The objective of this study was to evaluate the GreenFeed (GF) and respiration chambers (RC) for daily and intraday measurements of the enteric gaseous exchange, as well as the metabolic heat production, lying behavior, and feed intake (FI) rate of dairy cows at these 2 respective housing conditions [tie-stall barn (TS) vs. RC] during the summer periods. Sixteen multiparous lactating dairy cows were recruited and arranged in a randomized complete block design with a baseline period established for each cow. Cows were given a basal diet (CON) for a baseline period of 7 d and were then fed a 3-nitrooxypropanol (3-NOP)-containing feed for the subsequent 26 d as experimental period. During both the baseline and the last 7 d of treatment period, gaseous exchanges of each animal were measured in the TS using GF for 8 6-hourly staggered measurements over 3 d, immediately followed by the measurement in RC for 2 d. Corresponding DMI, milk yield, and behavior parameters (e.g., lying behavior and FI rate) in TS and RC were recorded. The correlation coefficients of CH₄ and H₂ using raw data were 0.84 and 0.85, respectively. For all gases, correlation coefficients between GF and RC on individual cow level decreased when the marginal fixed effects (e.g., inhibitor and breed) were corrected by a mixed model. There were no differences in daily CH₄ production or intensity between GF and RC (442 vs. 443 g CH₄/d or 16.6 vs. 16.2 g CH₄ /kg MY). However, greater CH₄ yield was measured by GF than RC (19.0 vs. 17.8 g CH₄/kg DMI), driven by a lower DMI (23.3 vs. 24.6 kg/d) when cows were housed in TS sampled by GF compared with cows being housed and sampled in RC. The correlations for CO₂ production and O₂ consumption were moderate and expected due to the variation associated with the mild heat stress condition during GF measurements in the TS (Thermal humidity index (THI) 56 vs. 68), as indicated by the reduced lying time (-2.1 h/d). At the intraday level, there was an interaction between techniques and hour-of-day for CH₄ production, as indicated by the discrepancies in post-prandial CH₄ emissions between techniques. In summary, this set of results showed that there were strong positive correlations for CH₄ and H₂ emissions between GF and RC based on individual cow data. However, such relationship should be interpreted with caution, given the data clustering resulting from the use of inhibitor 3-NOP. On treatment level, these 2 techniques detected similar inhibitor effect on the estimated daily CH₄ emissions. The intraday patterns of CH₄ and H₂ production captured by GF provided a close approximation for those measured by RC. Nevertheless, potential underestimation may occur, especially following fresh feed delivery. For measuring CO₂ production and O₂ consumption, the GF captured similar intraday variations to those in the RC. However, the estimated daily production and consumption were not directly comparable, which was expected due to the variable thermal conditions during the summer. Further evaluations under the same weather conditions are warranted.

Greenhouse gas emissions from livestock farming and in particular enteric methane (CH₄) from ruminants are criticized for being one of the main contributors to climate change. Different breeding, feeding and management strategies are tested to decrease these emissions, but a status quo analysis is also relevant to implement such measures. The present study aimed to analyze the concentration of CH₄ in air exhaled by dairy cows along a rural-urban gradient of Bangalore, India. Urban, mixed and rural areas were defined based on a survey stratification index (SSI) comprising build-up density and distance to the city center. Using a laser methane detector (LMD), CH₄ concentration was determined in 2-min spot measurements of exhaled air of 448 cows at three equally spaced visits between June 2017 and April 2018. Mean, maximum and CH₄ concentration per duration of the overall measurement, eructation and respiration bouts were calculated. For the overall mean and respiration bouts, CH₄ concentration was higher in cows from urban areas, which had also higher milk yield than cows from mixed and rural areas. Although no differences were found in terms of the intake level of fibrous diet components, the type of measurement location (indoor, half-outdoor or outdoor) and pasture access had an impact on CH₄ concentration. To our knowledge, this is the first study using the LMD on-farm and in an urbanizing environment. The LMD measurements show variations in enteric CH₄ emissions along the rural-urban gradient of Bangalore that reflect differences in dairy husbandry systems governed by the social-ecological context.

Natural calamities and pandemics massively affect small-scale entrepreneurs. In this paper, we aim to assess how the COVID-19 pandemic affected small dairy farms in the megacity of Bengaluru, India, where they supply a high share of the milk demand. In 2020 a total of 129 farms were visited before the first lockdown (January to March) and interviewed again after the lockdown had been loosened (August to September). Questions addressed feed supply to dairy cows, milk yield and marketing, and coping strategies for lockdown impacts. Results showed that the share of farmers not feeding concentrates increased from 1% before lockdown to 7% afterward (p < 0.05), and those not offering dry forages increased from 20% to 33% (p < 0.05) due to increasing forage prices. Milk yield dropped in all surveyed farms from 3905 L before to 2861 L after lockdown (p < 0.05) due to the sale of 30% of lactating cows across the farms. Enabling farmers to better cope with shocks through feed storage and by processing their surplus milk into durable products should be prioritised by supporting institutions such as dairy cooperatives. Alternatively, insurance schemes can capacitate farmers to maintain a fresh milk supply to urban consumers in the wake of global challenges.

Urbanization is a main driver of agricultural transition in the Global South but how it shapes trends of intensification or extensification is not yet well understood. The Indian megacity of Bengaluru combines rapid urbanization with a high demand for dairy products, which is partly supplied by urban and peri-urban dairy producers. To study the impacts of urbanization on dairy production and to identify key features of dairy production systems across Bengaluru’s rural-urban interface, 337 dairy producers were surveyed on the socio-economic profile of their household, their dairy herd and management, resources availability and, in- and output markets. A two-step cluster analysis identified four spatially explicit dairy production systems based on urbanization level of their neighborhood, reliance on self-cultivated forages, pasture use, cattle in- and outflow and share of specialized dairy genotypes. The most extensive dairy production system, common to the whole rural-urban interface, utilized publicly available feed resources and pasture grounds rather than to cultivate forages. In rural areas, two semi-intensive and one intensive dairy production systems relying on self-cultivation of forage with or without pasture further distinguished themselves by their herd and breeding management. In rural areas, the village’s dairy cooperative, which also provided access to inputs such as exotic genotype through artificial insemination, concentrate feeds and health care, was often the only marketing channel available to dairy producers, irrespective of the dairy production system to which they belonged. In urban areas, milk was mostly sold through direct marketing or a middleman. Despite rapidly progressing urbanization and a population of 10 million, Bengaluru’s dairy sector still relies on small-scale family dairy farms. Shifts in resources availability, such as land and labor, are potential drivers of market-oriented intensification but also extensification of dairy production in an urbanizing environment.

Among all livestock systems in tropical regions, the dairy sector is facing huge challenges to sustain productivity under the rapidly changing climatic conditions. To date, there is a lack of knowledge on the combined effects of climate, season, and farm location on trait responses in different cattle breeds. Consequently, this study presents a novel approach to assess the impact of several climatic and geographical factors on production traits, energy efficiency indicators, and hygiene traits in dairy cattle reared across the rural–urban interface in the tropical savanna region of Bengaluru, a rising megacity in southern India. In total, 96 cattle were selected across Bengaluru’s rural–urban interface, reflecting a broad variety of social-ecological systems. The traits considered included test day milk yield (MY), body condition score (BCS), body weight (BW), hock assessment score (HAS), udder hygiene score (UHS), and upper leg hygiene score (ULHS). Apart from cow-related factors such as breed, lactation stage, lactation number, and milking frequency, the environmental classification variables of season, farm location (as expressed by survey stratification index, SSI), and temperature humidity index (THI) significantly affected most of the traits, with indication for breed-by-environment interactions. In particular, season significantly influenced production and hygiene traits. Furthermore, an evident breed variation was observed in the seasonal influence on BW, wherein exotic cows had a higher BW than crossbreds during the summer season. The distinct trend of SSI in its influence on most of the traits indicates that cows housed in urban areas had better trait expression than those in rural areas, thereby revealing a predominant role of management. The THI had a significant effect on MY, BCS, and HAS, and THI = 75 was identified as heat stress threshold. The results indicate the importance of considering ecological, social, and climatic factors simultaneously in order to improve primary and functional breed-specific traits of dairy cattle reared in challenging environments.

The aim of the present study was to infer phenotypic trait expressions via mixed modeling considering both social and ecological continuous descriptors simultaneously. In this regard, we selected a challenging heterogeneous social-ecological environment, with focus on the rising megacity Bangalore, located in southern India. Dairy traits from 517 dairy cattle were recorded in 121 herds, equally distributed along a southern and a northern rural–urban gradient of Bangalore, distinguishing between urban, mixed, and rural areas. Repeated records from three visits per herd included production traits (daily milk yield in liter: MY), energy efficiency indicators (body condition score: BCS), cow wellbeing indicators (udder hygiene score: UddHS, upper leg hygiene score: ULHS, hock assessment score: HAS, rectal temperature in °C: RT), and health traits (locomotion score: LS, subclinical mastitis: SubMast). Associations between a continuous rural–urban gradient and phenotypic trait expressions were analyzed via mixed modeling, additionally considering “classic” environmental explanatory variables such as climatic conditions. MY and BCS were higher in urban than in rural areas, associated with reduced SubMast and improved hygiene scores for UddHS and ULHS. Scores for wellbeing indicators HAS and LS were unfavorable for cows in urban areas, indicating poor leg health conditions in that area. In rural areas, least-squares means for RT were quite large, probably due to the scarcity of shading and heat insulation of the barns. To the best of our knowledge, this is the first study disentangling phenotypic trait expressions in the context of social-ecological heterogeneity, contributing to a deeper understanding of physiological mechanisms underlying genotype by environment interactions.