Research graph
References from From observation to autonomous discovery: An epistemic-capability framework for artificial intelligence in food science. Local targets link to admitted publications; unresolved targets remain external evidence.
The rise of self-driving labs in chemical and materials sciences
10.1038/s44160-022-00231-0 · 2023 · External reference
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · 2024 · External reference
Rational food design and food microstructure
10.1016/j.tifs.2022.02.006 · 2022 · External reference
Flavor network and the principles of food pairing
10.1038/srep00196 · 2011 · External reference
Inverse design and AI/deep generative networks in food design: A comprehensive review
10.1016/j.tifs.2023.06.005 · 2023 · External reference
Artificial intelligence in food safety: A tertiary study
2026 · External reference
Innovation in precision fermentation for food ingredients
10.1080/10408398.2023.2166014 · 2024 · External reference
Artificial intelligence for food safety: From predictive models to real-world safeguards
10.1016/j.tifs.2025.105153 · 2025 · External reference
Consumer acceptance of precision fermentation technology: A cross-cultural study
10.1016/j.ifset.2023.103435 · 2023 · External reference
The unmapped chemical complexity of our diet
10.1038/s43016-019-0005-1 · 2020 · External reference
A novel physics-informed neural networks approach (PINN-MT) to solve mass transfer in plant cells during drying
10.1016/j.biosystemseng.2023.04.012 · 2023 · External reference
A physics-informed neural network-based surrogate framework to predict moisture concentration and shrinkage of a plant cell during drying
10.1016/j.jfoodeng.2022.111137 · 2022 · External reference
Bayesian optimization with safety constraints: Safe and automatic parameter tuning in robotics
10.1007/s10994-021-06019-1 · 2023 · External reference
Comprehensive study on applications of artificial neural network in food process modeling
10.1080/10408398.2020.1858398 · 2022 · External reference
Autonomous chemical research with large language models
10.1038/s41586-023-06792-0 · 2023 · External reference
Domain adaptation for in-line allergen classification of agri-food powders using near-infrared spectroscopy
10.3390/s22197239 · 2022 · External reference
Unresolved reference
2024 · External reference
A mobile robotic chemist
10.1038/s41586-020-2442-2 · 2020 · External reference
Multimodal AI for real-time food safety and quality: From sensors to foundation models, edge deployment, and regulation
10.1002/fsn3.71534 · 2026 · External reference
Artificial intelligence in metabolomics: A current review
10.1016/j.trac.2024.117852 · 2024 · External reference
Multi-information source Bayesian optimization of culture media for cellular agriculture
10.1002/bit.28132 · 2022 · External reference
Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development
10.1111/1541-4337.70068 · 2025 · External reference
Artificial intelligence for food innovation
10.1038/s43016-026-01380-7 · 2026 · External reference
PepVAE: Variational autoencoder framework for antimicrobial peptide generation and activity prediction
10.3389/fmicb.2021.725727 · 2021 · External reference
Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: A comprehensive review
10.1007/s42452-025-06472-w · 2025 · External reference
Precision fermentation for food proteins: Ingredient innovations, bioprocess considerations, and outlook
10.1016/j.cofs.2024.101194 · 2024 · External reference
Guidance on the scientific requirements for an application for authorisation of a novel food in the context of Regulation (EU) 2015/2283
2024 · External reference
Agentic artificial intelligence in food science: From automation to adaptation
2026 · External reference
A Bayesian experimental autonomous researcher for mechanical design
10.1126/sciadv.aaz1708 · 2020 · External reference
E-sensing systems for shelf life evaluation: A review on applications to fresh food of animal origin
10.1016/j.fpsl.2023.101221 · 2023 · External reference
Next-generation experimentation with self-driving laboratories
10.1016/j.trechm.2019.02.007 · 2019 · External reference
From Food Industry 4.0 to Food Industry 5.0: Identifying technological enablers and potential future applications in the food sector
2024 · External reference
Autonomous self-driving laboratories: A review of technology and policy implications
2025 · External reference
Implementation of digital twins in the food supply chain: A review and conceptual framework
10.1080/00207543.2024.2305804 · 2024 · External reference
Exploring trends and future developments in the application of artificial intelligence in food processing and preservation
10.1007/s12393-026-09445-w · 2026 · External reference
A critical review on computer vision and artificial intelligence in food industry
10.1016/j.jafr.2020.100033 · 2020 · External reference
Cultured meat reformulation: Health potential and sustainable food challenges: A narrative review
2025 · External reference
Machine learning-based modeling in food processing applications: State of the art
10.1111/1541-4337.12912 · 2022 · External reference
Predicting the textural properties of plant-based meat analogs with machine learning
10.3390/foods12020344 · 2023 · External reference
Facilitated machine learning for image-based fruit quality assessment
10.1016/j.jfoodeng.2022.111401 · 2023 · External reference
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back
10.1126/science.adi1407 · 2023 · External reference
Artificial intelligence technology in food safety: A behavioral approach
10.1016/j.tifs.2022.03.021 · 2022 · External reference
On-the-fly closed-loop materials discovery via Bayesian active learning
10.1038/s41467-020-19597-w · 2020 · External reference
Simple and scalable predictive uncertainty estimation using deep ensembles
2017 · External reference
Technology readiness levels for machine learning systems
10.1038/s41467-022-33128-9 · 2022 · External reference
A principal odor map unifies diverse tasks in olfactory perception
10.1126/science.ade4401 · 2023 · External reference
Artificial intelligence-based prediction of the rheological properties of hydrocolloids for plant-based meat analogues
10.1002/jsfa.13334 · 2024 · External reference
De novo synthetic antimicrobial peptide design with a recurrent neural network
2024 · External reference
Machine learning for quality control in the food industry: A review
10.3390/foods14193424 · 2025 · External reference
Sensor-integrated inverse design of sustainable food packaging materials via generative adversarial networks
10.3390/s25113320 · 2025 · External reference
Artificial intelligence in food safety: A decade review and bibliometric analysis
10.3390/foods12061242 · 2023 · External reference
Electronic tongue and electronic nose for food quality and safety
10.1016/j.foodres.2022.112214 · 2022 · External reference
Large language models in food science: Innovations, applications, and future
10.1016/j.tifs.2024.104488 · 2024 · External reference
Self-driving laboratory for accelerated discovery of thin-film materials
10.1126/sciadv.aaz8867 · 2020 · External reference
Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil
10.1016/j.crfs.2024.100913 · 2024 · External reference
Futures of artificial intelligence through technology readiness levels
10.1016/j.tele.2020.101525 · 2021 · External reference
Machine learning in drying
10.1080/07373937.2019.1690502 · 2020 · External reference
Application of artificial intelligence in food industry: A guideline
2021 · External reference
Scaling deep learning for materials discovery
10.1038/s41586-023-06735-9 · 2023 · External reference
A perspective on the regulation of cultivated meat in the European Union
10.1038/s41538-025-00384-0 · 2025 · External reference
Making food systems more resilient to food safety risks by including artificial intelligence, big data, and Internet of Things into food safety early warning and emerging risk identification tools
10.1111/1541-4337.13296 · 2024 · External reference
Enhancing food safety in the cold chain through Internet of Things and artificial intelligence
2026 · External reference
Artificial intelligence-based techniques for adulteration and defect detections in food and agricultural industry: A review
10.1016/j.jafr.2023.100590 · 2023 · External reference
Mapping the AI landscape in food science and engineering: A bibliometric analysis enhanced with interactive digital tools and company case studies
10.1007/s12393-025-09413-w · 2025 · External reference
How can AI help improve food safety?
10.1146/annurev-food-060721-013815 · 2023 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Applications of machine learning in food safety and HACCP monitoring of animal-source foods
10.3390/foods14060922 · 2025 · External reference
Utilization of AI: Reshaping the future of food safety, agriculture and food security: A critical review
10.1080/10408398.2024.2430749 · 2025 · External reference
A global perspective on artificial intelligence applications and barriers in food safety: A systematic review (2018-2025)
2026 · External reference
Autonomous chemical experiments: Challenges and perspectives on establishing a self-driving lab
10.1021/acs.accounts.2c00220 · 2022 · External reference
Machine vision combined with deep learning-based approaches for food authentication: An integrative review and new insights
10.1111/1541-4337.70054 · 2024 · External reference
Consumer acceptance of novel food technologies
10.1038/s43016-020-0094-x · 2020 · External reference
Predicting corn moisture content in continuous drying systems using LSTM neural networks
10.3390/foods14061051 · 2025 · External reference
The mechanical and sensory signature of plant-based and animal meat
10.1038/s41538-024-00330-6 · 2024 · External reference
De novo design and experimental characterization of bitter peptides
10.1038/s41538-026-00942-0 · 2026 · External reference
Safe exploration for optimization with Gaussian processes
2015 · External reference
Robotic optimization of powdered beverages leveraging computer vision and Bayesian optimization
10.3389/frobt.2025.1603729 · 2025 · External reference
An autonomous laboratory for the accelerated synthesis of novel materials
10.1038/s41586-023-06734-w · 2023 · External reference
Author correction: An autonomous laboratory for the accelerated synthesis of inorganic materials
10.1038/s41586-025-09992-y · 2026 · External reference
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
10.1038/s41467-023-36994-z · 2023 · External reference
Generative artificial intelligence creates delicious, sustainable, and nutritious burgers
10.1038/s41538-026-00953-x · 2026 · External reference
Generative AI for material design: A mechanics perspective from burgers to matter
10.1016/j.cma.2026.119171 · 2026 · External reference
Advancements in predictive microbiology: Integrating new technologies for efficient food safety models
10.1155/2024/6612162 · 2024 · External reference
The use of predictive microbiology for the prediction of the shelf life of food products
10.3390/foods12244461 · 2023 · External reference
Unresolved reference
2022 · External reference
What can large language models do for sustainable food?
2025 · External reference
Artificial intelligence and machine learning applications for cultured meat
10.3389/frai.2024.1424012 · 2024 · External reference
Self-driving laboratories for chemistry and materials science
10.1021/acs.chemrev.4c00055 · 2024 · External reference
Inventorship guidance for AI-assisted inventions
2024 · External reference
Open-source benchmarking of plant-based and animal meats
10.3390/foods15122112 · 2026 · External reference
Artificial intelligence in food safety
2026 · External reference
Attention is all you need
2017 · External reference
Using a region-based convolutional neural network for potato segmentation in a sorting process
10.3390/foods14071131 · 2025 · External reference
Performance metrics to unleash the power of self-driving labs in chemistry and materials science
10.1038/s41467-024-45569-5 · 2024 · External reference
AlphaFlow: Autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning
10.1038/s41467-023-37139-y · 2023 · External reference
Hyperspectral imaging and deep learning for quality and safety inspection of fruits and vegetables: A review
10.1021/acs.jafc.4c11492 · 2025 · External reference
Recent advances in food drying modeling: Empirical to multiscale physics-informed neural networks
10.1111/1541-4337.70194 · 2025 · External reference
Is AI food a gimmick or the future direction of food production? Predicting consumers' willingness to buy AI food based on cognitive trust and affective trust
10.3390/foods13182983 · 2024 · External reference
Generative artificial intelligence shaping the future of agri-food innovation
2026 · External reference
Generalized out-of-distribution detection: A survey
10.1007/s11263-024-02117-4 · 2024 · External reference
Research progress on the artificial intelligence applications in food safety and quality management
10.1016/j.tifs.2024.104855 · 2025 · External reference
TastePepAI: An artificial intelligence platform for taste peptide de novo design
10.1371/journal.pcbi.1013602 · 2025 · External reference
Revolutionizing the food industry: The transformative power of artificial intelligence: A review
10.1016/j.fochx.2024.101867 · 2024 · External reference
A generative model for inorganic materials design
10.1038/s41586-025-08628-5 · 2025 · External reference
De novo antimicrobial peptide design with feedback generative adversarial networks
10.3390/ijms25105506 · 2024 · External reference
Accelerated discovery of CO2 electrocatalysts using active machine learning
10.1038/s41586-020-2242-8 · 2020 · External reference
Deep learning and machine vision for food processing: A survey
10.1016/j.crfs.2021.03.009 · 2021 · External reference
Are you AI-ready? A framework for evaluating artificial intelligence applications in food safety programs
2026 · External reference
Multi-information source Bayesian optimization of culture media for cellular agriculture
10.1002/bit.28132 · ExternalCitation · doi-reference
Multimodal AI for real-time food safety and quality: From sensors to foundation models, edge deployment, and regulation
10.1002/fsn3.71534 · ExternalCitation · doi-reference
Artificial intelligence-based prediction of the rheological properties of hydrocolloids for plant-based meat analogues
10.1002/jsfa.13334 · ExternalCitation · doi-reference
Bayesian optimization with safety constraints: Safe and automatic parameter tuning in robotics
10.1007/s10994-021-06019-1 · ExternalCitation · doi-reference
Generalized out-of-distribution detection: A survey
10.1007/s11263-024-02117-4 · ExternalCitation · doi-reference
Mapping the AI landscape in food science and engineering: A bibliometric analysis enhanced with interactive digital tools and company case studies
10.1007/s12393-025-09413-w · ExternalCitation · doi-reference
Exploring trends and future developments in the application of artificial intelligence in food processing and preservation
10.1007/s12393-026-09445-w · ExternalCitation · doi-reference
Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: A comprehensive review
10.1007/s42452-025-06472-w · ExternalCitation · doi-reference
A novel physics-informed neural networks approach (PINN-MT) to solve mass transfer in plant cells during drying
10.1016/j.biosystemseng.2023.04.012 · ExternalCitation · doi-reference
Generative AI for material design: A mechanics perspective from burgers to matter
10.1016/j.cma.2026.119171 · ExternalCitation · doi-reference
Precision fermentation for food proteins: Ingredient innovations, bioprocess considerations, and outlook
10.1016/j.cofs.2024.101194 · ExternalCitation · doi-reference
Deep learning and machine vision for food processing: A survey
10.1016/j.crfs.2021.03.009 · ExternalCitation · doi-reference
Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil
10.1016/j.crfs.2024.100913 · ExternalCitation · doi-reference
Revolutionizing the food industry: The transformative power of artificial intelligence: A review
10.1016/j.fochx.2024.101867 · ExternalCitation · doi-reference
Electronic tongue and electronic nose for food quality and safety
10.1016/j.foodres.2022.112214 · ExternalCitation · doi-reference
E-sensing systems for shelf life evaluation: A review on applications to fresh food of animal origin
10.1016/j.fpsl.2023.101221 · ExternalCitation · doi-reference
Consumer acceptance of precision fermentation technology: A cross-cultural study
10.1016/j.ifset.2023.103435 · ExternalCitation · doi-reference
A critical review on computer vision and artificial intelligence in food industry
10.1016/j.jafr.2020.100033 · ExternalCitation · doi-reference
Artificial intelligence-based techniques for adulteration and defect detections in food and agricultural industry: A review
10.1016/j.jafr.2023.100590 · ExternalCitation · doi-reference
A physics-informed neural network-based surrogate framework to predict moisture concentration and shrinkage of a plant cell during drying
10.1016/j.jfoodeng.2022.111137 · ExternalCitation · doi-reference
Facilitated machine learning for image-based fruit quality assessment
10.1016/j.jfoodeng.2022.111401 · ExternalCitation · doi-reference
Futures of artificial intelligence through technology readiness levels
10.1016/j.tele.2020.101525 · ExternalCitation · doi-reference
Rational food design and food microstructure
10.1016/j.tifs.2022.02.006 · ExternalCitation · doi-reference
Artificial intelligence technology in food safety: A behavioral approach
10.1016/j.tifs.2022.03.021 · ExternalCitation · doi-reference
Inverse design and AI/deep generative networks in food design: A comprehensive review
10.1016/j.tifs.2023.06.005 · ExternalCitation · doi-reference
Large language models in food science: Innovations, applications, and future
10.1016/j.tifs.2024.104488 · ExternalCitation · doi-reference
Research progress on the artificial intelligence applications in food safety and quality management
10.1016/j.tifs.2024.104855 · ExternalCitation · doi-reference
Artificial intelligence for food safety: From predictive models to real-world safeguards
10.1016/j.tifs.2025.105153 · ExternalCitation · doi-reference
Artificial intelligence in metabolomics: A current review
10.1016/j.trac.2024.117852 · ExternalCitation · doi-reference
Next-generation experimentation with self-driving laboratories
10.1016/j.trechm.2019.02.007 · ExternalCitation · doi-reference
Autonomous chemical experiments: Challenges and perspectives on establishing a self-driving lab
10.1021/acs.accounts.2c00220 · ExternalCitation · doi-reference
Self-driving laboratories for chemistry and materials science
10.1021/acs.chemrev.4c00055 · ExternalCitation · doi-reference
Hyperspectral imaging and deep learning for quality and safety inspection of fruits and vegetables: A review
10.1021/acs.jafc.4c11492 · ExternalCitation · doi-reference
On-the-fly closed-loop materials discovery via Bayesian active learning
10.1038/s41467-020-19597-w · ExternalCitation · doi-reference
Technology readiness levels for machine learning systems
10.1038/s41467-022-33128-9 · ExternalCitation · doi-reference
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
10.1038/s41467-023-36994-z · ExternalCitation · doi-reference
AlphaFlow: Autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning
10.1038/s41467-023-37139-y · ExternalCitation · doi-reference
Performance metrics to unleash the power of self-driving labs in chemistry and materials science
10.1038/s41467-024-45569-5 · ExternalCitation · doi-reference
The mechanical and sensory signature of plant-based and animal meat
10.1038/s41538-024-00330-6 · ExternalCitation · doi-reference
A perspective on the regulation of cultivated meat in the European Union
10.1038/s41538-025-00384-0 · ExternalCitation · doi-reference
De novo design and experimental characterization of bitter peptides
10.1038/s41538-026-00942-0 · ExternalCitation · doi-reference
Generative artificial intelligence creates delicious, sustainable, and nutritious burgers
10.1038/s41538-026-00953-x · ExternalCitation · doi-reference
Accelerated discovery of CO2 electrocatalysts using active machine learning
10.1038/s41586-020-2242-8 · ExternalCitation · doi-reference
A mobile robotic chemist
10.1038/s41586-020-2442-2 · ExternalCitation · doi-reference
An autonomous laboratory for the accelerated synthesis of novel materials
10.1038/s41586-023-06734-w · ExternalCitation · doi-reference
Scaling deep learning for materials discovery
10.1038/s41586-023-06735-9 · ExternalCitation · doi-reference
Autonomous chemical research with large language models
10.1038/s41586-023-06792-0 · ExternalCitation · doi-reference
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · ExternalCitation · doi-reference
A generative model for inorganic materials design
10.1038/s41586-025-08628-5 · ExternalCitation · doi-reference
Author correction: An autonomous laboratory for the accelerated synthesis of inorganic materials
10.1038/s41586-025-09992-y · ExternalCitation · doi-reference
The unmapped chemical complexity of our diet
10.1038/s43016-019-0005-1 · ExternalCitation · doi-reference
Consumer acceptance of novel food technologies
10.1038/s43016-020-0094-x · ExternalCitation · doi-reference
Artificial intelligence for food innovation
10.1038/s43016-026-01380-7 · ExternalCitation · doi-reference
The rise of self-driving labs in chemical and materials sciences
10.1038/s44160-022-00231-0 · ExternalCitation · doi-reference
Flavor network and the principles of food pairing
10.1038/srep00196 · ExternalCitation · doi-reference
Implementation of digital twins in the food supply chain: A review and conceptual framework
10.1080/00207543.2024.2305804 · ExternalCitation · doi-reference
Machine learning in drying
10.1080/07373937.2019.1690502 · ExternalCitation · doi-reference
Comprehensive study on applications of artificial neural network in food process modeling
10.1080/10408398.2020.1858398 · ExternalCitation · doi-reference
Innovation in precision fermentation for food ingredients
10.1080/10408398.2023.2166014 · ExternalCitation · doi-reference
Utilization of AI: Reshaping the future of food safety, agriculture and food security: A critical review
10.1080/10408398.2024.2430749 · ExternalCitation · doi-reference
Machine learning-based modeling in food processing applications: State of the art
10.1111/1541-4337.12912 · ExternalCitation · doi-reference
Making food systems more resilient to food safety risks by including artificial intelligence, big data, and Internet of Things into food safety early warning and emerging risk identification tools
10.1111/1541-4337.13296 · ExternalCitation · doi-reference
Machine vision combined with deep learning-based approaches for food authentication: An integrative review and new insights
10.1111/1541-4337.70054 · ExternalCitation · doi-reference
Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development
10.1111/1541-4337.70068 · ExternalCitation · doi-reference
Recent advances in food drying modeling: Empirical to multiscale physics-informed neural networks
10.1111/1541-4337.70194 · ExternalCitation · doi-reference
A Bayesian experimental autonomous researcher for mechanical design
10.1126/sciadv.aaz1708 · ExternalCitation · doi-reference
Self-driving laboratory for accelerated discovery of thin-film materials
10.1126/sciadv.aaz8867 · ExternalCitation · doi-reference
A principal odor map unifies diverse tasks in olfactory perception
10.1126/science.ade4401 · ExternalCitation · doi-reference
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back
10.1126/science.adi1407 · ExternalCitation · doi-reference
How can AI help improve food safety?
10.1146/annurev-food-060721-013815 · ExternalCitation · doi-reference
Advancements in predictive microbiology: Integrating new technologies for efficient food safety models
10.1155/2024/6612162 · ExternalCitation · doi-reference
TastePepAI: An artificial intelligence platform for taste peptide de novo design
10.1371/journal.pcbi.1013602 · ExternalCitation · doi-reference
PepVAE: Variational autoencoder framework for antimicrobial peptide generation and activity prediction
10.3389/fmicb.2021.725727 · ExternalCitation · doi-reference
Artificial intelligence and machine learning applications for cultured meat
10.3389/frai.2024.1424012 · ExternalCitation · doi-reference
Robotic optimization of powdered beverages leveraging computer vision and Bayesian optimization
10.3389/frobt.2025.1603729 · ExternalCitation · doi-reference
Predicting the textural properties of plant-based meat analogs with machine learning
10.3390/foods12020344 · ExternalCitation · doi-reference
Artificial intelligence in food safety: A decade review and bibliometric analysis
10.3390/foods12061242 · ExternalCitation · doi-reference
The use of predictive microbiology for the prediction of the shelf life of food products
10.3390/foods12244461 · ExternalCitation · doi-reference
Is AI food a gimmick or the future direction of food production? Predicting consumers' willingness to buy AI food based on cognitive trust and affective trust
10.3390/foods13182983 · ExternalCitation · doi-reference
Applications of machine learning in food safety and HACCP monitoring of animal-source foods
10.3390/foods14060922 · ExternalCitation · doi-reference
Predicting corn moisture content in continuous drying systems using LSTM neural networks
10.3390/foods14061051 · ExternalCitation · doi-reference
Using a region-based convolutional neural network for potato segmentation in a sorting process
10.3390/foods14071131 · ExternalCitation · doi-reference
Machine learning for quality control in the food industry: A review
10.3390/foods14193424 · ExternalCitation · doi-reference
Open-source benchmarking of plant-based and animal meats
10.3390/foods15122112 · ExternalCitation · doi-reference
De novo antimicrobial peptide design with feedback generative adversarial networks
10.3390/ijms25105506 · ExternalCitation · doi-reference
Domain adaptation for in-line allergen classification of agri-food powders using near-infrared spectroscopy
10.3390/s22197239 · ExternalCitation · doi-reference
Sensor-integrated inverse design of sustainable food packaging materials via generative adversarial networks
10.3390/s25113320 · ExternalCitation · doi-reference
