Analysis of different non-genetic factors affecting production performance of Murrah buffaloes

Livestock sector as a component of Indian agriculture sector contributes 25.6 per cent in agricultural GDP and 4.11 per cent in total GDP, further dairy farming alone contributes 18.0 per cent in agricultural GDP in India (DAHD, 2017). India possess the largest (108.70 million) buffalo population of the world and produces 51.17 per cent (74.71 million tons) of total milk production (DAHD, 2017). Buffaloes have immense agricultural importance by virtue of their high production potential through milk and meat, besides being a source of sustenance to poor and marginal farmers as well as landless labourers in the developing world. The majority of well-defined breeds of buffalo are native of India and the Murrah buffalo is one such breed. It originated in valleys of Haryana (Jhajjar, Rohtak, Jind) and is considered as most suitable dairy buffalo breed and has now spread all over the world.
       
In order to enhance the productivity of dairy animal through efficient selection programme, it is necessary to develop an understanding of the factors affecting its milk production. There are many factors which influence the phenotypic expression of performance traits. Therefore, the present investigation was conducted to study the effect various non-genetic factors on production traits in Murrah buffaloes.
       
Data for the present study were collected from pedigree and production records of Murrah buffaloes (up to 4^th lactation) maintained at Directorate of Livestock Farms, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab from 2001 to 2016. The study was on conducted on 2,67,599 DMY records of 445 Murrah buffaloes of 171 sires. The production data were classified into 4 periods with four years duration (2001-2004, 2005-2008, 2009-2012 and 2013-2016); four parity groups (1^st, 2^nd, 3^rd & 4^th parity); six periods of birth of 4 years duration (1990-1993, 1994-1997, 1998-2001, 2002-2005, 2006-2009 and 2010-2013); five seasons of calving viz. summer (April to June), rainy (July to August), autumn (September to October), winter (November to January) and spring (February to March) and ten stages of lactation with 30 days duration viz. stage I (6-35 days), II (36-65 days), III (66-95 days), IV (96-125 days), V (126-155 days), VI (156-185 days), VII (186-215 days), VIII (216- 245 days), IX (246-275) and X (276-305 days). The milk production traits included in the study were daily milk yield (DMY), 305-day milk yield (305MY), total lactation milk yield (TLMY), peak yield (PY), days to attain peak yield (DPY) and lactation length (LL). Lactation records of less than 200 days’ length or less than 1000 kg of TLMY, and abnormal records like abortion, still birth as well as data from experimental animals, sold or auctioned animal and break lactation records were excluded for analysis.
       
SAS version 9.3 (Statistical Analysis System, Cary, USA) was used for statistical analysis of data. The following least-squares analysis fixed model was used:

 
                         Y_ijklm= µ + P_i + Pa_j + Pb_k+ LS_l­+ e_ijklm

 

Where,
Y_ijklm (record of  m^th individual in l^th stage of lactation, k^th period of birth, j^th parity, calved in i^th period), µ (overall mean), Pi (fixed effect of i^th period of calving), Pa_j (fixed effect of  j^th  parity), Pb_k (fixed effect of k^th period of birth), LS_l (fixed effect of l^th stage of lactation) and e_ijklm (random error associated with each observation and assumed to be normally and independently distributed with mean zero and variance s²e). The effect of stage of lactation was estimated for DMY while effect of season of calving was estimated for other production traits. Difference of least-squares means between subclasses for each effect was tested by Tukey-Kramer method (Kramer, 1956). 
       
The analysis of variance showed significant effect of non-genetic factors on daily milk yield and other production traits. The least-squares means of production traits of Murrah buffaloes in different classes of non-genetic factors considered in the study are presented in Table 1.
 

       
Period of birth was significantly affected (p<0.05) DMY, 305MY, PY and DPY while non-significant effect was observed for TLMY and LL. The highest daily milk yield and peak yield was observed in the animals born during the period of 1990 to 1993. There was decreasing trend observed for DMY and PY over the periods of birth. Several reports indicate significant effects of period of birth, period of calving, parity, and stage of lactation on daily milk yield Sigdel et al., (2015) and Hassan et al., (2017).
       
The period of calving had significant effect (p<0.01) on DMY, 305MY, TLMY and PY while LL and DPY were not significantly affected by period of calving. Increasing trend was observed over the periods of calving for daily milk yield, 305-day milk yield, total lactation milk yield and peak yield. The increasing trend indicated the persistent improvement in post-parturient care and management of buffalo cows at the organized herd. Pandey et al., (2015) and Jakhar et al., (2016) reported highly significant (p<0.01) effect of period of calving on TLMY and 305MY in Murrah buffaloes. While non-significant effect of period of calving on TLMY and 305MY was reported by Pawar et al., (2012) and Kumar et al., (2014) and on LL was reported by Jamuna et al., (2015) and Sigdel et al., (2015). The difference in performance of the animals among different periods might be attributed to differences in management practices, change in herd size, sires used for breeding, agro climatic conditions and variations in feed and fodder availability.
       
Significant effect of parity (p<0.05) was observed on all the production traits, except TLMY. However, there was a significant difference between parities, but no significant difference was observed in DMY second parity onwards as well as between performance of second, third and fourth parities of other production traits. Thiruvenkadan et al., (2015) and Jakhar et al., (2016) revealed highly significant (p<0.01) effect of parity on TLMY and PY in Murrah buffaloes. The highest DMY and PY were observed during third parity indicating that lacational maturity is attained in the third lactation, while highest LL and DPY were estimated in the first parity. The findings were in agreement with Hassan et al., (2017), Verma et al., (2016), Jamuna et al., (2015).
       
Changing body physiology across the lactation stages significantly (p<0.01) influenced the DMY in Murrah buffaloes. The animals attained the peak yield during the second stage of lactation (36 to 65 days), while lowest least-squares mean of DMY of Murrah buffaloes was found as 5.18±0.02 kg in tenth stage (276 to 305 days of lactation). All the stages were significantly different with a non-linear trend in DMY as per the standard lactation curve of animal (Fig 1).
 

       
The season of calving had significant effect (p<0.05) on PY and DPY, while non-significant effect was observed on 305MY, TLMY and LL. Buffaloes calved during winter had highest TLMY and PY, while buffaloes calved in autumn had maximum DPY. Non-significant effect of the factor on 305MY was observed by Jakhar et al., (2016), TLMY and PY by Sigdel et al., (2015) and Das et al., (2015); and on LL by Thiruvenkadan et al., (2014). Significant effect of the factor on PY and DPY was observed by Thiruvenkadan et al., (2014).

This study revealed that the non-genetic factors like period of birth, parity and season of calving had significant effect on all the production traits except TLMY.  Murrah buffaloes were found to attain optimum performance by the second and third parity. Further, the study revealed that calvings during winter season had favorable impact on production performance of buffaloes. The difference in production traits over different periods may be attributed to differences in nutrition, herd size, agro climatic conditions and managemental practices. Genetic improvement through selection in a breeding program depends on the accuracy of identifying genetically superior animals. Therefore, it can be concluded that environmental factors influenced the performance of buffalo herd, and their adjustments needed due emphasis for an efficient selection programme.

The authors would like to express their gratitude to Director Livestock Farms, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab for providing necessary facility and support for carrying out the research work.