Publication
Machine learning unveils the action of different endogenous phenolic compounds present or formed along the rooting development in olive stem cuttings
| dc.contributor.author | Santos-Rufo, Antonio | |
| dc.contributor.author | Rodríguez Solana, Raquel | |
| dc.contributor.author | Fernández-Recamales, Ángeles | |
| dc.contributor.author | Sayago-Gómez, Ana | |
| dc.contributor.author | Weiland-Ardáiz, Carlos | |
| dc.date.accessioned | 2024-07-16T09:15:05Z | |
| dc.date.available | 2024-07-16T09:15:05Z | |
| dc.date.issued | 2024-05 | |
| dc.description.abstract | Changes in the endogenous phenolic content of plant rooting could be influenced by genotype, hormones, or the interaction of both factors, thus modifying the plant rooting capacity/ability along the rooting development. In this study, the combined effects of IBA treatment and cultivar capacity on the rooting development of olive cuttings were modeled by the temporary assessment of simple and total phenolic content (TPC). Rooting ability and phenolic profile were monitored. Results indicated the lowest cumulative rooting in `Lechin-de-Sevilla´, and the highest rooting speed during the first days of the trial in high-rooting cultivars (‘Verdial-de-Hu´evar’ and ‘Arbequina’). A total of 14 phenolic compounds comprising phenolic acids and aldehyde (8), flavonoids (5), and a glycosylated seco-iridoid were quantified in rooted olive cuttings. Most of the phenolics presented a significant higher concentration in the ‘Lechin-de-Sevilla’ cultivar, except for the ferulic acid and luteolin, as well the TPC that varied as did the rooting parameter. At the end of the rooting trial (60 days), luteolin in `Verdial de Hu´evar’ and `Gordal sevillana’ cultivars and ferulic acid in `Lechin de Sevilla’ were the phenolics exclusively found in the highest concentrations. Time did not affect vanillin and oleuropein, although in the case of high-rooting cultivars, values for these compounds were almost constant, while in low- or medium-rooting cultivars, by general, increased or decreased, respectively. The Random Forest algorithm allowed to predict from a complex number of variables, which affected the rooting ability of olive cuttings independently of the cultivar and auxin treatment, finding that luteolin was the best indicator over time. | por |
| dc.description.sponsorship | RYC2022-036888-I; MCIU/AEI/10.13039/501100011033 | |
| dc.identifier.doi | 10.1016/j.scienta.2024.113175 | |
| dc.identifier.issn | 0304-4238 | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/25620 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier | |
| dc.relation.ispartof | Scientia Horticulturae | |
| dc.rights.uri | N/A | |
| dc.subject | Luteolin | |
| dc.subject | Machine learning | |
| dc.subject | Olea europaea L. | |
| dc.subject | Phenolic content | |
| dc.subject | Rhizogenesis | |
| dc.subject | Vegetative propagation | |
| dc.title | Machine learning unveils the action of different endogenous phenolic compounds present or formed along the rooting development in olive stem cuttings | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.startPage | 113175 | |
| oaire.citation.title | Scientia Horticulturae | |
| oaire.citation.volume | 331 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Rodríguez Solana | |
| person.givenName | Raquel | |
| person.identifier | 624004 | |
| person.identifier.ciencia-id | FE10-7889-0562 | |
| person.identifier.orcid | 0000-0003-4204-7387 | |
| person.identifier.rid | I-6317-2015 | |
| person.identifier.scopus-author-id | 55081917100 | |
| relation.isAuthorOfPublication | e54528cf-d25d-424e-b395-5f41019f05ee | |
| relation.isAuthorOfPublication.latestForDiscovery | e54528cf-d25d-424e-b395-5f41019f05ee |