Datasets for the environmental assessment of an apple value chain including fresh fruits, juice and applesauce from an organic low-input production farm.

Due to societal concerns, assess the environmental impacts, address the issues and provide labelling to the consumer are growing issues for the agri-food sector. In this context, provide datasets specific to alternative systems is crucial to be able to take into account the variability between systems then address their issues and label them appropriately. This data paper compiles all the data used to produce the life cycle assessment (LCA) environmental of an organic low-input apple value chain including the cultivation of apples at farm, the transformation of a part into juice and applesauce, the retail and the consumption stages. The raw data have mostly been obtained through interviews of the farmer and complemented by literature. They have been used to build a life cycle inventory (LCI), using Agribalyse 3.0 and Ecoinvent 3.8 as background databases. The dataset also compiles the life cycle impact assessment (LCIA) using the characterization method EF3.0. As discussed in an associated scientific paper, this dataset participates in filling two gaps: integrate the variability between systems in the discussion and link upstream (at farm) and downstream (transformation, retail, consuming) impacts. This is done by (1) covering the entire value chain from cradle to grave when most papers found in literature focusses on one stage (e.g. the cultivation of apples) and (2) applying LCA to a system that present specificities not well covered by LCA literature (e.g. low-input cultivation with no fertilization up to now).

Life cycle inventory and life cycle impact assessment datasets of PDO Feta production in Stymfalia region, Greece.

Considering and reducing the environmental impacts has become one of the main concerns of agri-food systems. More specifically, the agri-food sector is increasingly confronted to the necessity of quantifying environmental impacts, e.g., to eco-design their products or to inform the consumers. Literature shows a high variability in environmental impacts between existing systems, as for example between cheeses and the necessity of more case studies to validate statements. In this context, this data paper provides some data related to Feta production in Greece, based on 8 farms of a cooperative (7 sheep livestock and one goat livestock). Feta cheese is PDO (Protected Designation of Origin), composed solely of goat's milk and sheep's milk under specific percentages (at least 70% sheep). More specifically, the data paper displays all the data used to obtain environmental impacts (calculated by using life cycle assessment (LCA)) of the production of Feta, from cradle to consumer. It includes the - sheep and goat - milk productions, the transformation into cheese, the packaging and the transport to wholesalers, then stores and then consumers. The raw data have mostly been obtained through interviews and surveys with the cheese and milk producers and complemented by literature. Data were used to build a life cycle inventory (LCI). For the milk production, the LCI was modeled using MEANS InOut software. For the whole LCI, Agribalyse 3.0 and Ecoinvent 3.8 were used as background databases, with modifications to reflect Greek context. The dataset also compiles the life cycle impact assessment (LCIA). The characterization method used is method EF3.0. This dataset participates in filling two gaps: (1) providing data to represent the variability between Feta cheese production systems and (2) providing data linking impacts of farm, transformation, retail and transport in a value chain perspective. This is done by (1) enlarging the perimeter when most studies found in literature focus on one stage (e.g. the production of milk) and (2) applying LCA to data specific to a regional production (Stymfalia in Greece).

Data on the Life Cycle Assessment of pizzas cooked and consumed at home taking into account the variability of consumer practices.

Human food consumption is responsible for significant environmental impacts, which in recent years have been the focus of an increasing amount of research. One of the major results of these efforts has been an appreciation for the ways in which impacts can differ among products. To date, though, relatively little is known about possible differences in the environmental performance of a single food product that is made or produced in different contexts. Furthermore, the influence of consumer practices, such as cooking time or cleaning method, has not yet been investigated. The goals of the study were therefore (i) to compare the environmental impacts of a single food product-in this case, pizza-that is produced in different contexts (industrial, homemade, and assembled at home) and (ii) to investigate the influence of real-world consumer practices on these impacts. Two study models were used: a ham-and-cheese pizza and a mixed-cheese pizza. The functional units (FU) examined were one pizza and 1 kg of ready-to-eat pizza. The system boundaries extended from the agricultural production of ingredients to the consumption of the pizza at home. All inventory data related to the steps occurring before purchase (including storage at the supermarket) came from databases or the literature, while inventory data related to the steps occurring after the sale were obtained from questionnaires answered by 69 consumers who prepared and consumed the six pizza preparation pathways (two recipes multiply three methods of preparation) at home. Background data were selected in the AGRIBALYSE 3.0 and Ecoinvent 3.6 databases. The environmental impacts of the six pizza preparation pathways were calculated by Life Cycle Assessment (LCA) using the characterization method "EF 3.0 Method (adapted) V1.00 / EF 3.0 normalization and weighting set" in SimaPro software. To compare the environmental impacts of the six pizza preparation pathways, 69 LCAs were performed for each; to compensate for missing data from incomplete questionnaires, we performed random draws from the available data to generate the life cycle inventory for each assessment. The data obtained in this study can be used to make recommendations to consumers regarding more environmentally friendly food choices and practices.