Literature DB >> 31892095

Factorial design fingerprint discrimination of Coffea arabica beans under elevated carbon dioxide and limited water conditions.

Gustavo G Marcheafave1, Elis Daiane Pauli2, Cláudia D Tormena3, Maria Carolina V Ortiz3, Andressa G de Almeida3, Miroslava Rakocevic4, Roy E Bruns5, Ieda S Scarminio6.   

Abstract

Coffee is one of the most important commodities, showing sensitivity to environmental variations. The main effects and their interaction for two levels of atmospheric CO2 concentrations and two water regimes of a factorial design were investigated for the metabolic profiles of Coffea arabica raw beans using UV fingerprint analysis from a mixture design. UV fingerprint results obtained from pure ethanol and binary ethanol-dichloromethane mixtures showed the largest metabolic discriminations between CO2 levels and their extracts were investigated in detail. The biosynthesis of major metabolites, chlorogenic acids, cafestol, kahweol and caffeine were altered owing to environmental conditions. Higher amounts of chlorogenic acids and kahweol were observed in beans from unirrigated plants grown with enriched CO2 and irrigated ones at the current CO2 level. Water availability and CO2 concentration interaction affects the metabolite amounts. Besides a significant CO2 atmospheric effect water availability was a limiting factor for metabolite content only at current CO2 level, suggesting the successful metabolic coping of CO2 enriched Arabic coffee beans suffering future droughts.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Arabica coffee; Drought; Elevated CO(2); Metabolic modification; UV fingerprint

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Year:  2019        PMID: 31892095     DOI: 10.1016/j.talanta.2019.120591

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  1 in total

1.  Optimizing Shade Cultivation Method and Irrigation Amount to Improve Photosynthetic Characteristics, Bean Yield, and Quality of Coffee in a Subtropical Monsoon Climate.

Authors:  Kun Hao; Xiaogang Liu; Xiukang Wang; Liangjun Fei; Lihua Liu; Feilong Jie; Yilin Li; Qiliang Yang; Yunhui Shan
Journal:  Front Plant Sci       Date:  2022-04-29       Impact factor: 5.753

  1 in total

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