Our aim was to study Brazilian consumer attitudes towards cell-based meat and related issues. From 408 respondents from Curitiba and 218 from Joinville, the majority was women with higher level of education; 65.2% and 70.2% frequently consumed meat and 50.7% and 50.9% would not stop eating meat; 81.6% and 82.6% had little or no knowledge about cell-based meat. After watching an explanatory video, 41.9% and 34.4% stated they would eat cell-based meat without restrictions; 24.5% and 23.9% stated they would try depending on conditionals. Overall, 63.6% declared they would eat cell-based meat; among vegetarians and vegans, 24% and 8% stated they would eat cell-based meat, with additional 25.0% and 27.0% stating “it depends”; thus, the major public for cell-based meat seems to be meat eaters. Animal welfare was the principal reason for considering not eating meat and a major benefit of cell-based meat. In conclusion, the majority of respondents would not stop eating meat; additionally, they would eat cell-based meat.

No abstract

Cattle have a complex social organization, with negative (agonistic) and positive (affiliative) interactions that affect access to environmental resources. Thus, the social behaviour has a major impact on animal production, and it is an important factor to improve the farm animal welfare. The use of data from electronic bins to determine social competition has already been validated; however, the studies used non-free software or did not make the code available. With data from electronic bins is possible to identify when one animal takes the place of another animal, i.e. a replacement occurs, at the feeders or drinkers. However, there is no package for the R environment to detect competitive replacements from electronic bins data. Our general approach consisted in creating a user-friendly R package for social behaviour analysis. The workflow of the socialh package comprises several steps that can be used sequentially or separately, allowing data input from electronic systems, or obtained from the animals’ observation. We provide an overview of all functions of the socialh package and demonstrate how this package can be applied using data from electronic feed bins of beef cattle. The socialh package provides support for researchers to determine the social hierarchy of gregarious animals through the synthesis of agonistic interactions (or replacement) in a friendly, versatile, and open-access system, thus contributing to scientific research.