- Email: [email protected]
Assessment of finishing beef cattle mortality in a sustainable farming perspective
Livestock Science 178 (2015) 313–316
Contents lists available at ScienceDirect
Livestock Science journal homepage: www.elsevier.com/locate/livsci
Short communication
Assessment of finishing beef cattle mortality in a sustainable farming perspective Clelia Rumor, Marta Brscic n, Barbara Contiero, Giulio Cozzi, Flaviana Gottardo Department of Animal Medicine, Production and Health, University of Padova, Viale dell’Università 16, 35020 Legnaro (PD), Italy
art ic l e i nf o
a b s t r a c t
Article history: Received 19 January 2015 Received in revised form 15 June 2015 Accepted 16 June 2015
Cattle mortality has a relevant economic and environmental impact but it has been scarcely investigated in finishing beef cattle farms. Aim of this study was to investigate mortality rate in 45 intensive beef cattle farms located in North-Eastern Italy from 2010 to 2013 and to evaluate potential risk factors affecting it. Information from the Italian National Cattle Movement database, as source of mortality data, were crossed with descriptors of barn features and farm management gathered by an on-farm survey to identify factors influencing mortality at farm level, which could be of direct utility for the farmers to reduce cattle losses. Results showed an overall average mortality rate in the 4-year period of 1.4% ranging from 0% to 5.3%. Mortality occurred within the first half of the finishing period, on average 3.4 months after the arrival at the fattening unit. A multivariate regression model showed that mortality was affected by breed (P¼ 0.020) and by floor type as trend (P ¼0.083). Pure Charolaise (Odds ratio¼ 1.70, 95% Confidence interval¼1.11-2.59; P o0.005) and Limousine breeds (Odds ratio¼1.96, 95% Confidence interval¼1.26–3.05; Po 0.005) showed higher odds for mortality compared to other beef breeds or crosses. Bulls housed on fully slatted floor showed higher odds compared to those on deep litter (Odds ratio¼ 1.45, 95% Confidence interval¼1.01–2.08; Po 0.005). Season at arrival affected mortality (P ¼0.013), with summer (Odds ratio¼1.45, 95% Confidence interval¼1.14–1.84; P o 0.005) and autumn (Odds ratio¼ 1.74, 95% Confidence interval¼ 1.27–2.38; P o0.005) being the most critical seasons. Differently from expected, space allowance and barn features such as presence/absence of roof insulation and/or ventilation devices as well as the managerial choice of separating or not newly arrived bulls in a dedicated receiving area for quarantine did not affect mortality. Based on findings from this study, it could be concluded that the avoidance of rearing specialized French beef breeds, of using fully slatted floor and of importing young cattle during warm seasons could be considered as preventive measures to reduce the risk of mortality in intensive beef cattle farms. & 2015 Elsevier B.V. All rights reserved.
Keywords: Beef cattle Mortality Risk factor
1. Introduction It is known that cattle mortality varies considerably between countries, herds within a region, and among years. Mortality of dairy cows and of replacement cattle has been investigated and several risk factors have been identified including characteristics of the housing environment (Crescio et al., 2010; Morignat et al., 2014), herd management (Alvåsen et al., 2014; Raboisson et al., 2014), and health management (Gulliksen et al., 2009; Walker et al., 2012). On the contrary, there is a lack of information concerning mortality rates of finishing beef cattle and the few existing literature often refers to data from large US and Canadian feedlots (Cusack et al., 2007; EFSA, 2012; Loneragan et al., 2001), which are rather different from the intensive indoors systems used in some n
Corresponding author. Fax: þ 39 049 8272662. E-mail address: [email protected] (M. Brscic).
http://dx.doi.org/10.1016/j.livsci.2015.06.013 1871-1413/& 2015 Elsevier B.V. All rights reserved.
European countries (SCAHAW, 2001). Studies regarding the factors influencing beef cattle mortality report climate and housing conditions, feeding, and management of the receiving of newly imported bulls as the main critical points (Callan and Garry, 2002; Gottardo et al., 2009; Morignat et al., 2014; SCAHAW, 2001). According to Béranger (1986) mortality decreases as air volume and space allowance per bull increase. Bulls housed on fully slatted floor have a higher mortality than those on straw bedding with the same space allowance (SCAHAW, 2001). Inappropriate or unbalanced feeding results in metabolic disorders that lead to up to 42% of the mortality in intensively fed beef cattle (Béranger, 1986). Knowledge of the factors influencing mortality would give opportunities to improve the health status of beef cattle and consequently to reduce losses. It would be particularly important to minimize beef cattle mortality at a late state of the finishing to limit economic losses for the farmers and environmental impact. Italy is the third cattle producer in the 28-EU (10.6%) after France (24.6%) and Germany (12.3%), with more than 2.7 million of
314
C. Rumor et al. / Livestock Science 178 (2015) 313–316
cattle slaughtered in 2013 (European Statistics of DG Agriculture). Veneto is the first beef producing region at national level, with 950 farms and 420,000 heads reared in 2014. Beef cattle production is largely based on the finishing of imported young bulls and heifers (mainly from France, Ireland and eastern European countries). The Italian Official National Cattle Movement database gathers information about cattle herds (identification number, location) and animal movements (gender, breed, date of birth, date and reason of the movement). By processing this database it is possible to assess, besides mortality rate, the effects of year, season, age, farm size, and breed on cattle mortality but these information are not made useful for the farmers in order to reduce the mortality rate of their herds. Rationale behind the current study was that crossing information from the national database with data regarding barn features and farm management would allow to identify factors influencing mortality at farm level. Aim of the current study was to estimate mortality rates and to investigate risk factors in 45 intensive beef cattle farms in the Veneto region in North-Eastern Italy.
2. Material and methods The study involved 45 intensive beef cattle farms in the lowland of Veneto region part of the same Breeders’ Association UNICARVE (Padova, Italy) that were visited once during 2013. A questionnaire was submitted to each farmer to gather data regarding farm size, management and facilities. Having a single farm more barns with different characteristics (type of barn, floor, ventilation, roof insulation) a specific housing condition was ascribed to the farm if prevalent involving the majority of bulls reared. Data were collected from the Official National Cattle Movement database. For each farm, number of bulls reared (bulls exiting the farm from January 1st to December 31st of each year), slaughtered, and dead were collected for the years 2010, 2011, 2012 and 2013 in order to calculate mortality rates as proportion of dead animals over the total number of animals reared at farm level yearly. Mortality rate excluded early culled animals that for any reason did not complete the regular finishing cycle. For each bull, breed, gender, date of birth, date of arrival at the farm, and date of slaughter/death were also recorded. Characteristics of farms and number of farms per each classification level are reported in Table 1. Farm size in terms of total number of bulls reared per year varied from about 50 to over 5000 bulls with an average of 718 (SD 7951), 683 (SD 7921), 681 (SD 7913), and 675 (SD 7888) bulls in 2010, 2011, 2012, and 2013, respectively. Mainly young bulls of French breeds (36.2% Charolaise, 23.4% Limousine, 40.4% other meat type French breeds and crossbreds) were fattened indoors, with no access (in 43 of the 45 farms) to an outdoor area. The proportion of females was 20.3% (SD 731.9). Space allowance was on average 3.2 m2/bull (SD 70.7) on slatted floor and 4.1 m2/bull (SD 70.8) on deep litter. Data were statistically analyzed using SAS/STAT 9.3 (SAS Institute Inc., Cary NC) and differences were considered significant for P r0.05 and showing a trend of significance for P r0.1. Data were submitted to descriptive statistics to assess location parameters. Mortality rates per each year were submitted to Spearman rank correlations to test associations among them. Mortality (4 records/farm with year repeated) was the dependent variable while factors related to farm characteristics were considered as independent variables. All factors were at first submitted to univariate logistic regression analysis to test whether they tended to be associated to mortality and if not (P 40.1) they were excluded from further analysis. Based on the results of this analysis, factors were included in the building of a multivariate generalized linear
Table 1 Percentage of farms per each descriptor. Descriptor Size, number of cattle reared per year o 300 300–500 501–999 Z 1000 Prevalent breeda Charolaise Limousine Otherb Percentage of females o 10% 10–90% 4 90% Type of barn Opened Closed Presence of separate receiving area for quarantineof newly arrived animals No Yes Roof insulation No Yes Presence of ventilation No Yes Prevalent type of floor Fully slatted floor Concrete slats Perforated floor Rubber covered/coated Deep litter Flat Sloped Both types present at the farm Space allowance, m2/bullc o3 3–4 44 Number of drinkers/penc 1 drinker serving 2 pens At least 1 drinker/pen a b c
% of farms
31.1 33.3 22.2 13.3 42.2 20.0 37.8 57.8 31.1 11.1 35.6 64.4
20.7 79.3 44.2 55.8 34.9 65.1 37.8 88.5 7.7 3.8 62.2 40.7 33.3 25.9 20.0 42.2 37.8 82.6 17.4
The majority of bulls reared in 2012. Meat crossbreds and other meat type French breeds. Average at farm level.
model using ProcGenmod after testing multicollinearity among them. In order to study the effect of season at arrival and of season of death on mortality, two additional separate datasets were created. In the first one the dependent variable was the proportion of bulls dead according to the season at arrival calculated over the total number of bulls reared per year (4 records/farm per year for a total of 16 records/farm). In the second one, the dependent variable was the proportion of bulls dead in each season calculated over the total number of bulls dead per year (4 records/farm per year for a total of 16 records/farm). These data were submitted to statistical analysis using a multivariate generalized linear model with ProcGenmod that considered the effect of season at housing or of season of death, and farm within year as repeated option. For dead bulls, the moment of death during the fattening cycle (months from arrival) was calculated by subtracting age at arrival from age at death at individual level.
3. Results and discussion Results of the study showed that the majority of the animals completed the fattening cycle being regularly slaughtered on average after 8.2 (SD 71.5) months. Mortality rates for years 2010–
C. Rumor et al. / Livestock Science 178 (2015) 313–316
Table 2 Descriptive statistics of mortality rates (%) in 45 beef cattle farms of the Veneto Region in the four years considered in the study.
Table 3 Factors influencing prevalence of mortality. Factor1
Year
2010 2011 2012 2013
Number of records
39 43 44 42
Average
SD
Median
Minimum
Maximum
1.1 1.4 1.4 1.7
0.8 1.2 1.3 1.6
1.1 1.1 1.2 1.4
0.0 0.0 0.0 0.0
3.4 4.9 5.0 8.8
95% Confidence Interval
P-value
Prevalent type of floor1 Fully slatted floor Deep litter Prevalent cattle breed1 Charolaise Limousine Other breeds/crosses
Min
Max
1.26a 0.95b
1.45 1.01 – –
2.08 –
1.60a 1.84a 0.94b
1.70 1.11 1.96 1.26 – –
2.59 3.05 –
0.083
0.020
a,b Different superscript letters within each factor indicate significant differences for Po 0.05.
20 % bulls dead
Prevalence OR
Mortality rate, %
25
1 The generalized linear model considered the effects of prevalent type of floor, prevalent cattle breed, and prevalent type of floor prevalent cattle breed (P 40.05) as fixed effects, and farm within year as repeated option.
15 10 5 0
315
1st
2nd
3rd
4th 5th 6th month from arrival
7th
> 7th
Fig. 1. Distribution of the percentage of bulls dead within month from arrival over the total number of bulls dead.
2013 were similar (Table 2) and they were significantly correlated (rs 40.41; Pr 0.012). Animal death occurred after on average 3.4 (SD 73.3) months from arrival at the farm (median value of 2.5 months) at an average age of 13.2 (SD 7 5.5) months. Animals arrived at the farms at an average age of 10.4 (SD 71.6) months. Mortality per each month from arrival was displayed in Fig. 1. The fact that mortality occurred mainly within the first half of the finishing cycle could be linked to the greater susceptibility of newly arrived animals (Callan and Garry, 2002; Gottardo et al., 2009). Incoming bulls undergo highly stressful situations due to transport and change of climate and housing conditions which may predispose them to diseases outbreak that can lead to mortality (Stec and Mochol, 2003; Taylor et al., 2010). Although mortality should be minimized, it could be speculated that early death has a less negative impact on farm economics and environment than death at a late stage of fattening: every day on feed before death represents an additional feeding cost and more emissions from excreta and enteric fermentations. Factors such as farm size (P ¼0.052), prevalent type of floor (P ¼0.102), roof insulation (P ¼ 0.056), presence of ventilation (P ¼0.008), number of drinkers/pen (P ¼0.002), prevalent breed (P ¼0.002), and class of percentage of females (P ¼0.034) that were associated to mortality for P o0.10 in the one-way analysis of variance were tested for multicollinearity and were included stepwisely in the multivariate regression model. Concerning the barn facilities, the risk for animals to die was higher in bulls housed on fully slatted floor compared to those on deep litter (Table 3), which is in accordance with previous studies (Béranger, 1986; SCAHAW, 2001). Breed was found to be a risk factor for mortality, with bulls belonging to a pure Charolaise or Limousine breed having a higher risk to die during the finishing compared to other French meat type breeds or crosses (Table 3). Cusack et al. (2007) found a breed effect on mortality in feedlots but comparisons with the current study are rather unrealistic. A possible hypothesis is that genetic selection of specialized French beef breeds has weakened their coping capacity with the stressful condition of the intensive fattening units making them more susceptible to
disease compared to crosses and more rustic French beef genotypes. Season at death did not affect mortality, while the arrival of bulls at the farm particularly during summer and autumn increased significantly the risk of mortality compared to spring (Table 4). This might be related to heat stress, as it is known that cattle suffer the exposure to high temperatures and relative humidity (Cozzi et al., 2009; SCAHAW, 2001). It is likely that long onroad transportation and the following introduction into the new facilities during the hot season negatively affected cattle coping strategies to the new environment with detrimental consequences. The prevalence of mortality of bulls that were introduced in the farms during winter was not significantly different from that of bulls that arrived during spring likely due to the mild winters of the lowland of Veneto where all farms were located. These results should be taken into consideration by beef farmers and specific preventive measures and practices should be established to reduce the risk of mortality among newly arrived bulls. Importing cattle during summer should be minimized or at least, as suggested by Morignat et al. (2014), transport of cattle during the hottest hours of the day should be avoided. At arrival, animals should be provided with hydrating saline solutions and housed in barns equipped with systems that allow to control heat stress such as roof insulation and barn conditioning with shading, ventilation and cooling systems (Callan and Garry, 2002). Factors such as type of barn, access to outdoor paddock, space allowance, type of slatted floor and of deep litter, and age at arrival were not significantly associated to mortality and they were not included in further analysis of variance. The absence of a separate receiving area for newly arrived animals was reported to be a risk factor for the spreading of infectious diseases (Mee et al., 2012) that can lead to death (Ribble et al., 1995) but this relationship was not found in the current study. Differently from expected, also roof Table 4 Effect of season at arrival on mortality. Factora
Season of arrival Spring Summer Autumn Winter a,b
Prevalence
OR
95% Confidence Interval Min
Max
– 1.14 1.27 0.97
– 1.84 2.38 1.83
P-value
0.013 0.24b 0.35a 0.42a 0.32ab
– 1.45 1.74 1.33
Different superscript letters indicate significant differences for Po 0.05.
a The generalized linear model considered the effect of season of arrival, and farm within year as repeated option.
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C. Rumor et al. / Livestock Science 178 (2015) 313–316
insulation and presence of ventilation did not affect mortality even though they were previously recognized as effective tools to improve beef cattle welfare (Cozzi et al., 2009). Another unexpected result compared to the existing literature (SCAHAW, 2001) regarded the lack of association between space allowance and mortality. A possible explanation for this outcome may arise from a methodological shortcoming in the measure of the space allowance that was recorded as an average at farm level since 17 farms presented more than one barn with different flooring and housing conditions. This approach made it not possible to infer on which barn the single dead bull was housed.
4. Conclusions The association of information regarding features and management of beef cattle farms with mortality rate data to assess risk factors associated with mortality has shown to be a way to help farmers to reduce cattle losses improving farm profitability and environmental sustainability. Findings from this study suggest that, under the intensive rearing conditions of the Italian beef farms, the risk of cattle mortality could be lowered by finishing bulls of French beef crosses and more rustic genotypes and by avoiding fully slatted flooring systems and arrival of cattle during the hot season.
Conflict of interest None.
Acknowledgments This research was funded by the Veneto Region within the “GHGE project” of the Rural Development Program 2007–2013 and by a grant of the University of Padova within the EX 60% research funds. Authors acknowledge Unicarve Association for technical support in data collection.
References Alvåsen, K., Roth, A., Jansson Mörk, M., Hallén Sandgren, C., Thomsen, P.T., Emanuelson, U., 2014. Farm characteristics related to on-farm cow mortality in dairy herds: a questionnaire study. Animal 1, 1–8. C. Béranger, Pathologie des jeunes bovins à l’engrais, in: D. Micol (Ed.) Production de Viande Bovine, 1986, pp. 401–416. Callan, R.J., Garry, F.B., 2002. Biosecurity and bovine respiratory disease. Vet. Clin. Food Anim. 18, 57–77. Cozzi, G., Brscic, M., Gottardo, F., 2009. Main critical factors affecting the welfare of beef cattle and veal calves raised under intensive rearing systems in Italy: a review. Ital. J. Anim. Sci. 8 (Suppl. 1), S67–S80. Crescio, M.I., Forastiere, F., Maurella, C., Ingravalle, F., Ru, G., 2010. Heat-related mortality in dairy cattle: a case crossover study. Prev. Vet. Med. 97, 191–197. Cusack, P.M.V., McMeniman, N.P., Lean, I.J., 2007. Feedlot entry characteristics and climate: their relationship with cattle growth rate, bovine respiratory disease and mortality. Aust. Vet. J. 85, 311–316. EFSA, 2012. Panel on Animal Health and Welfare (AHAW); Scientific Opinion on the welfare of cattle kept for beef production and the welfare in intensive calf farming systems. EFSA J. 10 (5), 2669. Gottardo, F., Brscic, M., Contiero, B., Cozzi, G., Andrighetto, I., 2009. Towards the creation of a welfare assessment system in intensive beef cattle farms. Ital. J. Anim. Sci. 8 (Suppl. 1), S325–S342. Gulliksen, S., Lie, K., Loken, T., Osteras, O., 2009. Calf mortality in Norwegian dairy herds. J. Dairy Sci. 92, 2782–2795. Loneragan, G.H., Dargatz, D.A., Morley, P.S., Smith, M.A., 2001. Trends in mortality ratios among cattle in US feedlots. J. Am. Vet. Med. Assoc. 219, 1122–1127. Mee, J.F., Geraghty, T., O’Neill, R., More, S.J., 2012. Bioexclusion of diseases from dairy and beef farms: risks of introducing infectious agents and risk reduction strategies. Vet. J. 194, 143–150. Morignat, E., Perrin, J.-B., Gay, E., Vinard, J.-L., Calavas, D., Hénaux, V., 2014. Assessment of the impact of the 2003 and 2006 heat waves on cattle mortality in France. PLoS One 9 (3), e93176. Raboisson, D., Maigne, E., Sans, P., Allaire, G., Cahuzac, E., 2014. Factors influencing dairy calf and replacement heifer mortality in France. J Dairy Sci. 97, 202–211. Ribble, C.S., Meek, A.H., Shewen, P.E., Jim, G.K., Guichon, P.T., 1995. Effect of transportation on fatal fibrinous pneumonia and shrinkage in calves arriving at a large feedlot. J. Am. Vet. Med. Assoc. 207, 612–615. SCAHAW-Scientific Committee on Animal Health and Animal Welfare (2001), The Welfare of Cattle kept for Beef Production, 25 April 2001, SANCO.C.2/AH/R22/ 2000. Stec, A., Mochol, J., 2003. Risk factors and their importance in the etiology of bovine respiratory disease complex in calves and young beef cattle. Med. Weter 59 (8), 673–678. Taylor, J.D., Fulton, R.W., Lehenbauer, T.W., Step, D.L., Confer, A.W., 2010. The epidemiology of bovine respiratory disease: what is the evidence for predisposing factors. Can. Vet. J. 51, 1095–1102. Walker, W.L., Epperson, W.B., Wittum, T.E., Lord, L.K., Rajala-Schultz, P.J., Lakritz, J., 2012. Characteristics of dairy calf ranches: morbidity, mortality, antibiotic use practices, and biosecurity and biocontainment practices. J. Dairy Sci. 95, 2204–2214.
Contents lists available at ScienceDirect
Livestock Science journal homepage: www.elsevier.com/locate/livsci
Short communication
Assessment of finishing beef cattle mortality in a sustainable farming perspective Clelia Rumor, Marta Brscic n, Barbara Contiero, Giulio Cozzi, Flaviana Gottardo Department of Animal Medicine, Production and Health, University of Padova, Viale dell’Università 16, 35020 Legnaro (PD), Italy
art ic l e i nf o
a b s t r a c t
Article history: Received 19 January 2015 Received in revised form 15 June 2015 Accepted 16 June 2015
Cattle mortality has a relevant economic and environmental impact but it has been scarcely investigated in finishing beef cattle farms. Aim of this study was to investigate mortality rate in 45 intensive beef cattle farms located in North-Eastern Italy from 2010 to 2013 and to evaluate potential risk factors affecting it. Information from the Italian National Cattle Movement database, as source of mortality data, were crossed with descriptors of barn features and farm management gathered by an on-farm survey to identify factors influencing mortality at farm level, which could be of direct utility for the farmers to reduce cattle losses. Results showed an overall average mortality rate in the 4-year period of 1.4% ranging from 0% to 5.3%. Mortality occurred within the first half of the finishing period, on average 3.4 months after the arrival at the fattening unit. A multivariate regression model showed that mortality was affected by breed (P¼ 0.020) and by floor type as trend (P ¼0.083). Pure Charolaise (Odds ratio¼ 1.70, 95% Confidence interval¼1.11-2.59; P o0.005) and Limousine breeds (Odds ratio¼1.96, 95% Confidence interval¼1.26–3.05; Po 0.005) showed higher odds for mortality compared to other beef breeds or crosses. Bulls housed on fully slatted floor showed higher odds compared to those on deep litter (Odds ratio¼ 1.45, 95% Confidence interval¼1.01–2.08; Po 0.005). Season at arrival affected mortality (P ¼0.013), with summer (Odds ratio¼1.45, 95% Confidence interval¼1.14–1.84; P o 0.005) and autumn (Odds ratio¼ 1.74, 95% Confidence interval¼ 1.27–2.38; P o0.005) being the most critical seasons. Differently from expected, space allowance and barn features such as presence/absence of roof insulation and/or ventilation devices as well as the managerial choice of separating or not newly arrived bulls in a dedicated receiving area for quarantine did not affect mortality. Based on findings from this study, it could be concluded that the avoidance of rearing specialized French beef breeds, of using fully slatted floor and of importing young cattle during warm seasons could be considered as preventive measures to reduce the risk of mortality in intensive beef cattle farms. & 2015 Elsevier B.V. All rights reserved.
Keywords: Beef cattle Mortality Risk factor
1. Introduction It is known that cattle mortality varies considerably between countries, herds within a region, and among years. Mortality of dairy cows and of replacement cattle has been investigated and several risk factors have been identified including characteristics of the housing environment (Crescio et al., 2010; Morignat et al., 2014), herd management (Alvåsen et al., 2014; Raboisson et al., 2014), and health management (Gulliksen et al., 2009; Walker et al., 2012). On the contrary, there is a lack of information concerning mortality rates of finishing beef cattle and the few existing literature often refers to data from large US and Canadian feedlots (Cusack et al., 2007; EFSA, 2012; Loneragan et al., 2001), which are rather different from the intensive indoors systems used in some n
Corresponding author. Fax: þ 39 049 8272662. E-mail address: [email protected] (M. Brscic).
http://dx.doi.org/10.1016/j.livsci.2015.06.013 1871-1413/& 2015 Elsevier B.V. All rights reserved.
European countries (SCAHAW, 2001). Studies regarding the factors influencing beef cattle mortality report climate and housing conditions, feeding, and management of the receiving of newly imported bulls as the main critical points (Callan and Garry, 2002; Gottardo et al., 2009; Morignat et al., 2014; SCAHAW, 2001). According to Béranger (1986) mortality decreases as air volume and space allowance per bull increase. Bulls housed on fully slatted floor have a higher mortality than those on straw bedding with the same space allowance (SCAHAW, 2001). Inappropriate or unbalanced feeding results in metabolic disorders that lead to up to 42% of the mortality in intensively fed beef cattle (Béranger, 1986). Knowledge of the factors influencing mortality would give opportunities to improve the health status of beef cattle and consequently to reduce losses. It would be particularly important to minimize beef cattle mortality at a late state of the finishing to limit economic losses for the farmers and environmental impact. Italy is the third cattle producer in the 28-EU (10.6%) after France (24.6%) and Germany (12.3%), with more than 2.7 million of
314
C. Rumor et al. / Livestock Science 178 (2015) 313–316
cattle slaughtered in 2013 (European Statistics of DG Agriculture). Veneto is the first beef producing region at national level, with 950 farms and 420,000 heads reared in 2014. Beef cattle production is largely based on the finishing of imported young bulls and heifers (mainly from France, Ireland and eastern European countries). The Italian Official National Cattle Movement database gathers information about cattle herds (identification number, location) and animal movements (gender, breed, date of birth, date and reason of the movement). By processing this database it is possible to assess, besides mortality rate, the effects of year, season, age, farm size, and breed on cattle mortality but these information are not made useful for the farmers in order to reduce the mortality rate of their herds. Rationale behind the current study was that crossing information from the national database with data regarding barn features and farm management would allow to identify factors influencing mortality at farm level. Aim of the current study was to estimate mortality rates and to investigate risk factors in 45 intensive beef cattle farms in the Veneto region in North-Eastern Italy.
2. Material and methods The study involved 45 intensive beef cattle farms in the lowland of Veneto region part of the same Breeders’ Association UNICARVE (Padova, Italy) that were visited once during 2013. A questionnaire was submitted to each farmer to gather data regarding farm size, management and facilities. Having a single farm more barns with different characteristics (type of barn, floor, ventilation, roof insulation) a specific housing condition was ascribed to the farm if prevalent involving the majority of bulls reared. Data were collected from the Official National Cattle Movement database. For each farm, number of bulls reared (bulls exiting the farm from January 1st to December 31st of each year), slaughtered, and dead were collected for the years 2010, 2011, 2012 and 2013 in order to calculate mortality rates as proportion of dead animals over the total number of animals reared at farm level yearly. Mortality rate excluded early culled animals that for any reason did not complete the regular finishing cycle. For each bull, breed, gender, date of birth, date of arrival at the farm, and date of slaughter/death were also recorded. Characteristics of farms and number of farms per each classification level are reported in Table 1. Farm size in terms of total number of bulls reared per year varied from about 50 to over 5000 bulls with an average of 718 (SD 7951), 683 (SD 7921), 681 (SD 7913), and 675 (SD 7888) bulls in 2010, 2011, 2012, and 2013, respectively. Mainly young bulls of French breeds (36.2% Charolaise, 23.4% Limousine, 40.4% other meat type French breeds and crossbreds) were fattened indoors, with no access (in 43 of the 45 farms) to an outdoor area. The proportion of females was 20.3% (SD 731.9). Space allowance was on average 3.2 m2/bull (SD 70.7) on slatted floor and 4.1 m2/bull (SD 70.8) on deep litter. Data were statistically analyzed using SAS/STAT 9.3 (SAS Institute Inc., Cary NC) and differences were considered significant for P r0.05 and showing a trend of significance for P r0.1. Data were submitted to descriptive statistics to assess location parameters. Mortality rates per each year were submitted to Spearman rank correlations to test associations among them. Mortality (4 records/farm with year repeated) was the dependent variable while factors related to farm characteristics were considered as independent variables. All factors were at first submitted to univariate logistic regression analysis to test whether they tended to be associated to mortality and if not (P 40.1) they were excluded from further analysis. Based on the results of this analysis, factors were included in the building of a multivariate generalized linear
Table 1 Percentage of farms per each descriptor. Descriptor Size, number of cattle reared per year o 300 300–500 501–999 Z 1000 Prevalent breeda Charolaise Limousine Otherb Percentage of females o 10% 10–90% 4 90% Type of barn Opened Closed Presence of separate receiving area for quarantineof newly arrived animals No Yes Roof insulation No Yes Presence of ventilation No Yes Prevalent type of floor Fully slatted floor Concrete slats Perforated floor Rubber covered/coated Deep litter Flat Sloped Both types present at the farm Space allowance, m2/bullc o3 3–4 44 Number of drinkers/penc 1 drinker serving 2 pens At least 1 drinker/pen a b c
% of farms
31.1 33.3 22.2 13.3 42.2 20.0 37.8 57.8 31.1 11.1 35.6 64.4
20.7 79.3 44.2 55.8 34.9 65.1 37.8 88.5 7.7 3.8 62.2 40.7 33.3 25.9 20.0 42.2 37.8 82.6 17.4
The majority of bulls reared in 2012. Meat crossbreds and other meat type French breeds. Average at farm level.
model using ProcGenmod after testing multicollinearity among them. In order to study the effect of season at arrival and of season of death on mortality, two additional separate datasets were created. In the first one the dependent variable was the proportion of bulls dead according to the season at arrival calculated over the total number of bulls reared per year (4 records/farm per year for a total of 16 records/farm). In the second one, the dependent variable was the proportion of bulls dead in each season calculated over the total number of bulls dead per year (4 records/farm per year for a total of 16 records/farm). These data were submitted to statistical analysis using a multivariate generalized linear model with ProcGenmod that considered the effect of season at housing or of season of death, and farm within year as repeated option. For dead bulls, the moment of death during the fattening cycle (months from arrival) was calculated by subtracting age at arrival from age at death at individual level.
3. Results and discussion Results of the study showed that the majority of the animals completed the fattening cycle being regularly slaughtered on average after 8.2 (SD 71.5) months. Mortality rates for years 2010–
C. Rumor et al. / Livestock Science 178 (2015) 313–316
Table 2 Descriptive statistics of mortality rates (%) in 45 beef cattle farms of the Veneto Region in the four years considered in the study.
Table 3 Factors influencing prevalence of mortality. Factor1
Year
2010 2011 2012 2013
Number of records
39 43 44 42
Average
SD
Median
Minimum
Maximum
1.1 1.4 1.4 1.7
0.8 1.2 1.3 1.6
1.1 1.1 1.2 1.4
0.0 0.0 0.0 0.0
3.4 4.9 5.0 8.8
95% Confidence Interval
P-value
Prevalent type of floor1 Fully slatted floor Deep litter Prevalent cattle breed1 Charolaise Limousine Other breeds/crosses
Min
Max
1.26a 0.95b
1.45 1.01 – –
2.08 –
1.60a 1.84a 0.94b
1.70 1.11 1.96 1.26 – –
2.59 3.05 –
0.083
0.020
a,b Different superscript letters within each factor indicate significant differences for Po 0.05.
20 % bulls dead
Prevalence OR
Mortality rate, %
25
1 The generalized linear model considered the effects of prevalent type of floor, prevalent cattle breed, and prevalent type of floor prevalent cattle breed (P 40.05) as fixed effects, and farm within year as repeated option.
15 10 5 0
315
1st
2nd
3rd
4th 5th 6th month from arrival
7th
> 7th
Fig. 1. Distribution of the percentage of bulls dead within month from arrival over the total number of bulls dead.
2013 were similar (Table 2) and they were significantly correlated (rs 40.41; Pr 0.012). Animal death occurred after on average 3.4 (SD 73.3) months from arrival at the farm (median value of 2.5 months) at an average age of 13.2 (SD 7 5.5) months. Animals arrived at the farms at an average age of 10.4 (SD 71.6) months. Mortality per each month from arrival was displayed in Fig. 1. The fact that mortality occurred mainly within the first half of the finishing cycle could be linked to the greater susceptibility of newly arrived animals (Callan and Garry, 2002; Gottardo et al., 2009). Incoming bulls undergo highly stressful situations due to transport and change of climate and housing conditions which may predispose them to diseases outbreak that can lead to mortality (Stec and Mochol, 2003; Taylor et al., 2010). Although mortality should be minimized, it could be speculated that early death has a less negative impact on farm economics and environment than death at a late stage of fattening: every day on feed before death represents an additional feeding cost and more emissions from excreta and enteric fermentations. Factors such as farm size (P ¼0.052), prevalent type of floor (P ¼0.102), roof insulation (P ¼ 0.056), presence of ventilation (P ¼0.008), number of drinkers/pen (P ¼0.002), prevalent breed (P ¼0.002), and class of percentage of females (P ¼0.034) that were associated to mortality for P o0.10 in the one-way analysis of variance were tested for multicollinearity and were included stepwisely in the multivariate regression model. Concerning the barn facilities, the risk for animals to die was higher in bulls housed on fully slatted floor compared to those on deep litter (Table 3), which is in accordance with previous studies (Béranger, 1986; SCAHAW, 2001). Breed was found to be a risk factor for mortality, with bulls belonging to a pure Charolaise or Limousine breed having a higher risk to die during the finishing compared to other French meat type breeds or crosses (Table 3). Cusack et al. (2007) found a breed effect on mortality in feedlots but comparisons with the current study are rather unrealistic. A possible hypothesis is that genetic selection of specialized French beef breeds has weakened their coping capacity with the stressful condition of the intensive fattening units making them more susceptible to
disease compared to crosses and more rustic French beef genotypes. Season at death did not affect mortality, while the arrival of bulls at the farm particularly during summer and autumn increased significantly the risk of mortality compared to spring (Table 4). This might be related to heat stress, as it is known that cattle suffer the exposure to high temperatures and relative humidity (Cozzi et al., 2009; SCAHAW, 2001). It is likely that long onroad transportation and the following introduction into the new facilities during the hot season negatively affected cattle coping strategies to the new environment with detrimental consequences. The prevalence of mortality of bulls that were introduced in the farms during winter was not significantly different from that of bulls that arrived during spring likely due to the mild winters of the lowland of Veneto where all farms were located. These results should be taken into consideration by beef farmers and specific preventive measures and practices should be established to reduce the risk of mortality among newly arrived bulls. Importing cattle during summer should be minimized or at least, as suggested by Morignat et al. (2014), transport of cattle during the hottest hours of the day should be avoided. At arrival, animals should be provided with hydrating saline solutions and housed in barns equipped with systems that allow to control heat stress such as roof insulation and barn conditioning with shading, ventilation and cooling systems (Callan and Garry, 2002). Factors such as type of barn, access to outdoor paddock, space allowance, type of slatted floor and of deep litter, and age at arrival were not significantly associated to mortality and they were not included in further analysis of variance. The absence of a separate receiving area for newly arrived animals was reported to be a risk factor for the spreading of infectious diseases (Mee et al., 2012) that can lead to death (Ribble et al., 1995) but this relationship was not found in the current study. Differently from expected, also roof Table 4 Effect of season at arrival on mortality. Factora
Season of arrival Spring Summer Autumn Winter a,b
Prevalence
OR
95% Confidence Interval Min
Max
– 1.14 1.27 0.97
– 1.84 2.38 1.83
P-value
0.013 0.24b 0.35a 0.42a 0.32ab
– 1.45 1.74 1.33
Different superscript letters indicate significant differences for Po 0.05.
a The generalized linear model considered the effect of season of arrival, and farm within year as repeated option.
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C. Rumor et al. / Livestock Science 178 (2015) 313–316
insulation and presence of ventilation did not affect mortality even though they were previously recognized as effective tools to improve beef cattle welfare (Cozzi et al., 2009). Another unexpected result compared to the existing literature (SCAHAW, 2001) regarded the lack of association between space allowance and mortality. A possible explanation for this outcome may arise from a methodological shortcoming in the measure of the space allowance that was recorded as an average at farm level since 17 farms presented more than one barn with different flooring and housing conditions. This approach made it not possible to infer on which barn the single dead bull was housed.
4. Conclusions The association of information regarding features and management of beef cattle farms with mortality rate data to assess risk factors associated with mortality has shown to be a way to help farmers to reduce cattle losses improving farm profitability and environmental sustainability. Findings from this study suggest that, under the intensive rearing conditions of the Italian beef farms, the risk of cattle mortality could be lowered by finishing bulls of French beef crosses and more rustic genotypes and by avoiding fully slatted flooring systems and arrival of cattle during the hot season.
Conflict of interest None.
Acknowledgments This research was funded by the Veneto Region within the “GHGE project” of the Rural Development Program 2007–2013 and by a grant of the University of Padova within the EX 60% research funds. Authors acknowledge Unicarve Association for technical support in data collection.
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