Assessment of disposal patterns in Murrah and Nili-Ravi buffaloes

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Bharadwaj, A. K. Chaurasiya, Y. Bangar, S. Khanna, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4621403/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The current study was carried out to look into the disposal patterns of Murrah and Nili-Ravi buffaloes kept at ICAR-CIRB, Hisar and Sub-Campus Nabha, Punjab, respectively. The purpose of the investigation was to estimate the various non-genetic factors affecting culling and mortality patterns in buffaloes to suggest suitable health management practices, selection, and breeding strategies for enhancing genetic gain in buffaloes. From 1983 to 2017, 1180 data of 679 Murrah and 501 Nili-Ravi were used to calculate the frequency of culling and death. The impacts of several parameters on disposal were explored, including breed, period of disposal, season of disposal, and lactation completed. The findings revealed that in Murrah, 90.72% of buffaloes were disposed of due to culling and 9.28% due to mortality. While, in the instance of Nili-Ravi, animal disposal due to culling accounted for 89.62% of the total, with mortality accounting for 10.38%. The main reason for culling was old age and low production, while the majority of buffaloes died from cardiovascular, digestive, and respiratory problems. Furthermore, the effect of season was highly significant (p < 0.01) on the pattern of culling in buffaloes. Additionally, majority of the animals culled in the winter season, followed by summer and most of the animals culled were old aged (45 and 22%), low yielder (35 and 27%) and affected with mastitis (30 and 28%), respectively in both the winter and summer seasons. Moreover, the effect of period of disposal was highly significant (p < 0.01) on the both pattern of mortality and culling in buffaloes. Further, maximum (34%) number of animals culled in the period 1994-98 due to old age whereas lowest culling rate (3%) was seen during 2014 to 2018. In this sequence, it may be determined that the reason for disposal differs depending on the breed, period, season and lactation completed.As a result, our efforts should be directed towards improving management practices with the goal of lowering the rate of culling and mortality, which leads to higher lifetime performance and, as a result, the overall efficiency of the dairy farm. Breed Culling Disposal Mortality Murrah Nili-Ravi 1. INTRODUCTION India leads the globe in milk production (230.58 million tonnes), which has climbed by 3.83% over the previous year. In addition, per capita availability of milk up to 459 g/day has also recently been reached. Furthermore, buffalo accounts for around 44.81% of total milk output in the country with increament of 3.69% as compared to previous year and are well adapted to subtropical climates such as India. India ranks first in the total buffalo number and accounts for roughly 56.7% of the total global buffalo population. The overall number of buffaloes in the country is 109.85 million (54% of the world buffalo populatin), a 1.1% rise from the previous livestock census (DAHD 2023). According to DAHD 2023, India accounts for 75% of the global buffalo milk production. During 2022-23, the export of raw hides and skins of bovine (including buffalo) or horse totals Rs. 10.78 crore. In India, buffalo is the primary dairy animal, and it continues to be a vital source of revenue, nourishment, and employment for the country's enormous rural population (Tamboli et al., 2022 ). It is a quadruple-purpose animal, ideal for milk, meat, draught, and leather. The Murrah and Nili-Ravi breeds of milk producing buffalo have the best genetic material in the country. It has been regarded as one of the best global buffalo breeds, capable of producing high fat milk as well as meat (Tamboli et al., 2020 ). Futher, the buffaloes have spread across the entire country, with different population densities, with the bulk situated in the north and west. Murrah is a native of Haryana, and Nili-Ravi is found in the state of Punjab, primarily in the Ravi River valley. Moreover, the success of the dairy sector is dependent on the health of the livestock, since improved health enhances dairy farm output. Furthermore, animal disposal patterns include culling as well as mortality for a variety of reasons. Culling is the process of eliminating animals from a herd for specified purposes, most notably to remove undesirable qualities from the herd while retaining profit. Animals that are less productive or have health issues are culled through auction. Culling based on the poor output allows for the retention of high yielders for faster genetic improvement (Gupta et al. 2015 ). In addition, the main cause of the decrease in lifetime productivity and longevity is culling and adult mortality (Ilieva and Peeva 2007 ). Because an animal will have fewer lactations if culling or mortality occurs early in life. A high death rate also indicates poor management practices and is expensive for dairy producers as it eliminates superior genotypes from the herd and reduces the availability of young dairy stock for breeding. Therefore, it is essential to investigate the reasons behind animal disposal. Furthermore, according to Taraphder et al. ( 2011 ), the three main causes of culling in buffaloes were udder complications (22.76), insufficient milk production (24.01), and reproductive issues (38.62). According to Do et al. ( 2013 ), the biggest reason for culling (44%) in dairy cattle husbandry is failure to conceive during the first lactation. Animal disposal owing to mortality diminishes productive and herd life, which has a negative impact on their lifetime production performance (Taraphder et al. 2011 ). Moving further, there are numerous reasons for disposals, which vary according to breed, period, season, and number of lactations completed. Knowledge of disposal reasons and their management is critical for a healthy and profitable dairy enterprise. An examination of the literature revealed that observations on the effect of several characteristics such as breed, period of disposal, season of disposal, and number of lactations completed on the disposal patterns of Murrah and Nili-Ravi buffaloes are limited, particularly in Northern India's humid subtropical climate. Hence, this study was done to analyse the influence of various non-genetic factors on the culling and mortality patterns in buffaloes in order to recommend appropriate health management practises, selection, and breeding approaches for the genetic improvement of the buffaloes. 2. MATERIALS AND METHODS 2.1 Data collection The data on reason of disposals pertaining to Murrah and Nili-Ravi buffaloes was collected from the history sheet of animals for a period from 1989 to 2018 (29 years) maintained at ICAR-Central Institute for Research on Buffaloes, Hisar and Sub-Campus, Nabha, Punjab. The data for all the buffaloes born and calved in the farms was recorded up to the date of death/ disposal. The animals completed minimum of three lactations with minimum lactation length > 150 days and production > 1000kg for first lactation were selected. The data was collected on disposal records of 1180 adult buffaloes which included 679 Murrah and 501 Nili-Ravi. The reasons for culling of adult buffaloes were classified as old age, low yielder, mastitis, reproductive, health problems and other. Whereas, reasons for mortality were categorized as digestive, respiratory, reproductive, cardiovascular disorders, accidental deaths and other. The data was uniformly classified according to breed, period of disposal, season of disposal and number of lactations completed. The complete data were grouped into Murrah and Nili-Ravi breed. Period of disposal (1989 to 2018) was divided into six groups each consisting of five consecutive years. Each year was further delineated into four seasons of disposal according to geo-climatic conditions in the area viz. summer (April to June), rainy (July to September), autumn (October to November) and winter (December to March). The data on disposal traits were further classified according to the number of lactations completed into five categories namely three, four, five, six, seven & above. 2.2 Model and statistical analysis The IBM SPSS Statistics 20.0 software (Snedecor and Cochran 1994 ) was used to estimate the effects of various non-genetic factors and the results were interpreted in the tabular form. The rates of animals disposed from the herd were calculated by frequency distribution using descriptive statistics. The statistical significance between various reasons of culling and mortality with different factors was assessed using Chi-square test. The statistical significance was considered if P < 0.05. 3. RESULTS AND DISCUSSION 3.1 Disposal in Murrah and Nili-Ravi buffaloes Out of 679 Murrah buffalo 616 (90.72%) disposed due to culling and 63 (9.28%) due to mortality. In total 449 (89.62%) Nili-Ravi buffaloes were culled whereas mortality accounted for 52 (10.38%) out of 501 animals disposed during the same period of the study (Table 1 ). Appropriate housing, feeding, and other farm management techniques may have contributed to the buffaloes' lower mortality rate. However, Bangar et al. ( 2014 ) reported mortality rate of 7.98% in buffaloes of Maharastra region and overall mortality rate in bovine was reported 9.14% by Chaudhary et al. ( 2013 ) in Himanchal Pradesh. However, according to an investigation, Surti buffaloes had an overall mortality rate of 2.83 percent (Patel et al., 2017 ). Furthermore, according to Prasad et al. ( 2004 ), the average overall mortality in Sahiwal, Tharparkar, Karan Swiss, and Karan Fries was 14.35%, 7.21%, 17.12%, and 13.46%, respectively. Additionally, it was observed that the herd's overall breeding female culling rate was 14.3%, whilst the herd's overall mortality incidence was 1.1%. 6.9%, 6.4%, and 11.6% of the variation was explained by the herd when it came to disposal for any cause, culling, and mortality, respectively. After taking herd clustering into consideration, the estimated incidence rate of inventory loss for any cause was 19.8% (Waldner et al., 2009 ). However, Taraphder et al. ( 2011 ) found that 5.34 percent of buffaloes died for various reasons overall. Additionally, Ravi and Tomar ( 2021 ) noted that a number of reasons, including death (28.40%), culling (20.75%), transfer (39.92%), and stillbirths (3.28%), were cited for the animals' removal from the herd. Furthermore, according to Taneja et al. ( 1989 ), of the cows that were disposed of, 52.67% were auctioned, 15.78% were moved to different herds, 5.08% were killed, and 26.47% died. Mukerjee and Tomar (1997) found that the mortality rate of crossbred dairy cattle was higher than this, at 44.0%. Additionally, Jana et al. ( 1998 ) observed that mortality in crossbred cattle was 49.6% and the culling rate was 28.5%. Table 1 Overall culling and mortality pattern in Murrah and Nili-Ravi buffaloes Breed Total Culling (No.) Died (No.) Culling rate (%) Mortality rate (%) Murrah 679 616 63 90.72 9.28 Nili-Ravi 501 449 52 89.62 10.38 Total 1180 1065 115 90.25 9.75 3.1.1 Culling and mortality pattern in buffaloes The reasons for culling and mortality in the buffaloes during the period from 1989 to 2018 are presented in Table 2 . Among the buffaloes, out of culled animals (1065), the major reason of culling was old age and low milk production which accounted around 27 and 22%, respectively of total culling. Further, reproductive problems constituted 19% followed by mastitis (18%) and other health problems (6%). The other health problems comprised of lameness, abscess on knee joints, rheumatic arthritis, chronic arthritis, weakness, eye blindness, severe chronic eye injury, hide bound condition, tumour, hip deformity, pelvic deformity, fracture, herniation of reticulorumen and nervous symptoms.. In all about 9% animal culled by miscellaneous factors which includes off breed, wide horn, loose horn and white star on forehead in Murrah while, off breed and drooping horn in case of Nili-Ravi breed. Reproductive problems cover metritis, infertility, post-partum anoestrus, pyometra, cystic ovary, post-partum prolapse, cervical tumour, abortion and retention of placenta. Major reason for culling of animals was observed to be low milk production, reproduction problems and mastitis. Therefore, the management of animal diet and the execution of a genetic improvement program within the herd should receive more attention in order to enhance animal's genetic potential. The timely diagnosis of estrus, prompt artificial insemination, and care of pregnant animals are more areas that require attention in the realm of reproduction management. To stop mastitis and other illnesses from occurring in the animals, the animal shed needs to be kept clean and hygienic. Maintaining an animal's health and welfare requires prompt vaccination. These will lessen the need to cull high-yielding animals that ought to give more genetically to the next generation. More culling of low producers, however, allows us to keep high yielders, which accelerates genetic development in the herd's ability to produce milk. Ahmad ( 1999 ) found, in line with our results, that the primary cause of culling in Murrah buffaloes (31.3%) and Nili-Ravi buffaloes (27%), was inadequate milk output. Gupta et al. ( 2015 ) also examined the culling cycle and found that the largest percentage of buffaloes culled for insufficient milk production (30.77%) were followed by those culled for problems with reproduction (30.39%), old age (14.76%), disease (9.64%), health type (8.89%), and other conditions (5.55%). This indicated that reduced milk production and issues with reproduction accounted for nearly two thirds of culling (61.06%). Accordingly, Malhotra and Parmar ( 2005 ) discovered that the majority of dairy cattle were culled due to inadequate milk output. Furthermore, the results of Peeva and Ilieva ( 2007 ) illustrate that the buffaloes culled for gynecological reasons were highest (41%), followed by low productivity (19%), prolapsed (11%), short lactations (7%) and old age (9%). Similarly, Taraphder et al. ( 2011 ) reported that reproductive problems (38.62%), low milk production (24.01%) and udder problems (22.76%) as the three major reasons of culling. On the other hand, Do et al. ( 2013 ) noticed that the primary reason for culling (44%) was due to failure to conceive in first lactation in dairy cattle. In addition, Upadhyay et al. ( 2014 ) concluded that most of the adult cows were culled because of teat, udder and reproductive problems from the herd. Furthermore, lameness, cancerous eyes, and lumpy jaws frequently led to the culling of animals (Roeber et al., 2001 ). The different reasons of mortality in the buffaloes are depicted in the Table 2 . Out of total 115 animals disposed due to mortality in buffaloes, the maximum mortality occurred due to cardio-vascular (31%), followed by digestive (27%), respiratory disorder (23%), reproductive (6%) and accidental deaths (5%). Additionally, the animals died due to miscellaneous factors accounted 23%. Further, respiratory disorder includes pneumonia, adhesions in lungs and tuberculosis. Cardio-vascular disorder consists of haemorrhagic shock, traumatic pericarditis and septicaemia. Digestive disorder includes hepatitis, gastro-enteritis, peritonitis, tympanitis and traumatic reticuloperitonitis. The reproductive disorders comprise of endometritis, dystocia, post-partum prolapse and rupture of uterus. Furthermore, accidental deaths cover electrocution, drowning, trauma and snake bite. Whereas, nervous disorder, paralysis, parasitic diseases, nephritis and old age were included under the miscellaneous factors. In conformity with the finding, Taraphder et al. ( 2011 ) in Murrah buffaloes observed that the maximum mortality occurred due to digestive problems which accounted for 30.89% followed by cardio-vascular problems (26.02%), respiratory problems (21.14%), parasitic problems (8.13%) and uro-genital problems (5.69%). In some other studies, the highest adult mortality occurred due to digestive disorders (33.62%), respiratory disease (29.28%) and various other diseases (17.48%) (Rathore 1998 ). Conversely, acute illnesses (such as bloat) or infectious diseases were typically the cause of farm deaths, according to Waldner et al. ( 2009 ). Additionally, they showed that nutritional and feeding-related issues, such as traumatic reticuloperitonitis, rumen tympany (bloat), myopathy (possibly linked to a deficiency in vitamin E or selenium), nitrate toxicity, and polioencephalomalacia, were the most frequent causes of animal mortality. These together accounted for 21 percent of all fatalities. According to Patel et al. ( 2017 ), the leading cause for mortality in Surti buffaloes was pneumonia (23.89%), which was followed by diarrhoea (15.93%), debility (15.93%), septicemia (15.04%), unintentional fatalities (9.74%), blood protozoan infections (6.20%), snake bite (5.30%), and other causes 7.98%. Table 2 Various reasons of culling and mortality pattern in buffaloes Culling pattern Mortality pattern Reason Number % Reason Number % Old age 287 26.95 Cardiovascular 31 26.96 Low yielder 237 22.25 Digestive 27 23.48 Reproductive 202 18.97 Respiratory 23 20 Mastitis 187 17.56 Miscellaneous 23 20 Health problems 61 5.73 Reproductive 6 5.22 Miscellaneous 91 8.54 Accidental 5 4.35 Total culled 1065 100.00 Total died 115 100 3.1.2 Culling of buffaloes based on various factors 3.1.2.1 Breed wise culling Highly significant (p < 0.01) effects of breed were noticed on the culling pattern of buffaloes (Table 3 ). The number of animals culled due to old age was significantly higher in case of Murrah when compared with Nili-Ravi. Similarly, Waldner et al. ( 2009 ) also reported that rate of culling increases with the advance in age of animals. While, the number of animals discarded owing to low milk production and mastitis were greater in the Nili-Ravi breed. Furthermore, greater number of animals among Murrah breed were removed from the herd as a consequence of reproductive, health problem and miscellaneous factors in comparison with Nili-Ravi breed of the buffaloes. Taneja et al. ( 1989 ), on the other hand, observed that the rationales for animal disposal were not breed-specific. 3.1.2.2 Period wise reason of culling in buffaloes Period wise reason of culling in the buffaloes is presented in the Table 3 . Effect of period of disposal was highly significant (P < 0.01) on the culling pattern in buffaloes. Further, maximum (34%) number of animals culled in the period 1994-98 due to old age whereas lowest culling rate (3%) was seen during 2014 to 2018 depicting decreasing trend of culling across the periods which may be attributed to the fact that the different aspect of management practices was improved with the passage of time in the dairy farm. Moreover, highest number of buffaloes culled owing to low milk production between 1999 to 2003 while, the number of animals discarded because of mastitis were more from the period 2004 to 2013. Moving further, the buffaloes removed on account of reproductive problems accounted major proportion between 1999 to 2008. Moreover, highest number of animals (31%) culled due to health problems during 2009 to 2013. Additionally, majority of the culling occurred due miscellaneous factors from the year 2004 to 2008 besides other group of periods. Additionally, alterations in the culling pattern of buffalo herds across time periods may be ascribed to disparities in breeding sires, environmental circumstances, management practices, and the availability of forage and fodder. Similar to our findings, the culling rate was found to be the lowest in the last period, showing an improvement in production, reproduction, and herd health management over time. Furthermore, it was discovered that the last period's productivity, reproduction, health and management methods, and other environmental elements were optimal because only a small number of buffaloes were culled (Taraphder et al. 2011 ). In keeping with the findings, Gupta et al. ( 2015 ) found a substantial effect of period on culling pattern in Murrah buffaloes. They also observed that the largest prevalence of culling occurred between 1975–1980, followed by 1991–1995. Juneja et al. ( 1991 ) and Malhotra and Parmar ( 2005 ) conducted studies on crossbred cow herds, which support our findings. 3.1.2.3 Season wise incidence of culling in buffaloes It is evident from the Table 3 that the effect of season was highly significant (p < 0.01) on the pattern of culling in buffaloes. Further, majority of the animals culled in winter season, followed by summer. Similarly, Gupta et al. ( 2015 ) found a significant effect of season on culling in Murrah buffaloes, reporting higher culling in the winter (22.76%), followed by summer (22.31%) and spring (21.49%). Our findings are similarly consistent with those of Tomar and Rawal (1996), who studied dairy cattle herds. While, Waldner et al. ( 2009 ) noticed that the incidence of culling was highest during the monsoon season, followed by the winter, spring, and summer seasons. Most of the animals culled were old aged (45 and 22%), low yielder (35 and 27%) and affected with mastitis (30 and 28%), respectively in both the winter and summer seasons. Furthermore, the other causes of culling were reproductive and health problems, observed to be highest in the winter and autumn season, respectively. In this line, miscellaneous factors accounted major reason of culling during both winter and summer seasons. The results were in accordance with the findings of Shivahre et al. ( 2014 ) in Murrah buffaloes. 3.1.2.4 Reason of culling in different groups of lactation completed in buffaloes The perusal of the Table 3 revealed highly significant (p < 0.01) influence of lactation completed on the culling patterns in buffaloes. In addition, old age constituted major cause of culling among the animal completed 7 and above lactations while, the animals culled due to low milk production were mostly from the parity 3 as well as 4. Further, the majority of the animals discarded due to mastitis (24%) and reproductive problems (27%) had completed 3 lactations. Moreover, removal of the animals because of health problems were of mostly 7 and above parity. Whereas, maximum number of animals culled due to miscellaneous factors were from the set of animals completed 4 lactations. In line with the findings, Gupta et al. ( 2015 ) found that lactation completed (parity) had significant impacts on culling patterns in Murrah buffaloes. Furthermore, they showed that the majority of animals were culled in the first lactation (23.14%), followed by the second lactation (16.93%), and so on. In lactation no. 1st, 3rd, 4th, and 5th, the majority of animals were culled due to low milk production, followed by 2nd lactation, in which the majority of animals were culled due to reproduction-related problems, and in 6th and above parity, animals were culled owing to senility, i.e. old age, because after 6th and above parity, the animal becomes susceptible to various diseases. In this line, similar culling pattern was observed in Hariana cattle (Kumar 1999 ). Major reason of culling was old age, low production, mastitis, reproductive and health problems in all the set of parity. Additionally, similar rhythm of culling was also reported by Rawal and Tomar ( 1998 ) in Tharparkar breed. Furthermore, up to third parity, the largest rate of culling as a result of reproductive issues was noted. With the exception of lactations six and above parity, culling rates for general debility (health problems) was essentially same across all lactations (Taraphder et al. 2011 ). Table 3 Factors associated with culling pattern (%) of Murrah and Nili-Ravi buffaloes Factor Old age Low yielder Mastitis Reproductive Health problems Miscellaneous Chi-square Breed Murrah 90.59 35.86 36.90 50.99 54.10 72.53 219.10** Nili-Ravi 9.41 64.14 63.10 49.01 45.90 27.47 Period 1989-93 27.87 14.35 1.60 3.96 1.64 0.00 354.66** 1994-98 34.49 8.86 8.02 10.40 3.28 0.00 1999-03 15.68 24.47 22.46 23.76 13.11 18.68 2004-08 12.20 23.63 23.53 23.27 24.59 47.25 2009-13 6.62 12.24 23.53 18.81 31.15 29.67 2014-18 3.14 16.46 20.86 19.80 26.23 4.40 Season Summer 21.95 27.00 27.81 23.76 24.59 32.97 32.53** Rainy 16.72 18.14 23.53 21.78 11.48 20.88 Autumn 16.72 19.83 18.18 24.26 34.43 13.19 Winter 44.60 35.02 30.48 30.20 29.51 32.97 Lactation 3 24.04 34.18 24.06 26.73 14.75 24.18 87.99** 4 14.63 31.65 21.39 21.29 19.67 28.57 5 13.24 12.24 16.04 16.83 14.75 24.18 6 12.89 10.55 16.58 16.34 19.67 15.38 7 & above 35.19 11.39 21.93 18.81 31.15 7.69 Total 287 237 187 202 61 91 **Significant at 1% level 3.1.3 Mortality of buffaloes based on various factors 3.1.3.1 Breed wise mortality The perusal of the Table 4 indicates that the effect of breed was found to be non-significant on the pattern of mortality in the buffaloes. Further, the number of animals died due to digestive problem were 51.85 and 48.15 percent, respectively in Murrah and Nili-Ravi buffaloes. While, the animals deceased due to respiratory problems were found to be 34.78% in Murrah and 65.22 percent in Nili-Ravi. Additinally, the number of animals died due to reproductive, cardiovascular disorder, accidental deaths and miscellaneous factors in Murrah and Nili-Ravi buffaloers were 66.67 vs. 33.33, 58.06 vs. 41.94, 40 vs. 60 and 73.91 vs. 26.09 percent, respectively. In conformity with the findings, Mishra and Taneja ( 1991 ) also observed non-significant effect of the breed on the mortality. In contrast, Mukherjee and Tomar ( 1999 ) as well as Sharma and Jain ( 1982 ) noticed significant differences between breed. 3.1.3.2 Period wise reason of mortality in buffaloes The effect of period of disposal was highly significant (p < 0.01) on the pattern of mortality in buffaloes. It is clear from the Table 4 that among the buffaloes died as a consequence of digestive (59%) and respiratory disorder (48%), significantly more number were observed during the period 2009 to 2013 in comparison with other group of periods. Further, the buffaloes deceased on account of reproductive disorder were higher from the period 1999 to 2003. Moreover, the deaths as a cause of cardiovascular problems and accidental injury were noticed to be maximum from the year 2004 to 2008. In this sequence, majority of the deaths observed during 1989 to 1993 were as a result of miscellaneous factors and this reason of mortality was also higher relative to other class of periods. The higher rates of mortality in 1989-93 due to miscellaneous factors and 2009-13 as a result of digestive and respiratory disorders could be attributed to the prevalent environmental circumstances, such as climatological and managerial factors. Similarly, Patel et al. ( 2017 ) observed a significant influence of period on mortality patterns in Surti buffalos. In conformity with our results, Prasad et al. ( 2004 ) also reported variable mortality pattern during different periods in dairy cattle breeds. Additionally, Chavai (1996) also showed a significant disparity in mortality rates between time periods. 3.1.3.3 Season wise incidence of mortality in buffaloes The perusal of the Table 4 indicates season wise no significant difference on the mortality pattern in Murrah and Nili-Ravi buffaloes both. Our findings are consistent with Prasad et al. ( 2004 ), who found no significant effect of season on dairy animal mortality. 3.1.3.4 Reason of mortality in different groups of lactation completed in buffaloes It is evident from the Table 4 that the effect of lactation completed was non-significant on the pattern of mortality in both Murrah and Nili-Ravi buffaloes. Table 4 Factors associated with mortality pattern (%) of Murrah and Nili-Ravi buffaloes Digestive Respiratory Reproductive Cardiovascular Accidental Miscellaneous Chi-square Breed Murrah 51.85 34.78 66.67 58.06 40 73.91 8.12 NS Nili-Ravi 48.15 65.22 33.33 41.94 60 26.09 Period 1989-93 3.7 4.35 0 3.23 0 39.13 66.52** 1994-98 3.7 8.7 0 25.81 0 26.09 1999-03 11.11 13.04 50 3.23 20 4.35 2004-08 14.81 17.39 16.67 32.26 40 4.35 2009-13 59.26 47.83 16.67 16.13 20 13.04 2014-18 7.41 8.7 16.67 19.35 20 13.04 Season Summer 14.81 26.09 50 22.58 0 13.04 14.11 NS Rainy 25.93 26.09 16.67 19.35 60 30.43 Autumn 18.52 17.39 33.33 16.13 20 30.43 Winter 40.74 30.43 0 41.94 20 26.09 Lactation 3 29.63 21.74 0 22.58 20 39.13 20.82 NS 4 3.7 30.43 16.67 22.58 20 13.04 5 29.63 30.43 33.33 22.58 40 8.7 6 18.52 13.04 50 16.13 20 21.74 7 & above 18.52 4.35 0 16.13 0 17.39 Total 27 23 6 31 5 23 **Significant at 1% level; NS: Non-significant 4. CONCLUSION In Murrah breed, 90.72% buffaloes disposed due to culling and 9.28% due to mortality. While in case of Nili-Ravi, disposal of animals due to culling accounted 89.62% and mortality 10.38%. Major reason of culling was old age and low production whereas, majority of animals died due to cardiovascular, digestive and respiratory disorders in both Murrah as well as Nili-Ravi buffaloes. Buffaloes are generally culled for low production, fertility problems and other health complications, which decreases longevity. As a result, animal feeding management, reproduction management and the implementation of a genetic improvement program within the herd should be given more attention in order to increase the genetic potential of the animal. To prevent other health issues, the animal farm must be kept clean and sanitary. Maintaining an animal's health and welfare necessitates timely immunization. These will reduce the need to cull high-yielding animals, which means more genetic material will be passed on to subsequent generations. However, more culling of low producers helps us to keep high yielders, accelerating genetic improvement in the herd's ability to produce milk. Further, the high involuntary culling rate not only makes the dairy enterprises economically less profitable but also reduces the genetic improvement for milk production by lowering the selection differential. Therefore, the results obtained from this study may be utilized to develop improved management practices for decreasing rate of disposal of high yielders in the dairy farm. Declarations Acknowledgement The authors are highly thankful to the Director & Scientists ICAR-CIRB, Hisar for providing the research facilities and immense support to undertake this study. We would also wish to acknowledge ICAR-NDRI, Government of India, for granting funds and rendering essential assistance throughout the research work. Compliance with ethical standards Conflict of interest : The authors affirm that they have no conflict of interest. Statement of animal rights: There are no clinical studies or patient information in the manuscript. Funding status The animal study did not require funding because the investigation was based upon livestock data from disposals of Murrah and Nili-Ravi buffaloes. The information was gathered from animal history sheets kept at the ICAR-Central Institute for Research on Buffaloes, Hisar and Sub-Campus, Nabha, Punjab, over a 35-year period. Data availability statement The livestock data was recorded from the animal history sheet over a 35-year period, and the data will be made available as requested by the respective authors, without undue reserve. Author's contribution PT contributed to the collection of data, data curation, and drafting of the manuscript. AB contributed to the design of the experiment. AKC contributed to the interpretation of results and revision of the manuscript. YB contributed to the statistical analysis. SK contributed to the collection of data and curation. KPS contributed to the data classification. All authors contributed to the article and approved the submitted version. References Ahmad, M., 1999. Genetic evaluation of native and crossbred dairy cattle in Pakistan,(Ph.D. Thesis, Department of Animal Genetics and Breeding, University of New England, Australia). Bangar, Y.C., Khan, T.A., Dohare, A., Kolekar, D.V. and Avhad S.R., 2014. Study on Morbidity and Mortality Rates in Buffaloes in Pune Division of Maharashtra State in India, Journal of Buffalo Science, 3(2), 55-58. Chaudhary, J.K., Singh, B., Prasad, S. and Verma, M.R., 2013. Analysis of morbidity and mortality rates in bovine in Himachal Pradesh, Veterinary World, 6(9), 614-619. Chavai, B. R., Aswale, S. P. and Ulmek, B. K. 1996. Mortality pattern in crossbred cattle. Souvenir on Livestock Industry for Self/Gainful Employment held at Dept. of LPM, Madras Veterinary College, Chennai, PS, 1.17 DAHD., 2023. Ministry of Fisheries, Animal Husbandry and Dairying, Department of Animal Husbandry and Dairying, Animal Husbandry Statistics Division, Krishi Bhawan, New Delhi (20th Livestock Census-2019, All India Report). https://dahd.nic.in/sites/default/filess/20th-Livestock-census-2019-All-India-Report.pdf Do, C., Wasana, N., Cho, K., Choi, Y., Choi, T., Park, B. and Lee, D., 2013. The effect of age at first calving and calving interval on productive life and lifetime profit in Korean Holsteins, Asian-Australasian Journal of Animal Sciences, 26(11), 1511-1517. Gupta, N.M., Malhotra, P., Mehra, M.L. and Badyal, N., 2015. Studies on culling pattern in Murrah buffaloes at an organized farm, Indian Journal of Animal Research, 49(1), 136-139. Ilieva, Y. and Peeva, T., 2007. Productive life in buffalo cows and effect of some factors on it, Italian Journal of Animal Science, 6(2), 375-377. Jana, D. N., Pandey, H. N. and Srivastava, B. B. 1998. Disposal pattern in organised crossbred dairy herd. Indian Journal of Animal Health, 37(1), 47-50. Juneja, I.J., Sastri, N.S.R. and Yadav, B.L., 1991. A study on the incidence of diseases and culling pattern on herd of purebred (Jersey & Holstein Friesian) cows in semi-arid region, Indian Journal of Animal Production and Management,7, 191-195. Kumar, A., 1999. Genetic evaluation of Hariana cattle for selective value, (Ph.D. Thesis, CCS, HAU, Hisar, India). Malhotra, P. and Parmar, O.S., 2005. Studies on culling reasons vis-a vis milk production in cows, Indian Journal of Dairy Science,58(6), 433-35. Mishra, A.K. and Taneja, V.K., 1991. Factors influencing mortality rate in crossbred calves. Indian Jouunal of Animal Sciences, 61, 552–554 Mukherjee, K. and Tomar, S. S. 1999. Age-specific female calf mortality in a herd of Brown Swiss crosses. Indian Journal of Animal Sciences, 69(12), 1063-1064. Patel, M. D., Tyagi, K. K. and Sorathiya, L. M. 2017. Mortality pattern in an organized herd of Surti buffaloes of south Gujarat. Indian Journal of Animal Production and Management, 33(3-4), 40-47. Peeva, R. and Ilieva, Y., 2007. Longevity of buffalo cows and reasons for their culling, Italian Journal of Animal Science, 6(2), 378-380. Prasad, S., Ramachandran, N. and Raju, S., 2004. Mortality patterns in dairy animals under organized herd management conditions at Karnal India, Tropical Animal Health and Production,36(7), 645-654. Rathore, B.S., 1998. An epidemiological study on buffalo morbidity and mortality based on four-year observations on 18,630 buffaloes maintained at 28 livestock farms in India, Indian Journal of Comparative Microbiology, Immunology and Infectious Diseases, 19(1), 43-49. Ravi, P. and Tomar, A. K. S. 2021. Disposal trend analysis in crossbred cattle and Murrah buffaloes under organised farm conditions. The Pharma Innovation Journal, 10(12S), 1201-1203. Rawal, S.C. and Tomar, S.S., 1998. Population analysis for loss of cows and replacement index in Tharparkar cattle, Indian Journal of Animal Sciences,68, 183-184. Roeber, D. L., Mies, P. D., Smith, C. D., Belk, K. E., Field, T. G., Tatum, J. D., Scanga, J.A. and Smith, G. C. 2001. National market cow and bull beef quality audit—1999: A survey of producer-related defects in market cows and bulls. Journal of Animal Science, 79(3), 658-665. Sharma, K. N. S. and Jain, D. K. 1982. Note on calf mortality among Tharparkar crosses at an organized farm. Indian Jouunal of Animal Sciences, 52, 954–956. Shivahre, P.R., Gupta, A.K., Panmei, A., Bhakat, M., Chakravarty, A.K., Kumar, V., Dash, S.K. and Singh, M., 2014. Effect of non-genetic factors on culling and mortality rate in Murrah buffalo males, Advances in Animal and Veterinary Sciences, 2(12), 657-661. Snedecor, G.W. and Cochran, W.G., 1994. Statistical Methods. 8thedn. Oxford & IBH Pub. New Delhi. Tamboli, P., Bharadwaj, A., Bangar, Y. C. and Chaurasiya, A. 2020. Breeding efficiency of Murrah and Nili-Ravi buffaloes at ICAR-CIRB, Hisar. The Indian Journal of Animal Sciences, 90(10), 1430-1434. Tamboli, P., Bharadwaj, A., Chaurasiya, A., Bangar, Y. C. and Jerome, A. 2022. Association between age at first calving, first lactation traits and lifetime productivity in Murrah buffaloes. Animal bioscience, 35(8), 1151. Taneja, V. K., Dwivedi, V. K., Nivasarkar, A. E., Saxena, M. M. and Nautiyal, L. P. 1989. Disposal pattern in three halfbred groups. Indian Journal of Animal Science, 59(5), 158-161. Taraphder, S., Tomar, S.S., Gupta, A.K., Panja, P.K. and Biswas, P.K., 2011. Causes of disposal of Murrah buffalo from an organised herd, Online Journal of Veterinary Research,15(1), 68-75. Upadhyay, A., Sadana, D.K., Gupta, A.K., Chakravarty, A.K., Dash, S., Das, M.K., Anushree, M. and Shivahre, P.R., 2014. Age and lactation specific disposal pattern in Sahiwal cattle and influence of various genetic and non-genetic factors, Veterinary World,7(10), 842-847. Waldner, C.L., Kennedy, R.I., Rosengren, L. and Clark, E.G., 2009. A field study of culling and mortality in beef cows from western Canada, Canadian Veterinary Journal, 50(5), 491-499. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Bharadwaj","email":"","orcid":"","institution":"Central Institute for Research on Buffaloes","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"","lastName":"Bharadwaj","suffix":""},{"id":323382559,"identity":"58f3d3f1-dd24-433d-857f-c96c2f850021","order_by":2,"name":"A. K. Chaurasiya","email":"","orcid":"","institution":"Nanaji Deshmukh Veterinary Science University College of Veterinary and Animal Husbandry Jabalpur","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"K.","lastName":"Chaurasiya","suffix":""},{"id":323382560,"identity":"8074d9ed-babf-4e69-a827-e796b7ccc2c6","order_by":3,"name":"Y. Bangar","email":"","orcid":"","institution":"Lala Lajpat Rai University of Veterinary and Animal Sciences","correspondingAuthor":false,"prefix":"","firstName":"Y.","middleName":"","lastName":"Bangar","suffix":""},{"id":323382561,"identity":"798ce118-26eb-42ab-957d-fb256bf9f885","order_by":4,"name":"S. Khanna","email":"","orcid":"","institution":"Central Institute for Research on Buffaloes","correspondingAuthor":false,"prefix":"","firstName":"S.","middleName":"","lastName":"Khanna","suffix":""},{"id":323382562,"identity":"070e7113-8f01-4035-9067-30307d46ff9d","order_by":5,"name":"K.P. Singh","email":"","orcid":"","institution":"Central Institute for Research on Buffaloes","correspondingAuthor":false,"prefix":"","firstName":"K.P.","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2024-06-22 10:12:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4621403/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4621403/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68233441,"identity":"854f0c71-e622-46ce-852f-14a48f819142","added_by":"auto","created_at":"2024-11-05 06:34:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":794768,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4621403/v1/ce41ae1f-2c9b-46d6-be21-582c71824b62.pdf"}],"financialInterests":"","formattedTitle":"Assessment of disposal patterns in Murrah and Nili-Ravi buffaloes","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eIndia leads the globe in milk production (230.58\u0026nbsp;million tonnes), which has climbed by 3.83% over the previous year. In addition, per capita availability of milk up to 459 g/day has also recently been reached. Furthermore, buffalo accounts for around 44.81% of total milk output in the country with increament of 3.69% as compared to previous year and are well adapted to subtropical climates such as India. India ranks first in the total buffalo number and accounts for roughly 56.7% of the total global buffalo population. The overall number of buffaloes in the country is 109.85\u0026nbsp;million (54% of the world buffalo populatin), a 1.1% rise from the previous livestock census (DAHD 2023). According to DAHD 2023, India accounts for 75% of the global buffalo milk production. During 2022-23, the export of raw hides and skins of bovine (including buffalo) or horse totals Rs. 10.78 crore. In India, buffalo is the primary dairy animal, and it continues to be a vital source of revenue, nourishment, and employment for the country's enormous rural population (Tamboli et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is a quadruple-purpose animal, ideal for milk, meat, draught, and leather. The Murrah and Nili-Ravi breeds of milk producing buffalo have the best genetic material in the country. It has been regarded as one of the best global buffalo breeds, capable of producing high fat milk as well as meat (Tamboli et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Futher, the buffaloes have spread across the entire country, with different population densities, with the bulk situated in the north and west. Murrah is a native of Haryana, and Nili-Ravi is found in the state of Punjab, primarily in the Ravi River valley. Moreover, the success of the dairy sector is dependent on the health of the livestock, since improved health enhances dairy farm output. Furthermore, animal disposal patterns include culling as well as mortality for a variety of reasons. Culling is the process of eliminating animals from a herd for specified purposes, most notably to remove undesirable qualities from the herd while retaining profit. Animals that are less productive or have health issues are culled through auction. Culling based on the poor output allows for the retention of high yielders for faster genetic improvement (Gupta et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In addition, the main cause of the decrease in lifetime productivity and longevity is culling and adult mortality (Ilieva and Peeva \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Because an animal will have fewer lactations if culling or mortality occurs early in life. A high death rate also indicates poor management practices and is expensive for dairy producers as it eliminates superior genotypes from the herd and reduces the availability of young dairy stock for breeding. Therefore, it is essential to investigate the reasons behind animal disposal. Furthermore, according to Taraphder et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), the three main causes of culling in buffaloes were udder complications (22.76), insufficient milk production (24.01), and reproductive issues (38.62). According to Do et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the biggest reason for culling (44%) in dairy cattle husbandry is failure to conceive during the first lactation. Animal disposal owing to mortality diminishes productive and herd life, which has a negative impact on their lifetime production performance (Taraphder et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Moving further, there are numerous reasons for disposals, which vary according to breed, period, season, and number of lactations completed. Knowledge of disposal reasons and their management is critical for a healthy and profitable dairy enterprise. An examination of the literature revealed that observations on the effect of several characteristics such as breed, period of disposal, season of disposal, and number of lactations completed on the disposal patterns of Murrah and Nili-Ravi buffaloes are limited, particularly in Northern India's humid subtropical climate. Hence, this study was done to analyse the influence of various non-genetic factors on the culling and mortality patterns in buffaloes in order to recommend appropriate health management practises, selection, and breeding approaches for the genetic improvement of the buffaloes.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data collection\u003c/h2\u003e \u003cp\u003eThe data on reason of disposals pertaining to Murrah and Nili-Ravi buffaloes was collected from the history sheet of animals for a period from 1989 to 2018 (29 years) maintained at ICAR-Central Institute for Research on Buffaloes, Hisar and Sub-Campus, Nabha, Punjab. The data for all the buffaloes born and calved in the farms was recorded up to the date of death/ disposal. The animals completed minimum of three lactations with minimum lactation length\u0026thinsp;\u0026gt;\u0026thinsp;150 days and production\u0026thinsp;\u0026gt;\u0026thinsp;1000kg for first lactation were selected. The data was collected on disposal records of 1180 adult buffaloes which included 679 Murrah and 501 Nili-Ravi. The reasons for culling of adult buffaloes were classified as old age, low yielder, mastitis, reproductive, health problems and other. Whereas, reasons for mortality were categorized as digestive, respiratory, reproductive, cardiovascular disorders, accidental deaths and other.\u003c/p\u003e \u003cp\u003eThe data was uniformly classified according to breed, period of disposal, season of disposal and number of lactations completed. The complete data were grouped into Murrah and Nili-Ravi breed. Period of disposal (1989 to 2018) was divided into six groups each consisting of five consecutive years. Each year was further delineated into four seasons of disposal according to geo-climatic conditions in the area viz. summer (April to June), rainy (July to September), autumn (October to November) and winter (December to March). The data on disposal traits were further classified according to the number of lactations completed into five categories namely three, four, five, six, seven \u0026amp; above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Model and statistical analysis\u003c/h2\u003e \u003cp\u003eThe IBM SPSS Statistics 20.0 software (Snedecor and Cochran \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) was used to estimate the effects of various non-genetic factors and the results were interpreted in the tabular form. The rates of animals disposed from the herd were calculated by frequency distribution using descriptive statistics.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe statistical significance between various reasons of culling and mortality with different factors was assessed using Chi-square test. The statistical significance was considered if P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Disposal in Murrah and Nili-Ravi buffaloes\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOut of 679 Murrah buffalo 616 (90.72%) disposed due to culling and 63 (9.28%) due to mortality. In total 449 (89.62%) Nili-Ravi buffaloes were culled whereas mortality accounted for 52 (10.38%) out of 501 animals disposed during the same period of the study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Appropriate housing, feeding, and other farm management techniques may have contributed to the buffaloes' lower mortality rate. However, Bangar et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported mortality rate of 7.98% in buffaloes of Maharastra region and overall mortality rate in bovine was reported 9.14% by Chaudhary et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) in Himanchal Pradesh. However, according to an investigation, Surti buffaloes had an overall mortality rate of 2.83 percent (Patel et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, according to Prasad et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), the average overall mortality in Sahiwal, Tharparkar, Karan Swiss, and Karan Fries was 14.35%, 7.21%, 17.12%, and 13.46%, respectively. Additionally, it was observed that the herd's overall breeding female culling rate was 14.3%, whilst the herd's overall mortality incidence was 1.1%. 6.9%, 6.4%, and 11.6% of the variation was explained by the herd when it came to disposal for any cause, culling, and mortality, respectively. After taking herd clustering into consideration, the estimated incidence rate of inventory loss for any cause was 19.8% (Waldner et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, Taraphder et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) found that 5.34 percent of buffaloes died for various reasons overall. Additionally, Ravi and Tomar (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) noted that a number of reasons, including death (28.40%), culling (20.75%), transfer (39.92%), and stillbirths (3.28%), were cited for the animals' removal from the herd. Furthermore, according to Taneja et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), of the cows that were disposed of, 52.67% were auctioned, 15.78% were moved to different herds, 5.08% were killed, and 26.47% died. Mukerjee and Tomar (1997) found that the mortality rate of crossbred dairy cattle was higher than this, at 44.0%. Additionally, Jana et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) observed that mortality in crossbred cattle was 49.6% and the culling rate was 28.5%.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall culling and mortality pattern in Murrah and Nili-Ravi buffaloes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCulling (No.)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDied (No.)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCulling rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMortality rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMurrah\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNili-Ravi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Culling and mortality pattern in buffaloes\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe reasons for culling and mortality in the buffaloes during the period from 1989 to 2018 are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among the buffaloes, out of culled animals (1065), the major reason of culling was old age and low milk production which accounted around 27 and 22%, respectively of total culling. Further, reproductive problems constituted 19% followed by mastitis (18%) and other health problems (6%). The other health problems comprised of lameness, abscess on knee joints, rheumatic arthritis, chronic arthritis, weakness, eye blindness, severe chronic eye injury, hide bound condition, tumour, hip deformity, pelvic deformity, fracture, herniation of reticulorumen and nervous symptoms.. In all about 9% animal culled by miscellaneous factors which includes off breed, wide horn, loose horn and white star on forehead in Murrah while, off breed and drooping horn in case of Nili-Ravi breed. Reproductive problems cover metritis, infertility, post-partum anoestrus, pyometra, cystic ovary, post-partum prolapse, cervical tumour, abortion and retention of placenta. Major reason for culling of animals was observed to be low milk production, reproduction problems and mastitis. Therefore, the management of animal diet and the execution of a genetic improvement program within the herd should receive more attention in order to enhance animal's genetic potential. The timely diagnosis of estrus, prompt artificial insemination, and care of pregnant animals are more areas that require attention in the realm of reproduction management. To stop mastitis and other illnesses from occurring in the animals, the animal shed needs to be kept clean and hygienic. Maintaining an animal's health and welfare requires prompt vaccination. These will lessen the need to cull high-yielding animals that ought to give more genetically to the next generation. More culling of low producers, however, allows us to keep high yielders, which accelerates genetic development in the herd's ability to produce milk. Ahmad (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) found, in line with our results, that the primary cause of culling in Murrah buffaloes (31.3%) and Nili-Ravi buffaloes (27%), was inadequate milk output. Gupta et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) also examined the culling cycle and found that the largest percentage of buffaloes culled for insufficient milk production (30.77%) were followed by those culled for problems with reproduction (30.39%), old age (14.76%), disease (9.64%), health type (8.89%), and other conditions (5.55%). This indicated that reduced milk production and issues with reproduction accounted for nearly two thirds of culling (61.06%). Accordingly, Malhotra and Parmar (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) discovered that the majority of dairy cattle were culled due to inadequate milk output. Furthermore, the results of Peeva and Ilieva (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) illustrate that the buffaloes culled for gynecological reasons were highest (41%), followed by low productivity (19%), prolapsed (11%), short lactations (7%) and old age (9%). Similarly, Taraphder et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) reported that reproductive problems (38.62%), low milk production (24.01%) and udder problems (22.76%) as the three major reasons of culling. On the other hand, Do et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) noticed that the primary reason for culling (44%) was due to failure to conceive in first lactation in dairy cattle. In addition, Upadhyay et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) concluded that most of the adult cows were culled because of teat, udder and reproductive problems from the herd. Furthermore, lameness, cancerous eyes, and lumpy jaws frequently led to the culling of animals (Roeber et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe different reasons of mortality in the buffaloes are depicted in the Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Out of total 115 animals disposed due to mortality in buffaloes, the maximum mortality occurred due to cardio-vascular (31%), followed by digestive (27%), respiratory disorder (23%), reproductive (6%) and accidental deaths (5%). Additionally, the animals died due to miscellaneous factors accounted 23%. Further, respiratory disorder includes pneumonia, adhesions in lungs and tuberculosis. Cardio-vascular disorder consists of haemorrhagic shock, traumatic pericarditis and septicaemia. Digestive disorder includes hepatitis, gastro-enteritis, peritonitis, tympanitis and traumatic reticuloperitonitis. The reproductive disorders comprise of endometritis, dystocia, post-partum prolapse and rupture of uterus. Furthermore, accidental deaths cover electrocution, drowning, trauma and snake bite. Whereas, nervous disorder, paralysis, parasitic diseases, nephritis and old age were included under the miscellaneous factors. In conformity with the finding, Taraphder et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) in Murrah buffaloes observed that the maximum mortality occurred due to digestive problems which accounted for 30.89% followed by cardio-vascular problems (26.02%), respiratory problems (21.14%), parasitic problems (8.13%) and uro-genital problems (5.69%). In some other studies, the highest adult mortality occurred due to digestive disorders (33.62%), respiratory disease (29.28%) and various other diseases (17.48%) (Rathore \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Conversely, acute illnesses (such as bloat) or infectious diseases were typically the cause of farm deaths, according to Waldner et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Additionally, they showed that nutritional and feeding-related issues, such as traumatic reticuloperitonitis, rumen tympany (bloat), myopathy (possibly linked to a deficiency in vitamin E or selenium), nitrate toxicity, and polioencephalomalacia, were the most frequent causes of animal mortality. These together accounted for 21 percent of all fatalities. According to Patel et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the leading cause for mortality in Surti buffaloes was pneumonia (23.89%), which was followed by diarrhoea (15.93%), debility (15.93%), septicemia (15.04%), unintentional fatalities (9.74%), blood protozoan infections (6.20%), snake bite (5.30%), and other causes 7.98%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVarious reasons of culling and mortality pattern in buffaloes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCulling pattern\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMortality pattern\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReason\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReason\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow yielder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDigestive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReproductive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMastitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReproductive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAccidental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal culled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal died\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Culling of buffaloes based on various factors\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section4\"\u003e \u003ch2\u003e3.1.2.1 Breed wise culling\u003c/h2\u003e \u003cp\u003eHighly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) effects of breed were noticed on the culling pattern of buffaloes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The number of animals culled due to old age was significantly higher in case of Murrah when compared with Nili-Ravi. Similarly, Waldner et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) also reported that rate of culling increases with the advance in age of animals. While, the number of animals discarded owing to low milk production and mastitis were greater in the Nili-Ravi breed. Furthermore, greater number of animals among Murrah breed were removed from the herd as a consequence of reproductive, health problem and miscellaneous factors in comparison with Nili-Ravi breed of the buffaloes. Taneja et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), on the other hand, observed that the rationales for animal disposal were not breed-specific.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section4\"\u003e \u003ch2\u003e3.1.2.2 Period wise reason of culling in buffaloes\u003c/h2\u003e \u003cp\u003ePeriod wise reason of culling in the buffaloes is presented in the Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Effect of period of disposal was highly significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) on the culling pattern in buffaloes. Further, maximum (34%) number of animals culled in the period 1994-98 due to old age whereas lowest culling rate (3%) was seen during 2014 to 2018 depicting decreasing trend of culling across the periods which may be attributed to the fact that the different aspect of management practices was improved with the passage of time in the dairy farm. Moreover, highest number of buffaloes culled owing to low milk production between 1999 to 2003 while, the number of animals discarded because of mastitis were more from the period 2004 to 2013. Moving further, the buffaloes removed on account of reproductive problems accounted major proportion between 1999 to 2008. Moreover, highest number of animals (31%) culled due to health problems during 2009 to 2013. Additionally, majority of the culling occurred due miscellaneous factors from the year 2004 to 2008 besides other group of periods. Additionally, alterations in the culling pattern of buffalo herds across time periods may be ascribed to disparities in breeding sires, environmental circumstances, management practices, and the availability of forage and fodder. Similar to our findings, the culling rate was found to be the lowest in the last period, showing an improvement in production, reproduction, and herd health management over time. Furthermore, it was discovered that the last period's productivity, reproduction, health and management methods, and other environmental elements were optimal because only a small number of buffaloes were culled (Taraphder et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In keeping with the findings, Gupta et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found a substantial effect of period on culling pattern in Murrah buffaloes. They also observed that the largest prevalence of culling occurred between 1975\u0026ndash;1980, followed by 1991\u0026ndash;1995. Juneja et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and Malhotra and Parmar (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) conducted studies on crossbred cow herds, which support our findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section4\"\u003e \u003ch2\u003e3.1.2.3 Season wise incidence of culling in buffaloes\u003c/h2\u003e \u003cp\u003eIt is evident from the Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e that the effect of season was highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) on the pattern of culling in buffaloes. Further, majority of the animals culled in winter season, followed by summer. Similarly, Gupta et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found a significant effect of season on culling in Murrah buffaloes, reporting higher culling in the winter (22.76%), followed by summer (22.31%) and spring (21.49%). Our findings are similarly consistent with those of Tomar and Rawal (1996), who studied dairy cattle herds. While, Waldner et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) noticed that the incidence of culling was highest during the monsoon season, followed by the winter, spring, and summer seasons.\u003c/p\u003e \u003cp\u003eMost of the animals culled were old aged (45 and 22%), low yielder (35 and 27%) and affected with mastitis (30 and 28%), respectively in both the winter and summer seasons. Furthermore, the other causes of culling were reproductive and health problems, observed to be highest in the winter and autumn season, respectively. In this line, miscellaneous factors accounted major reason of culling during both winter and summer seasons. The results were in accordance with the findings of Shivahre et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) in Murrah buffaloes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section4\"\u003e \u003ch2\u003e3.1.2.4 Reason of culling in different groups of lactation completed in buffaloes\u003c/h2\u003e \u003cp\u003eThe perusal of the Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e revealed highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) influence of lactation completed on the culling patterns in buffaloes. In addition, old age constituted major cause of culling among the animal completed 7 and above lactations while, the animals culled due to low milk production were mostly from the parity 3 as well as 4. Further, the majority of the animals discarded due to mastitis (24%) and reproductive problems (27%) had completed 3 lactations. Moreover, removal of the animals because of health problems were of mostly 7 and above parity. Whereas, maximum number of animals culled due to miscellaneous factors were from the set of animals completed 4 lactations. In line with the findings, Gupta et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found that lactation completed (parity) had significant impacts on culling patterns in Murrah buffaloes. Furthermore, they showed that the majority of animals were culled in the first lactation (23.14%), followed by the second lactation (16.93%), and so on. In lactation no. 1st, 3rd, 4th, and 5th, the majority of animals were culled due to low milk production, followed by 2nd lactation, in which the majority of animals were culled due to reproduction-related problems, and in 6th and above parity, animals were culled owing to senility, i.e. old age, because after 6th and above parity, the animal becomes susceptible to various diseases. In this line, similar culling pattern was observed in Hariana cattle (Kumar \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Major reason of culling was old age, low production, mastitis, reproductive and health problems in all the set of parity. Additionally, similar rhythm of culling was also reported by Rawal and Tomar (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) in Tharparkar breed. Furthermore, up to third parity, the largest rate of culling as a result of reproductive issues was noted. With the exception of lactations six and above parity, culling rates for general debility (health problems) was essentially same across all lactations (Taraphder et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with culling pattern (%) of Murrah and Nili-Ravi buffaloes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOld age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow yielder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMastitis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReproductive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHealth problems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMurrah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e219.10**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNili-Ravi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeriod\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1989-93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e354.66**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1994-98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeason\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e32.53**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRainy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e87.99**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e**Significant at 1% level\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Mortality of buffaloes based on various factors\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section4\"\u003e \u003ch2\u003e3.1.3.1 Breed wise mortality\u003c/h2\u003e \u003cp\u003eThe perusal of the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e indicates that the effect of breed was found to be non-significant on the pattern of mortality in the buffaloes. Further, the number of animals died due to digestive problem were 51.85 and 48.15 percent, respectively in Murrah and Nili-Ravi buffaloes. While, the animals deceased due to respiratory problems were found to be 34.78% in Murrah and 65.22 percent in Nili-Ravi. Additinally, the number of animals died due to reproductive, cardiovascular disorder, accidental deaths and miscellaneous factors in Murrah and Nili-Ravi buffaloers were 66.67 vs. 33.33, 58.06 vs. 41.94, 40 vs. 60 and 73.91 vs. 26.09 percent, respectively. In conformity with the findings, Mishra and Taneja (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) also observed non-significant effect of the breed on the mortality. In contrast, Mukherjee and Tomar (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) as well as Sharma and Jain (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1982\u003c/span\u003e) noticed significant differences between breed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section4\"\u003e \u003ch2\u003e3.1.3.2 Period wise reason of mortality in buffaloes\u003c/h2\u003e \u003cp\u003eThe effect of period of disposal was highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) on the pattern of mortality in buffaloes. It is clear from the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e that among the buffaloes died as a consequence of digestive (59%) and respiratory disorder (48%), significantly more number were observed during the period 2009 to 2013 in comparison with other group of periods. Further, the buffaloes deceased on account of reproductive disorder were higher from the period 1999 to 2003. Moreover, the deaths as a cause of cardiovascular problems and accidental injury were noticed to be maximum from the year 2004 to 2008. In this sequence, majority of the deaths observed during 1989 to 1993 were as a result of miscellaneous factors and this reason of mortality was also higher relative to other class of periods. The higher rates of mortality in 1989-93 due to miscellaneous factors and 2009-13 as a result of digestive and respiratory disorders could be attributed to the prevalent environmental circumstances, such as climatological and managerial factors. Similarly, Patel et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) observed a significant influence of period on mortality patterns in Surti buffalos. In conformity with our results, Prasad et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) also reported variable mortality pattern during different periods in dairy cattle breeds. Additionally, Chavai (1996) also showed a significant disparity in mortality rates between time periods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section4\"\u003e \u003ch2\u003e3.1.3.3 Season wise incidence of mortality in buffaloes\u003c/h2\u003e \u003cp\u003eThe perusal of the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e indicates season wise no significant difference on the mortality pattern in Murrah and Nili-Ravi buffaloes both. Our findings are consistent with Prasad et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), who found no significant effect of season on dairy animal mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section4\"\u003e \u003ch2\u003e3.1.3.4 Reason of mortality in different groups of lactation completed in buffaloes\u003c/h2\u003e \u003cp\u003eIt is evident from the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e that the effect of lactation completed was non-significant on the pattern of mortality in both Murrah and Nili-Ravi buffaloes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with mortality pattern (%) of Murrah and Nili-Ravi buffaloes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigestive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReproductive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAccidental\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMurrah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.12\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNili-Ravi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeriod\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1989-93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.52**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1994-98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeason\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.11\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRainy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.82\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e**Significant at 1% level; NS: Non-significant\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. CONCLUSION","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn Murrah breed, 90.72% buffaloes disposed due to culling and 9.28% due to mortality. While in case of Nili-Ravi, disposal of animals due to culling accounted 89.62% and mortality 10.38%. Major reason of culling was old age and low production whereas, majority of animals died due to cardiovascular, digestive and respiratory disorders in both Murrah as well as Nili-Ravi buffaloes. Buffaloes are generally culled for low production, fertility problems and other health complications, which decreases longevity. As a result, animal feeding management, reproduction management and the implementation of a genetic improvement program within the herd should be given more attention in order to increase the genetic potential of the animal. To prevent other health issues, the animal farm must be kept clean and sanitary. Maintaining an animal's health and welfare necessitates timely immunization. These will reduce the need to cull high-yielding animals, which means more genetic material will be passed on to subsequent generations. However, more culling of low producers helps us to keep high yielders, accelerating genetic improvement in the herd's ability to produce milk. Further, the high involuntary culling rate not only makes the dairy enterprises economically less profitable but also reduces the genetic improvement for milk production by lowering the selection differential. Therefore, the results obtained from this study may be utilized to develop improved management practices for decreasing rate of disposal of high yielders in the dairy farm.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are highly thankful to the Director \u0026amp; Scientists ICAR-CIRB, Hisar for providing the research facilities and immense support to undertake this study. We would also wish to acknowledge ICAR-NDRI, Government of India, for granting funds and rendering essential assistance throughout the research work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with ethical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors affirm that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of animal rights:\u0026nbsp;\u003c/strong\u003eThere are no clinical studies or patient information in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal study did not require funding because the investigation was based upon livestock data from disposals of Murrah and Nili-Ravi buffaloes. The information was gathered from animal history sheets kept at the ICAR-Central Institute for Research on Buffaloes, Hisar and Sub-Campus, Nabha, Punjab, over a 35-year period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe livestock data was recorded from the animal history sheet over a 35-year period, and the data will be made available as requested by the respective authors, without undue reserve.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor's contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePT contributed to the collection of data, data curation, and drafting of the manuscript. AB contributed to the design of the experiment. AKC contributed to the interpretation of results and revision of the manuscript. YB contributed to the statistical analysis. SK contributed to the collection of data and curation. KPS contributed to the data classification. All authors contributed to the article and approved the submitted version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad, M., 1999. Genetic evaluation of native and crossbred dairy cattle in Pakistan,(Ph.D. Thesis, Department of Animal Genetics and Breeding, University of New England, Australia). \u003c/li\u003e\n\u003cli\u003eBangar, Y.C., Khan, T.A., Dohare, A., Kolekar, D.V. and Avhad S.R., 2014. Study on Morbidity and Mortality Rates in Buffaloes in Pune Division of Maharashtra State in India, Journal of Buffalo Science, 3(2), 55-58.\u003c/li\u003e\n\u003cli\u003eChaudhary, J.K., Singh, B., Prasad, S. and Verma, M.R., 2013. Analysis of morbidity and mortality rates in bovine in Himachal Pradesh, Veterinary World, 6(9), 614-619.\u003c/li\u003e\n\u003cli\u003eChavai, B. R., Aswale, S. P. and Ulmek, B. K. 1996. Mortality pattern in crossbred cattle. 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The Indian Journal of Animal Sciences, 90(10), 1430-1434.\u003c/li\u003e\n\u003cli\u003eTamboli, P., Bharadwaj, A., Chaurasiya, A., Bangar, Y. C. and Jerome, A. 2022. Association between age at first calving, first lactation traits and lifetime productivity in Murrah buffaloes. Animal bioscience, 35(8), 1151.\u003c/li\u003e\n\u003cli\u003eTaneja, V. K., Dwivedi, V. K., Nivasarkar, A. E., Saxena, M. M. and Nautiyal, L. P. 1989. Disposal pattern in three halfbred groups. Indian Journal of Animal Science, 59(5), 158-161.\u003c/li\u003e\n\u003cli\u003eTaraphder, S., Tomar, S.S., Gupta, A.K., Panja, P.K. and Biswas, P.K., 2011. Causes of disposal of Murrah buffalo from an organised herd, Online Journal of Veterinary Research,15(1), 68-75.\u003c/li\u003e\n\u003cli\u003eUpadhyay, A., Sadana, D.K., Gupta, A.K., Chakravarty, A.K., Dash, S., Das, M.K., Anushree, M. and Shivahre, P.R., 2014. Age and lactation specific disposal pattern in Sahiwal cattle and influence of various genetic and non-genetic factors, Veterinary World,7(10), 842-847.\u003c/li\u003e\n\u003cli\u003eWaldner, C.L., Kennedy, R.I., Rosengren, L. and Clark, E.G., 2009. A field study of culling and mortality in beef cows from western Canada, Canadian Veterinary Journal, 50(5), 491-499.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breed, Culling, Disposal, Mortality, Murrah, Nili-Ravi","lastPublishedDoi":"10.21203/rs.3.rs-4621403/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4621403/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe current study was carried out to look into the disposal patterns of Murrah and Nili-Ravi buffaloes kept at ICAR-CIRB, Hisar and Sub-Campus Nabha, Punjab, respectively. The purpose of the investigation was to estimate the various non-genetic factors affecting culling and mortality patterns in buffaloes to suggest suitable health management practices, selection, and breeding strategies for enhancing genetic gain in buffaloes. From 1983 to 2017, 1180 data of 679 Murrah and 501 Nili-Ravi were used to calculate the frequency of culling and death. The impacts of several parameters on disposal were explored, including breed, period of disposal, season of disposal, and lactation completed. The findings revealed that in Murrah, 90.72% of buffaloes were disposed of due to culling and 9.28% due to mortality. While, in the instance of Nili-Ravi, animal disposal due to culling accounted for 89.62% of the total, with mortality accounting for 10.38%. The main reason for culling was old age and low production, while the majority of buffaloes died from cardiovascular, digestive, and respiratory problems. Furthermore, the effect of season was highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) on the pattern of culling in buffaloes. Additionally, majority of the animals culled in the winter season, followed by summer and most of the animals culled were old aged (45 and 22%), low yielder (35 and 27%) and affected with mastitis (30 and 28%), respectively in both the winter and summer seasons. Moreover, the effect of period of disposal was highly significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) on the both pattern of mortality and culling in buffaloes. Further, maximum (34%) number of animals culled in the period 1994-98 due to old age whereas lowest culling rate (3%) was seen during 2014 to 2018. In this sequence, it may be determined that the reason for disposal differs depending on the breed, period, season and lactation completed.As a result, our efforts should be directed towards improving management practices with the goal of lowering the rate of culling and mortality, which leads to higher lifetime performance and, as a result, the overall efficiency of the dairy farm.\u003c/p\u003e","manuscriptTitle":"Assessment of disposal patterns in Murrah and Nili-Ravi buffaloes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-30 08:48:10","doi":"10.21203/rs.3.rs-4621403/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dc99dc2f-b5e0-470a-bb35-3a3ea80c3783","owner":[],"postedDate":"July 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-09T02:16:53+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-30 08:48:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4621403","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4621403","identity":"rs-4621403","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}