Page 24 - Baking Europe Journal - Winter 2022

TECHNOLOGY
24 AUTOMATION/AI

and ultrasound acoustics can personnel, as well as improvement of combination of ingredients, data and
determine the protein content and the health of patients in a hospital. In algorithms. The tool supports product
several other properties in fl our, with both instances, consumers will be developers in bakeries to identify
great precision, compared to able to input their preferences into a effi ciently optimal sugar replacements
conventional technologies. 1 machine, which will combine this and predicts optimised lower sugar
Computer vision combined with information with all the nutritional recipes.
artifi cial neural networks can predict requirements for the individual
temperature, volume and the consumer to predict and create a Case study 3: Detection of mould
browning index during the baking personalised food programme. This and other defects
process. The information obtained novel, digital process will then
1
from this data can be integrated into integrate consumer preferences with Quality assessment during food
advanced baking process control appropriate ingredients in a special production and storage is a labour-
algorithms and, eventually, this can food production system to produce intensive task is, therefore, usually
lead to an increased level of the unique product for the consumer only performed on a representative
automation. and present an ideal opportunity to sample of products. WUR researchers
showcase the power of smart have applied computer vision
Example case studies using manufacturing. technologies combined with expert
smart baking knowledge on the appearance of
Case study 2: Digital tool for sugar mould to detect automatically and
Case study 1: 3D printing reduction quantify mould on food surfaces. The
personalised nutrition current capabilities of data storage
Reducing the sugar content in sweet and image analysis facilitate
There is an increasing understanding bakery products whilst maintaining assessment of a large number of
of how the eff ect of food and the product quality characteristics individual food products with this
nutrition aff ects general human health such as texture and sweetness is a tool, potentially allowing full
and performance, as well as individual complicated process. WUR experts automation of mould detection of the
responses. Together with an industrial gained scientifi c insight into the entire production. Computer vision
consortium, WUR and TNO (Dutch physicochemical behaviour of sugar can also be used for detection of
contract research organisation) are and sweeteners in baked foods as other (surface) defects.
working to develop a personalised well as their interaction with other
food production system based on 3D ingredients in the formulation, such as
printing. The system now being starches, proteins and fi bre. However,
developed, will allow personalised implementing this complex FOR MORE INFORMATION →
food products to be made at any knowledge with other practical
time, based on individual dietary requirements, like nutritional and
requirements. This individualised food labelling aspects, into working recipes
production such as this will be is not without complications. Hence,
reproduced in real-life studies to WUR developed a digital
enhance the performance of military reformulation tool using a
3

References:
1. Jerome, Rifna E., Sushil K. Singh, and Madhuresh Dwivedi. "Process
analytical technology for bakery industry: A review." Journal of Food
Process Engineering 42.5 (2019): e13143.

2. Rovito, M. Smart Manufacturing: The Future of Making Is Digital, Redshift Martijn Noort
April 4, 2022 https://redshift.autodesk.com/articles/smart-manufacturing Wageningen Food & Biobased
Research
3. https://www.wur.nl/en/Research-Results/Research-Institutes/food- E: martijn.noort@wur.nl
biobased-research/Solutions/Healthy-clean-label-foods/Digital-Sugar- W: www.digitalfoodprocessing.com
reduction-tool.htm
W: www.wur.nl

BAKINGEUROPE Winter 2022/2023
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