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. 2021 Jul 29;9(8):1617.
doi: 10.3390/microorganisms9081617.

Does Organic Farming Increase Raspberry Quality, Aroma and Beneficial Bacterial Biodiversity?

Affiliations

Does Organic Farming Increase Raspberry Quality, Aroma and Beneficial Bacterial Biodiversity?

Daniela Sangiorgio et al. Microorganisms. .

Abstract

Plant-associated microbes can shape plant phenotype, performance, and productivity. Cultivation methods can influence the plant microbiome structure and differences observed in the nutritional quality of differently grown fruits might be due to variations in the microbiome taxonomic and functional composition. Here, the influence of organic and integrated pest management (IPM) cultivation on quality, aroma and microbiome of raspberry (Rubus idaeus L.) fruits was evaluated. Differences in the fruit microbiome of organic and IPM raspberry were examined by next-generation sequencing and bacterial isolates characterization to highlight the potential contribution of the resident-microflora to fruit characteristics and aroma. The cultivation method strongly influenced fruit nutraceutical traits, aroma and epiphytic bacterial biocoenosis. Organic cultivation resulted in smaller fruits with a higher anthocyanidins content and lower titratable acidity content in comparison to IPM berries. Management practices also influenced the amounts of acids, ketones, aldehydes and monoterpenes, emitted by fruits. Our results suggest that the effects on fruit quality could be related to differences in the population of Gluconobacter, Sphingomonas, Rosenbergiella, Brevibacillus and Methylobacterium on fruit. Finally, changes in fruit aroma can be partly explained by volatile organic compounds (VOCs) emitted by key bacterial genera characterizing organic and IPM raspberry fruits.

Keywords: Gluconobacter; Rubus idaeus L.; VOCs; anthocyanins; microbiome; volatilome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Krona chart showing bacterial community composition at phylum, order, class, family and genus level for (a) integrated pest management (IPM) and (b) organic raspberry fruits ‘Enrosadira’.
Figure 2
Figure 2
(a) Principal component analysis of bacterial families of raspberry fruits ‘Enrosadira’ cultivated with organic or IPM practices. Ellipses enclose confidence level = 95%. (b) Correlation circle plot with discriminating bacterial families is shown.
Figure 3
Figure 3
Main quality parameters (a), anthocyanidins content and color values (b) of raspberry fruit ‘Enrosadira’. Bars represent the mean ± SE. Different letters indicate significant differences between cultivation methods according to Student’s t-test at p-value < 0.05.
Figure 4
Figure 4
Canonical correlation analysis of bacterial genera discriminating organic from IPM grown fruit and quality parameters. Bacterial genera are coloured in brown, quality parameters in green.
Figure 5
Figure 5
Abundance of volatile organic compound classes are showed for organic and IPM grown raspberry fruits ‘Enrosadira’. Bars represent the mean ± SE. Different letter indicate significant differences between cultivation methods according to Student’s t-test at p-value < 0.05.
Figure 6
Figure 6
(a) Principal Component analysis of volatile organic compounds (VOCs) of raspberry fruits ‘Enrosadira’ cultivated with organic or IPM practices. Ellipses enclose confidence level = 95%. (b) Correlation circle plot with discriminating VOCs is shown.
Figure 7
Figure 7
Canonical correlation analysis of bacterial genera discriminating organic from IMP grown fruit and volatile organic compounds classes. Bacterial genera are coloured in brown, volatile organic compounds classes in green.
Figure 8
Figure 8
Characterization of volatile organic compound profiles, produced by assembling the emissions of single bacterial isolates from organic or IPM grown raspberries. Diagram shows (a) Principal Component (PC) 1 and 2 of principal component analysis (PCA) of the simulated fruits. Ellipses enclose confidence level = 95%. (b) loadings of the 20 m/z fragments showing highest correlation with PC1 in the PCA analysis.

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