Analysis of Bacterial Microbiota of Aerated Compost Teas and Effect on Tomato Growth.

Mature composts and their water-based extracts, known as aerated compost teas (ACTs), are biofertilizers that share bioactive effects like soil restoration and plant health promotion, widely used for sustainable agriculture. Bioactive effects of compost and ACTs could be associated with their physicochemical and biological characteristics, like carbon/nitrogen (C/N) ratio and microbiota structure respectively. In our study, we elaborated ACTs using mature homemade compost, wheat bran, and grass clippings, following the C/N ratio criteria. Irrigation of tomato plantlets with ACT whose C/N ratio was close to the expected C/N ratio for mature compost evidenced plant growth promotion. Exploring the bacterial microbiota of elaborated ACTs and origin compost revealed significant structural differences, including phyla involved in N mineralization and free-living N-fixing bacteria. Therefore, ACTs harbor diverse bacterial microbiota involved in the N cycle, which would enrich plant and soil bacterial communities at the taxonomic and functional levels. Furthermore, ACTs are considered a part of agroecological and circular economy approaches.

Genome analysis of Pseudomonas sp. 14A reveals metabolic capabilities to support epiphytic behavior.

The surface of aboveground plant parts, known as the phyllosphere, is a habitat for various microorganisms called epiphytes establishing biotrophic interactions with their hosts. However, these communities can be affected by environmental and anthropogenic variations such as the application of agrochemicals. Thus, epiphytes have the capacity to survive in such environments. In this study, we obtained the genome of Pseudomonas sp. 14A, an epiphyte isolated from the pepper phyllosphere. The phylogenomic analyses suggested that Pseudomonas sp. 14A may be novel species closely related to P. moraviensis R28-S. Notably, the metabolic pathways proposed consistent with epiphytic lifestyle in Pseudomonas sp. 14A, were shared with other species displaying a different degree of phylogenetic relatedness. Furthermore, variations in configuration of metabolic gene clusters were observed, that could expand microbial metabolic diversity in close relatedness species, highlighting the relevance of microbial diversity associated with plants.

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition.

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.