Ten trends in food sustainability

by Jul 15, 2016Climate Change, Food, Pollution0 comments

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The Sustainable Development Goals in terms of food, directly mentioned four main objectives: ending hunger, achieving food security, improving food nutrition and promoting sustainable production. Seeds&Chips – an the International Summit dedicated to food innovation from farm to fork – heped to spot ten trends that are driving the food-tech industry towards this aimed more sustainable foodscape.

Until now, labels were giving information about original ingredients, ignoring the result of cooking processes. Massive public and private structured-data infrastructures has been built around medicinal value of drugs, while the role of food, diet, and lifestyle has been largely undervalued. The scene is quickly changing. The democratization of nutritional information is here to stay. The final goal is to achieve food security and knowledge through traceability, at the largest scale possible, leveraging on sensors, analysis system and applications, specific nutrients presence and building data infrastructures to create a world common food-print. This is increasingly associated to health world. From probiotic beverages to functional food, edible solutions that help preventing or curing various pathologies are quickly emerging. It is called bio-informatics and the goal is to unlock food sources, providing natural, sustainable and scientifically proven health solutions. The design of a new food system plays a crucial role in minimising food consumption while maximising its nutrient injection, using existing or new products through food fabrication. Different from robotics-based food manufacturing technologies (which are designed to automate manual processes for mass production), 3D food printing integrates technology and digital gastronomy technique to manufacture completely customised food products.
Ingredients can now be matched working with aromas (80% of what we call taste is actually aroma) to empower everyone to make the best food choices in terms of taste and nutritional value. This is just an example of how data analysis and machine learning are now applied to the food space.

Read full story: BarillaCFN

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