This study examines poultry production stocking density (SD) effect on bird welfare and economic performance. It is based on a large dataset from commercial production including observations for 2.2 million male broilers and 2.3 million female broilers from 37 production sites, with SD ranging from 20.63 kg/m² to 41.15 kg/m². The data collection was originally motivated by a processor’s economic concerns that increasing SD could cause slower broiler growth, higher condemnations, and lower grade meat. The data was examined using several linear regressions to determine how production parameters impacted these performance indicators. Results regarding foot pad lesion, condemnations, and mortality rates are consistent with those found in the literature. However, we find that daily weight gain is positively associated with SD, contrasting with past experimental results. The difference between the scope of commercial and experimental productions is discussed as a possible reason for these conflicting results.

Analysing production systems from a circular economy (CE) perspective helps to pinpoint interventions to mitigate the environmental footprint by improving resource use efficiency, waste recovery, and prolonged product usage, recycling and reuse. Few studies exist on the measurement of CE at the micro-level. Additionally, available metrics/indicators address only certain aspects of the CE’s socio-economic metabolism, ignoring important components of the CE concept. Other frameworks propose a single indicator that aggregates and summarizes several facets of CE. This study develops a holistic approach for designing indicators with a structured methodology and an analytical framework to assess CE at the micro (unit of production) level in agriculture. The proposed approach is based on the ECOGRAI method for indicator development, and on validation of the methods with experts and final users via an application to egg production in Canada. Twenty-five performance indicators (PI) were generated for 11 decision variables that were selected as important for the sector. This resulted in a practical tool that proposes fourteen actions to improve the economic circularity (EC) of egg farms. Our methodological approach could be replicated to assess CE performance in other agricultural sectors.

Food items are increasingly chosen based on sustainability attributes as the public is becoming increasingly aware of the environmental and animal welfare impacts of production systems, in addition to the traditional consideration for nutrition. Although surveys have been used to investigate the demand for these attributes in unprocessed products, little information exists on how these attributes impact consumer preferences in the case of processed products or prepared meals. This study uses a stated preference survey to examine Quebec (Canada) consumers’ preferences for eggs from four production systems with different impacts on animal welfare and on the environment. We compare the respondents’ choices of fresh eggs and two prepared meals that contain eggs. Furthermore, we examine the shift in choices following information treatments on animal welfare, nutrition, or environmental impact attributes. Results indicate that respondents choose eggs from more sustainable production systems more frequently when included in prepared meals than in their unprocessed form. The provision of information led participants to update prior beliefs and revise their initial choices, especially for animal welfare attributes.

Previous meta-analyses examined hypothetical bias studies with the aim of identifying characteristics of stated preference (SP) design that potentially reduce hypothetical bias. However, previous meta-analyses combined observations for both public and private goods in their models. In this paper, we argue that eliciting values for public and private goods should be considered in separate models. Individuals’ behaviours, the choice of mechanism and the efficiency of mitigation techniques are specific to each type of good. Separating the models should allow more precise model specification and better identification of design effects. With two meta-regressions hierarchical mixed-effect models we provide the first meta-analysis for public and private goods separately. This approach provides specific information regarding SP design and better insight into the efficiency of mitigation techniques to reduce hypothetical bias.