Introduction

Red Sindhi cattle are the most popular of all Zebu dairy breeds. The breed originated in the Sindh province of Pakistan, they are widely kept for milk production across Pakistan, India, Bangladesh, Sri Lanka and other countries. The Red Sindhi range in color from a deep reddish brown to a yellowish red, but most commonly a deep red. They are distinguished from the other dairy breeds of Sindh and Tharparkar, both by color and form, the Red Sindhi being smaller, rounder, with a more typical dairy form, and with short, curved horns. It has been crossed with Holstein Friesian, Brown Swiss and Danish Red. It has also been used to improve beef and dual purpose cattle in many tropical countries, as the high milk production helps give a fast-growing calf which is ready for market at one year. Estimates of genetic parameters are available in most of the Indian cattle [Pundir and Raheja (1997), Hossain et al. (2002), Pundir and Singh (2007), Deb et al. (2008), Rehman et al. (2013) and Mishra et al. (2017)] but are scanty on Red Sindhi cattle. In the present study an attempt has been made to estimate genetic parameters (heritability and genotypic and phenotypic correlations).

Materials and Methods

Management

At Kalsi Red Sindhi cattle breeding farm, Dehra Dun, Uttarakhand feeding and management practices adopted were same for all the animals. Dry fodder includes wheat and rice straws. Concentrates are fed to cows according to their milk production. Cows are milked twice a day by hand milking, early in the morning and evening. In general animals are free from the diseases except some cases of mastitis. In this area, minimum and maximum temperature ranged from 8-10°C (December-January) to 48°C (June). This area experiences good rains in July-August.

Data

The data comprised 125 first lactation records of Red Sindhi cows, spread over a period of 22 years from 1994 to 2015 maintained at State Government Cattle Breeding Farm, Kalsi, Dehra Dun, (Uttarakhand), India, were used to estimate the genetic parameters of performance traits by mixed model. Cows having different abnormal and incomplete records due to sickness, abortion and death of calf within a week of calving were excluded from the study. The total duration of study was divided in to 4 periods, viz. P1 (1994-99), P2 (2000-04), P3 (2005-09), P4 (2010-15). Each year was divided in to 4 seasons, i.e. season 1(December-March), season 2 (April-June), season 3 (July-September) and season 4 (October-November). Traits considered in the study were first lactation milk yield (kg), first lactation length (days), first dry period (days) and first calving interval (days).

Methods

Due to non-orthogonal and disproportionate sub-class frequencies, the statistical analysis of the data was carried on by using LSMLMW, PC-2 version computer programme (Harvey, 1990) considering sire as random effect, period of calving and season of calving as fixed effects. The significant sub class differences were tested by the criteria of least critical difference (Snedecor and Cochran, 1967). Heritability and genetic correlations were estimated by Paternal half sib method (Becker, 1985).

Genetic Correlation (r_g)

Cov s _XY

r_{g (xy)}    =  √σ_s² _(X) σ_s² _(Y)

where,

X and Y are two different traits

Cov s_XY is sire component of covariance between traits X and Y.

σ_s² (X) and σ_s² (Y) are the sire component of variance for trait X and Y respectively.

Phenotypic Correlation (r_p)

Phenotypic correlation was estimated as-

Cov_s(XY) + Cov_e(XY)

            r_{p (xy)} =

                                             √ [σ_s² (X)+σ_e² (X)] [σ_s² (Y)+ σ_e² (Y)]

where,

Cov_s (XY) is the sire component of covariance between traits X and Y

σ_e² (X) and σ_e² (Y) are the error component of variance for traits X and Y, respectively.

Standardization and Normalization of Data

Culling in the middle of lactation, abortion, still-birth or any other pathological causes which affected the lactation yield were considered as abnormalities and thus, such records were not taken for the study. The outliers beyond two-standard deviation on both the tail ends of normal distribution were excluded from the data.

Results and Discussion

The least squares means of first lactation traits are presented in Table1. The overall least squares means of FLMY was 1561±47 kg, which was lower compared to an earlier report by Chauhan et al. (1976 ), who found the estimates of  2146.2 and Pundir and Singh (2007) who found the estimates of 1575±575 kg. The effect of season of calving on FLMY was non-significant, similar results were reported by Das et al. (1990) and Mustafa et al. (2002). This might be due to uniformity in the availability of feeds and fodders throughout the year and also due to adaptability of animals to local climatic conditions. The effect of period of calving on FLMY was found to be non-significant. Similar results were reported by Das et al. (1990) and Mustafa et al. (2002) in Red Sindhi cattle. The overall least-squares mean of FLL was observed to be 298±5 days and the effect of season of calving was found to be non-significant on FLL which was similar to the results of Taneja and Sikka (1981), Yadav et al. (1995) and Mustafa et al. (2002) in Red Sindhi cattle. In the present study autumn calvers were having lower lactation length (Table1). Period of calving was found to be non-significant. The results were contrary to those found by Mustafa et al. (2002) and Pundir and Singh (2007).

Table 1: Least square means and effect of season and period of calving on different traits

The overall least-squares mean of FCI was 456±10 days, though in autumn calvers FCI was found to be higher, no significant effect of season of calving was observed on this trait. Similar results were reported by Taneja and Sikka (1981), Yadav et al. (1995). However higher estimates of FCI were found by Patro and Rao (1983), Kar et al. (1987), Gogoi et al. (1993) and Pundir and Singh (2007). Period of calving was found to have significant effect on FCI (P≤0.05). A decreasing trend in FCI was observed from P1 to P4. The findings were similar to those put forward by Rao et al (1984) in Ongole, Tharparkar and Malvi. The average FDP (days) was found to be 124±1 days in Red Sindhi cattle which was lower in comparison to the reports of Pundir and Singh (2007) and Mustafa et al. (2002). Least squares analysis of variance revealed no significant effect of season, contrary to results of Mustafa et al. (2002) in Red Sindhi cattle. Period of calving had a highly significant effect on FDP. Significant effects were also reported by Vij et al. (1992) and Jat et al. (1996). However, Mustafa et al. (2002) found contrary to present results in Red Sindhi cattle.

Heritability Estimates

The heritability estimate (Table2) for FLMY was 0.15±0.051. The estimate was lower than  reports of Taylor et al (1979), Rao and Patro (1983), Rege et al (1992), Rahumathulla et al (1993) Gogoi et al  (1993), Hossain et al  (2002) and Pundir and Singh (2007). The moderate estimate of heritability indicated that the trait can be improved through direct selection. The heritability estimate for FLL was 0.20±0.036. Estimates of similar magnitude were reported by Rao and Patro (1983) and Hossain et al (2002). However, Rahumathulla et al. (1993) and Pundir and Singh (2007) reported lower estimate of heritability for LL than the present study.

Table 2: Genetic and Phenotypic correlations among different production trait

^*Genetic correlation below diagonal, phenotypic correlation above diagonal. Heritability is bold.

The heritability estimate of FCI was 0.12±0.046. Similar estimates of heritability for FCI were reported by Patro and Rao (1983) and Pundir and Singh (2007) and higher by Rahumathulla et al. (1993).The heritability estimate of dry period was 0.085±0.044. Taylor et al. (1979), Rahumathulla et al. (1993), Rao and Patro (1983) and Pundir and Singh (2007) reported higher estimates as compared to present study.

Correlation Estimates

The genetic correlation (Table2) coefficient of First lactation milk yield with Lactation length was 0.18±0.05 which is positive and highly significant. Similar estimates were found by Tomar and Singh (1981) in Sahiwal cattle. However, However, Khan (1987) reported higher estimate of genetic correlation (0.78) between the two traits in Holstein Friesian cows in Pakistan. The genetic correlation (Table2) coefficient of First lactation milk yield with First calving interval was 0.11±0.05, which is positive and highly significant. However, Mantysaari and Van Vleck (1989) and Khan et al. (1999) found higher estimates than present study in Holstein cattle. With First dry period (0.02±0.01) it was lowly correlated positive and significant. However, higher estimates were found by Katoch and Yadav (1990), who reported genetic correlation of 0.75±0.67 between the two traits in Jersey cattle. The genetic correlation coefficient of First lactation length with First calving interval (-0.20±0.11) is negatively correlated, highly significant and moderate and with First dry period (-0.04±0.02) is negatively, lowly correlated and significant. The genetic correlation coefficient of First calving interval with First dry period (0.10±0.10) was positive and non-significantly correlated. The most of traits were positive highly significant to significantly correlated. Thus we may conclude that selection for one trait will bring about improvement simultaneously in other production performance traits. The phenotypic correlation (Table2) coefficient of First lactation milk yield with First Lactation length was 0.27±0.12 and was positive and significantly correlated. However, Singh and Raut (1982), reported higher phenotypic correlation between the two traits as 0.40 in Indian village cows.  The phenotypic correlation (Table2) coefficient of First lactation milk yield with First calving interval was 0.25±0.11 which is positive and significantly correlated. However, Mantysaari and Van Vleck (1989) and Khan et al. (1999) found higher estimates than present study in Holstein cattle. With First dry period (0.03±0.01) it was lowly correlated positive and significant. The phenotypic correlation coefficient of First lactation length with First calving interval (0.13±0.05) is positively correlated, highly significant and moderate and with First dry period (-0.06±0.02) is negatively, lowly correlated and significant. The phenotypic correlation coefficient of First calving interval with First dry period (0.17±0.08) was positive and highly significantly correlated. The highly significant to significant phenotypic correlation of First lactation milk yield with lactation length may lead to the conclusion that Red Sindhi cattle can very well be selected on the phenotypic improved performance in terms of First lactation milk yield for future improved production performance.

Conclusion

It may be stated that the present estimates of heritability and genetic correlation of different economically important traits of Red Sindhi are within the normal range reported by others in different cattle population. However, the variations so far observed may be due to sample sizes, analytical models and environmental and production management systems. However, the information of present study may be used in planning future breeding activities for further improvement of the breed as well as other indigenous cattle genotypes of the country. The milk production traits which are significant positive genetically and phenotypically correlated may be considered for selection criteria to improve the production ability in Red Sindhi cattle.

Acknowledgement

Authors thank the officials and staff members of CBF, Kalsi Uttarakhand for providing necessary facilities and help during the study.

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