Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms Article Swipe
Bruna Carbas
,
Pedro Sampaio
,
Sílvia Cruz Barros
,
Andreia Freitas
,
A. Sanches‐Silva
,
Carla Brites
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.fochx.2025.102351
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.fochx.2025.102351
Fumonisins occurrence in maize represents a significant global challenge, impacting economic stability and food safety. This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). PLS models demonstrated strong correlation coefficient (R2) values of 0.90 (FB1), 0.98 (FB2), and 0.91 (FB1 + FB2) for calibration, with ratio of prediction to deviation (RPD) values ranging 2.8-3.6. Similarly, ANN models showed good predictive performance, particularly for FB1 + FB2, with R = 0.99, and the root means square error (RMSE) of 131 μg/kg for calibration; and R = 0.95, RMSE = 656 μg/kg for validation. These findings underscore the efficacy of NIR spectroscopy as a rapid, non-destructive tool for fumonisin screening in maize, with chemometric algorithms enhancing model accuracy, offering a valuable method for ensuring food safety.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.fochx.2025.102351
- OA Status
- gold
- Cited By
- 7
- References
- 73
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408286948
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4408286948Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.fochx.2025.102351Digital Object Identifier
- Title
-
Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithmsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-03-10Full publication date if available
- Authors
-
Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, A. Sanches‐Silva, Carla BritesList of authors in order
- Landing page
-
https://doi.org/10.1016/j.fochx.2025.102351Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.fochx.2025.102351Direct OA link when available
- Concepts
-
Spectroscopy, Algorithm, Infrared, Computer science, Artificial intelligence, Machine learning, Physics, Optics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7Per-year citation counts (last 5 years)
- References (count)
-
73Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4408286948 |
|---|---|
| doi | https://doi.org/10.1016/j.fochx.2025.102351 |
| ids.doi | https://doi.org/10.1016/j.fochx.2025.102351 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/40160715 |
| ids.openalex | https://openalex.org/W4408286948 |
| fwci | 31.18025367 |
| type | article |
| title | Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms |
| biblio.issue | |
| biblio.volume | 27 |
| biblio.last_page | 102351 |
| biblio.first_page | 102351 |
| topics[0].id | https://openalex.org/T10520 |
| topics[0].field.id | https://openalex.org/fields/11 |
| topics[0].field.display_name | Agricultural and Biological Sciences |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1110 |
| topics[0].subfield.display_name | Plant Science |
| topics[0].display_name | Mycotoxins in Agriculture and Food |
| topics[1].id | https://openalex.org/T10733 |
| topics[1].field.id | https://openalex.org/fields/11 |
| topics[1].field.display_name | Agricultural and Biological Sciences |
| topics[1].score | 0.9958999752998352 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1110 |
| topics[1].subfield.display_name | Plant Science |
| topics[1].display_name | Wheat and Barley Genetics and Pathology |
| 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 | 0.9957000017166138 |
| 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/F4320334779 |
| funders[0].ror | https://ror.org/00snfqn58 |
| funders[0].display_name | Fundação para a Ciência e a Tecnologia |
| is_xpac | False |
| apc_list.value | 1950 |
| apc_list.currency | USD |
| apc_list.value_usd | 1950 |
| apc_paid.value | 1950 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1950 |
| concepts[0].id | https://openalex.org/C32891209 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5015401840209961 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q483666 |
| concepts[0].display_name | Spectroscopy |
| concepts[1].id | https://openalex.org/C11413529 |
| concepts[1].level | 1 |
| concepts[1].score | 0.4981083869934082 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[1].display_name | Algorithm |
| concepts[2].id | https://openalex.org/C158355884 |
| concepts[2].level | 2 |
| concepts[2].score | 0.45104408264160156 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11388 |
| concepts[2].display_name | Infrared |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.4268476366996765 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.4052903652191162 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C119857082 |
| concepts[5].level | 1 |
| concepts[5].score | 0.3453614115715027 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[5].display_name | Machine learning |
| concepts[6].id | https://openalex.org/C121332964 |
| concepts[6].level | 0 |
| concepts[6].score | 0.20954880118370056 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[6].display_name | Physics |
| concepts[7].id | https://openalex.org/C120665830 |
| concepts[7].level | 1 |
| concepts[7].score | 0.10835179686546326 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q14620 |
| concepts[7].display_name | Optics |
| concepts[8].id | https://openalex.org/C62520636 |
| concepts[8].level | 1 |
| concepts[8].score | 0.0 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[8].display_name | Quantum mechanics |
| keywords[0].id | https://openalex.org/keywords/spectroscopy |
| keywords[0].score | 0.5015401840209961 |
| keywords[0].display_name | Spectroscopy |
| keywords[1].id | https://openalex.org/keywords/algorithm |
| keywords[1].score | 0.4981083869934082 |
| keywords[1].display_name | Algorithm |
| keywords[2].id | https://openalex.org/keywords/infrared |
| keywords[2].score | 0.45104408264160156 |
| keywords[2].display_name | Infrared |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.4268476366996765 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.4052903652191162 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/machine-learning |
| keywords[5].score | 0.3453614115715027 |
| keywords[5].display_name | Machine learning |
| keywords[6].id | https://openalex.org/keywords/physics |
| keywords[6].score | 0.20954880118370056 |
| keywords[6].display_name | Physics |
| keywords[7].id | https://openalex.org/keywords/optics |
| keywords[7].score | 0.10835179686546326 |
| keywords[7].display_name | Optics |
| language | en |
| locations[0].id | doi:10.1016/j.fochx.2025.102351 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210189394 |
| locations[0].source.issn | 2590-1575 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2590-1575 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Food Chemistry X |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | |
| locations[0].pdf_url | |
| 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 | Food Chemistry: X |
| locations[0].landing_page_url | https://doi.org/10.1016/j.fochx.2025.102351 |
| locations[1].id | pmid:40160715 |
| 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 | Food chemistry: X |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/40160715 |
| locations[2].id | pmh:oai:doaj.org/article:23106c940ad24615af6d8e9327e1a0db |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| 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 | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Food Chemistry: X, Vol 27, Iss , Pp 102351- (2025) |
| locations[2].landing_page_url | https://doaj.org/article/23106c940ad24615af6d8e9327e1a0db |
| locations[3].id | pmh:oai:europepmc.org:10762315 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306400806 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | Europe PMC (PubMed Central) |
| locations[3].source.host_organization | https://openalex.org/I1303153112 |
| locations[3].source.host_organization_name | European Bioinformatics Institute |
| locations[3].source.host_organization_lineage | https://openalex.org/I1303153112 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/11951204 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5017895334 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5941-8749 |
| authorships[0].author.display_name | Bruna Carbas |
| authorships[0].countries | PT |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210105339 |
| authorships[0].affiliations[0].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I4210092303 |
| authorships[0].affiliations[1].raw_affiliation_string | Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253, Bragança, Portugal. |
| authorships[0].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[0].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[0].institutions[0].type | facility |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[0].institutions[0].country_code | PT |
| authorships[0].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[0].institutions[1].id | https://openalex.org/I4210092303 |
| authorships[0].institutions[1].ror | https://ror.org/00prsav78 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I4210092303 |
| authorships[0].institutions[1].country_code | PT |
| authorships[0].institutions[1].display_name | Polytechnic Institute of Bragança |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Bruna Carbas |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253, Bragança, Portugal., National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[1].author.id | https://openalex.org/A5041172102 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-2917-4904 |
| authorships[1].author.display_name | Pedro Sampaio |
| authorships[1].countries | PT |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I88596544 |
| authorships[1].affiliations[0].raw_affiliation_string | Computação e Cognição Centrada nas Pessoas, Lusófona University, Campo Grande, 376, 1749-019 Lisboa, Portugal. |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I4210105339 |
| authorships[1].affiliations[1].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[1].affiliations[2].raw_affiliation_string | GREEN-IT Bioresources for Sustainability, ITQB NOVA, Av. da República, 2780-157 Oeiras, Portugal. |
| authorships[1].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[1].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[1].institutions[0].type | facility |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[1].institutions[0].country_code | PT |
| authorships[1].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[1].institutions[1].id | https://openalex.org/I88596544 |
| authorships[1].institutions[1].ror | https://ror.org/05xxfer42 |
| authorships[1].institutions[1].type | education |
| authorships[1].institutions[1].lineage | https://openalex.org/I88596544 |
| authorships[1].institutions[1].country_code | PT |
| authorships[1].institutions[1].display_name | Universidade Lusófona |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Pedro Sampaio |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Computação e Cognição Centrada nas Pessoas, Lusófona University, Campo Grande, 376, 1749-019 Lisboa, Portugal., GREEN-IT Bioresources for Sustainability, ITQB NOVA, Av. da República, 2780-157 Oeiras, Portugal., National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[2].author.id | https://openalex.org/A5102847250 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-8017-5668 |
| authorships[2].author.display_name | Sílvia Cruz Barros |
| authorships[2].countries | PT |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210105339 |
| authorships[2].affiliations[0].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[2].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[2].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[2].institutions[0].country_code | PT |
| authorships[2].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sílvia Cruz Barros |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[3].author.id | https://openalex.org/A5070084344 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-3292-5473 |
| authorships[3].author.display_name | Andreia Freitas |
| authorships[3].countries | PT |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210105339 |
| authorships[3].affiliations[0].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I4210138594 |
| authorships[3].affiliations[1].raw_affiliation_string | Associated Laboratory for Green Chemistry of the Network of Chemistry and Technology, LAQV, REQUIMTE, R.D. Manuel II, 4051-401 Porto, Portugal. |
| authorships[3].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[3].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[3].institutions[0].country_code | PT |
| authorships[3].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[3].institutions[1].id | https://openalex.org/I4210138594 |
| authorships[3].institutions[1].ror | https://ror.org/04j14t006 |
| authorships[3].institutions[1].type | nonprofit |
| authorships[3].institutions[1].lineage | https://openalex.org/I4210138594 |
| authorships[3].institutions[1].country_code | PT |
| authorships[3].institutions[1].display_name | Rede de Química e Tecnologia |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Andreia Freitas |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Associated Laboratory for Green Chemistry of the Network of Chemistry and Technology, LAQV, REQUIMTE, R.D. Manuel II, 4051-401 Porto, Portugal., National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[4].author.id | https://openalex.org/A5071789351 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0226-921X |
| authorships[4].author.display_name | A. Sanches‐Silva |
| authorships[4].countries | PT |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210105339 |
| authorships[4].affiliations[0].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I76903346 |
| authorships[4].affiliations[1].raw_affiliation_string | University of Coimbra, Faculty of Pharmacy, Coimbra, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal. |
| authorships[4].affiliations[2].institution_ids | https://openalex.org/I182534213 |
| authorships[4].affiliations[2].raw_affiliation_string | Centre for Animal Science Studies (CECA), University of Porto, Porto, Portugal. |
| authorships[4].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[4].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[4].institutions[0].country_code | PT |
| authorships[4].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[4].institutions[1].id | https://openalex.org/I182534213 |
| authorships[4].institutions[1].ror | https://ror.org/043pwc612 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I182534213 |
| authorships[4].institutions[1].country_code | PT |
| authorships[4].institutions[1].display_name | Universidade do Porto |
| authorships[4].institutions[2].id | https://openalex.org/I76903346 |
| authorships[4].institutions[2].ror | https://ror.org/04z8k9a98 |
| authorships[4].institutions[2].type | education |
| authorships[4].institutions[2].lineage | https://openalex.org/I76903346 |
| authorships[4].institutions[2].country_code | PT |
| authorships[4].institutions[2].display_name | University of Coimbra |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Ana Sanches Silva |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Centre for Animal Science Studies (CECA), University of Porto, Porto, Portugal., National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal., University of Coimbra, Faculty of Pharmacy, Coimbra, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal. |
| authorships[5].author.id | https://openalex.org/A5061181990 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-1949-172X |
| authorships[5].author.display_name | Carla Brites |
| authorships[5].countries | PT |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210105339 |
| authorships[5].affiliations[0].raw_affiliation_string | National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| authorships[5].affiliations[1].raw_affiliation_string | GREEN-IT Bioresources for Sustainability, ITQB NOVA, Av. da República, 2780-157 Oeiras, Portugal. |
| authorships[5].institutions[0].id | https://openalex.org/I4210105339 |
| authorships[5].institutions[0].ror | https://ror.org/01fqrjt38 |
| authorships[5].institutions[0].type | facility |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210105339 |
| authorships[5].institutions[0].country_code | PT |
| authorships[5].institutions[0].display_name | Instituto Nacional de Investigação Agrária e Veterinária |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Carla Brites |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | GREEN-IT Bioresources for Sustainability, ITQB NOVA, Av. da República, 2780-157 Oeiras, Portugal., National Institute for Agricultural and Veterinary Research (INIAV), I.P., Av. Da República, Quinta do Marquês, 2780-157 Oeiras, Portugal. |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.fochx.2025.102351 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10520 |
| primary_topic.field.id | https://openalex.org/fields/11 |
| primary_topic.field.display_name | Agricultural and Biological Sciences |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1110 |
| primary_topic.subfield.display_name | Plant Science |
| primary_topic.display_name | Mycotoxins in Agriculture and Food |
| related_works | https://openalex.org/W2961085424, https://openalex.org/W4306674287, https://openalex.org/W4387369504, https://openalex.org/W4394896187, https://openalex.org/W3170094116, https://openalex.org/W4386462264, https://openalex.org/W3107602296, https://openalex.org/W4364306694, https://openalex.org/W4312192474, https://openalex.org/W4283697347 |
| cited_by_count | 7 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 7 |
| locations_count | 4 |
| best_oa_location.id | doi:10.1016/j.fochx.2025.102351 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210189394 |
| best_oa_location.source.issn | 2590-1575 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2590-1575 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Food Chemistry X |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | |
| best_oa_location.pdf_url | |
| 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 | Food Chemistry: X |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.fochx.2025.102351 |
| primary_location.id | doi:10.1016/j.fochx.2025.102351 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210189394 |
| primary_location.source.issn | 2590-1575 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2590-1575 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Food Chemistry X |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | |
| primary_location.pdf_url | |
| 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 | Food Chemistry: X |
| primary_location.landing_page_url | https://doi.org/10.1016/j.fochx.2025.102351 |
| publication_date | 2025-03-10 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W2564339002, https://openalex.org/W4402240032, https://openalex.org/W4391879363, https://openalex.org/W3156082978, https://openalex.org/W3097492344, https://openalex.org/W4388126989, https://openalex.org/W6798415653, https://openalex.org/W4386850136, https://openalex.org/W2883732796, https://openalex.org/W2972225545, https://openalex.org/W2967549856, https://openalex.org/W3002673705, https://openalex.org/W4225424837, https://openalex.org/W2057474369, https://openalex.org/W4309001744, https://openalex.org/W6862157216, https://openalex.org/W6859560662, https://openalex.org/W4399582892, https://openalex.org/W6845878501, https://openalex.org/W6798178251, https://openalex.org/W6804990510, https://openalex.org/W6846172341, https://openalex.org/W2520130504, https://openalex.org/W2995762126, https://openalex.org/W4385605786, https://openalex.org/W6839330540, https://openalex.org/W6843053707, https://openalex.org/W2944630496, https://openalex.org/W6853188239, https://openalex.org/W6807220450, https://openalex.org/W1979900616, https://openalex.org/W6875382100, https://openalex.org/W2037480358, https://openalex.org/W2486966212, https://openalex.org/W4391683022, https://openalex.org/W6869019335, https://openalex.org/W6855670134, https://openalex.org/W6808583821, https://openalex.org/W6858810010, https://openalex.org/W2967304050, https://openalex.org/W2406518378, https://openalex.org/W2939216114, https://openalex.org/W6778996332, https://openalex.org/W3206781198, https://openalex.org/W6788248785, https://openalex.org/W2576771258, https://openalex.org/W4287832300, https://openalex.org/W6866041792, https://openalex.org/W2073503722, https://openalex.org/W6852267588, https://openalex.org/W3048610172, https://openalex.org/W6870832435, https://openalex.org/W4309632366, https://openalex.org/W3119890564, https://openalex.org/W4200443292, https://openalex.org/W4400843042, https://openalex.org/W4380324508, https://openalex.org/W4399358865, https://openalex.org/W4391850712, https://openalex.org/W4405941448, https://openalex.org/W4387223510, https://openalex.org/W3178459924, https://openalex.org/W4389474098, https://openalex.org/W3181075469, https://openalex.org/W4300981877, https://openalex.org/W4296052061, https://openalex.org/W4282920946, https://openalex.org/W3031866229, https://openalex.org/W4396593985, https://openalex.org/W4385707675, https://openalex.org/W4206986297, https://openalex.org/W4388336682, https://openalex.org/W4212871955 |
| referenced_works_count | 73 |
| abstract_inverted_index.+ | 72, 96 |
| abstract_inverted_index.= | 100, 116, 119 |
| abstract_inverted_index.a | 5, 133, 149 |
| abstract_inverted_index.B1 | 35 |
| abstract_inverted_index.B2 | 38 |
| abstract_inverted_index.as | 132 |
| abstract_inverted_index.in | 2, 31, 140 |
| abstract_inverted_index.of | 20, 64, 78, 109, 129 |
| abstract_inverted_index.to | 28, 80 |
| abstract_inverted_index.131 | 110 |
| abstract_inverted_index.656 | 120 |
| abstract_inverted_index.ANN | 87 |
| abstract_inverted_index.FB1 | 95 |
| abstract_inverted_index.For | 33 |
| abstract_inverted_index.NIR | 44, 130 |
| abstract_inverted_index.PLS | 56 |
| abstract_inverted_index.and | 12, 37, 51, 69, 102, 114 |
| abstract_inverted_index.for | 74, 94, 112, 122, 137, 152 |
| abstract_inverted_index.the | 18, 103, 127 |
| abstract_inverted_index.(FB1 | 71 |
| abstract_inverted_index.0.90 | 65 |
| abstract_inverted_index.0.91 | 70 |
| abstract_inverted_index.0.98 | 67 |
| abstract_inverted_index.FB2) | 73 |
| abstract_inverted_index.FB2, | 97 |
| abstract_inverted_index.RMSE | 118 |
| abstract_inverted_index.This | 15 |
| abstract_inverted_index.food | 13, 154 |
| abstract_inverted_index.good | 90 |
| abstract_inverted_index.root | 104 |
| abstract_inverted_index.tool | 136 |
| abstract_inverted_index.were | 41 |
| abstract_inverted_index.with | 25, 76, 98, 142 |
| abstract_inverted_index.(FB1) | 36 |
| abstract_inverted_index.(FB2) | 39 |
| abstract_inverted_index.(NIR) | 22 |
| abstract_inverted_index.(PLS) | 50 |
| abstract_inverted_index.(RPD) | 82 |
| abstract_inverted_index.0.95, | 117 |
| abstract_inverted_index.0.99, | 101 |
| abstract_inverted_index.These | 124 |
| abstract_inverted_index.error | 107 |
| abstract_inverted_index.least | 48 |
| abstract_inverted_index.maize | 3 |
| abstract_inverted_index.means | 105 |
| abstract_inverted_index.model | 146 |
| abstract_inverted_index.ratio | 77 |
| abstract_inverted_index.study | 16 |
| abstract_inverted_index.using | 46 |
| abstract_inverted_index.(ANN). | 55 |
| abstract_inverted_index.(FB1), | 66 |
| abstract_inverted_index.(FB2), | 68 |
| abstract_inverted_index.(RMSE) | 108 |
| abstract_inverted_index.detect | 29 |
| abstract_inverted_index.global | 7 |
| abstract_inverted_index.levels | 40 |
| abstract_inverted_index.maize, | 141 |
| abstract_inverted_index.maize. | 32 |
| abstract_inverted_index.method | 151 |
| abstract_inverted_index.models | 45, 57, 88 |
| abstract_inverted_index.neural | 53 |
| abstract_inverted_index.rapid, | 134 |
| abstract_inverted_index.showed | 89 |
| abstract_inverted_index.square | 106 |
| abstract_inverted_index.strong | 59 |
| abstract_inverted_index.values | 63, 83 |
| abstract_inverted_index.μg/kg | 111, 121 |
| abstract_inverted_index.partial | 47 |
| abstract_inverted_index.ranging | 84 |
| abstract_inverted_index.safety. | 14, 155 |
| abstract_inverted_index.squares | 49 |
| abstract_inverted_index.2.8-3.6. | 85 |
| abstract_inverted_index.<i>R</i> | 99, 115 |
| abstract_inverted_index.combined | 24 |
| abstract_inverted_index.economic | 10 |
| abstract_inverted_index.efficacy | 128 |
| abstract_inverted_index.ensuring | 153 |
| abstract_inverted_index.findings | 125 |
| abstract_inverted_index.networks | 54 |
| abstract_inverted_index.offering | 148 |
| abstract_inverted_index.valuable | 150 |
| abstract_inverted_index.accuracy, | 147 |
| abstract_inverted_index.developed | 42 |
| abstract_inverted_index.deviation | 81 |
| abstract_inverted_index.enhancing | 145 |
| abstract_inverted_index.evaluates | 17 |
| abstract_inverted_index.fumonisin | 34, 138 |
| abstract_inverted_index.impacting | 9 |
| abstract_inverted_index.potential | 19 |
| abstract_inverted_index.screening | 139 |
| abstract_inverted_index.stability | 11 |
| abstract_inverted_index.Fumonisins | 0 |
| abstract_inverted_index.Similarly, | 86 |
| abstract_inverted_index.algorithms | 27, 144 |
| abstract_inverted_index.artificial | 52 |
| abstract_inverted_index.challenge, | 8 |
| abstract_inverted_index.fumonisins | 30 |
| abstract_inverted_index.occurrence | 1 |
| abstract_inverted_index.prediction | 79 |
| abstract_inverted_index.predictive | 43, 91 |
| abstract_inverted_index.represents | 4 |
| abstract_inverted_index.underscore | 126 |
| abstract_inverted_index.chemometric | 26, 143 |
| abstract_inverted_index.coefficient | 61 |
| abstract_inverted_index.correlation | 60 |
| abstract_inverted_index.significant | 6 |
| abstract_inverted_index.validation. | 123 |
| abstract_inverted_index.calibration, | 75 |
| abstract_inverted_index.calibration; | 113 |
| abstract_inverted_index.demonstrated | 58 |
| abstract_inverted_index.particularly | 93 |
| abstract_inverted_index.performance, | 92 |
| abstract_inverted_index.spectroscopy | 23, 131 |
| abstract_inverted_index.near-infrared | 21 |
| abstract_inverted_index.(R<sup>2</sup>) | 62 |
| abstract_inverted_index.non-destructive | 135 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.7200000286102295 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.99334944 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |