Low field, time domain NMR in the agriculture and agrifood sector: An overview of applications in plants, foods and biofuels (2021)
- Authors:
- Autor USP: MONARETTO, TATIANA - IQSC
- Unidade: IQSC
- DOI: 10.1016/j.jmr.2020.106899
- Subjects: AGRICULTURA; ALIMENTOS; BIOCOMBUSTÍVEIS; FRUTAS; RESSONÂNCIA MAGNÉTICA NUCLEAR
- Keywords: TD-NMR; Relaxation; Starch
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Magnetic Resonance
- ISSN: 1090-7807
- Volume/Número/Paginação/Ano: v. 323, p.106899, fev. 2021
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: other-oa
-
ABNT
COLNAGO, Luiz Alberto et al. Low field, time domain NMR in the agriculture and agrifood sector: An overview of applications in plants, foods and biofuels. Journal of Magnetic Resonance, v. fe 2021, p. 106899, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.jmr.2020.106899. Acesso em: 28 dez. 2025. -
APA
Colnago, L. A., Wiesman, Z., Pages, G., Musse, M., Monaretto, T., Windt, C. W., & Rondeau-Mouro, C. (2021). Low field, time domain NMR in the agriculture and agrifood sector: An overview of applications in plants, foods and biofuels. Journal of Magnetic Resonance, fe 2021, 106899. doi:10.1016/j.jmr.2020.106899 -
NLM
Colnago LA, Wiesman Z, Pages G, Musse M, Monaretto T, Windt CW, Rondeau-Mouro C. Low field, time domain NMR in the agriculture and agrifood sector: An overview of applications in plants, foods and biofuels [Internet]. Journal of Magnetic Resonance. 2021 ; fe 2021 106899.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.jmr.2020.106899 -
Vancouver
Colnago LA, Wiesman Z, Pages G, Musse M, Monaretto T, Windt CW, Rondeau-Mouro C. Low field, time domain NMR in the agriculture and agrifood sector: An overview of applications in plants, foods and biofuels [Internet]. Journal of Magnetic Resonance. 2021 ; fe 2021 106899.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.jmr.2020.106899 - Selection of industrial tomatoes using TD-NMR data and computational classification methods
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Informações sobre o DOI: 10.1016/j.jmr.2020.106899 (Fonte: oaDOI API)
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