Assessing lameness prevalence and associated risk factors in crossbred dairy cows across diverse management environments.

BACKGROUND: A thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India. METHODS: The research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables. RESULTS: The overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows. CONCLUSIONS: The findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments.

Assessment of carbon footprint of milk production and identification of its major determinants in smallholder dairy farms in Karnataka, India.

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

Scrotal infrared digital thermography predicts effects of thermal stress on buffalo (Bubalus bubalis) semen.

The objective was to use scrotal infrared digital thermography to evaluate effects of thermal stress on semen quality of Murrah buffalo (Bubalus bubalis) breeding bulls. Ejaculates from 109 Murrah bulls maintained at three semen stations were evaluated for: ejaculate volume, sperm concentration (SCON), initial motility (IM), percent live sperm (LIVE), acrosome integrity of fresh semen (AIFS), plasma membrane integrity of fresh semen (PMIFS), head abnormalities of fresh semen (HAFS), midpiece abnormalities of fresh semen (MPAFS), tail abnormalities of fresh semen (TAFS), post-thaw motility (PTM), acrosome integrity of post-thawed semen (AIPT) and plasma membrane integrity of post-thawed semen (PMIPT). Scrotal and ocular surface temperatures were acquired during rainy, winter and summer seasons, using an FLIR i5 infrared camera. Thermographic images were analyzed with Quick Report 1.2 SP2 software and temperature data acquired. Daily mean temperature and mean relative humidity were used to determine the temperature-humidity index (THI). Environmental factors were analyzed using CORR to determine collinearity among independent variables. There was a high correlation among THI, proximal, mid and distal scrotal temperatures (r ≥ 0.73). Therefore, distal pole temperature (DPT), THI, temperature gradient (TG) and ocular temperature (OcT) were used in the analysis of variance (ANOVA) and in regression analysis of dependent variables. The THI, DPT, TG and OcT had significant influences on sperm abnormalities, acrosome and plasma membrane integrity of fresh as well as post-thawed semen. The TG had significant effects on LIVE and SCON. All semen quality parameters were predicted (regression analysis) as a function of the three independent factors. We concluded that scrotal infrared thermography was useful for assessing influences of thermal stress and environmental factors on characteristics of buffalo semen.