Introduction

The approach for genetic improvement needs to be systematically based through understanding of the genetic constitutions of the individuals in a population. Improvement in production and reproduction characteristics of indigenous breeds has become essential to make the dairy enterprise economically viable. The permanent improvement in performance characteristics of indigenous breeds can be brought about by changing their genetic composition through adopting appropriate breeding strategies. Tharparkar breed of cattle is very important breed of this ecophene and it is adapted to the hostile environment with extremes of temperature ranging from subzero to fifty degree Celsius, shadow of sand storms, recurrent famines and xerophyllic vegetation which are totally unsuitable for dairy animals (Kachawa, 1993). The breed is well adapted to hot climate and provide considerable amount of milk and economic assistance to the farmer with almost zero input.

Materials and Methods

The present study was designed by including different production and reproduction traits to evaluate performance of Tharparkar cattle during 1995-2014 from Livestock Research Station, Chandan, Jaisalmer.

The data of different production traits of Tharparkar cattle were collected from history sheets maintained at Livestock Research Station, Chandan, Jaisalmer for each individual cow with different sires, period (1995-2015) viz.; P₁ (1995-1999), P₂ (2000-2004), P₃ (2005-2009), P₄ (2010-2014), parity (I^st to VI^th) and season (winter, summer, monsoon, post monsoon) viz. S₁ (Dec to Feb), S₂ (Mar to Jun), S₃ (July to Sep), S₄ (Oct to Nov) were considered for present study. The data pertaining to individual cow’s production performance representing all the factors (sire, parity, period and season) were considered for the present study. The incomplete data of individual cows were eliminated from the present study. In this study the production and reproduction parameters taken into consideration were as follows days to reach the peak yield, peak yield,lactation milk yield, lactation length and milk yield per day of lactation Length

Statistical Methodology

The data on production and reproduction performance were subjected to the Least Squares Analysis Technique as outlined by Harvey (1976) of variance using following mathematical model.

Y_ijklm = µ+ K_i + L_j + P_k +S_l + e_ijklm

Where,

Y_ijklm = Indicate the observation of m^th cow of i^th sire

In j^th parity, k^th period and l^thseason

µ = Population mean

K_i = effect of i^th Sire (Sire K₁ to K₆)

L_j = effect of j^th Parity (Parity L₁ to L₆)

P_k = effect of k^th Period (Period P₁ to P₄)

S_l = effect of l^th Season (Season S₁ to S₄)

e_ijklm = The random error associated with Y_ijklm production and reproduction characters and assumed to be independently and normally distributed about a mean zero and with variance σ²e.

The corrected data was used for estimation of r_g. The formula for estimation of r_g is as under,

Cov_SXY

r_g(XY) =

√ [(σ²_SX) (σ²_SY)]

Where,

X and Y are the traits of the same individual

Cov_sxy = Sire component of Covariance between traits X and Y.

σ²_S X and σ²_S Y = Sire component of variance for traits X and Y, respectively.

The phenotypic correlations between different reproduction traits of Tharparkar will be calculated with following formula:

Cov_s(XY)+ Cov_e(XY)

r_p(XY)=

√ {[σ²s(X) + σ²e(X)] [σ²s(Y) + σ²e(Y)]

Where

Cov_s(XY)= Sire component of covariance between traits X and Y

Cov_e(XY) = Error component of covariance between traits X and Y

σ²e(X) and σ²e(Y) = Error component of variance for traits X and Y,respectively

σ²s (X) and σ²s(Y) = Sire component of variance for traits X and Y, respectively

Based on corrected data, heritabilities were estimated by Paternal Half-Sib correlation method as outlined by Hazel and Terril (1945).

Result and Discussion

Days to Reach Peak Yield

The overall Least Square Mean for days to reach peak yield (Table 1)for the Tharparkar cattle was recorded as 43.38 ± 0.66 days which were in close agreement with Bhutkar et al. (2014) 44.81±2.52 days in Deoni cattle. The higher days to reach peak yield were reported by Shingare (2012) as 79.38 ± 3.97 days in Deoni cattle; whereas lower days to reach peak yield was reported by Vohra et al. (2016) as 39.34 ±4.53 days in Belahi cattle. In present study the non-significant effect (Table 2) of sire, parity, period and season were observed which was in agreement with Bhutkar et al. (2014). The non-significant effect of sire, parity, period and season on days to reach peak yield in Tharparkar cattle might be due the fact that 40 days are required for involution of uterus and to retain cyclicity of ovary. As Tharparkar cattle being more cyclic animal so it exhibited peak yield immediately after pueperium and for which the period ranged between 41 to 46 days which is quite normal and comparable with other milch breed.

Table 1: Least Squares Means And Standard Errors For Days To Reach Peak Yield, Peak Yield,

Lactation Milk Yield, Lactation Length And Milk Yield Per Day Of Lactation Length Of Tharparkar

Cattle

Table 2: Least Squares Analysis of Variance (ANOVA) for Days to reach peak yield, peak yield, lactation milk yield, Lactation length sand milk yield per day of lactation length of Tharparkar cattle

* P<0.05; **P<0.01

Table 3: Genotypic correlation, phenotypic correlation and heritability of Days to reach peak yield, peak yield, lactation milk yield, lactation length and milk yield per day of lactation length of Tharparkar cattle

(Heritability estimates were shown on diagonal and genotypic and phenotypic correlation were shown above and below diagonal respectively)

* P<0.05; **P<0.01

Peak Yield

The overall Least Squares Mean (Table 1) of peak yield for the Tharparkar cattle was recorded as 12.71 ± 0.13 kg. The lower peak yield was reported by Kumar (2016) as 3.98 ±0.14 kg in Ongole cattle and Vohra et al. (2016) as 5.8 ±0.32 kg in Belahi cattle.

In present study the highly significant effect (Table 2) of sire and parity was observed on peak yield which was in agreement with Kumar et al. (2016) and season also has highly significant effect on peak yield whereas significant effect of period was observed which was in agreement with Patel et al. (2000) in Tharparkar cattle and Kumar et al. (2016) in Ongole cattle. The highly significant effect of sire on peak yield in Tharparkar cattle may lead to the conclusion that the sires with superior sire indices have contributed greatly in expressing the increased peak yield than the other sires. Similarly highly significant effect of parity may be indicative of the fact that as age and parity advances it has a direct bearing in improvement of body weight, physiological adaptation and full development of secretary glands of udder resulting into increased peak yield with increasing parity. The highly significant effect of season of calving on peak yield of Tharparkar cattle may be indicative of the fact that winter calvers are having significantly higher peak yield as compared to the other seasons and this might be due to availability of good quality leguminous fodder during winter season and vice-versa. The significant effect of period of calving on peak yield of Tharparkar cattle endorsed fact that the highly significant effect of sire, parity and season indicated that the peak yield is governed by genetic, physiological and seasonal variation but not by the cyclic changes of the periodicity.

Lactation Milk Yield

The overall LSM lactation milk yield (Table 1) was 2261.28±37.26 kg which is in close agreement with Chand (2011) as 2064.57±18.02 kg and Kamal kishore (2012) as 2021 ±42.806 kg in Tharparkar cattle. The lower lactation milk yield than observed in present study reported by Vataliya et al. (2013) as 1838 kg in Gir cattle; Kuralkar et al. (2014) as 910.95 ± 43.11 kg in Deoni cattle and Kumar et al.(2016) 678.84± 43.11 kg in Ongole cattle.

In present study the highly significant (Table 2) effect (P<0.01) of sire, parity, period and season on lactation milk yield of Tharparkar cattle were observed which was in agreement with Chand (2011); Kamal Kishore (2012) in Tharparkar cattle. The highly significant effect of sire, parity, period and season on the lactation milk yield in Tharparkar cattle may lead to the strong conclusion that genetic contribution from sire, physiological adaption with increasing parity, periodic improvement in set of management practices and season of calving are all the contributing factors with additive effect in expressing the lactation milk yield.The critical observation of the lactation milk yield in Tharparkar cattle has indicated that sire K3 and K1, K1 had superior performance in their progenies hence may be selected for future breeding. Similarly the gradual increase in lactation milk yield of Tharparkar cattle from parity L1 to L6 may be indicative of the fact that longevity of production with increasing trend and hence Tharparkar cattle can be economically reared up to 6^th lactation with maintained and increasing trend of lactation milk yield.

Lactation Length

The overall LSM lactation length (Table 1) was 294.93±2.58 days which were in close agreement with Gandhi et al. (2011) as 295.71±2.61 days in Sahiwal cattle. The lower lactation length were reported by Chand (2011) and Kamal Kishore (2012) as 279.19±3.271 days and 288.68 ± 3.14 days in Tharparkar cattle; Kuralkar et al. (2014) as 246.12± 1.77 days in Deoni cattle; Kumar et al.(2016) as 225.78± 9.70 in Ongole cattle, respectively. The higher lactation length were reported by Patel et al.(2000) and Gahlot (1999) as 327.13± 13.20 and 307.30± 1.08 days in Tharparkar cattle.

In present study the highly significant (Table 2) effect (P<0.01) of sire, period and non-significant effect of parity was in agreement with Kamal Kishore (2012) in Tharparkar cattle. The highly significant effect of season on lactation length observed in present study could not be supported by literature. The highly significant effect of period and season on lactation length of Tharparkar cattle may be indicative of the fact that periodic improvement in management practices and season of calving being non-genetic factors can alter the exhibition of this trait as the winter calvers have longer duration of lactation as compared to other seasons. Even though parity has exhibited non-significant effect on the lactation length of Tharparkar cattle but the critical observation has revealed longer lactation length in first parity and gradual decrease up to third parity and thereafter gradual increase up to sixth parity.

Milk Yield per Day of Lactation Length

The overall least square mean (Table 1) of milk yield per day of lactation length was observed to be 7.62 ± 0.10 kg which is in close agreement with Kamal Kishore (2012) and Chand (2011) as 7.44 ± 0.06 kg, 7.45±0.088 kg, respectively in Tharparkar cattle.The lower milk yield per day of lactation length was observed by Patel et al. (2000) and Gahlot (1999) as 4.65±0.13 litres, 6.12 ± 0.05 kg, respectively in Tharparkar cattle. In present study the (Table 2) highly significant (P<0.01) effect of period, parity and season whereas significant effect (P<0.05) of sire was observed which was in agreement with Kamal Kishore (2012) in Tharparkar cattle. The highly significant effect of parity, period and season and significant effect of sire on milk yield per day of lactation length may lead to the conclusion that physiological condition, set of management practices and environment interaction with genetics were very important factors deciding this trait in Tharparkar cattle.

Correlation

The genetic correlation (Table 3) coefficient of days to reach peak yield with peak yield (0.269) and lactation milk yield (0.210) were positive and highly significant; lactation length (0.061) positive and non-significant and milk yield per day of lactation length (0.189) was positive and highly significantly correlated. The genetic correlation coefficient of peak yield with lactation milk yield (0.881), lactation length (0.386) were positive and highly significantly; and milk yield per day of lactation length (0.638) was positive and highly significantly correlated. The genetic correlation coefficient of lactation milk yield with lactation length (0.708) was positive and highly significantly correlated and milk yield per day of lactation length (0.730) was positive and highly significantly correlated. The genetic correlation coefficient of lactation length with milk yield per day of lactation length (0.174) was positive and highly significantly correlated. The most of traits were positive highly significant to significantly correlated which may concluded as selection for one trait will bring about improvement simultaneously in other production performance traits.

The phenotypic correlation (Table 3) coefficient of days to reach peak yield with peak yield (0.111), lactation milk yield (0.124)were positive and significantly correlated; lactation length (0.047) was positive and non-significantly correlated and milk yield per day of lactation length (0.138) was positive and highly significantly correlated. The phenotypic correlation coefficient of peak yield with lactation milk yield (0.725), lactation length (0.290) and milk yield per day of lactation length (0.728) were positive and highly significantly correlated. The phenotypic correlation coefficient of lactation milk yield with lactation length (0.644) and milk yield per day of lactation length (0.839) were positive and highly significantly correlated. The phenotypic correlation coefficient of lactation length with milk yield per day of lactation length (0.147) was positive and highly significantly correlated. The highly significant to significant phenotypic correlation of peak yield with lactation milk yield, lactation length and milk yield per day of lactation length may lead to the conclusion that Tharparkar cattle can very well be selected on the phenotypic improved performance in terms of peak yield for future improved production performance.

Heritability

The heritability estimate (Table 3) for days to reach peak yield was 0.12±0.07. The heritability estimate for peak yield was 0.12±0.1 which was in close agreement with Kumar et al. (2016) as 0.14±0.03 in Ongole cattle. The heritability estimate for lactation milk yield was 0.19±0.06 which was in close agreement with Kamal Kishore (2012) as 0.19 ±0.071 in Tharparkar cattle. The heritability estimate for lactation length was 0.23±0.08 which was in close agreement with Chand (2011) and Kamal kishore (2012) as 0.27 ± 0.14 and 0.24± 0.088 in Tharparkar cattle. The heritability estimates for milk yield per day of lactation length was 0.05±0.04 which was in agreement with Kamal Kishore (2012) as 0.05± 0.045 in Tharparkar cattle. The low to moderate magnitude of heritability of production traits indicated that, these traits are mostly governed by the management hence could be improved by efficient management, proper care and feeding during lactation.

Conclusion

The overall improved productive performance over the period of last 20 years may be attributed to the rigorous selection of good individuals and culling of the low performing individual Tharparkar cattle at Livestock Research Station, Chandan, Jaisalmer, RAJUVAS, Bikaner and hence this herd may be classified as open nucleus breeding herd of Tharparkar for future breeding and further improvement of the breed. It is universally accepted fact that the sires are half of the herd in contributing the production performance traits so it can be concluded that the significant effect of sires on almost all production traits under study is indicating that selection of sires can bring improvement in production traits of Tharparkar cattle. The significant to highly significant effect of non-genetic factors (parity, period and seasons) play important role in performance of animal so higher emphasis on management practices, nutrition, health cover will help in improving the production of animal. The low to moderate heritability observed in most of the traits under study indicated that improvement in management practices can further enhance the better expressibility of these production traits.

References

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