Machine Learning-Based Analytical Systems: Food Forensics Article Swipe
Ranbir
,
Manish Kumar
,
Gagandeep Singh
,
Jasvir Singh
,
Navneet Kaur
,
Narinder Singh
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1021/acsomega.2c05632
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1021/acsomega.2c05632
Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.
Related Topics
Concepts
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1021/acsomega.2c05632
- https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632
- OA Status
- gold
- Cited By
- 32
- References
- 93
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4313296055
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4313296055Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1021/acsomega.2c05632Digital Object Identifier
- Title
-
Machine Learning-Based Analytical Systems: Food ForensicsWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-16Full publication date if available
- Authors
-
Ranbir, Manish Kumar, Gagandeep Singh, Jasvir Singh, Navneet Kaur, Narinder SinghList of authors in order
- Landing page
-
https://doi.org/10.1021/acsomega.2c05632Publisher landing page
- PDF URL
-
https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632Direct OA link when available
- Concepts
-
Computer science, Food safety, Artificial intelligence, Biochemical engineering, Food spoilage, Machine learning, Food quality, Engineering, Chemistry, Food science, Genetics, Bacteria, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 14, 2024: 15, 2023: 3Per-year citation counts (last 5 years)
- References (count)
-
93Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4313296055 |
|---|---|
| doi | https://doi.org/10.1021/acsomega.2c05632 |
| ids.doi | https://doi.org/10.1021/acsomega.2c05632 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/36591133 |
| ids.openalex | https://openalex.org/W4313296055 |
| fwci | 3.55191584 |
| type | review |
| title | Machine Learning-Based Analytical Systems: Food Forensics |
| awards[0].id | https://openalex.org/G1829095358 |
| awards[0].funder_id | https://openalex.org/F4320320719 |
| awards[0].display_name | |
| awards[0].funder_award_id | SP/YO/2019/1609 |
| awards[0].funder_display_name | Department of Science and Technology, Ministry of Science and Technology, India |
| biblio.issue | 51 |
| biblio.volume | 7 |
| biblio.last_page | 47535 |
| biblio.first_page | 47518 |
| topics[0].id | https://openalex.org/T11667 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2204 |
| topics[0].subfield.display_name | Biomedical Engineering |
| topics[0].display_name | Advanced Chemical Sensor Technologies |
| topics[1].id | https://openalex.org/T12388 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9991000294685364 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1312 |
| topics[1].subfield.display_name | Molecular Biology |
| topics[1].display_name | Identification and Quantification in Food |
| topics[2].id | https://openalex.org/T10640 |
| topics[2].field.id | https://openalex.org/fields/16 |
| topics[2].field.display_name | Chemistry |
| topics[2].score | 0.9944999814033508 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1602 |
| topics[2].subfield.display_name | Analytical Chemistry |
| topics[2].display_name | Spectroscopy and Chemometric Analyses |
| funders[0].id | https://openalex.org/F4320320719 |
| funders[0].ror | https://ror.org/0101xrq71 |
| funders[0].display_name | Department of Science and Technology, Ministry of Science and Technology, India |
| is_xpac | False |
| apc_list.value | 1685 |
| apc_list.currency | USD |
| apc_list.value_usd | 1685 |
| apc_paid.value | 1685 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1685 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.6471556425094604 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C516717267 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5524149537086487 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q909821 |
| concepts[1].display_name | Food safety |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5159345269203186 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C183696295 |
| concepts[3].level | 1 |
| concepts[3].score | 0.49631673097610474 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2487696 |
| concepts[3].display_name | Biochemical engineering |
| concepts[4].id | https://openalex.org/C147490202 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4611527919769287 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q5465528 |
| concepts[4].display_name | Food spoilage |
| concepts[5].id | https://openalex.org/C119857082 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4536024332046509 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[5].display_name | Machine learning |
| concepts[6].id | https://openalex.org/C51592225 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4190061390399933 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2498665 |
| concepts[6].display_name | Food quality |
| concepts[7].id | https://openalex.org/C127413603 |
| concepts[7].level | 0 |
| concepts[7].score | 0.18003904819488525 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[7].display_name | Engineering |
| concepts[8].id | https://openalex.org/C185592680 |
| concepts[8].level | 0 |
| concepts[8].score | 0.11188235878944397 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[8].display_name | Chemistry |
| concepts[9].id | https://openalex.org/C31903555 |
| concepts[9].level | 1 |
| concepts[9].score | 0.09185296297073364 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1637030 |
| concepts[9].display_name | Food science |
| concepts[10].id | https://openalex.org/C54355233 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7162 |
| concepts[10].display_name | Genetics |
| concepts[11].id | https://openalex.org/C523546767 |
| concepts[11].level | 2 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q10876 |
| concepts[11].display_name | Bacteria |
| concepts[12].id | https://openalex.org/C86803240 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[12].display_name | Biology |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.6471556425094604 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/food-safety |
| keywords[1].score | 0.5524149537086487 |
| keywords[1].display_name | Food safety |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.5159345269203186 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/biochemical-engineering |
| keywords[3].score | 0.49631673097610474 |
| keywords[3].display_name | Biochemical engineering |
| keywords[4].id | https://openalex.org/keywords/food-spoilage |
| keywords[4].score | 0.4611527919769287 |
| keywords[4].display_name | Food spoilage |
| keywords[5].id | https://openalex.org/keywords/machine-learning |
| keywords[5].score | 0.4536024332046509 |
| keywords[5].display_name | Machine learning |
| keywords[6].id | https://openalex.org/keywords/food-quality |
| keywords[6].score | 0.4190061390399933 |
| keywords[6].display_name | Food quality |
| keywords[7].id | https://openalex.org/keywords/engineering |
| keywords[7].score | 0.18003904819488525 |
| keywords[7].display_name | Engineering |
| keywords[8].id | https://openalex.org/keywords/chemistry |
| keywords[8].score | 0.11188235878944397 |
| keywords[8].display_name | Chemistry |
| keywords[9].id | https://openalex.org/keywords/food-science |
| keywords[9].score | 0.09185296297073364 |
| keywords[9].display_name | Food science |
| language | en |
| locations[0].id | doi:10.1021/acsomega.2c05632 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210239500 |
| locations[0].source.issn | 2470-1343 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2470-1343 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | ACS Omega |
| locations[0].source.host_organization | https://openalex.org/P4310320006 |
| locations[0].source.host_organization_name | American Chemical Society |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320006 |
| locations[0].source.host_organization_lineage_names | American Chemical Society |
| locations[0].license | |
| locations[0].pdf_url | https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | ACS Omega |
| locations[0].landing_page_url | https://doi.org/10.1021/acsomega.2c05632 |
| locations[1].id | pmid:36591133 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | ACS omega |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/36591133 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:9798398 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | ACS Omega |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/9798398 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5022354554 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Ranbir |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I119241673 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[0].institutions[0].id | https://openalex.org/I119241673 |
| authorships[0].institutions[0].ror | https://ror.org/02qkhhn56 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I119241673 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Indian Institute of Technology Ropar |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | None Ranbir |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[1].author.id | https://openalex.org/A5101914248 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-0832-0642 |
| authorships[1].author.display_name | Manish Kumar |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I119241673 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[1].institutions[0].id | https://openalex.org/I119241673 |
| authorships[1].institutions[0].ror | https://ror.org/02qkhhn56 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I119241673 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Indian Institute of Technology Ropar |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Manish Kumar |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[2].author.id | https://openalex.org/A5008234335 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0815-0268 |
| authorships[2].author.display_name | Gagandeep Singh |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I119241673 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[2].institutions[0].id | https://openalex.org/I119241673 |
| authorships[2].institutions[0].ror | https://ror.org/02qkhhn56 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I119241673 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Indian Institute of Technology Ropar |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Gagandeep Singh |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[3].author.id | https://openalex.org/A5019309865 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-9751-7361 |
| authorships[3].author.display_name | Jasvir Singh |
| authorships[3].countries | IN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I904467727 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Chemistry, Himachal Pradesh University, Shimla 171005, India |
| authorships[3].institutions[0].id | https://openalex.org/I904467727 |
| authorships[3].institutions[0].ror | https://ror.org/02s5yma07 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I904467727 |
| authorships[3].institutions[0].country_code | IN |
| authorships[3].institutions[0].display_name | Himachal Pradesh University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Jasvir Singh |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Chemistry, Himachal Pradesh University, Shimla 171005, India |
| authorships[4].author.id | https://openalex.org/A5002219999 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0012-6151 |
| authorships[4].author.display_name | Navneet Kaur |
| authorships[4].countries | IN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I51452335 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Chemistry, Panjab University, Chandigarh 160014, India |
| authorships[4].institutions[0].id | https://openalex.org/I51452335 |
| authorships[4].institutions[0].ror | https://ror.org/04p2sbk06 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I51452335 |
| authorships[4].institutions[0].country_code | IN |
| authorships[4].institutions[0].display_name | Panjab University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Navneet Kaur |
| authorships[4].is_corresponding | True |
| authorships[4].raw_affiliation_strings | Department of Chemistry, Panjab University, Chandigarh 160014, India |
| authorships[5].author.id | https://openalex.org/A5073780661 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-8794-8157 |
| authorships[5].author.display_name | Narinder Singh |
| authorships[5].countries | IN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I119241673 |
| authorships[5].affiliations[0].raw_affiliation_string | Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[5].affiliations[1].institution_ids | https://openalex.org/I119241673 |
| authorships[5].affiliations[1].raw_affiliation_string | Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| authorships[5].institutions[0].id | https://openalex.org/I119241673 |
| authorships[5].institutions[0].ror | https://ror.org/02qkhhn56 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I119241673 |
| authorships[5].institutions[0].country_code | IN |
| authorships[5].institutions[0].display_name | Indian Institute of Technology Ropar |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Narinder Singh |
| authorships[5].is_corresponding | True |
| authorships[5].raw_affiliation_strings | Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India, Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar 140001, Punjab, India |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Machine Learning-Based Analytical Systems: Food Forensics |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11667 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2204 |
| primary_topic.subfield.display_name | Biomedical Engineering |
| primary_topic.display_name | Advanced Chemical Sensor Technologies |
| related_works | https://openalex.org/W1801823505, https://openalex.org/W4205867427, https://openalex.org/W2358120884, https://openalex.org/W4225115302, https://openalex.org/W4213203992, https://openalex.org/W2370976072, https://openalex.org/W4379781081, https://openalex.org/W2183758195, https://openalex.org/W4242971969, https://openalex.org/W2945052678 |
| cited_by_count | 32 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 14 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 15 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 3 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1021/acsomega.2c05632 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210239500 |
| best_oa_location.source.issn | 2470-1343 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2470-1343 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | ACS Omega |
| best_oa_location.source.host_organization | https://openalex.org/P4310320006 |
| best_oa_location.source.host_organization_name | American Chemical Society |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320006 |
| best_oa_location.source.host_organization_lineage_names | American Chemical Society |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | ACS Omega |
| best_oa_location.landing_page_url | https://doi.org/10.1021/acsomega.2c05632 |
| primary_location.id | doi:10.1021/acsomega.2c05632 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210239500 |
| primary_location.source.issn | 2470-1343 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2470-1343 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | ACS Omega |
| primary_location.source.host_organization | https://openalex.org/P4310320006 |
| primary_location.source.host_organization_name | American Chemical Society |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320006 |
| primary_location.source.host_organization_lineage_names | American Chemical Society |
| primary_location.license | |
| primary_location.pdf_url | https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c05632 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | ACS Omega |
| primary_location.landing_page_url | https://doi.org/10.1021/acsomega.2c05632 |
| publication_date | 2022-12-16 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W3097628033, https://openalex.org/W4206638596, https://openalex.org/W2041962508, https://openalex.org/W3193668794, https://openalex.org/W2790852339, https://openalex.org/W2546724206, https://openalex.org/W2050604127, https://openalex.org/W4206316422, https://openalex.org/W2967314029, https://openalex.org/W3043027384, https://openalex.org/W4241273490, https://openalex.org/W2809282179, https://openalex.org/W4290649643, https://openalex.org/W2959691252, https://openalex.org/W3029260840, https://openalex.org/W3113394170, https://openalex.org/W2555017836, https://openalex.org/W2164568072, https://openalex.org/W2509108354, https://openalex.org/W2312968374, https://openalex.org/W2789933186, https://openalex.org/W2052237331, https://openalex.org/W2807733030, https://openalex.org/W2418631124, https://openalex.org/W2335610720, https://openalex.org/W3207760471, https://openalex.org/W3132956480, https://openalex.org/W2910555889, https://openalex.org/W2777886168, https://openalex.org/W3159156584, https://openalex.org/W1578803970, https://openalex.org/W170028715, https://openalex.org/W2047787252, https://openalex.org/W2128728535, https://openalex.org/W2041423397, https://openalex.org/W1984981454, https://openalex.org/W1991362481, https://openalex.org/W2140196823, https://openalex.org/W3118359415, https://openalex.org/W2025025456, https://openalex.org/W2116296021, https://openalex.org/W3210740626, https://openalex.org/W3155907534, https://openalex.org/W2889675990, https://openalex.org/W1997082874, https://openalex.org/W1506767743, https://openalex.org/W2026085713, https://openalex.org/W2075074809, https://openalex.org/W2217320229, https://openalex.org/W2726978631, https://openalex.org/W2398029297, https://openalex.org/W2370134619, https://openalex.org/W1976837844, https://openalex.org/W2963728730, https://openalex.org/W3005015973, https://openalex.org/W3156779132, https://openalex.org/W4200464230, https://openalex.org/W2884375617, https://openalex.org/W4214527022, https://openalex.org/W4281621269, https://openalex.org/W4283696759, https://openalex.org/W1974780886, https://openalex.org/W2621944631, https://openalex.org/W3013960009, https://openalex.org/W3112353314, https://openalex.org/W2330855044, https://openalex.org/W2334989186, https://openalex.org/W2467342379, https://openalex.org/W2621541809, https://openalex.org/W2607909626, https://openalex.org/W2899603885, https://openalex.org/W1781003552, https://openalex.org/W2806189582, https://openalex.org/W2932702995, https://openalex.org/W3198131703, https://openalex.org/W2315677793, https://openalex.org/W2547288684, https://openalex.org/W2775353861, https://openalex.org/W2788788945, https://openalex.org/W3090417167, https://openalex.org/W43394346, https://openalex.org/W3027344391, https://openalex.org/W2759259612, https://openalex.org/W3024314157, https://openalex.org/W3002047737, https://openalex.org/W3216389696, https://openalex.org/W4283381515, https://openalex.org/W3203678148, https://openalex.org/W2677169684, https://openalex.org/W2034951977, https://openalex.org/W2889500153, https://openalex.org/W4206918543, https://openalex.org/W3178108585 |
| referenced_works_count | 93 |
| abstract_inverted_index.a | 1, 29, 108 |
| abstract_inverted_index.as | 62, 127, 129 |
| abstract_inverted_index.by | 120, 210 |
| abstract_inverted_index.in | 42, 55, 67, 123, 152, 222 |
| abstract_inverted_index.is | 117 |
| abstract_inverted_index.of | 4, 46, 51, 75, 107, 146, 168, 178, 186, 225 |
| abstract_inverted_index.on | 8, 190 |
| abstract_inverted_index.to | 32, 69, 137, 216 |
| abstract_inverted_index.we | 198 |
| abstract_inverted_index.The | 49 |
| abstract_inverted_index.and | 12, 25, 35, 73, 90, 111, 165, 192, 201, 213, 220 |
| abstract_inverted_index.are | 101 |
| abstract_inverted_index.for | 82, 104, 174 |
| abstract_inverted_index.has | 181 |
| abstract_inverted_index.one | 136 |
| abstract_inverted_index.the | 43, 47, 63, 105, 121, 139, 144, 147, 156, 162, 179, 184, 203, 223 |
| abstract_inverted_index.been | 59, 94 |
| abstract_inverted_index.both | 9 |
| abstract_inverted_index.food | 10, 37, 57, 71, 218, 226 |
| abstract_inverted_index.have | 58, 93 |
| abstract_inverted_index.most | 177 |
| abstract_inverted_index.pace | 45 |
| abstract_inverted_index.pose | 28 |
| abstract_inverted_index.thus | 36 |
| abstract_inverted_index.well | 128 |
| abstract_inverted_index.with | 19, 143 |
| abstract_inverted_index.These | 133 |
| abstract_inverted_index.Thus, | 173 |
| abstract_inverted_index.acid, | 89 |
| abstract_inverted_index.allow | 135 |
| abstract_inverted_index.based | 189 |
| abstract_inverted_index.being | 6 |
| abstract_inverted_index.check | 70 |
| abstract_inverted_index.draws | 39 |
| abstract_inverted_index.fast, | 163 |
| abstract_inverted_index.field | 224 |
| abstract_inverted_index.focus | 180 |
| abstract_inverted_index.food. | 77 |
| abstract_inverted_index.human | 33 |
| abstract_inverted_index.large | 2 |
| abstract_inverted_index.money | 5 |
| abstract_inverted_index.order | 68 |
| abstract_inverted_index.other | 26 |
| abstract_inverted_index.solve | 138 |
| abstract_inverted_index.spent | 7 |
| abstract_inverted_index.using | 170 |
| abstract_inverted_index.amines | 54 |
| abstract_inverted_index.amount | 3 |
| abstract_inverted_index.enable | 161 |
| abstract_inverted_index.highly | 109 |
| abstract_inverted_index.modern | 44 |
| abstract_inverted_index.neural | 159 |
| abstract_inverted_index.review | 202 |
| abstract_inverted_index.safety | 38, 219 |
| abstract_inverted_index.sensor | 171, 194, 207 |
| abstract_inverted_index.threat | 31 |
| abstract_inverted_index.toward | 183 |
| abstract_inverted_index.world. | 48 |
| abstract_inverted_index.Despite | 0 |
| abstract_inverted_index.Various | 78 |
| abstract_inverted_index.arrays. | 172, 195 |
| abstract_inverted_index.briefly | 199 |
| abstract_inverted_index.complex | 148 |
| abstract_inverted_index.control | 13 |
| abstract_inverted_index.health, | 34 |
| abstract_inverted_index.herein, | 197 |
| abstract_inverted_index.machine | 130, 157, 211 |
| abstract_inverted_index.majorly | 118 |
| abstract_inverted_index.method. | 114 |
| abstract_inverted_index.methods | 81, 188 |
| abstract_inverted_index.monitor | 217 |
| abstract_inverted_index.nucleic | 88 |
| abstract_inverted_index.popular | 103 |
| abstract_inverted_index.precise | 112 |
| abstract_inverted_index.primary | 64 |
| abstract_inverted_index.problem | 141 |
| abstract_inverted_index.quality | 65, 221 |
| abstract_inverted_index.robust, | 164 |
| abstract_inverted_index.sensing | 99, 116 |
| abstract_inverted_index.serious | 30 |
| abstract_inverted_index.shifted | 182 |
| abstract_inverted_index.systems | 208 |
| abstract_inverted_index.toxins, | 21 |
| abstract_inverted_index.typical | 140 |
| abstract_inverted_index.various | 15, 52 |
| abstract_inverted_index.accurate | 110, 166 |
| abstract_inverted_index.analyses | 11 |
| abstract_inverted_index.analytes | 85, 169 |
| abstract_inverted_index.becoming | 102 |
| abstract_inverted_index.biogenic | 53 |
| abstract_inverted_index.chemical | 193 |
| abstract_inverted_index.however, | 96 |
| abstract_inverted_index.learning | 212 |
| abstract_inverted_index.networks | 160 |
| abstract_inverted_index.patterns | 150 |
| abstract_inverted_index.presence | 50 |
| abstract_inverted_index.recently | 204 |
| abstract_inverted_index.reported | 205 |
| abstract_inverted_index.response | 149 |
| abstract_inverted_index.spoilage | 74 |
| abstract_inverted_index.analytics | 215 |
| abstract_inverted_index.attention | 41 |
| abstract_inverted_index.detecting | 83 |
| abstract_inverted_index.detection | 80, 167 |
| abstract_inverted_index.employed; | 95 |
| abstract_inverted_index.freshness | 72 |
| abstract_inverted_index.generated | 151 |
| abstract_inverted_index.hazardous | 84 |
| abstract_inverted_index.highlight | 200 |
| abstract_inverted_index.illnesses | 17 |
| abstract_inverted_index.including | 86 |
| abstract_inverted_index.measures, | 14 |
| abstract_inverted_index.parameter | 66 |
| abstract_inverted_index.processed | 56 |
| abstract_inverted_index.recently, | 97 |
| abstract_inverted_index.supported | 209 |
| abstract_inverted_index.Therefore, | 196 |
| abstract_inverted_index.analytical | 113, 125, 187 |
| abstract_inverted_index.associated | 18, 142 |
| abstract_inverted_index.colorants, | 24 |
| abstract_inverted_index.commercial | 175 |
| abstract_inverted_index.considered | 61 |
| abstract_inverted_index.electrical | 191 |
| abstract_inverted_index.food-borne | 16 |
| abstract_inverted_index.forensics. | 227 |
| abstract_inverted_index.frequently | 60 |
| abstract_inverted_index.pathogens, | 20 |
| abstract_inverted_index.strategies | 100 |
| abstract_inverted_index.techniques | 92, 126, 134 |
| abstract_inverted_index.Array-based | 115 |
| abstract_inverted_index.approaches. | 132 |
| abstract_inverted_index.array-based | 98, 153, 206 |
| abstract_inverted_index.development | 106, 185 |
| abstract_inverted_index.facilitated | 119 |
| abstract_inverted_index.microscopy, | 87 |
| abstract_inverted_index.pesticides, | 22 |
| abstract_inverted_index.strategies. | 154 |
| abstract_inverted_index.adulterants, | 23 |
| abstract_inverted_index.advancements | 122 |
| abstract_inverted_index.considerable | 40 |
| abstract_inverted_index.contaminants | 27 |
| abstract_inverted_index.conventional | 79 |
| abstract_inverted_index.multivariate | 124, 214 |
| abstract_inverted_index.protein-rich | 76 |
| abstract_inverted_index.Consequently, | 155 |
| abstract_inverted_index.applications, | 176 |
| abstract_inverted_index.interpretation | 145 |
| abstract_inverted_index.learning-based | 131, 158 |
| abstract_inverted_index.immunoassay-based | 91 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5073780661, https://openalex.org/A5002219999 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I119241673, https://openalex.org/I51452335 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.90723381 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |