AIMC Topic: Food-Processing Industry
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Predicting single-cell protein production from food-processing wastewater in sequencing batch reactors using ensemble learning.
Bioresource technology
Apr 19, 2025
Producing single-cell protein (SCP) from food-processing wastewater offers a sustainable approach to resource recovery, animal feed production, and wastewater treatment. Decision-makers need accurate system performance data under variable influent co...
Recent advances in artificial intelligence towards the sustainable future of agri-food industry.
Food chemistry
Mar 5, 2024
Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a ...
Safely and autonomously cutting meat with a collaborative robot arm.
Scientific reports
Jan 2, 2024
Labor shortages in the United States are impacting a number of industries including the meat processing sector. Collaborative technologies that work alongside humans while increasing production abilities may support the industry by enhancing automati...
Bioengineered Enzymes and Precision Fermentation in the Food Industry.
International journal of molecular sciences
Jun 15, 2023
Enzymes have been used in the food processing industry for many years. However, the use of native enzymes is not conducive to high activity, efficiency, range of substrates, and adaptability to harsh food processing conditions. The advent of enzyme e...
The fourth industrial revolution in the food industry-part II: Emerging food trends.
Critical reviews in food science and nutrition
Aug 5, 2022
The food industry has recently been under unprecedented pressure due to major global challenges, such as climate change, exponential increase in world population and urbanization, and the worldwide spread of new diseases and pandemics, such as the CO...
Application of deep neural techniques in predictive modelling for the estimation of Escherichia coli growth rate.
Journal of applied microbiology
Nov 3, 2020
AIMS: To develop a predictive model for Escherichia coli using deep neural networks.
Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble.
Sensors (Basel, Switzerland)
Jul 4, 2019
Imaging sensors are largely employed in the food processing industry for quality control. Flour from malting barley varieties is a valuable ingredient in the food industry, but its use is restricted due to quality aspects such as color variations and...
Use of artificial neuronal networks for prediction of the control parameters in the process of anaerobic digestion with thermal pretreatment.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Apr 19, 2018
This article focuses on the analysis of the behavior patterns of the variables involved in the anaerobic digestion process. The objective is to predict the impact factor and the behavior pattern of the variables, i.e., temperature, pH, volatile solid...
Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.
Environmental science and pollution research international
Sep 30, 2017
In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A li...
Modeling and optimization of Newfoundland shrimp waste hydrolysis for microbial growth using response surface methodology and artificial neural networks.
Marine pollution bulletin
Jun 14, 2016
The hydrolyzed protein derived from seafood waste is regarded as a premium and low-cost nitrogen source for microbial growth. In this study, optimization of enzymatic shrimp waste hydrolyzing process was investigated. The degree of hydrolysis (DH) wi...
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