Ecometabolic mixture design-fingerprints from exploratory multi-block data analysis in Coffea arabica beans from climate changes: Elevated carbon dioxide and reduced soil water availability

1H NMR Mixture Design-Fingerprints and ASCA Analysis in Ilex paraguariensis: Model Stability in Search of a Global Metabolome

The effects of experimental repetitions and solvent extractors on the 1H NMR fingerprinting of yerba mate extracts, obtained from two genders and two light environments, were analyzed in-depth by ANOVA-simultaneous component analysis (ASCA). Different solvents were used according to a mixture design based on ethanol, dichloromethane, and hexane and their combinations. The number of experimental repetitions significantly affected the ASCA results. Increasing repetitions led to decreases in the percentage effect variance values and an increase in the percentage residual variance. However, secondary sexual dimorphism, light availability, and their interaction effects became more significant with decreasing p-values at or above the 95% confidence level. The choice of a solvent extractor significantly affects the chemical profile and can lead to distinct conclusions regarding the significance of effect values. Pure solvents yielded different conclusions about the significance of factorial design effects, with each solvent extracting unique metabolites and maximizing information for specific effects. However, the use of binary solvent mixtures, such as ethanol-dichloromethane, proved more efficient in extracting sets of compounds that simultaneously differentiate between different experimental conditions. The mixture design-fingerprint strategy provided satisfactory results expanding the range of extracted metabolites with high percentage of residual variances and low explained percentage effect variances in the ASCA models. Ternary and even higher-ordered mixtures could be good alternative extracting media for work-intensive procedures. Our study underscores the significance of experimental design and solvent selection in metabolomic analysis, improving the accuracy, robustness, and interpretability of metabolomic models, leading to a better understanding of the chemical composition and biological implications of plant extracts.

Comprehensive HPLC fingerprint analysis based on a two-step extraction method for quality evaluation of Perilla frutescens (L.) Britt

Abundant chemical components are key to ensure the evaluation accuracy of fingerprint analysis of traditional Chinese medicines (TCMs). A two-step extraction method combining supercritical fluid extraction (SFE) and water ultrasonic extraction was established for the quality evaluation of Perilla frutescens (L.) Britt. Weakly polar components were extracted under optimal SFE conditions (15% co-solvent (EtOH : n-hexane = 1 : 14, (v/v)), 40 °C, 250 bar, and 30 min), and polar components were subsequently extracted by an ultrasonic step (100% water as solvent, 40 °C, and 45 min). Then, HPLC methods were established, which were validated to be accurate, stable, and reliable. In this work, 25 batches of samples were evaluated and the data were analysed by similarity analysis (SA) and hierarchical cluster analysis (HCA). The similarity values of SFE extracts and aqueous extracts were respectively 0.616-0.999, and 0.252-0.997, proving the importance of the extraction method for the accuracy of the subsequent fingerprint analysis results. For the HCA, 25 samples were divided into two categories (leaves and stems), among which four batches of leaves with less similarity were considered as stems, indicating that quality differences of P. frutescens depending on medicinal parts and origin exist. The two-step extraction method developed in this work has been proved to be suitable for the quality evaluation of TCMs with complex compositions.

A Systematic Review on the Impacts of Climate Change on Coffee Agrosystems

Coffee production is fragile, and the Intergovernmental Panel on Climate Change (IPCC) reports indicate that climate change (CC) will reduce worldwide yields on average and decrease coffee-suitable land by 2050. This article adopted the systematic review approach to provide an update of the literature available on the impacts of climate change on coffee production and other ecosystem services following the framework proposed by the Millenium Ecosystem Assessment. The review identified 148 records from literature considering the effects of climate change and climate variability on coffee production, covering countries mostly from three continents (America, Africa, and Asia). The current literature evaluates and analyses various climate change impacts on single services using qualitative and quantitative methodologies. Impacts have been classified and described according to different impact groups. However, available research products lacked important analytical functions on the precise relationships between the potential risks of CC on coffee farming systems and associated ecosystem services. Consequently, the manuscript recommends further work on ecosystem services and their interrelation to assess the impacts of climate change on coffee following the ecosystem services framework.