Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • Persone
  • Pubblicazioni
  • Strutture
  • Competenze

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • Persone
  • Pubblicazioni
  • Strutture
  • Competenze
  1. Pubblicazioni

Prediction models for assessing anthocyanins in grape berries by fluorescence sensors: Dependence on cultivar, site and growing season

Articolo
Data di Pubblicazione:
2018
Abstract:
Fluorescence sensors are useful tools for the non-destructive assessment of grape berry anthocyanins. The Multiplex (Mx) sensor here studied provides two anthocyanin indices: ANTHR= log(1/Chl-fluorescence_R) and ANTHRG= log(Chl-fluorescence_R/Chl-fluorescence_G), based on the chlorophyll (Chl) fluorescence excited with red (R) and green (G) light. These indices were calibrated against wet chemistry. The dependence of anthocyanin prediction models on cultivar, season and site was studied on four cultivars in two Italian regions during three consecutive years. The 2010 global model (all cultivars at both growing sites) gave relative prediction errors on anthocyanin content less than 14.1% (ANTHR) and 19.0% (ANTHRG). The ANTHRG was independent of season, maintaining a relative error of about 20% in both 2011 and 2012. In field applications of the calibrated Mx, it showed its ability to detect inter-plot and inter-season differences on both growing sites.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Anthocyanins; Fluorescence; In-field applications; Non-destructive measurements; Optical sensors
Elenco autori:
Agati, Giovanni
Autori di Ateneo:
AGATI GIOVANNI
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/342327
Pubblicato in:
FOOD CHEMISTRY
Journal
  • Dati Generali

Dati Generali

URL

https://publications.cnr.it/doc/379185
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)