Introduction. Coffee (Coffea spp.) is the second most traded product globally and is cultivated in over eighty countries. Its cultivation is complex because it belongs to an ecosystem where abiotic and biotic factors interact under various agronomic management conditions. To understand the development of the coffee plant and its influence on the sensory quality of the final product, it is necessary to explore the intricate interactions between the coffee plant and the native microorganisms within the crop environment. Objective. To describe the role of the coffee soil microbiota, specially bacteria and fungi, and how they may contribute to the final quality of the beverage. Development. Soil is one of the most diverse and least studied ecosystems, where crucial ecological functions for plant growth and development take place. Identifying soil microbial components and their interactions with other organisms is important from an agronomic perspective. The soil microbiota can enhance plant physiology; thus, this review aims to connect how the sensory attributes of coffee beverage can be positively influenced by soil microbiota. Articles from ScienceDirect, Scopus, Web of Science, and Google Scholar from 2011 to 2023 were reviewed. The data show the diversity of plant growth-promoting rhizobacteria (PGPR), nitrogen-fixing bacteria (NFB), and arbuscular mycorrhizal fungi (AMF) associated with coffee cultivation. Additionally, microbial compounds play an important role in the formation of sensory attributes and are related to the coffee cup quality. Conclusion. The microbial diversity of soil and on the fruit can synthesize or degrade compounds that affect the sensory profile of the coffee beverage, which could have implications for sustainability and quality.

Teak ( Tectona grandis ) is a premier hardwood timber, extensively cultivated throughout the tropics. The study aimed to undertake the first genomic selection of teak clones using single nucleotide polymorphism (SNP) markers and evaluate the prospects for prediction of stem volume (VOL), diameter (DBH), form Quality Score (QS), Specific Gravity (SG), and Heartwood Percentage (HW). Thirty-three elite teak clones from a genetic test in northern Costa Rica were genotyped at 10812 SNP loci and aligned to the teak reference genome sequence. The genomic relationship matrix revealed 7 cryptic groups of more highly related clones and within-group kinship values were consistent with full-sib families. Clone values for each of the 5 traits were calculated from 5-year field data for 26 of the geno-typed clones. Genomic prediction models were fitted to clone values using Bayesian Ridge Regression, BayesA, BayesB, BayesC, and Bayes Lasso. Predictive ability (PA) was greatest for DBH (up to 0.66), VOL (up to 0.63), SG (0.58), with 0.42 and 0.40 as the best PA for QS and HW, respectively. GWAS resulted in the discovery of 7 unique SNP markers for volume, 7 for DBH, 4 for QS, and 8 for SG. The small experimental size resulted in relatively large false discovery rates. Teak breeders are well positioned to benefit from the genomic tools and approaches to genotyping teak breeding and deployment populations on a large scale. Significant advantages are expected from widespread integration of genomic technologies into teak breeding systems to allow shortening of the breeding cycle.

The negative effects of climate change impact both farmers and consumers. This is exemplified in coffee, one of the most widely consumed beverages in the world. Yield loss in high-quality Coffea arabica L., due to the spread of coffee leaf rust (Hemileia vastatrix), results in lower income for subsistence farmers and volatile prices in markets and cafes. Genetic improvement of crops is a proven approach to support sustainable production while mitigating the effects of biotic and abiotic stresses and simultaneously maintaining or improving quality. However, the improvement of many species, including coffee, is hindered by low genetic diversity. This can be overcome by inducing novel genetic variation via treatment of seeds or cells with mutagens. To evaluate this approach in coffee, mutant populations created by incubating seed or embryogenic calli with the chemical mutagens ethyl methanesulphonate or sodium azide were subject to reduced-representation DNA sequencing using the ddRADseq approach. More than 10,000 novel variants were recovered. Functional analysis revealed hundreds of sequence changes predicted to be deleterious for gene function. We discuss the challenges of unambiguously assigning these variants as being caused by the mutagenic treatment and describe purpose-built computational tools to facilitate the recovery of novel genetic variation from mutant plant populations.