Identification of maize kernel resistance proteins against Aspergillus flavus by a statistical approach: A predictive model of resistance capacity.
Rattachement africain : us, ec. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Although kernel infection by Aspergillus flavus and pre-harvest aflatoxin contamination of Zea mays grain is a significant crop production problem, not only in Venezuela but also around the world, little progress has been made in identifying proteins and metabolic pathways associated with this pathogen resistance. Usually, a protein with a two-fold expression between control and condition is considered a biomarker of some phenomena, but we think it is essential to evaluate its contribution to resistance. That is why we decided to determine the behavior's resistance capacity in terms of expression levels of an identified protein of maize kernels infected with A. flavus by using a multivariate approach. In this work, we identify 47 of 66 differentially expressed spots with a remarkable contribution to resistance against the fungus Aspergillus flavus. We finally test this approach to know if it can be used as a predictive resistance model and probe it by including theoretical and experimental protein expression profiles of other inoculated maize lines.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Identification of maize kernel resistance proteins against Aspergillus flavus by a statistical approach: A predictive model of resistance capacity.
- Date Crossref
- 15/05/2021
- Éditeur
- Clinical Biotec S.L.
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
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