Impact of non-genetic factors on clinical mastitis incidence in Murrah buffaloes

doi:10.21203/rs.3.rs-1967312/v1

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Impact of non-genetic factors on clinical mastitis incidence in Murrah buffaloes

https://doi.org/10.21203/rs.3.rs-1967312/v1

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Mastitis brings on economic losses, declined milk production, uplifted treatment costs and accelerated culling in buffaloes. Also, being multi-etiological in nature, control of mastitis is challenging in dairy animals. Hence, knowing the risk factors governing clinical mastitis incidence in buffalo might help in minimizing its occurrence. So, the present study was undertaken in 96 adult Murrah buffaloes to investigate the effect of parity, period of calving, season of calving and level of milk production on incidence of clinical mastitis using logistic regression in SAS v 9.3. The data of mastitis incidence was collected over a period of eighteen years (1997–2014) from Health record register of Livestock Research Centre of the institute. The incidence of mastitis was maximum in second parity (7.65%) followed by parity five and above (7.41%). Parity and period of calving had significant effects (p < 0.05) on mastitis incidence. The odds ratio for incidence of mastitis of animals in parity (5 and above) was highest (3.832), in comparison to first lactation. The animals calving during the period (2004–2007), exhibited maximum incidence of clinical mastitis (14.75%). Higher mastitis incidence in higher parity animals may be due to the compromised immune system and widened teat canal. Therefore, proper management of animals especially for advanced pregnant animals is recommended for reducing incidence of mastitis.

mastitis

season

parity

odds ratio

mammary gland

Mastitis is defined as an inflammatory reaction of the parenchyma of the mammary gland which brings huge economic loss to dairy farmers because of the reduced milk production, expenses of treatment, labour costs, discarding of milk following treatment due to the deleterious effects on the chemical and cytological composition of milk, premature culling and sometimes death (Yang et al., 2012). Mastitis can occur in clinical and subclinical forms based on severity, nature of exudate, duration and primary cause. Clinical mastitis is the symptomatic form and characterized by physical, chemical and bacteriological changes in milk such as presence of blood, water, flakes and pus having clots as well as pathological changes evident in the glandular tissue of udder. According to its severity, rapid onset and duration, clinical form is further classified into peracute, acute, subacute and chronic forms (Fagiolo et al., 2007). Progressive fibrosis accompanied by enlargement, and in severe cases, atrophy of mammary gland is seen in chronic form. While in subclinical mastitis, somatic cell count increases with normal appearance of udder and milk. So, it can be detected by screening tests such as California Mastitis test, detection of bacterial agents and electrical conductivity. Mastitis incidence is largely influenced by management practices, interaction between a variety of microbial infections and host responses in the udder (Fagiolo et al., 2007). Moreover, mastitis being multifactorial in nature, no proper control measures are evident to contain the disease (Kavitha et al., 2009).

India is the highest milk producing country in the world with a total milk production of 209.96 million tonnes and with a population of 109.85 million (Livestock Census, 2019), nearly 45% of the total milk production of India is contributed by buffaloes (Annual Report, 2021-22), and it is twice as rich in fat and other constituents of milk as compared to the cow milk (Kumar et al., 2017). Bovine mastitis poses a significant impact on dairy farm economy. The first comprehensive report on economic loss caused by mastitis in India was published in 1962 reporting an annual loss of Rs. 52.9 crores (Dandha & Sethi, 1962). However, later on with the upcoming of Operation flood milk yield of bovine population increased tremendously which came up with many fold increment in economic loss too. Reshi et al. (2015) reported the annual economic losses due to bovine mastitis to be Rs. 7165.51 crores in India.

Although buffaloes are less susceptible to mastitis than cattle because of thicker streak canal epithelium (Uppal et al., 1994) but a high mortality rate of the calves is seen in the first three months of life due to maternal mastitis, which further leads to decline in buffalo productivity (Akhtar and Ali, 1994). The incidence of clinical mastitis varies as per the physiological status of animal and more predominantly with the environment. The environment factors include the non-genetic factors such as season of calving, period of calving, parity, feeding regime, milk production levels, etc. that significantly affect the incidence of mastitis in dairy herds. A number of researchers have reported significant effect of different non-genetic factors like season of calving (Joshi and Shrestha, 1995; Taraphder et al., 2006), period of calving (Chand et al., 1995), parity (Chand et al., 1995; Joshi and Shrestha, 1995; Taraphder et al., 2006; Sharma et al., 2013; Jingar et al., 2014) on incidence of clinical mastitis in buffaloes. Taraphder et al. (2006) reported 8.75% incidence of clinical mastitis in winter season while 16.28% in rainy season and they also observed a consistent increase in mastitis incidence with increase in parity. Jingar et al. (2014) reported that incidence of mastitis increased from 22.78% (first parity) to 32.89% (fourth parity) during different parities. For bringing out increased milk production, the phenotypic selection is done which predisposes the milch animals for environmental influences subsequently causing mastitis infection (Sinha et al., 2021). So, the present study was carried out to investigate the effect of season of calving, period of calving, parity and levels of milk production on the incidence of clinical mastitis in Murrah buffaloes.

Experimental station and data sources

Adult Murrah buffaloes (N = 96) reared at Livestock Research Centre, ICAR-National Dairy Research Institute, Karnal (Haryana), India were undertaken for carrying out the present study during 2020–2021. The experimental animals were housed under loose housing system with an open paddock having proper drainage system with an adequate slope. The mastitis incidence data was recorded over a period of nineteen years (2000–2018) from the Mastitis register kept at Animal Health Complex of Livestock Research Centre (LRC) of ICAR-National Dairy Research Institute (ICAR-NDRI). The mastitis incidence was recorded such that the animals who got affected with mastitis even once throughout their lifetime were given the code 1 (affected) and those who never got infected even once till date were given the code 0 (not affected). The recording for affected was based on the clinical symptoms being recorded in the Mastitis register which were udder swelling, flakes in milk, hardening of udder and based on the treatment given to the affected ones along with the date of recovery. The data for other variables like season and period of calving and parity was recorded from the birth register and history-cum-pedigree sheets kept in the record room of Animal Genetics and Breeding division of ICAR-NDRI, Karnal.

Data classification

The data classification for different variables (Table 1) like season of calving, period of calving, parity and level of milk production was done according to the variation(s) observed.

Based on the climate at experimental region and fodder resources available at the farm, the season was classified into four groups which are: December–March (season 1 = Winter), April–June (2 = Summer), July–August (season 3 = Rainy), September–November (season 4 = Autumn). For period of calving, data was classified into five groups, taking four years in each group which were coded from 1 to 5 as: 2000–2003 (code 1), 2004–2007 (code 2), 2008–2011 (code 3), 2012–2015 (code 4) and 2016–2020 (code 5). Parity was classified into five groups based on number of animals in each parity and the classification was as follows: First Parity (code 1), Second Parity (code 2), Third Parity (code 3), Fourth Parity (code 4) and Fifth and above (code 5). Animals of parity 5 and above were taken in one group as very few animals belonged to the fifth parity and above in the herd. On the basis of level of milk production (kg) in 305 days for the first lactation of each animal, the data was classified into three production groups as: low (< 1500 kg) producers coded as 1, medium (1500–2500 kg) producers coded as 2 and the high (> 2500 kg) coded as 3.

Table 1

classification of non-genetic factors and their coding
Season of calving		Period of calving		Parity		Level of milk production
Duration	Code	Period	Code	Parity number	Code	Milk yield (kg) in 305 days	Code
December to March (Winter)	1	2000–2003	1	First parity	1	Low (< 1500)	1
April to June (Summer)	2	2004–2007	2	Second parity	2	Medium (1500–2500)	2
July to August (Rainy)	3	2008–2011	3	Third parity	3	High (> 2500)	3
September to November (Autumn)	4	2012–2015	4	Fourth parity	4
				Fifth parity and above	5 and above

Statistical analysis

The effect of non-genetic factors viz. season of calving, period of calving, parity and level of milk production on the incidence of clinical mastitis was investigated by using the maximum likelihood method of the LOGISTIC procedure of SAS Version 9.3.

The Dichotomous Logistic model is as follows:

$$ln\left[\frac{p}{1-p}\right]= {\beta }_{o}+ \sum _{j=1}^{c}{\beta }_{j}{X}_{j}$$

Marginal one unit increase in X _j brings about an increase in Log [p_i/1 – p_i] by β₁

P = Probability of mastitis resistant animals

β₀ = Intercept

β_j = Partial regression coefficients

X_j = Non-genetic factor

Effect of non-genetic factors on incidence of clinical mastitis

The effect of non-genetic factors on the incidence of clinical mastitis was investigated taking four factors which are season of calving, period of calving, parity and milk production levels. Based on the results obtained from maximum likelihood method of the Logistic procedure of SAS Version 9.3, it was found that parity and period of calving had significant effects while season of calving and milk production levels did not have any major influence on the incidence of clinical mastitis in the present study (Table 2). The implicated factors like parity (Sinha et al., 2021; Abo-Gamil et al., 2021) milk production levels (Sinha et al., 2021), lactation stage and season of calving (Oliveira et al., 2015; Abo-Gamil et al., 2021), percentage of grass silage in diet, age and herd incidence rate (Waage et al., 1998) have been reported to have significant influence on clinical mastitis incidence. This difference in significant risk factors may be due to lesser number of samples in the present study due to which it might not have achieved the significance threshold (p < 0.05). The study conducted by Sinha et al. (2021) on two different breeds viz. Sahiwal and Karan Fries showed that level of milk production had significant effect on mastitis incidence in Sahiwal while it was not so in Karan Fries animals, the possible reason for that was reported to be because of presence of less variability in milk production among the animals of Karan Fries animals. The present study also shows that level of milk production did not have much animals in category of high level of milk production.

Table 2

Analysis of effects on clinical mastitis incidence
Effect	Wald chi-square	p-value
Parity	10.1979	0.0372*
Season of Calving	3.1627	0.3672
Period of Calving	13.7061	0.0083**
Milk Production Level	2.3214	0.3133
Significant at p < 0.05, *Significant at p < 0.01

The percentage of incidence of mastitis was maximum in second parity (7.65%) as the animal produces more milk during second parity, the energy store is directed more towards the mammary gland and moreover, the pathogen load increases at the same time, hence, the animal is more prone to mastitis during the second parity. The animals who calved during second period of calving (2004–2007) showed maximum incidence of clinical mastitis 14.75% (Table 3). Wald chi-square analysis revealed that parity had significant effect for incidence of clinical mastitis (p < 0.05). The incidence of clinical mastitis was lesser in first and fourth parity as compared to the second, third and fifth & above parity. The odds ratio of parity fifth and above was highest (3.832) which indicates that fifth and higher parity was having the maximum odds of being associated with mastitis (Table 3). This shows that the incidence of clinical mastitis for parity fifth and above, was 383.2% more as compared to the first parity, with a 95% confidence interval lying in the range of 1.495–9.825 (Table 3). The capability to fight infection decreases substantially as parity increases owing to reduced effectiveness of streak canal as barrier (Wilson et al. 2004; Khate and Yadav 2010). Yu et al. (2011) reported that as the parity advances somatic cell count also increases indicating subclinical mastitis.

The animals who calved during second period of calving (2004–2007) had maximum incidence of mastitis (14.75%) for which the management conditions could also be a possible reason. The odds ratio revealed that clinical mastitis incidence was 447.8% and 326.1% more in second (2004–2007) and fifth period (2016–2020) of calving with confidence interval of (1.738–11.539) and (1.091–9.752) respectively in comparison to first period of calving (2000–2003) as shown in Table 3.

Table 3

Incidence of clinical mastitis under different categories of non-genetic factors and their effect on incidence of clinical mastitis
Effect	Incidence (%)	Estimate ± SE	Wald Chi square	p-value	Odds Ratio	95% CI
Intercept		-2.3886 ± 0.5988	15.9097	0.0001
Parity
Parity 1 (1st )	4.44%
Parity 2 (2nd )	7.65%	0.3356 ± 0.3687	0.8286	0.3627	1.399	0.679–2.881
Parity 3 (3rd )	5.68%	0.0251 ± 0.3956	0.0040	0.9494	1.025	0.472–2.227
Parity 4 (4th )	3.70%	0.0277 ± 0.4619	0.0036	0.9521	1.028	0.416–2.542
Parity 5 (5 and above)	7.41%	1.3434 ± 0.4804	7.8213	0.0052**	3.832	1.495–9.825
Season
Season 1 (Dec to Mar)	8.58%
Season 2 (Apr to Jun)	4.56%	-0.5181 ± 0.3871	1.7918	0.1807	0.596	0.279–1.272
Season 3 (Jul to Aug)	4.02%	-0.5521 ± 0.3920	1.9839	0.1590	0.576	0.267–1.241
Season 4 (Sept to Nov)	10.46%	-0.1123 ± 0.3118	0.1297	0.7188	0.894	0.485–1.647
Period
POC 1 (2000–2003)	1.61%
POC 2 (2004–2007)	14.75%	1.4993 ± 0.4829	9.6392	0.0019**	4.478	1.738–11.539
POC 3 (2008–2011)	2.14%	0.3206 ± 0.6819	0.2210	0.6383	1.378	0.362–5.244
POC 4 (2012–2015)	3.75%	1.0088 ± 0.5731	3.0984	0.0784	2.742	0.892–8.432
POC 5 (2016–2020)	5.36%	1.1820 ± 0.5589	4.4732	0.0344*	3.261	1.091–9.752
Level of production
MP 1 (< 1500 Kg)	6.41%
MP 2 (1500–2500 Kg)	18.72%	0.4132 ± 0.3263	1.6035	0.2054	1.512	0.797–2.865
MP 3 (> 2500 Kg)	3.33%	0.00977 ± 0.4717	0.0004	0.9835	1.010	0.401–2.546
Significant at p<0.05, *Significant at p<0.01

Mastitis being one of the common and devastating diseases affecting the bovine industry across the world. Environmental factors influence the occurrence of mastitis to a great extent in dairy animals. The present study revealed that the non-genetic factors (parity and period of calving) should be considered while performing evaluation of dairy animals. The incidence of mastitis was maximum in second parity (7.65%) while the second period of calving (2004–2007) had maximum incidence of mastitis (14.75%). The compromised immune system and widened teat canal and elongated teat shape are the primary predisposing factors for mastitis infection with the increase in parity. Therefore, for animals in advanced parity proper management and care is recommended to prevent mastitis infection.

Acknowledgements

The authors thank the Director, ICAR-National Dairy Research Institute for the financial assistance to carry out this research work.

Conflict of Interest

The authors have no conflicts of interest to disclose.

Funding

“This work was supported by Director, ICAR-National Dairy Research Institute.

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Author contributions

Archana Verma contributed to the study conception and design. Data collection and analysis were performed by Komal Jaglan, Nidhi Sukhija, Linda George and Rani Alex. The first draft of the manuscript was written by Komal Jaglan and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Impact of non-genetic factors on clinical mastitis incidence in Murrah buffaloes

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Abstract

Introduction

Materials And Methods

Experimental station and data sources

Data classification

Statistical analysis

Results And Discussion

Effect of non-genetic factors on incidence of clinical mastitis

Declarations

References

Supplementary Files

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