Coffee Cell Suspensions as a Platform for Transient Gene Expression Analysis.

Coffea arabica L. is a crucial crop globally, but its genetic homogeneity leads to its susceptibility to diseases and pests like the coffee berry borer (CBB). Chemical and cultural control methods are difficult due to the majority of the CBB life cycle taking place inside coffee beans. One potential solution is the use of the gene cyt1Aa from Bacillus thuringiensis as a biological insecticide. To validate candidate genes against CBB, a simple, rapid, and efficient transient expression system is necessary. This study uses cell suspensions as a platform for expressing the cyt1Aa gene in the coffee genome (C. arabica L. var. Catuaí) to control CBB. The Agrobacterium tumefaciens strain GV3101::pMP90 containing the bar and cyt1Aa genes are used to genetically transform embryogenic cell suspensions. PCR amplification of the cyt1Aa gene is observed 2, 5, and 7 weeks after infection. This chapter describes a protocol that can be used for the development of resistant varieties against biotic and abiotic stresses and CRISPR/Cas9-mediated genome editing.

Genetic diversity and structure of the coffee leaf rust fungus Hemileia vastatrix across different coffee management systems in Ethiopia / Diversidad genética y estructura del hongo de la roya del café Hemileia vastatrix en diferentes sistemas de manejo del café en Etiopía

Although coffee leaf rust (CLR), caused by Hemileia vastatrix, poses an increasing threat to coffee production in Ethiopia, little is known regarding its genetic diversity and structure and how these are affected by coffee management. Here, we used genetic fingerprinting based on sequence-related amplified polymorphism (SRAP) markers to genotype H. vastatrix samples from different coffee shrubs, across 40 sites, covering four coffee production systems (forest coffee, semi plantation coffee, home garden coffee, and plantation coffee) and different altitudes in Ethiopia. In total, 96 H. vastatrix samples were successfully genotyped with three primer combinations, producing a total of 79 scorable bands. We found 35.44% of amplified bands to be polymorphic, and the polymorphic information content (PIC) was 0.45, suggesting high genetic diversity among our CLR isolates. We also found significant isolation-by-distance across the samples investigated and detected significant differences in fungal genetic composition among plantation coffee and home garden coffee and a marginally significant difference among plantation coffee and forest coffee. Furthermore, we found a significant effect of altitude on CLR genetic composition in the forest coffee and plantation systems. Our results suggest that both spore dispersal and different selection pressures in the different coffee management systems are likely responsible for the observed high genetic diversity and genetic structure of CLR isolates in Ethiopia. When selecting Ethiopian coffee genotypes for crop improvement, it is important that these genotypes carry some resistance against CLR. Because our study shows large variation in genetic composition across relatively short geographical distances, a broad selection of rust isolates must be used for coffee resistance screening.(AU)

Overexpression of Water-Responsive Genes Promoted by Elevated CO2 Reduces ROS and Enhances Drought Tolerance in Coffea Species.

Drought is a major constraint to plant growth and productivity worldwide and will aggravate as water availability becomes scarcer. Although elevated air [CO2] might mitigate some of these effects in plants, the mechanisms underlying the involved responses are poorly understood in woody economically important crops such as Coffea. This study analyzed transcriptome changes in Coffea canephora cv. CL153 and C. arabica cv. Icatu exposed to moderate (MWD) or severe water deficits (SWD) and grown under ambient (aCO2) or elevated (eCO2) air [CO2]. We found that changes in expression levels and regulatory pathways were barely affected by MWD, while the SWD condition led to a down-regulation of most differentially expressed genes (DEGs). eCO2 attenuated the impacts of drought in the transcripts of both genotypes but mostly in Icatu, in agreement with physiological and metabolic studies. A predominance of protective and reactive oxygen species (ROS)-scavenging-related genes, directly or indirectly associated with ABA signaling pathways, was found in Coffea responses, including genes involved in water deprivation and desiccation, such as protein phosphatases in Icatu, and aspartic proteases and dehydrins in CL153, whose expression was validated by qRT-PCR. The existence of a complex post-transcriptional regulatory mechanism appears to occur in Coffea explaining some apparent discrepancies between transcriptomic, proteomic, and physiological data in these genotypes.

A comparative analysis of genomic and phenomic predictions of growth-related traits in 3-way coffee hybrids.

Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.

Constitutive Defense Strategy of Coffee Under Field Conditions: A Comparative Assessment of Resistant and Susceptible Cultivars to Rust.

Coffea arabica is the most economically important coffee species worldwide. However, its production is severely limited by diseases such as rust. The mechanisms underlying constitutive defense responses in coffee are still poorly understood, compared with induced defense mechanisms. We aimed to characterize constitutive defense responses of thirteen cultivars of C. arabica. Cultivars were classified under field conditions according to the level of resistance to rust: resistant (R), moderately resistant (MR), and susceptible (S). Based on this classification, the stability of eight reference genes (RGs) was evaluated. The most stable RGs were EF1α, APT1, and 24S. We also evaluated the expression of CaWRKY1, CaPAL1, CaCAD1, and CaPOX1, and activities of PAL, CAD, and POX, which are involved in lignin biosynthesis, and leaf content of total phenolic compounds and lignin. Gene expression and enzymatic activity were not correlated with defense metabolites in the R cultivar group but showed a negative correlation with phenolic compounds in MR cultivars. Cultivar S showed positive correlations of gene expression and enzyme activity with phenolic compounds. These results may assist coffee breeding programs regarding selection of genotypes and in optimization of rust resistance.

In silico guided structural and functional analysis of genes with potential involvement in resistance to coffee leaf rust: A functional marker based approach.

Physiology-based differentiation of SH genes and Hemileia vastatrix races is the principal method employed for the characterization of coffee leaf rust resistance. Based on the gene-for-gene theory, nine major rust resistance genes (SH1-9) have been proposed. However, these genes have not been characterized at the molecular level. Consequently, the lack of molecular data regarding rust resistance genes or candidates is a major bottleneck in coffee breeding. To address this issue, we screened a BAC library with resistance gene analogs (RGAs), identified RGAs, characterized and explored for any SH related candidate genes. Herein, we report the identification and characterization of a gene (gene 11), which shares conserved sequences with other SH genes and displays a characteristic polymorphic allele conferring different resistance phenotypes. Furthermore, comparative analysis of the two RGAs belonging to CC-NBS-LRR revealed more intense diversifying selection in tomato and grape genomes than in coffee. For the first time, the present study has unveiled novel insights into the molecular nature of the SH genes, thereby opening new avenues for coffee rust resistance molecular breeding. The characterized candidate RGA is of particular importance for further biological function analysis in coffee.

Limited genotypic and geographic variability of 16-O-methylated diterpene content in Coffea arabica green beans.

The acknowledged marker of Robusta coffee, 16-O-methylcafestol (16-OMC), can be quantified by NMR as a mixture with 16-O-methylkahweol (16-OMK), which accounts for approximately 10% of the mixture. In the present study, we detected and quantified 16-O-methylated diterpenes (16-OMD) in 248 samples of green Coffea arabica beans by NMR. We did not observe any differences between genotypes introgressed by chromosomal fragments of Robusta and non-introgressed genotypes. Environmental effects suggesting a possible protective role of 16-OMD for adaptation, as well as genotypic effects that support a high heritability of this trait were observed. Altogether, our data confirmed the presence of 16-OMD in green Arabica at a level approximately 1.5% that of a typical Robusta, endorsing the validity of 16-OMD as a marker for the presence of Robusta.

Evolutionarily conserved plant genes responsive to root-knot nematodes identified by comparative genomics.

Root-knot nematodes (RKNs, genus Meloidogyne) affect a large number of crops causing severe yield losses worldwide, more specifically in tropical and sub-tropical regions. Several plant species display high resistance levels to Meloidogyne, but a general view of the plant immune molecular responses underlying resistance to RKNs is still lacking. Combining comparative genomics with differential gene expression analysis may allow the identification of widely conserved plant genes involved in RKN resistance. To identify genes that are evolutionary conserved across plant species, we used OrthoFinder to compared the predicted proteome of 22 plant species, including important crops, spanning 214 Myr of plant evolution. Overall, we identified 35,238 protein orthogroups, of which 6,132 were evolutionarily conserved and universal to all the 22 plant species (PLAnts Common Orthogroups-PLACO). To identify host genes responsive to RKN infection, we analyzed the RNA-seq transcriptome data from RKN-resistant genotypes of a peanut wild relative (Arachis stenosperma), coffee (Coffea arabica L.), soybean (Glycine max L.), and African rice (Oryza glaberrima Steud.) challenged by Meloidogyne spp. using EdgeR and DESeq tools, and we found 2,597 (O. glaberrima), 743 (C. arabica), 665 (A. stenosperma), and 653 (G. max) differentially expressed genes (DEGs) during the resistance response to the nematode. DEGs' classification into the previously characterized 35,238 protein orthogroups allowed identifying 17 orthogroups containing at least one DEG of each resistant Arachis, coffee, soybean, and rice genotype analyzed. Orthogroups contain 364 DEGs related to signaling, secondary metabolite production, cell wall-related functions, peptide transport, transcription regulation, and plant defense, thus revealing evolutionarily conserved RKN-responsive genes. Interestingly, the 17 DEGs-containing orthogroups (belonging to the PLACO) were also universal to the 22 plant species studied, suggesting that these core genes may be involved in ancestrally conserved immune responses triggered by RKN infection. The comparative genomic approach that we used here represents a promising predictive tool for the identification of other core plant defense-related genes of broad interest that are involved in different plant-pathogen interactions.

Development of an Efficient Protocol to Obtain Transgenic Coffee, Coffea arabica L., Expressing the Cry10Aa Toxin of Bacillus thuringiensis.

This report presents an efficient protocol of the stable genetic transformation of coffee plants expressing the Cry10Aa protein of Bacillus thuringiensis. Embryogenic cell lines with a high potential of propagation, somatic embryo maturation, and germination were used. Gene expression analysis of cytokinin signaling, homedomains, auxin responsive factor, and the master regulators of somatic embryogenesis genes involved in somatic embryo maturation were evaluated. Plasmid pMDC85 containing the cry10Aa gene was introduced into a Typica cultivar of C. arabica L. by biobalistic transformation. Transformation efficiency of 16.7% was achieved, according to the number of embryogenic aggregates and transgenic lines developed. Stable transformation was proven by hygromycin-resistant embryogenic lines, green fluorescent protein (GFP) expression, quantitative analyses of Cry10Aa by mass spectrometry, Western blot, ELISA, and Southern blot analyses. Cry10Aa showed variable expression levels in somatic embryos and the leaf tissue of transgenic plants, ranging from 76% to 90% of coverage of the protein by mass spectrometry and from 3.25 to 13.88 µg/g fresh tissue, with ELISA. qPCR-based 2-ΔΔCt trials revealed high transcription levels of cry10Aa in somatic embryos and leaf tissue. This is the first report about the stable transformation and expression of the Cry10Aa protein in coffee plants with the potential for controlling the coffee berry borer.

Evaluation of chloroplast genome annotation tools and application to analysis of the evolution of coffee species.

Chloroplast sequences are widely used for phylogenetic analysis due to their high degree of conservation in plants. Whole chloroplast genomes can now be readily obtained for plant species using new sequencing methods, giving invaluable data for plant evolution However new annotation methods are required for the efficient analysis of this data to deliver high quality phylogenetic analyses. In this study, the two main tools for chloroplast genome annotation were compared. More consistent detection and annotation of genes were produced with GeSeq when compared to the currently used Dogma. This suggests that the annotation of most of the previously annotated chloroplast genomes should now be updated. GeSeq was applied to species related to coffee, including 16 species of the Coffea and Psilanthus genera to reconstruct the ancestral chloroplast genomes and to evaluate their phylogenetic relationships. Eight genes in the plant chloroplast pan genome (consisting of 92 genes) were always absent in the coffee species analyzed. Notably, the two main cultivated coffee species (i.e. Arabica and Robusta) did not group into the same clade and differ in their pattern of gene evolution. While Arabica coffee (Coffea arabica) belongs to the Coffea genus, Robusta coffee (Coffea canephora) is associated with the Psilanthus genus. A more extensive survey of related species is required to determine if this is a unique attribute of Robusta coffee or a more widespread feature of coffee tree species.

The first genetic linkage map for Fraxinus pennsylvanica and syntenic relationships with four related species.

KEY MESSAGE: The genetic linkage map for green ash (Fraxinus pennsylvanica) contains 1201 DNA markers in 23 linkage groups spanning 2008.87cM. The green ash map shows stronger synteny with coffee than tomato. Green ash (Fraxinus pennsylvanica) is an outcrossing, diploid (2n = 46) hardwood tree species, native to North America. Native ash species in North America are being threatened by the rapid spread of the emerald ash borer (EAB, Agrilus planipennis), an invasive pest from Asia. Green ash, the most widely distributed ash species, is severely affected by EAB infestation, yet few genomic resources for genetic studies and improvement of green ash are available. In this study, a total of 5712 high quality single nucleotide polymorphisms (SNPs) were discovered using a minimum allele frequency of 1% across the entire genome through genotyping-by-sequencing. We also screened hundreds of genomic- and EST-based microsatellite markers (SSRs) from previous de novo assemblies (Staton et al., PLoS ONE 10:e0145031, 2015; Lane et al., BMC Genom 17:702, 2016). A first genetic linkage map of green ash was constructed from 90 individuals in a full-sib family, combining 2719 SNP and 84 SSR segregating markers among the parental maps. The consensus SNP and SSR map contains a total of 1201 markers in 23 linkage groups spanning 2008.87 cM, at an average inter-marker distance of 1.67 cM with a minimum logarithm of odds of 6 and maximum recombination fraction of 0.40. Comparisons of the organization the green ash map with the genomes of asterid species coffee and tomato, and genomes of the rosid species poplar and peach, showed areas of conserved gene order, with overall synteny strongest with coffee.

Coffea arabica and C. canephora discrimination in roasted and ground coffee from reference material candidates by real-time PCR.

To produce specific desirable coffee blends, Coffea arabica and C. canephora are mixed each other, in some cases to suit consumer preference, but in others to reduce production costs. In this scenario, the aim of this work was to evaluate standard candidate reference materials (RMc) for analysis of different blends of roasted and ground coffee. For this purpose, we analyzed different percentages of C. arabica and C. canephora (100:0; 50:50; 25:75; and 0:100, respectively). These RMc samples were developed in a previous study with green coffee beans submitted to medium roasting. In this work, coffee species differentiation (C. arabica and C. canephora) was analyzed by real-time PCR, using specific primers previously developed, called ARA primers. The RMc material with 100% C. canephora did not present amplification, in contrast with the samples containing C. arabica, which all presented amplification. These results indicate the specificity of ARA primers for C. arabica and that the detection system assay can be used as a promising molecular tool to identify and quantify percentages of C. arabica in different coffee blends.

Valve-Enabled Sample Preparation and RNA Amplification in a Coffee Mug for Zika Virus Detection.

The recent outbreaks of Zika virus (ZIKV) infection represent a public health challenge. Rapid, cost-effective, and reliable diagnostic tools for ZIKV detection at the point of care (POC) are highly desirable, especially for resource-limited nations. To address the need, we have developed an integrated device to achieve sample-to-answer ZIKV detection. The device features innovative ball-based valves enabling the storage and sequential delivery of reagents for virus lysis and a paper-based unit for RNA enrichment and purification. The paper unit is placed in a commercially available coffee mug that provides a constant temperature for reverse transcription loop-mediated isothermal amplification (RT-LAMP), followed by colorimetric detection by naked eye or a cellphone camera. Using the device, we demonstrated the reproducible detection of ZIKV in human urine and saliva samples.

Interindividual Differences in Caffeine Metabolism and Factors Driving Caffeine Consumption.

Most individuals adjust their caffeine intake according to the objective and subjective effects induced by the methylxanthine. However, to reach the desired effects, the quantity of caffeine consumed varies largely among individuals. It has been known for decades that the metabolism, clearance, and pharmacokinetics of caffeine is affected by many factors such as age, sex and hormones, liver disease, obesity, smoking, and diet. Caffeine also interacts with many medications. All these factors will be reviewed in the present document and discussed in light of the most recent data concerning the genetic variability affecting caffeine levels and effects at the pharmacokinetic and pharmacodynamic levels that both critically drive the level of caffeine consumption. The pharmacokinetics of caffeine are highly variable among individuals due to a polymorphism at the level of the CYP1A2 isoform of cytochrome P450, which metabolizes 95% of the caffeine ingested. Moreover there is a polymorphism at the level of another critical enzyme, N-acetyltransferase 2. At the pharmacodynamic level, there are several polymorphisms at the main brain target of caffeine, the adenosine A2A receptor or ADORA2. Genetic studies, including genome-wide association studies, identified several loci critically involved in caffeine consumption and its consequences on sleep, anxiety, and potentially in neurodegenerative and psychiatric diseases. We start reaching a better picture on how a multiplicity of biologic mechanisms seems to drive the levels of caffeine consumption, although much more knowledge is still required to understand caffeine consumption and effects on body functions.

Population genomic footprints of host adaptation, introgression and recombination in coffee leaf rust.

Coffee leaf rust, caused by Hemileia vastatrix (Hv), represents the biggest threat to coffee production worldwide and ranks amongst the most serious fungal diseases in history. Despite a recent series of outbreaks and emergence of hypervirulent strains, the population evolutionary history and potential of this pathogen remain poorly understood. To address this issue, we used restriction site-associated DNA sequencing (RADseq) to generate ∼19 000 single nucleotide polymorphisms (SNPs) across a worldwide collection of 37 Hv samples. Contrary to the long-standing idea that Hv represents a genetically unstructured and cosmopolitan species, our results reveal the existence of a cryptic species complex with marked host tropism. Using phylogenetic and pathological data, we show that one of these lineages (C3) infects almost exclusively the most economically valuable coffee species (tetraploids that include Coffea arabica and interspecific hybrids), whereas the other lineages (C1 and C2) are severely maladapted to these hosts, but successfully infect diploid coffee species. Population dynamic analyses suggest that the C3 group may be a recent 'domesticated' lineage that emerged via host shift from diploid coffee hosts. We also found evidence of recombination occurring within this group, which could explain the high pace of pathotype emergence despite the low genetic variation. Moreover, genomic footprints of introgression between the C3 and C2 groups were discovered and raise the possibility that virulence factors may be quickly exchanged between groups with different pathogenic abilities. This work advances our understanding of the evolutionary strategies used by plant pathogens in agro-ecosystems with direct and far-reaching implications for disease control.

High throughput transcriptome analysis of coffee reveals prehaustorial resistance in response to Hemileia vastatrix infection.

KEY MESSAGE: We provide a transcriptional profile of coffee rust interaction and identified putative up regulated resistant genes Coffee rust disease, caused by the fungus Hemileia vastatrix, is one of the major diseases in coffee throughout the world. The use of resistant cultivars is considered to be the most effective control strategy for this disease. To identify candidate genes related to different mechanism defense in coffee, we present a time-course comparative gene expression profile of Caturra (susceptible) and Híbrido de Timor (HdT, resistant) in response to H. vastatrix race XXXIII infection. The main objectives were to obtain a global overview of transcriptome in both interaction, compatible and incompatible, and, specially, analyze up-regulated HdT specific genes with inducible resistant and defense signaling pathways. Using both Coffea canephora as a reference genome and de novo assembly, we obtained 43,159 transcripts. At early infection events (12 and 24 h after infection), HdT responded to the attack of H. vastatrix with a larger number of up-regulated genes than Caturra, which was related to prehaustorial resistance. The genes found in HdT at early hours were involved in receptor-like kinases, response ion fluxes, production of reactive oxygen species, protein phosphorylation, ethylene biosynthesis and callose deposition. We selected 13 up-regulated HdT-exclusive genes to validate by real-time qPCR, which most of them confirmed their higher expression in HdT than in Caturra at early stage of infection. These genes have the potential to assist the development of new coffee rust control strategies. Collectively, our results provide understanding of expression profiles in coffee-H. vastatrix interaction over a time course in susceptible and resistant coffee plants.

A first insight into the involvement of phytohormones pathways in coffee resistance and susceptibility to Colletotrichum kahawae.

Understanding the molecular mechanisms underlying coffee-pathogen interactions are of key importance to aid disease resistance breeding efforts. In this work the expression of genes involved in salicylic acid (SA), jasmonic acid (JA) and ethylene (ET) pathways were studied in hypocotyls of two coffee varieties challenged with the hemibiotrophic fungus Colletotrichum kahawae, the causal agent of Coffee Berry Disease. Based on a cytological analysis, key time-points of the infection process were selected and qPCR was used to evaluate the expression of phytohormones biosynthesis, reception and responsive-related genes. The resistance to C. kahawae was characterized by restricted fungal growth associated with early accumulation of phenolic compounds in the cell walls and cytoplasmic contents, and deployment of hypersensitive reaction. Similar responses were detected in the susceptible variety, but in a significantly lower percentage of infection sites and with no apparent effect on disease development. Gene expression analysis suggests a more relevant involvement of JA and ET phytohormones than SA in this pathosystem. An earlier and stronger activation of the JA pathway observed in the resistant variety, when compared with the susceptible one, seems to be responsible for the successful activation of defense responses and inhibition of fungal growth. For the ET pathway, the down or non-regulation of ET receptors in the resistant variety, together with a moderate expression of the responsive-related gene ERF1, indicates that this phytohormone may be related with other functions besides the resistance response. However, in the susceptible variety, the stronger activation of ERF1 gene at the beginning of the necrotrophic phase, suggests the involvement of ET in tissue senescence. As far as we know, this is the first attempt to unveil the role of phytohormones in coffee-C. kahawae interactions, thus contributing to deepen our understanding on the complex mechanisms of plant signaling and defense.

A genome-wide analysis of the RNA-guided silencing pathway in coffee reveals insights into its regulatory mechanisms.

microRNAs (miRNAs) are derived from self-complementary hairpin structures, while small-interfering RNAs (siRNAs) are derived from double-stranded RNA (dsRNA) or hairpin precursors. The core mechanism of sRNA production involves DICER-like (DCL) in processing the smallRNAs (sRNAs) and ARGONAUTE (AGO) as effectors of silencing, and siRNA biogenesis also involves action of RNA-Dependent RNA Polymerase (RDR), Pol IV and Pol V in biogenesis. Several other proteins interact with the core proteins to guide sRNA biogenesis, action, and turnover. We aimed to unravel the components and functions of the RNA-guided silencing pathway in a non-model plant species of worldwide economic relevance. The sRNA-guided silencing complex members have been identified in the Coffea canephora genome, and they have been characterized at the structural, functional, and evolutionary levels by computational analyses. Eleven AGO proteins, nine DCL proteins (which include a DCL1-like protein that was not previously annotated), and eight RDR proteins were identified. Another 48 proteins implicated in smallRNA (sRNA) pathways were also identified. Furthermore, we identified 235 miRNA precursors and 317 mature miRNAs from 113 MIR families, and we characterized ccp-MIR156, ccp-MIR172, and ccp-MIR390. Target prediction and gene ontology analyses of 2239 putative targets showed that significant pathways in coffee are targeted by miRNAs. We provide evidence of the expansion of the loci related to sRNA pathways, insights into the activities of these proteins by domain and catalytic site analyses, and gene expression analysis. The number of MIR loci and their targeted pathways highlight the importance of miRNAs in coffee. We identified several roles of sRNAs in C. canephora, which offers substantial insight into better understanding the transcriptional and post-transcriptional regulation of this major crop.

Differentiation of Chinese robusta coffees according to species, using a combined electronic nose and tongue, with the aid of chemometrics.

Electronic nose and tongue sensors and chemometric multivariate analysis were applied to characterize and classify 7 Chinese robusta coffee cultivars with different roasting degrees. Analytical data were obtained from 126 samples of roasted coffee beans distributed in the Hainan Province of China. Physicochemical qualities, such as the pH, titratable acidity (TA), total soluble solids (TSS), total solids (TS), and TSS/TA ratio, were determined by wet chemistry methods. Data fusion strategies were investigated to improve the performance of models relative to the performance of a single technique. Clear classification of all the studied coffee samples was achieved by principal component analysis, K-nearest neighbour analysis, partial least squares discriminant analysis, and a back-propagation artificial neural network. Quantitative models were established between the sensor responses and the reference physicochemical qualities, using partial least squares regression (PLSR). The PLSR model with a fusion data set was considered the best model for determining the quality parameters.