Time dependent berry maturation for planting density levels in Coffea arabica L. beans: Mixture design-fingerprinting using near-infrared transmittance spectroscopy

Climate risks and vulnerabilities of the Arabica coffee in Brazil under current and future climates considering new CMIP6 models

The susceptibility to climate change concerns the coffee market worldwide due to possible severe productivity losses. Brazil is the world's largest Arabica coffee producer and has crops in regions considered persistent climate change hotspots. Our study analyzed risks, vulnerabilities, and susceptibilities to pests and diseases in these regions under current and future climates and outlined adaptive measures to reduce future vulnerabilities. Ten risk indicators based on Arabica coffee requirements were proposed: water supply (Iw), base (TIB) and maximum temperature stresses (TImax), which delimit the temperature range where Arabica coffee grows and productivity is penalized outside both ranges, frost stress (TIfrost), diseases such as rust (DIrust), brown eye spot (DIbrown), and Phoma leaf spot (DIphoma), pests such as coffee berry borer (PIberry), coffee leaf miner (PIminer), and yield loss due to water stress (Iyg). Daily near-surface air temperature (minimum, mean, and maximum), relative humidity, precipitation, and global solar radiation were used from 16 General Circulation Models (GCMs) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), which are derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in three Shared Socioeconomic Pathways scenarios (SSP245, SSP370 and SSP585). All risk indicators were calculated for the current climate (1995-2014) and projected for the near (2041-2060), intermediate (2061-2080), and far future (2081-2100) in three SSPs and then classified into five risk classes (very low, low, moderate, high and very high). Our results indicated that due to increases in TImax and Iyg indicators, with high to very high risk in area and magnitude, Arabica coffee plantations will be negatively affected and economically unfeasible for about 35 % to 75 % of the studied area throughout the 21st century. Furthermore, the rust and the leaf miner will remain a concern in future climates due to increased temperatures and reduced relative humidity. The future of Arabica coffee crops in Brazil will depend on adopting effective adaptive measures and prudent agricultural strategies to address anticipated risks, including shifting crops to higher altitude areas, introducing more climate-resilient coffee cultivars/varieties, using agroforestry or intercropping systems, planting in closer spacing or higher density planting, and employing dripper or partial root-zone irrigation techniques.

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.

Chemical analysis and NIR spectroscopy in the determination of the origin, variety and roast time of Mexican coffee

Coffee is a product whose quality and price are associated with its geographical, genetic and processing origin; therefore, the development of analytical techniques to authenticate the above mentioned is important to avoid adulteration. The objective of this study was to compare conventional analytical methods with NIR technology for the authentication of roasted and ground coffee samples from different producing regions in Mexico (origins) and different varieties. A second objective was to determine, under the same processing conditions, if roasting times can be differentiated by using this technology. A total of 120 samples of roasted and ground commercial coffee were obtained from the states of Chiapas, Oaxaca, Tabasco and Veracruz in Mexico, 30 locally available samples per state. Samples from Veracruz included three different varieties, grown on the same farm and processed under the same conditions. One of these varieties was selected to evaluate the chemical composition of samples roasted at 185 °C using four different roasting times (15, 17, 19 and 21 min). Samples from different producing regions showed significant differences (P < 0.05) in fat content (from 7.45 ± 0.42% in Tabasco to 18.40 ± 2.95% in Chiapas), which was associated with the altitude of coffee plantations (Pearson's r = 0.96). The results indicate that NIR technology generates sufficient useful information to authenticate roasted and ground coffee from different geographical origins in Mexico and different varieties from the same coffee plantation, with similar results to those obtained by conventional analytical methods.