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In the food and beverage industries, implementing novel methods using digital technologies such as artificial intelligence (AI), sensors, robotics, computer vision, machine learning (ML), and sensory analysis using augmented reality (AR) has become critical to maintaining and increasing the products’ quality traits and international competitiveness, especially within the past five years. Fermented beverages have been one of the most researched industries to implement these technologies to assess product composition and improve production processes and product quality. This Special Issue (SI) is focused on the latest research on the application of digital technologies on beverage fermentation monitoring and the improvement of processing performance, product quality and sensory acceptability.
Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- sensor networks --- automation --- beer acceptability --- beer fermentation --- RoboBEER --- machine learning --- ultrasonic measurements --- long short-term memory --- industrial digital technologies --- yeast morphology --- automated image analysis --- heat stress --- vacuoles --- cell size --- computer vision --- foam stability --- image analysis --- lager beer --- foam retention --- polyphenols --- LC-ESI-QTOF-MS/MS --- HPLC --- medicinal plants --- ginger --- lemon --- mint --- herbal tea infusion --- antioxidants --- black pepper --- focus group --- hops --- Kawakawa --- off aromas --- gas sensors --- robotic pourer --- aroma thresholds --- climate change --- artificial neural networks --- volatile phenols --- glycoconjugates --- bushfires --- sparkling wine --- fermentation --- biogenic amines --- wine quality --- liquid chromatography --- principal component analysis --- augmented reality --- non-dairy yogurt --- contexts --- consumer acceptability --- emotional responses --- Fermentation --- Olea europaea --- respiration rate --- storage conditions --- transport --- TeeBot --- high throughput --- liquid handling robot --- metabolite analysis --- stochastic dynamic optimisation --- uncertainty --- n/a
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In the food and beverage industries, implementing novel methods using digital technologies such as artificial intelligence (AI), sensors, robotics, computer vision, machine learning (ML), and sensory analysis using augmented reality (AR) has become critical to maintaining and increasing the products’ quality traits and international competitiveness, especially within the past five years. Fermented beverages have been one of the most researched industries to implement these technologies to assess product composition and improve production processes and product quality. This Special Issue (SI) is focused on the latest research on the application of digital technologies on beverage fermentation monitoring and the improvement of processing performance, product quality and sensory acceptability.
sensor networks --- automation --- beer acceptability --- beer fermentation --- RoboBEER --- machine learning --- ultrasonic measurements --- long short-term memory --- industrial digital technologies --- yeast morphology --- automated image analysis --- heat stress --- vacuoles --- cell size --- computer vision --- foam stability --- image analysis --- lager beer --- foam retention --- polyphenols --- LC-ESI-QTOF-MS/MS --- HPLC --- medicinal plants --- ginger --- lemon --- mint --- herbal tea infusion --- antioxidants --- black pepper --- focus group --- hops --- Kawakawa --- off aromas --- gas sensors --- robotic pourer --- aroma thresholds --- climate change --- artificial neural networks --- volatile phenols --- glycoconjugates --- bushfires --- sparkling wine --- fermentation --- biogenic amines --- wine quality --- liquid chromatography --- principal component analysis --- augmented reality --- non-dairy yogurt --- contexts --- consumer acceptability --- emotional responses --- Fermentation --- Olea europaea --- respiration rate --- storage conditions --- transport --- TeeBot --- high throughput --- liquid handling robot --- metabolite analysis --- stochastic dynamic optimisation --- uncertainty --- n/a
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In the food and beverage industries, implementing novel methods using digital technologies such as artificial intelligence (AI), sensors, robotics, computer vision, machine learning (ML), and sensory analysis using augmented reality (AR) has become critical to maintaining and increasing the products’ quality traits and international competitiveness, especially within the past five years. Fermented beverages have been one of the most researched industries to implement these technologies to assess product composition and improve production processes and product quality. This Special Issue (SI) is focused on the latest research on the application of digital technologies on beverage fermentation monitoring and the improvement of processing performance, product quality and sensory acceptability.
Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- sensor networks --- automation --- beer acceptability --- beer fermentation --- RoboBEER --- machine learning --- ultrasonic measurements --- long short-term memory --- industrial digital technologies --- yeast morphology --- automated image analysis --- heat stress --- vacuoles --- cell size --- computer vision --- foam stability --- image analysis --- lager beer --- foam retention --- polyphenols --- LC-ESI-QTOF-MS/MS --- HPLC --- medicinal plants --- ginger --- lemon --- mint --- herbal tea infusion --- antioxidants --- black pepper --- focus group --- hops --- Kawakawa --- off aromas --- gas sensors --- robotic pourer --- aroma thresholds --- climate change --- artificial neural networks --- volatile phenols --- glycoconjugates --- bushfires --- sparkling wine --- fermentation --- biogenic amines --- wine quality --- liquid chromatography --- principal component analysis --- augmented reality --- non-dairy yogurt --- contexts --- consumer acceptability --- emotional responses --- Fermentation --- Olea europaea --- respiration rate --- storage conditions --- transport --- TeeBot --- high throughput --- liquid handling robot --- metabolite analysis --- stochastic dynamic optimisation --- uncertainty
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This book is the result of a Special Issue published in Applied Sciences, entitled “New Trends in Recycled Aggregate Concrete"". It identifies emerging research areas within the field of recycled aggregate concrete and contributes to the increased use of this eco-efficient material.Its contents are organised in the following sections: Upscaling the use of recycled aggregate concrete in structural design; Large scale applications of recycled aggregate concrete; Long-term behaviour of recycled aggregate concrete; Performance of recycled aggregate concrete in very aggressive environments; Reliability of recycled aggregate concrete structures; Life cycle assessment of recycled aggregate concrete; New applications of recycled aggregate concrete.
crushing --- heavyweight waste glass --- n/a --- recycled aggregate quality --- seismic load --- microstructure --- construction waste --- permeability --- bond strength --- seismic performance --- aggregate interlock mechanism --- recycled concrete aggregates --- compressive strength --- crumb rubber --- cellular concrete --- model --- cyclic load --- recycled aggregate --- crushed glass --- models --- recycled aggregate concrete --- reactive power concrete --- recycled aggregate concrete (RAC) --- energy absorbing --- creep --- elevated temperature --- fiber-reinforced concrete --- size effect --- recycled concrete aggregate --- geological nature of aggregates --- mechanical properties --- recycled concrete --- artificial neural networks --- recycled aggregates --- steel fibre --- quality of aggregates --- aggregates --- foam stability --- ceramic foam --- durable characteristics --- nylon fiber --- concrete --- mechanical characteristics --- strain rate --- steel reinforced recycled aggregate concrete (SRRAC) --- dynamic mechanical property --- concrete sludge fines --- water absorption --- columns --- environmental impact --- blast-furnace slag --- input variable --- tensile splitting strength --- aggregate --- returned concrete --- reinforced concrete member --- variable sensitivity --- soil stabilization --- numerical analysis --- shear behavior --- fly-ash --- modulus --- life cycle assessment --- foam structure --- silica fume --- recycling --- recycled coarse aggregate concrete --- ready-mixed concrete --- foam concrete --- flexural behavior --- mixture proportioning --- aggregate characteristic --- residual properties --- CT --- reinforced concrete --- shrinkage
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