The impact of main Areca Catechu root exudates on soil microbial community structure and function in coffee plantation soils.

Coffee is an important cash crop worldwide, but it has been plagued by serious continuous planting obstacles. Intercropping with Areca catechu could alleviate the continuous planting obstacle of coffee due to the diverse root secretions of Areca catechu. However, the mechanism of Areca catechu root secretion in alleviating coffee continuous planting obstacle is still unclear. The changes of coffee rhizosphere soil microbial compositions and functions were explored by adding simulated root secretions of Areca catechu, the primary intercropping plant species (i.e., amino acids, plant hormone, organic acids, phenolic acids, flavonoids and sugars) in current study. The results showed that the addition of coffee root exudates altered soil physicochemical properties, with significantly increasing the availability of potassium and organic matter contents as well as promoting soil enzyme activity. However, the addition of plant hormone, organic acids, or phenolic acids led to a decrease in the Shannon index of bacterial communities in continuously planted coffee rhizosphere soil (RS-CP). The inclusion of phenolic acids specifically caused the decrease of fungal Shannon index. Plant hormone, flavonoids, phenolic acids, and sugars increased the relative abundance of beneficial bacteria with reduced bacterial pathogens. Flavonoids and organic acids increased the relative abundance of potential fungal pathogen Fusarium. The polyphenol oxidase, dehydrogenase, urease, catalase, and pH were highly linked with bacterial community structure. Moreover, catalase, pH, and soil-available potassium were the main determinants of fungal communities. In conclusion, this study highlight that the addition of plant hormone, phenolic acids, and sugars could enhance enzyme activity, and promote synergistic interactions among microorganisms by enhancing the physicochemical properties of RS-CP, maintaining the soil functions in coffee continuous planting soil, which contribute to alleviate the obstacles associated with continuous coffee cultivation.

Effects of coffee pericarp and litter mulsching on soil microbiomes diversity and functions in a tropical coffee plantation, South China.

In recent decades, ecological cyclic cultivation models have attracted increasing attention, primarily because the decomposition of crop residues and litter enhances soil organic matter content, thereby altering the soil microenvironment and regulating the diversity and functions of soil microbial communities. However, the effects of different coffee waste mulching on the diversity of soil microbial communities and their functions are still unclear. Therefore, this study set up four kinds of covering treatments: uncovered coffee waste (C), covered coffee litter (L), covered coffee pericarp (P), and both covered coffee litter and pericarp (PL). The results showed that compared to the control, coffee pericarp mulching significantly increased the soil available potassium (SAK) content by 18.45% and alkali hydrolyzed N (SAN) content by 17.29%. Furthermore, coffee pericarp mulching significantly increased bacterial richness and diversity by 7.75 and 2.79%, respectively, while litter mulching had little effect on bacterial abundance and diversity was smaller. The pericarp mulching significantly increased the abundance of Proteus by 22.35% and the abundance of Chlamydomonas by 80.04%, but significantly decreased the abundance of Cyanobacteria by 68.38%, while the coffee litter mulching significantly increased the abundance of Chlamydomonas by 48.28%, but significantly decreased the abundance of Cyanobacteria by 73.98%. The increase in soil SAK promoted bacterial Anoxygenic_photoautotrophy, Nitrogen_respiration, Nitrate_respiration, Nitrite_respiration, and Denitrification functions. The above results indicate that the increase in available soil potassium and alkali hydrolyzed N content under coffee pericarp cover is the main reason for promoting the diversity and richness of bacterial community and promoting the changes in bacterial community structure and function. The use of coffee pericarps in coffee plantations for ecological recycling helps to improve the diversity of the soil microbial community and maintain the relative stability of the microbial community structure and function, promoting soil health conservation and the sustainable development of related industries.

Resequencing 93 accessions of coffee unveils independent and parallel selection during Coffea species divergence.

Coffea arabica, C. canephora and C. excelsa, with differentiated morphological traits and distinct agro-climatic conditions, compose the majority of the global coffee plantation. To comprehensively understand their genetic diversity and divergence for future genetic improvement requires high-density markers. Here, we sequenced 93 accessions encompassing these three Coffea species, uncovering 15,367,960 single-nucleotide polymorphisms (SNPs). These SNPs are unequally distributed across different genomic regions and gene families, with two disease-resistant gene families showing the highest SNP density, suggesting strong balancing selection. Meanwhile, the allotetraploid C. arabica exhibits greater nucleotide diversity, followed by C. canephora and C. excelsa. Population divergence (FST), population stratification and phylogeny all support strong divergence among species, with C. arabica and its parental species C. canephora being closer genetically. Scanning of genomic islands with elevated FST and structure-disruptive SNPs contributing to species divergence revealed that most of the selected genes in each lineage are independent, with a few being selected in parallel for two or three species, such as genes in root hair cell development, flavonols accumulation and disease-resistant genes. Moreover, some of the SNPs associated with coffee lipids exhibit significantly biased allele frequency among species, being valuable for interspecific breeding. Overall, our study not only uncovers the key population genomic patterns among species but also contributes a substantial genomic resource for coffee breeding.

Long-Term Coffee Monoculture Alters Soil Chemical Properties and Microbial Communities.

Long-term monoculture severely inhibits coffee plant growth, decreases its yield and results in serious economic losses in China. Here, we selected four replanted coffee fields with 4, 18, 26 and 57 years of monoculture history in Hainan China to investigate the influence of continuous cropping on soil chemical properties and microbial communities. Results showed long-term monoculture decreased soil pH and organic matter content and increased soil EC. Soil bacterial and fungal richness decreased with continuous coffee cropping. Principal coordinate analysis suggested monoculture time was a major determinant of bacterial and fungal community structures. Relative abundances of bacterial Proteobacteria, Bacteroidetes and Nitrospira and fungal Ascomycota phyla decreased over time. At genus level, potentially beneficial microbes such as Nitrospira and Trichoderma, significantly declined over time and showed positive relationships with coffee plant growth in pots. In conclusion, continuous coffee cropping decreased soil pH, organic matter content, potentially beneficial microbes and increased soil EC, which might lead to the poor growth of coffee plants in pots and decline of coffee yields in fields. Thus, developing sustainable agriculture to improve soil pH, organic matter content, microbial activity and reduce the salt stress under continuous cropping system is important for coffee production in China.

Large scale newborn deafness genetic screening of 142,417 neonates in Wuhan, China.

Almost one third of the three million people in China suffering severe deafness are children, and 50% of these cases are believed to have genetic components to their etiology. Newborn hearing genetic screening can complement Universal Neonatal Hearing Screening for the diagnosis of congenital hearing loss as well as identifying children at risk for late-onset and progressive hearing impairment. The aim of this joint academic and Ministry of Health project was to prototype a cost effective newborn genetic screen in a community health setting on a city-wide level, and to ascertain the prevalence of variation at loci that have been associated with non-syndromic hearing loss. With the participation of 143 local hospitals in the city of Wuhan, China we screened 142,417 neonates born between May 2014 and Dec. 2015. The variants GJB2 c.235delC, SLC26A4 c.919-2A>G, and mitochondrial variants m.1555A>G and m.1494C>T were assayed using real time PCR. Newborns found to carry a variant were re-assayed by sequencing in duplicate. Within a subset of 707 newborns we assayed using real-time PCR and ARMS-PCR to compare cost, sensitivity and operating procedure. The most frequent hearing loss associated allele detected in this population was the 235delC variant in GJB2 gene. In total, 4289 (3.01%) newborns were found to carry at least one allele of either GJB2 c.235delC, SLC26A4 c.919-2A>G or two assayed MT-RNR1 variants. There was complete accordance between the real-time PCR and the ARMS PCR, though the real-time PCR had a much lower failure rate. Real-time PCR had a lower cost and operating time than ARMS PCR. Ongoing collaboration with the participating hospitals will determine the specificity and sensitivity of the association of the variants with hearing loss at birth and arising in early childhood, allowing an estimation of the benefits of newborn hearing genetic screening in a large-scale community setting.

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.