Next Article in Journal
Organic Ingredients as Alternative Protein Sources in the Diet of Juvenile Organic Seabass (Dicentrarchus labrax)
Next Article in Special Issue
Molecular Diagnosis of Footrot and Contagious Ovine Digital Dermatitis in Small Ruminants in the Iberian Peninsula
Previous Article in Journal
Pain Assessment in Goat Kids: Focus on Disbudding
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Animals
Volume 13
Issue 24
10.3390/ani13243815
animals-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

Environmental and Breed Risk Factors Associated with the Prevalence of Subclinical Mastitis in Dual-Purpose Livestock Systems in the Arauca Floodplain Savannah, Colombian Orinoquia

by
Arcesio Salamanca-Carreño
1,*,
Mauricio Vélez-Terranova
2,
Diana Patricia Barajas-Pardo
1,
Rita Tamasaukas
3,
Raúl Jáuregui-Jiménez
4 and
Pere M. Parés-Casanova
5
1
Facultad de Medicina Veterinaria y Zootecnia, Universidad Cooperativa de Colombia, Villavicencio 500001, Colombia
2
Facultad de Ciencias Agropecuarias, Universidad Nacional de Colombia, Palmira 763531, Colombia
3
Unidad de Biotecnología, LABIPRESAN-UNERG, San Juan de los Morros 2301, Venezuela
4
Centro Universitario de Oriente, Universidad San Carlos de Guatemala, Chiquimula 20001, Guatemala
5
Institució Catalana d’Història Natural, 08001 Cataluña, Spain
*
Author to whom correspondence should be addressed.
Animals 2023, 13(24), 3815; https://doi.org/10.3390/ani13243815
Submission received: 2 November 2023 / Revised: 1 December 2023 / Accepted: 7 December 2023 / Published: 11 December 2023
(This article belongs to the Special Issue Diagnosis and Prevention of Endemic Diseases in Ruminants)
Browse Figures
Review Reports Versions Notes

Abstract

:

Simple Summary

Bovine mastitis is inflammation of the mammary gland. Subclinical mastitis (SCM) does not present visible changes in the udder or milk but does result in reduced production and alterations in milk. The aim of this study was to evaluate the environmental and breed risk factors associated with the presence of SCM in dual-purpose livestock systems in Arauca, Colombian Orinoquia. Milk samples were taken from the individual mammary quarters of 481 cows and the on-farm California Mastitis Test (CMT) was applied. Risk factors were determined by multiple logistic regression analysis. The response variable was the absence (0) or presence (1) of SCM. The environmental risk factors that were significantly associated (p < 0.05) with the presence of SCM were the number of cows and milk production. The Taurus-Indicus and composite breeds showed greater susceptibility to SCM compared to the Indicus predominance. The prevalence of SCM detected in this study is considered low compared to other studies in tropical regions.

Abstract

The aim of this study was to assess the environmental and breed risk factors associated with the prevalence of subclinical mastitis (SCM) in cows in the dual-purpose livestock system of Arauca, Colombian Orinoquia. Milk samples were taken from 1924 mammary quarters, corresponding to 481 cows on 28 different farms, and the California Mastitis Test (CMT) was applied. Risk factors associated with SCM were determined using multiple logistic regression analysis. The response variable was the presence (1) or absence (0) of SCM. Breed was included as a genetic risk factor, and daily milk production, number of cows in production, lactation month, calving number, cow age, climatic period, and body condition were included as environmental risk factors. The analysis of the odds ratio (OR) of significant effects indicated that the factors significantly associated with the presence of SCM were the number of cows (OR = 2.29; p = 0.005), milk production (OR = 0.88; p = 0.045), and the Taurus-Indicus breeds (OR = 1.79; p = 0.009) and composite breed (OR = 3.95; p = 0.005). In this study, the occurrence of SCM was determined by the following risk factors: number of cows, milk production, and breed. Likewise, the highest prevalence seemed to occur on farms with less technological development and sanitary management of producers from the lowest socioeconomic stratum.

1. Introduction

Mastitis is a common disease in dairy farms that causes economic losses at local, regional, and global levels [1,2,3]. The disease is generally caused by microorganisms or trauma to the udder. It can be clinical when signs of disease and abnormal milk are visible or subclinical when there are no visible clinical signs [2,4] and the milk appears to be normal [5]. Subclinical mastitis (SCM) is considered the most predominant [6], being one of the most costly diseases in terms of milk production losses [7].
There are risk factors that predispose animals to the disease [8]. Among the risk factors associated with cows are genetic traits [8,9,10,11], the lactation stage, the calving number, the level of production [8,10,12], and the cow age [13]. At the milking level, the risk factors associated with the presence of SCM are inadequate washing of the udder and mammary quarters [13,14], cowshed hygiene [12], and handwashing [15]. Studies have indicated that the number of cows on the farm, the size of the farm, and the climatic period influence the presence of SCM [13,16,17]. Likewise, other studies have shown that the calving number, the farm system, the milking area, the region, and the herd are risk factors that significantly affect the prevalence of SCM [18].
The SCM influences the quality of milk, mainly in terms of composition, such as the reduction of phosphorus, calcium, protein, and fats, while increasing chlorine and sodium [19]. On the other hand, the consumption of raw milk with the presence of mastitis causes public health problems [20]. Understanding the risk factors is a prerequisite for improving udder health in a herd, region, or country [21].
At the farm level, a widely used and efficient method for the diagnosis of SCM is the California Mastitis Test (CMT), which has been used for decades under field conditions for the diagnosis of mastitis in cattle [22,23,24]. The CMT is a rapid, practical, and low-cost test with reliable results [25,26,27]. The precision of the CMT test has been evidenced in comparative tests of sensitivity and specificity [28]. Other studies have concluded that CMT is the most accurate test after somatic cell count and other laboratory tests; therefore, CMT is a reliable diagnostic method under farm conditions [23].
The CMT is a manual test that measures the quantity of somatic cells in milk generated by inflammatory processes [29,30]. Somatic cells migrate from the blood to milk as a response to infection [31]. The CMT identifies the inflammatory response based on the gel viscosity. The test contains a dye (bromocresol purple) that indicates pH changes that occur in milk as a result of inflammation [32].
The test does not provide a numerical result, but rather a categorical result, so any result above a vestigial reaction is considered suspicious, providing validity for the SCM diagnosis [33,34]. However, the test score with the number of somatic cells is valid for low-performing cows since they physiologically have a high level of somatic cells [35]. Other studies have determined, for individual cows, as CMT-positive, a score equal to or greater than 2, regardless of the absence of clinical symptoms, milk abnormalities, or the timing of milk production [18].
Milk production in Arauca (Colombia) comes mainly from the dual-purpose livestock system that is developed in tropical conditions, with low inputs and lower technological levels. The dual-purpose livestock system corresponds to groups of animals resulting from the crossing of Zebu cattle with European breeds. In the region, the health status of the udder of dairy animals is unknown, due to the few reports available in the area. Public order problems, the distance from urban centers, and the lack of passable access roads make access to the farms difficult. Therefore, microbiological examinations for the detection of SCM are difficult to perform. The practical applicability of CMT on the farm allows rapid diagnosis of SCM without the need for costly and time-consuming microbiological culture [36]. The study of risk factors for the prevalence of SCM allows us to measure the presence of an animal health problem in an area with a livestock attitude [19]. The aim of this cross-sectional study was to assess the environmental and breed risk factors associated with the prevalence of SCM in cows from the dual-purpose livestock system in the floodplain of Arauca, Colombian Orinoquia.

2. Materials and Methods

2.1. Study Area

The study was carried out in Arauca department, eastern Colombia (latitude: 7°5′5″ N; longitude: 70°45′32.7″ W) (Figure 1). The climatic regime of the region corresponds to a rainy period (May–October), with a relative humidity of 85% and an average ambient temperature of 30.1 °C, and a dry period (November–April), with a relative humidity of 65% and an average ambient temperature of 32.6 °C. The annual rainfall is less than 1500 mm [37,38].
The farms where the animals were sampled belong to small producers with a low technological level. The farms were chosen for convenience after a meeting with the Livestock Association Producers of the region. The average farm size was 65 hectares (ranging from 30 to 100 hectares). An average of 18 dairy cows per farm were found (range: 7–57 cows). All farms have productive and reproductive records. On the farms, milk production is measured every day (L/day/cow), and milking is performed by hand (once a day), with the calf’s presence, and is carried out under a covered cowshed or in open environments. The calf sucks before milking to stimulate milk let-down and then sucks again after milking. This is a normal practice in tropical dairy production. In most farms, animal feeding is based on extensive grazing systems with grasses, mainly Brachiaria decumbes and Brachiaria arrecta. On some farms, sodium chloride (white salt) is provided, and mineralized salts are provided to a lesser extent [36]. The destination of the milk is for self-consumption, homemade or artisan production, reception in collection centers, or direct sale to consumers. At the time of milking, udder washing of the cows was not observed. There was no health plan.

2.2. Evaluated Animals

Individual milk samples from 1924 mammary quarters belonging to 481 cows from the dual-purpose livestock system (Bos indicus x Bos taurus multiracial crosses), aged 3 to 10 years, with 1 to 8 calvings and 1 to 7 lactation months, were evaluated from 28 farms in 19 Territorial Division Centers.
Due to the lack of genealogical records for the animals (except the Gyrolando breed), the classification of cow breeds was based on their phenotype and the information provided by the producers, as recommended by other authors [39,40]:
  • Taurus-Indicus (F1 cows Zebu x Holstein, Zebu x Brown Swiss, Zebu x Norman, and Zebu x Simental; n = 275)
  • Indicus predominance (Cows with a phenotype higher than 50% Indicus of the Gyr, Guzerat, and Brahman breeds; n = 184)
  • Composite breed (Gyrolando breed cows). The Gyrolando breed is a composite breed resulting from the cross between the Holstein breed (Bos taurus) and the Gyr breed (Bos indicus), with a racial pattern in grade 5/8 Holstein + 3/8 Gyr (n = 22).
Milk samples were taken from the cows in the morning (4:00 a.m. to 6:00 a.m.). All cows that were milked on the farm at the time of the visit were sampled. Only cows with functional mammary quarters and without antibiotic treatments during the last three months were included in the study. The samples were taken during the rainy period (May to October 2021) and the dry period (November to April 2022), following the recommendations available in the literature [18,26]. Mammary quarters were identified, and samples were taken in that order (Figure 2).

2.3. California Mastitis Test (CMT)

To sample each mammary quarter, 2 mL of milk was deposited in each receptacle of the plastic test paddle and mixed with 2 mL of CMT reagent (Mastit read) (Figure 2), following the standard procedure [29,30,32]. The mixture was homogenized for 10 s with circular movements [29] and the test results were then read with a 45° inclination. Interpretation of results was based on the standard procedure, following the CMT grades: 0 = negative, trace = possible infection, + = positive grade 1 (infected), ++ = positive grade 2 (infected), and +++ = positive grade 3 (infected) [29,30,32]. In the study, all results with some degree to CMT reaction were counted as SCM positive [27]. All tests were carried out by a single person.

2.4. Prevalence Determination

Prevalence is an indicator of existence or “stock”, since it considers all present cases, whether new or old, and refers to the number of cases in which a disease or infectious event occurs in a given place and time [41]. The cow-level prevalence (with at least one affected mammary quarter), prevalence at the level of total mammary quarters, and prevalence at the level of the mammary quarter by position were processed according to the following mathematical formulas [27,36,42]:
  • Cow-level prevalence = (number of positive cows/total number of sampled cows) × 100
  • Prevalence at the level of total mammary quarters = (total number of positive mammary quarters/total number of sampled mammary quarters) × 100
  • Prevalence at the level of the mammary quarter by position = (total number of positive mammary quarters per position/total number of mammary quarters per position) × 100
Test data at the farm level were compiled and organized in Excel format for further analysis. The collected information included data related to risk factors: breed, cow age, calving number, lactation month, body condition, climatic period, number of cows in production, and daily milk production per cow. The body condition was subjectively evaluated at the time of taking the milk sample, on a scale from 1 to 5, where 1 is a very thin cow and 5 is a very obese cow [43].

2.5. Statistical Analysis

Frequency tables were estimated for the variables related to the number of positive cows (animals with any degree of positivity to SCM in any mammary quarter, as declared by the test), number of positive mammary quarters per cow (1 to 4), and positive mammary quarters by position (RP, LP, RA, and LA).
To determine the factors associated with SCM, a standard multiple logistic regression analysis was used, which is widely used for this study type [44]. The response variable was the SCM presence (1) or absence (0) obtained with the CMT.
To compare the variables of the number of cows and breed, dummy variables were created, and the categories with more than 26 cows (group 3) and animals with an Indicus predominance (group 2) were taken as a reference point, respectively. In the standard multiple logistic regression analysis, breed was included as a genetic risk factor, and the environmental risk factors included: cow age, daily milk production, lactation month, body condition, climatic period, number of cows in production, and calving number.
The following was the standard multiple logistic regression model used:
Ni = log(π/(1 − π)) = M + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + β6X6 + β7X7 + β8X8 + εi
where:
Ni =i-th modeled probability of having SCM-positive animals
π =odds ratio: (1 − π) probability of not having the presence of SCM
M =slope
X1 =effect of the age variable (3 to 10 years)
X2 =effect of the milk production variable (2 to 12 L)
X3 =effect of the lactation month variable (1 to 7)
X4 =effect of the body condition variable (1 to 5)
X5 =effect of the climatic period variable (rainy and dry)
X6 =effect of the number of cows variable (1 = 7 to 16 cows; 2 = 17 to 26 cows; 3 ≥ 26 cows)
X7 =effect of the breed variable (1 = Taurus-Indicus; 2 = Indicus predominance; 3 = composite breed)
X8 =effect of the calving number variable (1 to 8)
εi =accumulated error
βi =regression coefficients associated with each independent variable.
The analyses were carried out using the statistical software InfoStat free version 2020 [45].

3. Results

A total of 1924 mammary quarters corresponding to 481 cows from the dual-purpose livestock system were sampled. The number of cows with mammary quarters affected by SCM, within the evaluated sample, is shown in Table 1. The cow-level prevalence indicates whether a cow presented the disease or if at least one of its mammary quarters were positive. Results showed that 151 cows were positive for SCM according to the CMT test, indicating a cow-level prevalence of 31.4% (151/481).
The SCM prevalence levels for total mammary quarters and mammary quarters by position are presented in Table 2. The CMT test showed a total mammary quarters prevalence level of 14.3% (2758/1924), while the highest mammary quarters prevalence level by position was for RP (16.0%) and RA (14.8%).
Table 3 shows that the highest prevalence of SCM was observed with 7 to 16 cows in production (39.2%), in cows with 2 to 5 L/day (32.9%), in cows with more than 3 lactation months (33.1%), in cows more than 6 years of age (33.7%), in cows with a body condition of 2.5–3.5 (33.2%), and in cows with more than 4 calvings (38.9%). Regarding breed, the highest prevalence of SCM was observed in the composite breed (50.0%). On farms with 17–26 cows and >26 cows, the prevalence was similar (27.3% and 27.6%), and likewise between dry and rainy periods (31.1% and 31.4%).
Table 4 presents the factors that were significantly associated with the SCM presence in the evaluated systems. The standard multiple logistic regression analysis showed that most of the factors did not influence the positivity of SCM found with the CMT test, with the exception of the number of cows, milk production, and breed (p < 0.05).
The analysis of the odds ratio (OR) of the significant effects indicated that that cows raised in herds composed of 7 to 16 animals had a 2.29 times higher probability of presenting SCM than those raised in herds with more than 26 cows. In the case of milk production, for each unit increase in milk production, the odds of having sick animals with SCM vs. not sick with SCM was reduced by approximately 12%. With respect to breed, the Taurus-Indicus cows and composite breed cows were 1.79 and 3.95 more likely to present SCM than Indicus predominance cows.
It was observed that the number of cows per farm (7 to 16 cows) was a significant risk factor for the presence of SCM (39.2%; OR = 2.29; p = 0.005), compared to farms with a greater number of animals. Daily milk production was a factor that indicated a small statistical difference (p = 0.045; OR = 0.88; Wald LI_LS = 0.77–1.00) associated with the prevalence of SCM. Cows with 2 to 5 L of milk had the highest prevalence of SCM (32.9%), while the lowest prevalence was observed in cows with 6 to 12 L of milk (29.5%; Table 3 and Table 4).
Breed was a statistically significant factor associated with the prevalence of SCM. The highest prevalence (50%) was observed in composite breed cows (p = 0.005; OR = 3.95; Wald LI_LS = 1.50–10.40), while in Taurus-Indicus cows, a prevalence of 33.8% was observed (p = 0.009; OR = 1.79; Wald LI_LS = 1.15–2.79), compared to the Indicus predominance cows, which showed the lowest prevalence of SCM (25%).

4. Discussion

In this study, the CMT test detected a higher prevalence of SCM at the cow level than reported in other studies (20.2% and 20.5%) [14,46], but similar to other studies in tropical regions [4,47]. However, the results of the current study are considered low compared to other reports also in tropical regions [18,23,27,48]. On the study farms, milking was supported by the calf, and at the end of milking the residual milk was consumed, which may limit the growth of bacteria in the udder by reducing the presence of SCM [49]. The highest prevalence was observed in the RP and RA mammary quarters. The authors of this study observed that on the farms, during their rest period, the cows adopted a sternal decubitus position, often to the right side, which may allow the mammary gland to be more vulnerable to infection by environmental microorganisms. They also observed that manual milking usually began from the two right mammary quarters, or in a crossed way, starting with the RP and LA mammary quarters, which can facilitate the presence of mastitis in mammary quarters [36].
In this study, the number of cows per farm (7 to 16 cows) was a significant risk factor for the presence of SCM (OR = 2.29; p = 0.005), compared to farms with a greater number of animals (17 to 26 cows). These results may be associated with inadequate management practices in smaller farms, represented by poor milking practices, a milking place with dirt floors that facilitate environmental–animal contamination, insufficient infrastructure, poor handwashing of the milker and the udder, and not using sealant and gloves for milking. In addition, workers did not change or wash their clothes between milkings. These conditions were also evidenced in another study [50]. These results are similar to those reported in Southeast Asian countries [51] and in herds in Ethiopia [21]. However, the results of the present study differ from those reported in intensive milk production systems, where a higher cow density is associated with a greater risk of presenting SCM compared to semi-intensive systems (p = 0.017) [18]. Cows managed in intensive systems have a 10.3 times higher risk of suffering from SCM than those managed in systems with fewer cows [47]. In studies carried out in tropical climates of Bangladesh, the highest prevalence of SCM was for cows with semi-intensive management, stabled in areas with low grooming conditions, compared to those kept under intensive management (27.6% vs. 10.5%) [52].
Lower milk production indicated a small difference (OR = 0.88; p = 0.045) as a risk factor for the presence of SCM. However, the results were not conclusive, and future studies are required with a larger number of farms to obtain more reliable results. Direct observation by the authors infers that this risk factor seems to be associated with smaller farms, without sanitary management and a lower technological level. Furthermore, because these are lower production cows, farmers paid little attention to this form of mastitis. This result is similar to that reported in Sri Lanka, where the highest prevalence was found in daily milk production of 3 to 5 L/day [47]. In a study in Perú, it was found that hygiene before milking was a determining factor for the presentation of SCM in small producers [49]. However, in another study, milk/cow production was not considered as a risk factor for the prevalence of mastitis (p > 0.05) [18].
In this study, the Taurus-Indicus breeds (OR = 1.79; p = 0.009) and the composite breed (OR = 3.95; p = 0.005) were a significant risk factor associated with the presence of SCM, with a higher prevalence value compared to the Indicus predominance breeds. In a prevalence study in adapted Zebu breeds, Holstein Friesian crosses with local Zebu breeds, and Jersey breeds, a higher infection of the mammary gland was detected in Jersey cows (78.6%) and crossbreeds (51.9%) compared with the adapted Zebu breeds (16.7%) [53], which implies that the SCM presence is associated with high-yielding cows [54]. Various studies have reported that the breed effect is related to the presence of mastitis [55,56]. The higher SCM prevalence reflected in Taurus-Indicus cows and the composite breed suggests that milk production with manual milking and with the calf presence in the dual-purpose cattle system in Arauca with Indicus predominance cows may demonstrate a lower risk associated with SCM prevalence.
In another study, the authors found that breed and/or crossbreeding was not a risk factor in the prevalence of SCM, while the calving number (primiparous and multiparous), geographic region, and milk production (<10 L, 10–20 L, or >20 L) contributed significantly (p = 0.036) to the risk of SCM. In multiparous cows, the odds of having SCM were 2.51 times higher than the odds in first-calving cows [18]. It has also been reported that the prevalence of SCM was significant (p < 0.05) in European crosses (60.7%) compared to Sahiwal (55.5%) and local cattle (0%) [47].
Cows of breeds with high milk production are more susceptible to SCM [57] due to the size of the teats, which can easily become loose and allow the entry of pathogens, ultimately causing an infection [58]. In cows crossed with the Friesian breed, higher prevalence of SCM has been reported than in the local Zebu breed (56.4% vs. 26.8%) [28]. Likewise, higher levels of SCM have been reported for cross-breeds (p < 0.005) vs. local breeds, such as Zebu in Sri Lankan herds [52].
Finally, the highest prevalence was observed in smaller farms with a lower level of production, which differs from most studies. This indicates that the highest prevalence seemed to occur on farms of producers from the lowest socioeconomic stratum and with less technological development and sanitary management.

5. Conclusions

The occurrence of SCM in dual-purpose livestock systems of Arauca, Colombian Orinoquia, was determined by the risk factors of milk production, number of cows, and breed. In the current study, the prevalence of SCM detected at the cow level was considered low compared to other studies in tropical regions. Composite breeds and Taurus-Indicus under conditions of extensive management and manual milking were more susceptible to the presence of SCM. A higher prevalence of SCM was observed on farms with fewer cows and with milk production of 2 to 5 L. The results suggest that studies of risk factors associated with SCM should be carried out in dual-purpose livestock production systems in other regions.

Author Contributions

Writing—preparation of the original manuscript, A.S.-C. and M.V.-T.; methodology and formal analysis, M.V.-T., R.T. and A.S.-C.; statistical analysis, M.V.-T. and R.T.; review—editing and conceptualization, R.J.-J., P.M.P.-C. and D.P.B.-P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Research Committee—CONADI (ID2958)—of the Universidad Cooperativa de Colombia.

Institutional Review Board Statement

Bioethical Concept No. BIO163, issued by the Research Bioethics Subcommittee of the Bucaramanga Sectional Universidad Cooperativa de Colombia (Act No. 4, 4 November 2021).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the second author. The data are not publicly available due to we are going to carry out other analyzes.

Acknowledgments

The authors thank the auxiliary students who helped in the collection of farm data, the farmers, for providing the animals for taking milk samples, and the anonymous referees for their valuable comments on the manuscript. All persons included in this section have consented to the acknowledgments.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mera, R.; Muñoz, M.; Artieda, J.; Ortíz, P.; González, R.; Vega, V. Mastitis bovina y su repercusión en la calidad de la leche. Rev. Elect. Vat. 2017, 18, 1–16. [Google Scholar]
  2. Cuenca-Condoy, M.; García-Bracho, D.; Reinoso-García, L.; González-Rojas, J.; Torracchi-Carrasco, J. Detección de Mastitis Subclínica Bovina y factores asociados, en fincas lecheras de la Provincia del Cañar—Biblián, Ecuador. Rev. Cientif. FCV-LUZ 2021, 31, 93–97. [Google Scholar] [CrossRef]
  3. Girma, A.; Tamir, D. Prevalence of Bovine Mastitis and Its Associated Risk Factors among Dairy Cows in Ethiopia during 2005–2022: A Systematic Review and Meta-Analysis. Vet. Med. Int. 2022, 2022, 7775197. [Google Scholar] [CrossRef] [PubMed]
  4. Ndahetuye, J.B.; Twambazimana; Nyman, A.-K.; Karege, C.; Tukei, M.; Ongol, M.P.; Persson, Y.; Båge, R. A cross sectional study of prevalence and risk factors associated with subclinical mastitis and intramammary infections, in dairy herds linked to milk collection centers in Rwanda. Med. Vet. Prev. 2020, 179, 105007. [Google Scholar] [CrossRef]
  5. Oliveira, C.; Sousa, M.; Silva, N.; Mendonça, C.; Silveira, J.; Oaigen, R.; Andrade, S.; Barbosa, J. Prevalência e etiologia da mastite bovina na bacia leiteira de Rondon do Pará, estado do Pará. Pesq. Vet. Bras. 2011, 31, 104–110. [Google Scholar] [CrossRef]
  6. Viguier, C.; Arora, S.; Gilmartin, N.; Welbeck, K.; O’Kennedy, R. Mastitis detection: Current trends and future perspectives. Trends Biotechnol. 2009, 27, 486–493. [Google Scholar] [CrossRef] [PubMed]
  7. Bardhan, D. Estimates of economic losses due to clinical mastitis in organized dairy farms. Indian J. Dairy Sci. 2013, 66, 168–172. [Google Scholar]
  8. Sinha, M.K.; Thombare, N.N.; Monddal, B. Subclinical Mastitis in Dairy Animals: Incidence, Economics, and Predisposing Factors. Sci. World J. 2014, 15, 1–4. [Google Scholar] [CrossRef]
  9. Steeneveld, W.; Hogeveen, H.; Barkema, H.W.; Van Den Broek, J.; Huirne, R.B.M. The Influence of Cow Factors on the Incidence of Clinical Mastitis in Dairy Cows. J. Dairy Sci. 2008, 91, 1391–1402. [Google Scholar] [CrossRef]
  10. Kebebew, G.; Jorga, E. Prevalence and risk factors of bovine mastitis in Ambo town of West Shewa Zone, Oromia, Ethiopia. Ethiop. Vet. J. 2016, 20, 123–134. [Google Scholar] [CrossRef]
  11. Akter, S.; Rahman, M.; Sayeed, A.; Islam, N.; Hossain, D.; Hoque, A.; Koop, G. Prevalence, aetiology and risk factors of subclinical mastitis in goats in Bangladesh. Small Rumin. Res. 2020, 184, 106046. [Google Scholar] [CrossRef]
  12. Schukken, Y.H.; Barb, D.; Hertl, J.; Gröhn, Y.T. Correlated time to event data: Modeling repeated clinical mastitis data from dairy cattle in New York State. Prev. Vet. Med. 2010, 97, 150–156. [Google Scholar] [CrossRef] [PubMed]
  13. Ali, W.; Yaqoob, M.; Arshad, A.; Dai, G.; Ullah, S.; Arshad, M.; Ullah, I.; Ullah, I. Bacterial and antibiotic profile of mastitic milk of beetal goat in District Jhelum. Pak. J. Zool. 2021, 53, 1–5. [Google Scholar] [CrossRef]
  14. Olivares-Pérez, J.; Kholif, A.E.; Rojas-Hernández, S.; Elghandour, M.M.; Salem, A.Z.M.; Bastida, A.Z.; Velázquez-Reynoso, D.; Cipriano-Salazar, M.; Camacho-Díaz, L.M.; Alonso-Fresan, M.U.; et al. Prevalence of bovine subclinical mastitis, its etiology and diagnosis of antibiotic resistance of dairy farms in four municipalities of a tropical region of Mexico. Trop. Anim. Health Prod. 2015, 47, 1497–1504. [Google Scholar] [CrossRef] [PubMed]
  15. Mesele, F.; Leta, S.; Amenu, K.; Abunna, F. Occurrence of Escherichia Coli O157:H7 in lactating cows and dairy farm environment and the antimicrobial susceptibility pattern at adami Tulu Jido Kombolcha District, Ethiopia. BMC Vet. Res. 2023, 19, 6. [Google Scholar] [CrossRef]
  16. Insua, D.A.; Oses, R.R.; Saura, G.G.; Pedraza, M.A. Impacto de la humedad relativa mínima en la prevalencia de mastitis subclinica bovina utilizando regresión lineal. Rev. Elect. Vet. 2010, 11, 1–9. [Google Scholar]
  17. Ramírez Sánchez, J.M. Prevalencia y factores predisponentes a mastitis subclínica en establos lecheros de la provincia de Trujillo. Rev. CEDAMAZ 2015, 5, 12–23. [Google Scholar]
  18. Ranasinghe, R.M.S.B.K.; Deshapriya, R.M.C.; Abeygunawardana, D.I.; Rahularaj, R.; Dematawewa, C.M.B. Subclinical mastitis in dairy cows in major milk-producing areas of Sri Lanka: Prevalence, associated risk factors, and effects on reproduction. J. Dairy Sci. 2021, 104, 12900–12911. [Google Scholar] [CrossRef]
  19. Ormaza Montenegro, D.J.; Rueda Abad, R.J.; Huera Ordóñez, D.S.; Ibarra Rosero, E.M. Mastitis bovina en el cantón Montúfar-Carchi. Prevalencia, agente causal y factores de riesgo. AXIOMA—Rev. Científ. Investig. Docenc. Proyec. Soc. 2021, 1, 5–10. [Google Scholar]
  20. Murphy, S.; Martin, N.; Barbano, D.; Wiedmann, M. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield? J. Dairy Sci. 2016, 99, 10128–10149. [Google Scholar] [CrossRef]
  21. Mekonnen, S.A.; Koop, G.; Melkie, S.T.; Getahun, C.D.; Hogeveen, H.; Lam, T. Prevalence of subclinical mastitis and associated risk factors at cow and herd level in dairy farms in North-West Ethiopia. Prev. Vet. Med. 2017, 145, 23–31. [Google Scholar] [CrossRef] [PubMed]
  22. Deb, R.; Kumar, A.; Chakraborty, S.; Kumar Verma, A.; Tiwuari, R.; Dhama, K.; Singh, U.; Kumar, S. Trends in Diagnosis and Control of Bovine Mastitis: A review. Pakist. J. Biol. Sci. 2013, 16, 1653–1661. [Google Scholar] [CrossRef] [PubMed]
  23. Badiuzzaman, M.; Samad, M.A.; Siddiki, S.H.M.F.; Islam, M.T.; Saha, S. Subclinical mastitis in lactating cows: Comparison of four screening tests and effect of animal factors on its occurrence. Bangl. J. Vet. Med. 2015, 13, 41–50. [Google Scholar] [CrossRef]
  24. Maldonado-Arias, D.F.; Santos-Calderón, C.R.; Quilapanta-Guamán, A.E.; Mena-Miño, L.A. Diagnosis of Subclinical Mastitis Using Three Methods for Control and Treatment. Dom. Cien. 2022, 8, 773–790. [Google Scholar]
  25. Sanford, C.J.; Keefe, G.P.; Sanchez, J.; Dingwell, R.T.; Barkema, H.W.; Leslie, K.E.; Dohoo, I.R. Test characteristics from latent-class models of the California Mastitis Test. Prev. Vet. Med. 2006, 77, 96–108. [Google Scholar] [CrossRef] [PubMed]
  26. Bedoya, C.C.; Castañeda, V.H.; Wolter, W. Métodos de detección de la mastitis bovina. Rev. Elect. Vet. 2007, 8, 1–17. [Google Scholar]
  27. Gómez-Quispe, O.E.; Santivañez-Ballón, C.S.; Arauco-Villa, F.; Espezua-Flores, O.H.; Manrique-Meza, J. Criterios de Interpretación para California Mastitis Test en el Diagnóstico de Mastitis Subclínica en Bovinos. Rev. Investig. Vet. Perú 2015, 26, 86–95. [Google Scholar] [CrossRef]
  28. Hoque, M.N.; Das, Z.C.; Talukder, A.K.; Alam, M.S.; Rahman, A.N. Different screening tests and milk somatic cell count for the prevalence of subclinical bovine mastitis in Bangladesh. Trop. Anim. Health Prod. 2014, 47, 79–86. [Google Scholar] [CrossRef]
  29. Mellenberger, R.; Roth, C.J. Hoja de Información de la Prueba de Mastitis California (CMT). 2000. Available online: https://bit.ly/43iegJq (accessed on 23 December 2022).
  30. NMC. Laboratory Handbook on Bovine Mastitis, 3rd ed.; National Mastitis Council, Inc.: New Prague, MN, USA, 2017; p. 151. [Google Scholar]
  31. Philpot, W.N.; Nickerson, S.N. Winning the Fight against Mastitis; Westfalia Surge, Inc.: Naperville, IL, USA, 2001; p. 192. [Google Scholar]
  32. Guízar, J.I.; Bedolla, J.L.C. Determinación de la prevalencia de mastitis bovina en el municipio de Tarímbaro, Michoacán, mediante la prueba de California. Rev. Electrón. Vet. 2008, 9, 1–35. [Google Scholar]
  33. AL-Edany, A.A.; Khudor, M.H.; AL-Mousawi, K.S. Comparison of three indirect tests for the diagnosis of bovine subclinical mastitis caused by coagulase negative staphylococci with their susceptibility to seven antibiotics. Bas. J. Vet. Res. 2012, 11, 75–83. [Google Scholar] [CrossRef]
  34. Hernández, J.M.; Bedoya, J.L. Importancia del conteo de células somáticas en la calidad de la leche. Rev. Elect. Vet. 2008, 9, 1–35. [Google Scholar]
  35. Kivaria, F.M.; Noordhuizen, J.P.; Nielen, M. Interpretation of California mastitis test scores using Staphylococcus aureus culture results for screening of subclinical mastitis in low yielding smallholder dairy cows in the Dar es Salaam region of Tanzania. Prev. Vet. Med. 2007, 78, 274–285. [Google Scholar] [CrossRef]
  36. Salamanca Carreño, A.; Vélez-Terranova, M.; Tamasaukas, R.; Jáuregui-Jiménez, R.; Parés-Casanova, P.M.; Arias-Landazábal, J.N. Assessment of the Prevalence of Subclinical Mastitis in Dual Purpose Livestock System of Colombian Orinoquia: On-Farm Diagnostic Tests Comparison. Preprints. Org 2023, 2023040902, 1–16. [Google Scholar]
  37. IDEAM—Instituto de Hidrología, Meteorología y Estudios Ambientales. Información Aeronáutica. Climatología. Available online: http://bart.ideam.gov.co/cliciu/arauca/precipitacion.htm (accessed on 23 December 2022).
  38. Arauca. Clima: Arauca, Aeropuerto Santiago Pérez (En línea). Available online: https://es.allmetsat.com/clima/venezuela.php?code=80099 (accessed on 3 October 2023).
  39. López, J.; Vaccaro, L. Comportamiento productivo de cruces Holstein Friesian-cebú comparados con Pardo Suizo-cebú en sistemas de doble propósito en tres zonas de Venezuela. Zoot. Trop. 2002, 20, 397–414. [Google Scholar]
  40. Sheen, S.; Riesco, A. Factores que afectan la producción de leche en vacas de doble propósito en el trópico húmedo (Pucallpa). Rev. Investig. Vet. Perú. 2002, 13, 25–31. [Google Scholar]
  41. Manterola, C.; Otzen, T. Valoración Clínica del Riesgo, Interpretación y Utilidad Práctica. Int. J. Morphol. 2015, 33, 842–849. [Google Scholar] [CrossRef]
  42. Santivañez-Ballón, C.S.; Gómez-Quispe, O.E.; Cárdenas-Villanueva, L.A.; Escobedo-Enríquez, M.H.; Bustinza-Cardenas, R.H.; Peña-Sánchez, J. Prevalencia y factores asociados a la mastitis subclínica bovina en los Andes peruanos. Vet. Zoot. 2013, 7, 92–104. [Google Scholar] [CrossRef]
  43. Edmonson, A.J.; Lean, I.J.; Weaver, L.D.; Farver, T.; Webster, G. A Body Condition Scoring Chart for Holstein Dairy Cows. J. Dairy Sci. 1989, 71, 68–78. [Google Scholar] [CrossRef]
  44. Taucher, E. Bioestadística; Editorial Universitaria: Santiago de Chile, Chile, 1997; p. 310. [Google Scholar]
  45. InfoStat. InfoStat Versión 2020. Manual del Usuario. Universidad Nacional de Córdoba, Argentina. 2020. Available online: https://www.infostat.com.ar/index.php?mod=page&id=46 (accessed on 12 June 2023).
  46. Sarker, S.C.; Parvin, M.S.; Rahman, A.K.M.; Islam, M.T. Prevalence and risk factors of subclinical mastitis in lactating dairy cows in north and south regions of Bangladesh. Trop. Anim. Health Prod. 2013, 45, 1171–1176. [Google Scholar] [CrossRef]
  47. Sanotharan, N.; Pagthinathan, M.; Nafees, M.S.M. Prevalence of bovine subclinical mastitis and its association with bacteria and risk factors in milking cows of Batticaloa district in Sri Lanka. Int. J. Sci. Res. Innov. Technol. 2016, 3, 137–150. [Google Scholar]
  48. Rahularaj, R.; Deshapriya, R.M.C.; Ranasinghe, K.M.S.B.K. Influence of bovine sub-clinical mastitis and associated risk factors on calving interval in a population of crossbred lactating cows in Sri Lanka. Trop. Anim. Health Prod. 2019, 51, 2413–2419. [Google Scholar] [CrossRef] [PubMed]
  49. Sánchez Herencia, D.; Mamani-Mango, G.D. Mastitis subclínica bovina y factores de riesgo ambientales en pequeños productores de ganado lechero criado en alta montaña. Rev. Investig. Vet. Perú 2022, 33, e20466. [Google Scholar] [CrossRef]
  50. Mojica, J.; Jaramillo, D. Prevalencia de mastitis subclínica en sistemas de producción bovina doble propósito de la vereda Matepiña del municipio de Arauca. Rev. Sist. Prod. Agroecol. 2014, 5, 126–142. [Google Scholar] [CrossRef]
  51. Bari, M.S.; Rahman, M.M.; Persson, Y.; Derks, M.; Sayeed, M.A.; Hossain, D.; Singha, S.; Hoque, M.A.; Sivaraman, S.; Fernando, P.; et al. Subclinical mastitis in dairy cows in south-Asian countries: A review of risk factors and etiology to prioritize control mmastitis in dairy cows in south-Asian countries: A review of risk factors and etiology to prioritize control measures. Vet. Res. Commun. 2022, 46, 621–640. [Google Scholar] [CrossRef] [PubMed]
  52. Begum, M.; Hossain, M.; Ershaduzzaman, M.; Islam, M.; Rana, M. Study on prevalence and risk factors of subclinical mastitis in lactating dairy cows in rajshahi and rangpur division of Bangladesh. Wayamba J. Anim. Sci. 2015, 14, 1129–1137. [Google Scholar]
  53. Fesseha, H.; Mathewos, M.; Aliye, S.; Wolde, A. Study on Prevalence of Bovine Mastitis and Associated Risk Factors in Dairy Farms of Modjo Town and Suburbs, Central Oromia, Ethiopia. Vet. Med. Res. Rep. 2021, 12, 271–283. [Google Scholar] [CrossRef]
  54. Radostits, O.M.; Gay, C.C.; Hinchcliff, K.W.; Constable, P.D. Vet. Medic: A Text Book of the Disease of Cattle, Horses, Sheep, Pigs and Goats, 10th ed.; Mosby Elsevier Ltd.: Toronto, ON, Canada, 2007; p. 2156. [Google Scholar]
  55. Biffa, D.; Debela, E.; Beyene, F. Prevalence and Risk Factors of Mastitis in Lactating Dairy Cows in Southern Ethiopia. Int. J. Appl. Res. Vet. Med. 2005, 3, 189–198. [Google Scholar]
  56. Szyda, J.; Mielczarek, M.; Frąszczak, M.; Minozzi, G.; Williams, J.L.; Wojdak-Maksymiec, K. The Genetic Background of Clinical Mastitis in Holstein-Friesian Cattle. Animal 2019, 13, 2156–2163. [Google Scholar] [CrossRef]
  57. Santman-Berends, I.M.G.A.; Swinkels, J.M.; Lam, T.J.G.M.; Keurentjes, J.; van Schaik, G. Evaluation of udder health parameters and risk factors for clinical mastitis in Dutch dairy herds in the context of a restricted antimicrobial usage policy. J. Dairy Sci. 2016, 99, 2930–2939. [Google Scholar] [CrossRef]
  58. Muluye, M.; Alemayehu, K.; Gizaw, S. Milk production performances of local and crossbred dairy cows in West Gojam Zone, Amhara Region, Ethiopía. J. Appl. Sci. 2017, 10, 35–46. [Google Scholar]
Animals 13 03815 g001
Figure 1. Red color: location of the department of Arauca, Colombian Orinoquia. Circle: area where the farms were sampled.
Figure 1. Red color: location of the department of Arauca, Colombian Orinoquia. Circle: area where the farms were sampled.
Animals 13 03815 g001
Animals 13 03815 g002
Figure 2. Mammary quarters’ positions for milk sampling. RP = right posterior, LP = left posterior, RA = right anterior, and LA = left anterior.
Figure 2. Mammary quarters’ positions for milk sampling. RP = right posterior, LP = left posterior, RA = right anterior, and LA = left anterior.
Animals 13 03815 g002
Table 1. Number of cows with affected mammary quarters and cow-level prevalence in the sample evaluated in the dual-purpose livestock system of Arauca, Colombian Orinoquia.
Table 1. Number of cows with affected mammary quarters and cow-level prevalence in the sample evaluated in the dual-purpose livestock system of Arauca, Colombian Orinoquia.
Total sampled cows481%
Affected mammary quarters 1
18517.7
2306.2
3142.9
4224.6
Positive cows151
Cow-level prevalence 31.4
1 = Cows with 1, 2, 3, and 4 affected mammary quarters.
Table 2. Prevalence of SCM (%) at the levels of total mammary quarters and mammary quarters by position (RP, LP, RA, and LA) by the CMT test in a dual-purpose livestock system of Arauca, Colombian Orinoquia.
Table 2. Prevalence of SCM (%) at the levels of total mammary quarters and mammary quarters by position (RP, LP, RA, and LA) by the CMT test in a dual-purpose livestock system of Arauca, Colombian Orinoquia.
Total mammary quarters sampled1924%
Positives275
Prevalence at the level of total mammary quarters14.3
Prevalence at the level of mammary quarters by position
Mammary quartersnPositives
RP4817716.0
LP4816413.3
RA4817114.8
LA4816313.1
n = Number of mammary quarters by position; RP = right posterior; LP = left posterior; RA = right anterior; LA = left anterior.
Table 3. Prevalence of SCM (%) according to the number of cows in production, daily milk production, lactation month, cow age, climatic period, body condition, calving number, and breed, in Arauca, Colombian Orinoquia (descriptive analysis).
Table 3. Prevalence of SCM (%) according to the number of cows in production, daily milk production, lactation month, cow age, climatic period, body condition, calving number, and breed, in Arauca, Colombian Orinoquia (descriptive analysis).
VariableRPLPRALAPositive Mammary QuartersPositive CowsSampled Cows%
Number of cows in production
7–16 cows26202327966015339.2
17–26 cows252633231075319427.3
>26 cows26181513723713427.6
Daily milk production/cow
2 to 5 L413341331487823732.9
6 to 12 L363130301277224429.5
Lactation month
1–3 months463945381689932730.3
More than 3 months312526251075115433.1
Cow age
3 and 4 years17172216724115326.8
5 years29212124955015332.7
6 or more years312628231085917533.7
Climatic period
Rainy7357665625212841131.1
Dry 475723227031.4
Body condition
2.5–3.5403232271316920833.2
3.6–4.5373239361448127329.7
Calving number
113121613543311628.4
227192122884916529.7
31516151258269228.3
>422171917754210838.9
Breed
Taurus-Indicus434344361669327533.8
Indicus predominance27162424914618425.0
Composite breed 753318112250.0
RP = right posterior; LP = left posterior; RA = right anterior; LA = left anterior.
Table 4. Odds ratios of the variables included in the standard multiple logistic regression for the associated factors with the SCM prevalence in dual-purpose livestock systems of Arauca, Colombian Orinoquia.
Table 4. Odds ratios of the variables included in the standard multiple logistic regression for the associated factors with the SCM prevalence in dual-purpose livestock systems of Arauca, Colombian Orinoquia.
Regressor VariablesORWald LI-LS (95%)p-Value
Environmental factors
Age1.230.94–1.61NS
Calvings0.950.70–1.30NS
Lactation0.980.83–1.15NS
Body condition0.670.27–1.62NS
Period0.520.25–1.08NS
Number of cows a
7 to 162.291.29–4.070.005
17 to 261.070.64–1.79NS
Milk production0.880.77–1.000.045
Genetic factors
Breed b
Taurus-Indicus1.791.15–2.790.009
Composite breed3.951.50–10.400.005
OR: odds ratio; Wald LI-LS (95%): Wald confidence limits to 95%; a = reference point group 3 (>26 cows); b = reference point group 2 (Indicus predominance); NS = not significant.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Salamanca-Carreño, A.; Vélez-Terranova, M.; Barajas-Pardo, D.P.; Tamasaukas, R.; Jáuregui-Jiménez, R.; Parés-Casanova, P.M. Environmental and Breed Risk Factors Associated with the Prevalence of Subclinical Mastitis in Dual-Purpose Livestock Systems in the Arauca Floodplain Savannah, Colombian Orinoquia. Animals 2023, 13, 3815. https://doi.org/10.3390/ani13243815

AMA Style

Salamanca-Carreño A, Vélez-Terranova M, Barajas-Pardo DP, Tamasaukas R, Jáuregui-Jiménez R, Parés-Casanova PM. Environmental and Breed Risk Factors Associated with the Prevalence of Subclinical Mastitis in Dual-Purpose Livestock Systems in the Arauca Floodplain Savannah, Colombian Orinoquia. Animals. 2023; 13(24):3815. https://doi.org/10.3390/ani13243815

Chicago/Turabian Style

Salamanca-Carreño, Arcesio, Mauricio Vélez-Terranova, Diana Patricia Barajas-Pardo, Rita Tamasaukas, Raúl Jáuregui-Jiménez, and Pere M. Parés-Casanova. 2023. "Environmental and Breed Risk Factors Associated with the Prevalence of Subclinical Mastitis in Dual-Purpose Livestock Systems in the Arauca Floodplain Savannah, Colombian Orinoquia" Animals 13, no. 24: 3815. https://doi.org/10.3390/ani13243815

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop