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This paper analyzes French winemakers' decision-making process to adapt to climate change, and how the institutional and relational context of an innovation system, including a clean technological regime, affect these decisions. Our study used a mixed method research based on original face-to-face interviews with 92 winemakers in three French regional wine clusters that have been affected by climate change: Bordeaux, Champagne and Languedoc. We perform a logistic model to tests how managers' personal backgrounds, wine-producing company characteristics, and innovation system components, including cleaner technological regime, might explain the adaptation decision-making process. Our results show that economic variables have little influence on climate change adaptation decision-making. On the contrary, variables expressing the relationship built by wine producing companies within the Innovation System, their involvement in organic wine production, and the manager's personal background affect the decision-making process to adapt to climate change. Furthermore, many of the adaptation strategies rely on adopting cleaner production approach. Our findings show that the decision-making process depends on networks and clean technological regimes embedded in an innovation system, with regional and sector dimensions.

This paper analyzes French winemakers' decision-making process to adapt to climate change, and how the institutional and relational context of an innovation system, including a clean technological regime, affect these decisions. Our study used a mixed method research based on original face-to-face interviews with 92 winemakers in three French regional wine clusters that have been affected by climate change: Bordeaux, Champagne and Languedoc. We perform a logistic model to tests how managers' personal backgrounds, wine-producing company characteristics, and innovation system components, including cleaner technological regime, might explain the adaptation decision-making process. Our results show that economic variables have little influence on climate change adaptation decision-making. On the contrary, variables expressing the relationship built by wine producing companies within the Innovation System, their involvement in organic wine production, and the manager's personal background affect the decision-making process to adapt to climate change. Furthermore, many of the adaptation strategies rely on adopting cleaner production approach. Our findings show that the decision-making process depends on networks and clean technological regimes embedded in an innovation system, with regional and sector dimensions.

In the context of the increasingly damaging impact of agro-food systems on human health and the environment, this study aimed to evaluate the sustainability of current dietary patterns using multi criteria analysis to characterize consumers with different dietary patterns. In a sample of 29,413 participants of the NutriNet-Sante Study, total and organic food intakes of 264 items gathered in 17 food groups were evaluated using a food frequency questionnaire. Eight sustainability indicators were assessed individually. To identify combinations of food groups explaining the maximum variation in the sustainability indicators, we applied reduced rank regression with food groups as predictors and sustainability indicators as response variables. Then, the first two RRR-derived factors were used to classify participants using an ascending hierarchical classification. Six clusters were identified, among then one cluster (N = 23.07%) presented a good compromise between all the sustainable dimensions. Indeed, their diets emitted on average 36% less greenhouses gas, included 30% more organic food and exhibited a close level of affordability compared to the average. The dietary composition in this group, were characterized by -58% of red meat, -37% of white meat, -25% of cheese but +15% of fruits, +15% of vegetable and a similar contribution of fish and starches, compared to the sample average. Finally, this study showed that in the current food system context, the observed diets rarely meet all sustainability criteria. Oppositions between healthy, eco-friendly and affordability often remain. However, we obServed some diets with high compatibility with all sustainable indicators selected for the study. Thus sustainable diets are emerging and should be promoted. However, it would be relevant to conduct additional research in other population to estimate acceptability.

In the context of the increasingly damaging impact of agro-food systems on human health and the environment, this study aimed to evaluate the sustainability of current dietary patterns using multi criteria analysis to characterize consumers with different dietary patterns. In a sample of 29,413 participants of the NutriNet-Sante Study, total and organic food intakes of 264 items gathered in 17 food groups were evaluated using a food frequency questionnaire. Eight sustainability indicators were assessed individually. To identify combinations of food groups explaining the maximum variation in the sustainability indicators, we applied reduced rank regression with food groups as predictors and sustainability indicators as response variables. Then, the first two RRR-derived factors were used to classify participants using an ascending hierarchical classification. Six clusters were identified, among then one cluster (N = 23.07%) presented a good compromise between all the sustainable dimensions. Indeed, their diets emitted on average 36% less greenhouses gas, included 30% more organic food and exhibited a close level of affordability compared to the average. The dietary composition in this group, were characterized by -58% of red meat, -37% of white meat, -25% of cheese but +15% of fruits, +15% of vegetable and a similar contribution of fish and starches, compared to the sample average. Finally, this study showed that in the current food system context, the observed diets rarely meet all sustainability criteria. Oppositions between healthy, eco-friendly and affordability often remain. However, we obServed some diets with high compatibility with all sustainable indicators selected for the study. Thus sustainable diets are emerging and should be promoted. However, it would be relevant to conduct additional research in other population to estimate acceptability.

In the current context of the end of dairy quotas, the increasing size of dairy farms and the expected growth in food demand, European dairy production systems are facing major challenges. The aim of this study was to assess environmental impacts of dairy system intensification to identify production systems that combine high productivity and low environmental impacts. We used the concept of the Technological Management Route, i.e. a logical set of technical options designed by farmers, to describe the diversity of milk production systems in France. Life Cycle Assessment was used to estimate impacts of these systems according to two functional units: t milk and hectare of total (on- and off-farm) land occupied. Dairy system intensification has three major effects: i) an increase in all impacts when expressed per hectare, ii) a decrease in eutrophication and land occupation per t milk, and iii) no clear effects on other impacts when expressed per t milk. The two first effects are due mostly to the switch from grass-based feed to maize silage and concentrate feed when intensifying production systems. Furthermore, the choice of functional unit leads to radically different conclusions. Using only a mass-based functional unit, which is predominant in current life cycle assessment practice, does not provide a balanced view of the impacts of intensification and could mislead decision makers in identifying promising dairy systems. More generally, current LCA practice seems largely blind to the negative environmental consequences of agricultural system intensification, as revealed by the area-based functional unit. Therefore, we recommend the use of both mass-based and area-based functional units in life cycle assessments of agricultural goods.

As one of the largest users of pesticides in the world, banana production is responsible for numerous types of pollution affecting water, soil and air and causing a variety of health issues. Agroecological innovations can help to reduce pesticide use and achieve cleaner and more sustainable banana production systems. Innovations must be well suited to the diversity of banana farms and acceptable to the stakeholders involved in production. We tested the impact of 18 agroecological innovations in Guadeloupe on the sustainability of three contrasted production systems, using the multi-criteria assessment model MASC. These innovations included different types of fallow (A), bans on pesticides (B), conditional applications of pesticides (C), intercropping (D), resistant cultivars (E), and integrated systems (F). In the assessment, we introduced the views of 29 stakeholders involved in sustainability issues relative to banana grouped through three sets of weightings, obtained by direct weighting of the indicators used in a multi-criteria assessment tool. We analysed the effects of each set of weightings on the sustainability level for these different banana production systems. Our results showed that the adoption of innovations can have negative, positive or no effects on the overall sustainability of banana production systems. Although none of the innovations had a positive effect on all cropping systems, some innovations were relevant to several farm types. However, this depended on the sets of weightings considered, because we found several types of stakeholder with opposing views on the importance of sustainability components. Integrated and organic systems produced the best results in terms of increasing sustainability and were relevant to current farming systems. However, in order to obtain cleaner banana production at the landscape scale, a combination of these innovations, tailored to the diversity of farmers' situations and stakeholder preferences, still needs to

In the current context of the end of dairy quotas, the increasing size of dairy farms and the expected growth in food demand, European dairy production systems are facing major challenges. The aim of this study was to assess environmental impacts of dairy system intensification to identify production systems that combine high productivity and low environmental impacts. We used the concept of the Technological Management Route, i.e. a logical set of technical options designed by farmers, to describe the diversity of milk production systems in France. Life Cycle Assessment was used to estimate impacts of these systems according to two functional units: t milk and hectare of total (on- and off-farm) land occupied. Dairy system intensification has three major effects: i) an increase in all impacts when expressed per hectare, ii) a decrease in eutrophication and land occupation per t milk, and iii) no clear effects on other impacts when expressed per t milk. The two first effects are due mostly to the switch from grass-based feed to maize silage and concentrate feed when intensifying production systems. Furthermore, the choice of functional unit leads to radically different conclusions. Using only a mass-based functional unit, which is predominant in current life cycle assessment practice, does not provide a balanced view of the impacts of intensification and could mislead decision makers in identifying promising dairy systems. More generally, current LCA practice seems largely blind to the negative environmental consequences of agricultural system intensification, as revealed by the area-based functional unit. Therefore, we recommend the use of both mass-based and area-based functional units in life cycle assessments of agricultural goods.

As one of the largest users of pesticides in the world, banana production is responsible for numerous types of pollution affecting water, soil and air and causing a variety of health issues. Agroecological innovations can help to reduce pesticide use and achieve cleaner and more sustainable banana production systems. Innovations must be well suited to the diversity of banana farms and acceptable to the stakeholders involved in production. We tested the impact of 18 agroecological innovations in Guadeloupe on the sustainability of three contrasted production systems, using the multi-criteria assessment model MASC. These innovations included different types of fallow (A), bans on pesticides (B), conditional applications of pesticides (C), intercropping (D), resistant cultivars (E), and integrated systems (F). In the assessment, we introduced the views of 29 stakeholders involved in sustainability issues relative to banana grouped through three sets of weightings, obtained by direct weighting of the indicators used in a multi-criteria assessment tool. We analysed the effects of each set of weightings on the sustainability level for these different banana production systems. Our results showed that the adoption of innovations can have negative, positive or no effects on the overall sustainability of banana production systems. Although none of the innovations had a positive effect on all cropping systems, some innovations were relevant to several farm types. However, this depended on the sets of weightings considered, because we found several types of stakeholder with opposing views on the importance of sustainability components. Integrated and organic systems produced the best results in terms of increasing sustainability and were relevant to current farming systems. However, in order to obtain cleaner banana production at the landscape scale, a combination of these innovations, tailored to the diversity of farmers' situations and stakeholder preferences, still needs to

In this study, we used LCA to test the influence of practicing low-input farming, on-farm processing and direct distribution on the environmental impact of bread consumption. Primary data were collected from four commercially active producers (two in France, one in Italy and one in Portugal) who cultivate cereals under low levels of inputs, process grains on farm and distribute their products directly to end consumers. Environmental impacts of products were compared to equivalents from supermarkets, characterised by higher rates of applied inputs at the agricultural stage, industrial processing and centralised distribution. The scope of LCA was from cradle to the consumer. The study revealed a high variability of results between individual cases. At the agricultural stage, products from a low-input cropping system integrated with livestock production in France and from a small-scale labour intensive production in Portugal showed similar or better performance on most impact categories to those from high-input agriculture, while horse farming in France and a stockless cultivation of ancient wheat cultivars in Italy revealed mostly higher environmental burdens. Decentralised processing and distribution in France had similar or slightly higher impacts to conventional supply chains, while Italian and Portuguese cases revealed clearly higher environmental burdens for most impact categories. Results demonstrate that while there might be a positive relationship between the scale and eco-efficiency of processing and distribution, the level of agricultural inputs, yields and transport distances cannot be used as proxies of environmental performance. Products of low-input systems can have much higher, similar or lower impacts to their high-input counterparts due to the influence of site conditions and the management. More research assessing the effectiveness of context-specific management systems is needed as oppose to the generic comparisons between labelling schemes (i.e. or

In this study, we used LCA to test the influence of practicing low-input farming, on-farm processing and direct distribution on the environmental impact of bread consumption. Primary data were collected from four commercially active producers (two in France, one in Italy and one in Portugal) who cultivate cereals under low levels of inputs, process grains on farm and distribute their products directly to end consumers. Environmental impacts of products were compared to equivalents from supermarkets, characterised by higher rates of applied inputs at the agricultural stage, industrial processing and centralised distribution. The scope of LCA was from cradle to the consumer. The study revealed a high variability of results between individual cases. At the agricultural stage, products from a low-input cropping system integrated with livestock production in France and from a small-scale labour intensive production in Portugal showed similar or better performance on most impact categories to those from high-input agriculture, while horse farming in France and a stockless cultivation of ancient wheat cultivars in Italy revealed mostly higher environmental burdens. Decentralised processing and distribution in France had similar or slightly higher impacts to conventional supply chains, while Italian and Portuguese cases revealed clearly higher environmental burdens for most impact categories. Results demonstrate that while there might be a positive relationship between the scale and eco-efficiency of processing and distribution, the level of agricultural inputs, yields and transport distances cannot be used as proxies of environmental performance. Products of low-input systems can have much higher, similar or lower impacts to their high-input counterparts due to the influence of site conditions and the management. More research assessing the effectiveness of context-specific management systems is needed as oppose to the generic comparisons between labelling schemes (i.e. or

The objective of this study was to model land use configuration for a sustainable dairy sector in Brittany. France, using results from Life Cycle Assessment (LCA) in Multiple-Goal Linear Programming (MGLP). To generate future land-use configurations that met environmental targets, the approach required (1) defining a set of current and alternative land-use types, (2) defining a set of characteristics of these land-use types, (3) quantifying these characteristics for all land-use types, (4) calculating the regional sum of each indicator for current land-use types to establish the baseline scenario, and (5) defining scenarios consisting of a set of goals to meet (maximize milk production or farm profit) and environmental constraints not to violate (per-ha limits on nitrate leaching, non-renewable energy use, and greenhouse gas emissions). Existing dairy farms were classified into 5 groups (from organic to intensive) according to their mode of production, quantity of milk production, and fodder-crop and grass area. Alternative land uses, namely 100%-grass-based dairy systems or forest, were characterized to explore the potential effects of replacing current dairy farmland with them. The MGLP model was unable to find a combination of current land-use types that could meet the three environmental constraints while using all of the land available. With alternative land-use types allowed, however, the model maximized milk production while meeting environmental constraints by allocating 55-60, 21-44, and 1-19% of the area to grass-based dairy systems, intensive farms, and forest, respectively, which decreased regional milk production by 8-30%. The trade-offs shown in MGLP results predict consequences of applying environmental constraints on agricultural production, revealing challenges that agricultural policies may face. The major benefits of coupling MGLP and LCA results include (1) taking into account social and economic indicators while considering environmental concern

The objective of this study was to model land use configuration for a sustainable dairy sector in Brittany. France, using results from Life Cycle Assessment (LCA) in Multiple-Goal Linear Programming (MGLP). To generate future land-use configurations that met environmental targets, the approach required (1) defining a set of current and alternative land-use types, (2) defining a set of characteristics of these land-use types, (3) quantifying these characteristics for all land-use types, (4) calculating the regional sum of each indicator for current land-use types to establish the baseline scenario, and (5) defining scenarios consisting of a set of goals to meet (maximize milk production or farm profit) and environmental constraints not to violate (per-ha limits on nitrate leaching, non-renewable energy use, and greenhouse gas emissions). Existing dairy farms were classified into 5 groups (from organic to intensive) according to their mode of production, quantity of milk production, and fodder-crop and grass area. Alternative land uses, namely 100%-grass-based dairy systems or forest, were characterized to explore the potential effects of replacing current dairy farmland with them. The MGLP model was unable to find a combination of current land-use types that could meet the three environmental constraints while using all of the land available. With alternative land-use types allowed, however, the model maximized milk production while meeting environmental constraints by allocating 55-60, 21-44, and 1-19% of the area to grass-based dairy systems, intensive farms, and forest, respectively, which decreased regional milk production by 8-30%. The trade-offs shown in MGLP results predict consequences of applying environmental constraints on agricultural production, revealing challenges that agricultural policies may face. The major benefits of coupling MGLP and LCA results include (1) taking into account social and economic indicators while considering environmental concern

The comparison of the environmental performance of contrasting agricultural production systems using life cycle assessment (LCA) requires very specific data for each production mode, especially for direct emissions on the farm. In a case study of pig production, three contrasting production scenarios were defined: conventional good agricultural practice (GAP), organic agriculture (OA), and red label (RL). An expert panel produced methods for the estimation of emissions for key-processes of these scenarios. Clear differences were obtained for these emissions between the three scenarios. Finally, the summation of the main emissions for the entire life cycle allowed the identification of weak points for each scenario, which can be explained by the differences obtained for the emissions of the key-processes studied. (C) 2006 Elsevier Ltd. All rights reserved.

The comparison of the environmental performance of contrasting agricultural production systems using life cycle assessment (LCA) requires very specific data for each production mode, especially for direct emissions on the farm. In a case study of pig production, three contrasting production scenarios were defined: conventional good agricultural practice (GAP), organic agriculture (OA), and red label (RL). An expert panel produced methods for the estimation of emissions for key-processes of these scenarios. Clear differences were obtained for these emissions between the three scenarios. Finally, the summation of the main emissions for the entire life cycle allowed the identification of weak points for each scenario, which can be explained by the differences obtained for the emissions of the key-processes studied. (C) 2006 Elsevier Ltd. All rights reserved.