A study on the determination of body condition score and somatic cell count in Turkish Saanen goats

Abstract

The aim of the study was to evaluate body condition score (BCS) and somatic cell count (SCC) of milk in Turkish Saanen goats. Data were obtained from 95 goats during the morning milking. While a 1–5 scale was used to assess BCS, direct microscopy was performed to analyse SCC. Effect of stage of lactation (SL) and number of kids at birth (NK) were evaluated in three subgroups. While SL has not affected the parameters, goats with a single kid had significantly higher BCS (P < 0.05) than goats with twins. Correlation coefficient between evaluated parameters was estimated as weak (r = 0.08). In conclusion, milk SCC and BCS levels of Turkish Saanen goats were assumed to be in acceptable thresholds.

Keywords:

• goat
• body condition score
• somatic cell count
• kid number
• stage of lactation

1. Introduction

Animal production has a great importance in Turkey's economic structure. In recent years, milking ruminants suitable for semi-extensive conditions have especially been preferred in the country. In this context, Saanen goat raising has pervaded in most of the goat farms. However, lack of data recording on yields is still an important problem to achieve more productivity and selecting quality breeder goat in many regions. For this purpose, analysing milk quality markers or keeping condition status of animals can be seen useful processes. Of the important markers, body condition score (BCS) is a reliable predictor of body fat deposit, and excessive low or high BCS can cause a decline in reproductive performance of goats (Yilmaz et al. 2011). Besides, microbial analysing of milk can be assumed the gold rule to determine more quality of raw milk. However, cheap and reliable indirect test can be applied in dairy enterprises (Atasever 2012). Of these tests, somatic cell count (SCC) is a credible and common method and basically, elevated SCC in milk indicates an abnormality in udder gland of a goat.

Maximum acceptable SCC in the USA is 10⁶ cells/ml, and this level is under discussion in the European Union countries (Berry & Broughan 2007). At the same time, heritability of SCC for Saanen goats was estimated to be 0.24 (Rupp et al. 2011), and this case clearly indicates that SCC is highly affected by environmental factors. Energy use by goats in different conditions and the role of SCC in intramammary infections and milk and cheese quality are inspected in depth by Argueello (2011). Also, in spite of some studies having been conducted on BCS or milk production characteristics in goats (Cetin et al. 2010; Yilmaz et al. 2011; Cimen & Topcu 2013), no knowledge has been reported on the relationships of BCS and SCC in Turkey. Moreover, revealing effects of some factors on production parameters could be beneficial for herd owners. The aim of the present investigation was to evaluate production parameters (BCS and SCC) in Turkish Saanen goats.

2. Materials and methods

2.1. Animal selection

The present work was conducted in a private farm in Samsun Province, which is located in the Black Sea Region of Turkey (41°43′N, 35°82′E and 171 m above the sea level). A total of 95 Turkish Saanen goats with three ages were used as the study material. The goats were milked two times in a day with machine and fed with similar conditions in the farm. Both BCS and SCC data were obtained during the morning milking time.

2.2. Body condition scoring

In BCS evaluation, feeling the amount of muscling and fat deposition over and around the vertebrae in the loin region of the goats were regarded. While a scale with 1–5 points was applied in the study, half or quarter scores were also used when needed. Scores were recorded as follows (Cimen & Topcu 2013):

• BCS 1: Spinous processes (SP) are sharp and prominent. Loin eye muscle is shallow with no fat cover.

• BCS 2: Loin eye muscle has little fat cover but is full.

• BCS 3: SP are smooth and rounded, and one can feel individual processes with pressure, loin eye muscle is full with some fat cover.

• BCS 4: SP can be detected only with pressure as a hard line, traverse processes cannot be felt and loin eye muscle is full with a thick fat cover.

• BCS 5: It is impossible to detect SP, and the loin eye muscle is very full with thick fat cover.

2.3. Milk sample collecting and somatic cell counting

Approximately 10–15 ml sample of milk was taken from each goat during morning milking time, and the samples were stored at +4°C using an ice-box until SCC test. No preservative material was added into raw milk samples. In SCC analysis, direct microscopy that is the reference method of International Dairy Federation (1995) was applied. In SCC analysis, dye solution was composed of 0.6 g certified methylene blue, 52 ml ethyl alcohol (95%), 44 ml tetrachlorethane and 4 ml glacial acetic acid (Atasever & Erdem 2013). Total number of fields counted per prepared slide was 40 and the working factor (WF) was 13225.

2.4. Statistical analysis

SCC values were transformed to log₁₀ for normality and homogeneity of variances. To evaluate parameters by stage of lactation (SL), three groups were occurred (<69 d, 70–94 d and >95 d). To determine the effect of number of kids at birth (NK) on the parameters, three subgroups were constituted (single, twins and triplet). The two parameters were examined by analysis of variance (ANOVA) and means were compared by Tukey's test (Onder & Cebeci 2009). The linear model was as follows: where; y_ijk is the observation value for SCC or BCS, µ is population mean, a_i is the effect of the NK (i = 1, 2, 3), b_j is the effect of stage of lactation and e_ijk is the random residual effect.

Also, distribution of BCS data were matched with three different groups (BCS = <2.75, 3 and >3.25).

All statistical analyses were performed using SPSS 17.0 for Windows at the 0.05 significance level.

3. Results

Descriptive values obtained in the present investigation are given in Table 1. It is seen that general mean of the SCC data was 1010400 ± 712168 cells/ml, and this value was found as nearby to 10⁶ cells/ml, which is suggested to be the highest threshold of SCC in goat milk used for human consumption (Schaeren & Maurer 2006; Berry & Broughan 2007). Besides, SCC mean of transformed values (logSCC) was calculated as 5.92 ± 0.24 in the study.

Table 1. Descriptive values of investigated parameters.

Parameter	n	Minimum	Maximum	Mean ± SD
SCC	65	212,080	4,241,600	1,010,400 ± 712,168
logSCC	65	5.33	6.63	5.92 ± 0.24
BCS	65	2.50	3.50	2.98 ± 0.22

Note: SCC: somatic cell count, BCS: vody condition score.

In the present work, BCS values ranged between 2.50 and 3.50, and the mean was 2.98 ± 0.22 (Table 1).

Changes of BCS and logSCC values by NK are given in Table 2. In BCS evaluation, BCS means of NK1 and NK2 groups (2.94 ± 0.22 and 3.06 ± 0.20, respectively) were found as statistically different (P < 0.05). In other words, BCS levels of goats with twins were higher than the levels of goats with single kid. Also, no significant difference was found between BCS levels of goats with triplet and BCS levels belonging to other groups. Similarly, no significant difference was determined among logSCC values by NK groups (Table 2).

Table 2. Change of two parameters by NK.

NK	n	BCS	logSCC
1	58	2.94 ± 0.22^a	5.91 ± 0.24
2	31	3.06 ± 0.20^b	5.97 ± 0.26
3	6	2.91 ± 0.20^ab	5.84 ± 0.19
Overall	95	2.98 ± 0.22	5.92 ± 0.24

Note: Different superscript letters in the same column indicate statistically significant differences (P < 0.05).

LS 1 = 1 (single kid), LS 2 = 2 (twins), LS 3 = 3 (triplet).

BCS: body condition score, SCC: somatic cell count.

Effects of SL on both parameters are shown in Table 3. It is seen that SL was not effective on the parameters, statistically. In SCC evaluation, logSCC mean was lowest in the first SL. But, in spite of a waved trend that was observed in logSCC values by SL (Table 3), no significant difference was determined among the groups.

Table 3. Change of two parameters (means ± SD) by SL.

SL	n	BCS	logSCC
1	27	2.98 ± 0.22	5.88 ± 0.28
2	46	2.98 ± 0.23	5.95 ± 0.24
3	22	2.97 ± 0.21	5.91 ± 0.21
Overall	95	2.98 ± 0.22	5.92 ± 0.24

Note: SL 1 = ≤69 days in milk, SL 2 = 70–90 days in milk, SL 3 = ≥91 days in milk.

BCS: body condition score, SCC: somatic cell count.

Distribution of logSCC values by BCS groups is presented in Figure 1. While a linear elevation in logSCC values was observed, no statistical difference was determined among logSCC means by BCS subgroups.

Figure 1. Distribution of logSCC values by BCS subgroups.

Note: SCC: somatic cell count, BCS = body condition score.

Correlations between BCS and logSCC are presented in Figure 2 and estimated correlation coefficient between two parameters was weak (r = 0.083).

Figure 2. Correlation between BCS and logSCC values (r = 0.08).

Note: SCC: somatic cell count, BCS = body condition score.

4. Discussion

In the study, obtained SCC mean clearly points out to some risks in milk quality or udder health due to its high level in the investigated goat farm. However, owing to SCC ranges that appeared between 212080 and 4241600 cells/ml, SCC levels could be reduced to lower thresholds in terms of basic husbandries applications. Actually, Delgado-Pertiñeza et al. (2003) emphasized that condensing hygienic practices and applying proper milking procedure are the main approaches to minimize milk SCC in goats. Obtained mean was lower than the results of some study findings of Lerondelle and Poutrel (1984), but higher than the study result of Persson and Olofsson (2011).

With a general term, BCS refers to fatness or muscle status of livestock, and thus, BCS data are commonly used for animal selection in the farms. Also, BCS levels of animals are related to reproductive performance and productivity (Serin et al. 2010). In this investigation, obtained BCS findings point out to desired levels for milking goats (Table 1). Besides, BCS mean of the study (2.98 ± 0.22) was higher than result of Serin et al. (2010) who conducted a study on Turkish Saanen goats.

In BCS evaluation by NK, no significant difference was determined between BCS levels of goats with triplet and BCS levels belonging to other groups (Table 2). Essentially, an adverse effect of multiple kids at birth is an expected result. Factors such as higher number of kids at birth, suckling and lactation stress can be assumed as the main reasons for negative energy balance if consumed energy amount is not sufficient for animal. Cimen and Topcu (2013) emphasized that the goats cannot eat enough to meet their energy need in early lactation in which body fat reserves are necessary to allow them to mobilize energy for high production. This negative case can be recognized by tissue mobilization and reduced BCS in body. Serin et al. (2010) reported that BCS has a significant effect on fertility of goats during the breeding season and the necessity of using higher energy feeding in goats with lower BCS. However, obtained alternative BCS results by NK groups in the present study might be caused by non-uniform sample numbers of each evaluated groups. In a contrast attitude, goats with twins would be fed in better conditions, but because no group feeding was applied in the farm, this concept could not be found as a true approach. Also, obtained insignificant difference among logSCC values by NK groups (Table 2) clearly indicates that NK was not an effective factor on SCC, which is assumed as a reliable reflector of udder health or raw milk quality for milking goats (Karzis et al. 2007). In contrast, Zumbro et al. (2004) reported that goats with multiple kids have shown significantly higher daily milk yield and SCC than goats with a single kid. Table 2 also shows that general production status of Turkish Saanen goats were in acceptable levels in semi-intensive conditions. However, conducting more studies focused on the relationship between NK and milk yield is advised to further researchers.

As seen from Table 3, BCS means by SL groups were highly analogous with general mean (2.98 ± 0.22). This finding indicates that BCS levels of Turkish Saanen goats have not changed throughout lactation period. Kocsisné et al. (2011) calculated the BCS at three different SL (at the beginning, in the middle and at the end of lactation) to be 2.5, 3 and 3.3, respectively.

In Figure 1, similar logSCC means by BCS subgroups are attractive. Although high BCS can results in some metabolic disorders in dairy animals, excessive loss in BCS may cause a failure in productivity (Yilmaz et al. 2011). Hussain et al. (1996) revealed that BCS at mating was positively correlated to kidding rate and negatively to reproductive losses. In this study, narrow ranges of BCS groups (between 2.75 and 3.75) might be the main reason of similar logSCC values. Presumptively, different statistical results might be obtained for logSCC when a 1–10 scale of BCS (Morris et al. 2002) would be used. However, further investigations on this subject are needed to confirm this assumption.

In Figure 2, an intense is attractive in 2.75 and 3.75 BCS columns. Determined weak correlation between two parameters can be assumed as an expected case. Actually, if this correlation had been estimated as high, this value would point out to a linear elevation in SCC levels. As mentioned earlier, high SCC of raw milk clearly refers to an abnormality in milk or udder health of animal. Moreover, in addition to BCS data, measuring udder traits could be advised as a useful process to goat selection for later lactations in the farms (Capote et al. 2006).

It is concluded that milk SCC levels of Turkish Saanen goats might be tolerable, and BCS levels could be assumed to be in acceptable thresholds. In this view, readjusting some managemental practices related to hygiene and milking procedure can primarily be suggested to achieve more productive herds.