHODS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Data
Records on warm carcass weight data were available on 23,556 terminal crossbred pigs [Duroc1 x (Landrace x Large White)] slaughtered from May 2005 through December 2006 (Smithfield Premium Genetics Group, Rose Hill, NC). Duroc1 corresponds to the Duroc nucleus line P1 (Zumbach et al., 2007). The animals were raised on 2 commercial, 1,200-sow farrow-to-finish farms.
Farm 1 provided 12,771 records, whereas farm 2 contributed 10,785 records. Both farms were located in North Carolina about 8 km apart. The average age at slaughter was 200 d, and the average carcass weight was 89 kg. There was no evidence of a seasonal pattern for age at slaughter (Table 1). Typical and similar corn-soybean diets were used at both sites. Feeding was ad libitum for all animals.
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). A THI (NOAA, 1976) for each day (average of 24-h period) of the experimental period was calculated based on the formula:
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Because a single day of heat stress could be compensated by following cooler days, THI was calculated on a 7-d basis (rolling average) as the average of daily THI.
Quantification of Heat Load
Let heat load in a unit of time (h) be:
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where THI = average THI for a unit of time and THI0 = threshold of heat stress (upper critical temperature). Let tij be THI of animal i at age j. Assume that any effect of heat stress up to age p is compensated later and that growth after age p is constant, except being linearly affected by heat load. Then, the weight at time of slaughter s is:
where weightis = BW of animal i at slaughter and adgi = ADG of animal i. This can be simplified to:
where weighti0 = slaughter weight of animal i in the absence of heat load and Hi = total of heat load for that animal in the time interval from p+1 to s.
Daily heat load was defined as the number of degrees exceeding the threshold. The weekly heat load was defined as a mean of daily THI exceeding the threshold. The total heat load (H) was defined as the sum of weekly heat loads over the last n weeks of life, where n is a constant.
Both the threshold and the number n were selected based on the greatest coefficient of determination (R2) obtained with the following model:
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where yijklm = carcass weight on farm-year i, sex j, with slaughter age k standardized to 200 d, and heat load l. The fixed effects were FYi = farm-year, i = 1 to 4; Sj = sex, j = 1, 2; b1 = regression coefficient 1; agek = age at slaughter of the kth animal, k = 1 to 21,653; b2 = regression coefficient 2; Hl = heat load at slaughter date, l = 1 to 103; eijklm = the residual. This model could not include the day of slaughter because of confounding with heat load.
Seasonal Effects
Least squares means for year-month of slaughter and year-week of slaughter were calculated according to the model:
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where yijklm = carcass weight on farm-year-week or farm-year-month of slaughter date i, sex j, with slaughter age k standardized to 200 d, and birth litter l. The fixed effects were FYWi/FYMi = farm-year-week of slaughter date, i = 1 to 170/farm-year-month of slaughter date, i = 1 to 40; Sj = sex, j = 1, 2; b = regression coefficient; agek = age at slaughter of the kth animal, k = 1 to 21,653. The effects ll = birth litter, l = 1 to 4,305, and eijklm = residual were random. The number of observations per slaughter month and farm are shown in Table 1
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RESULTS AND DISCUSSION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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. The R2 ranged between 9.55 and 10.45% showing maxima for the period of 10 wk for all THI thresholds considered. The decrease to the right (more weeks considered) was slower than to the left (shorter period), and the optimum was broad (e.g., considering 9 to 13 wk of heat stress, R2 varied only about 0.2%). The curve with THI0 = 18°C was on the greatest level followed by THI0 = 16°C. At the maximum, R2 was similar for the different combinations. It differed less than 0.1% between THI0 = 18 and 16°C and about 0.2% between THI0 = 18 and 20°C.
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. The maxima of H were at the beginning of September in both years. They coincided for the 3 THI0 considered. The period of non-heat load (H = 0) was from January to April-May 2006. The lower the THI0, the earlier was the onset of H. For example, the onset of H in 2005 for THI0 = 20°C was in the beginning of June. At that time, H had reached 6 and 14% of the maximum, for THI0 = 18°C and THI0 = 16°C, respectively. The end of the heat stress period (H = 0) was at about the same time for all of the thresholds considered.
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. The onset of H was identical for the periods of 8, 10, and 12 wk. The maxima of the 2-wk longer periods were delayed by about 1 wk, whereas the offsets were prolonged by about 2 wk. In experimental studies with controlled heat regulation inside the stable, the upper critical temperature for voluntary feed intake in pigs was between 22.9 and 25.5°C (Huynh et al., 2005); Quiniou et al. (2001) and Le Bellego et al. (2002) considered 23 and 24°C, respectively, as thermoneutrality.
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The optimum THI0 was 18°C and was lower than thresholds found elsewhere. This could have been due to the definition of THI as a 24-h average, which was additionally averaged over a period of 1 wk. A 24-h average would be greater than a 2-d average during the peak of heat stress, when THI drops very slowly, and lower at the beginning or the end of summer, when nightly cooling occurs more quickly. Studies to identify the most suitable THI in dairy cattle used THI based on maximum temperature and minimum humidity and the average temperature and humidity (Ravagnolo et al., 2000) or THI with different weights for temperature and humidity for assessing losses in milk performance (Bohmanova et al., 2007).
The least squares means of carcass weight across the months of slaughter and the computed heat load for the 2 farms are presented in Figure 4. Weights for farm 1 had large fluctuations that appeared to be non-heat stress related. On both farms, drops in carcass weight occurred during August through November in 2005 and July through October in 2006. The difference in carcass weight between heat stress and non-heat stress months was about 6 kg. The 2 farms had an identical design and were located about 8 km apart. Differences between the farms were due to management and random factors that could not be accounted for in this study.
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presents the weights using combined data from the 2 farms and the H curve. The months with the lower carcass weights coincided with those of increased heat load. The onset and recovery from heat stress in 2005 seemed to occur 1 mo later than the increase and decrease of H, whereas in 2006, H and carcass weight were in agreement (see also Figure 6). In Figure 6, the carcass weights and H are shown on a weekly basis. Although the fluctuations between weeks of slaughter were large, the pattern of the curve coincided with the H curve. In Figure 7, a scatter plot of weekly carcass weights against H shows the tendency of decreasing carcass weights with increasing H.
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and Edwards et al. (2006).
Because humidity combined with high temperature affects pig growth (Huynh et al., 2005), THI seemed to be an appropriate variable for the definition of H. With the summation of THI above thermoneutrality, our definition of H accounted for both severity and duration of heat stress. The model did not allow for compensatory growth for heat stress occurring up to 10 wk before slaughter. This seemed to hold, because pigs were kept under commercial conditions where several stressors such as stocking rate or disease pressure are acting simultaneously. Kerr et al. (2005) reported greater live weight gain after the heat stress application for pigs housed individually at low density compared with pigs maintained at high density. The effect of disease challenge was reported to be more profound than that of heat stress (Kerr et al., 2003). The fluctuations in the carcass weight curves in this study indicated the existence of stressors different from heat. These occurred without any seasonal pattern throughout the study period. No seasonal pattern could be detected for mortality (unpublished data). Although the function of heat load provided only a limited fit to real carcass weights, the limitation was due to lack of data. A study of more accurate accounting for heat stress will be undertaken when more data with smaller weekly-monthly fluctuations become available.
In conclusion, reduced carcass weight in pigs due to heat stress can be quantified by the combined heat load during 2 to 3 mo preceding slaughter. In North Carolina, these reductions were present in weights of pigs slaughtered from July to November. The quantification can be used for determining the quality of management, properties of particular lines with respect to heat stress, and possibly in genetic selection toward heat tolerance.
1 Corresponding author: Birgit.zumbach{at}norsvin.no
Received for publication August 16, 2007. Accepted for publication April 21, 2008.
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LITERATURE CITED |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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This article has been cited by other articles:
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  B. Zumbach, I. Misztal, S. Tsuruta, J. P. Sanchez, M. Azain, W. Herring, J. Holl, T. Long, and M. Culbertson Genetic components of heat stress in finishing pigs: Parameter estimation J Anim Sci, September 1, 2008; 86(9): 2076 - 2081. [Abstract] [Full Text] [PDF]
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