This chapter is an overview of artificial intelligence (AI) and machine learning (ML) in food science and bioprocesses. This comprehensive work introduces the subject of AI to new readers, focusing on the important applications and progress of this technology in food science and related areas such as bioprocess. Food science involves examining the biological, chemical, and physical makeup of food, understanding what leads to food spoilage, and grasping the principles behind food processing Bioprocessing on the other hand, is loosely defined as the production of value-added materials to industrial scale from a living source such as living cells. AI has revolutionized many industries, altering operational frameworks to offer innovative solutions to longstanding challenges. This book chapter first provides an overview of the food science and bioprocess industries and comprehensively describes the various AI and ML applications in food science and also emerging applications in the bioprocess development. Limitations of AI are then discussed before concluding with the final section of the chapter, which emphasizes the futuristic perspective of AI and ML in food science and bioprocess development.
This article explores how participatory approaches and transnational cooperation can be advanced to advance multi-level governance in pursuit of the Sustainable Development Goals, focusing on SDG 11 “Sustainable cities and communities”. Based on qualitative research in Finland and Sweden we show that participatory approaches fail due to a lack of administrative capacity, path dependencies, societal conflicts and power asymmetries between the actors involved, which limit the transformative scope and legitimacy of policies. We argue that central governments in particular need to take more responsibility, provide more guidance and invest in capacity building and community empowerment at the local level.
This article explores how participatory approaches and transnational cooperation can be advanced to advance multi-level governance in pursuit of the Sustainable Development Goals, focusing on SDG 11 “Sustainable cities and communities”. Based on qualitative research in Finland and Sweden we show that participatory approaches fail due to a lack of administrative capacity, path dependencies, societal conflicts and power asymmetries between the actors involved, which limit the transformative scope and legitimacy of policies. We argue that central governments in particular need to take more responsibility, provide more guidance and invest in capacity building and community empowerment at the local level.
This article explores how participatory approaches and transnational cooperation can be advanced to advance multi-level governance in pursuit of the Sustainable Development Goals, focusing on SDG 11 “Sustainable cities and communities”. Based on qualitative research in Finland and Sweden we show that participatory approaches fail due to a lack of administrative capacity, path dependencies, societal conflicts and power asymmetries between the actors involved, which limit the transformative scope and legitimacy of policies. We argue that central governments in particular need to take more responsibility, provide more guidance and invest in capacity building and community empowerment at the local level.