Dataset Information

An Imaging Approach to Identify Mechanisms of Resistance to Pineapple Fruitlet Core Rot.

ABSTRACT: Fruitlet core rot is one of the major postharvest disease of pineapple (Ananas comosus var. comosus). In the past, control strategies were designed to eliminate symptoms without addressing their causes or mechanisms, thus achieving only moderate success. In this study, (i) we focused on the anatomy of the fruitlets in the resistant "MD-2" and susceptible "Queen" pineapple cultivars; (ii) we identified the key role of the carpel margin in the infection process; (iii) we identified the key role of the sinuous layer of thick-walled cells in the inhibition of Fusarium ananatum colonization; and (iv) we linked the anatomy of the fruitlets with the phenolic content of cell walls. The fruitlet anatomy of the two cultivars was studied using X-ray, fluorescence, and multiphoton microscopy. Sepals and bracts were not perfectly fused with each other, allowing the pathogen to penetrate the fruit even after flowering. In fact, the fungi were found in the blossom cups of both cultivars but only became pathogenic in the flesh of the "Queen" pineapple fruit under natural conditions. The outer layer of the "MD-2" cavity was continuous with thick cell walls composed of ferulic and coumaric acids. The cell walls of the "Queen" blossom cup were less lignified at the extremities, and the outer layer was interspersed with cracks. The carpel margins were fused broadly in the "MD-2" pineapple, in contrast to the "Queen" pineapple. This blemish allows the fungus to penetrate deeper into the susceptible cultivar. In pineapple fruitlets, the hyphae of F. ananatum mainly progressed directly between cell walls into the parenchyma but never reached the vascular region. A layer of thick-walled cells, in the case of the resistant cultivar, stopped the colonization, which were probably the infralocular septal nectaries. Anatomical and histochemical observations coupled with spectral analysis of the hypodermis suggested the role of lignin deposition in the resistance to F. ananatum. The major phenolics bound to the cell walls were coumaric and ferulic acids and were found in higher amounts in the resistant cultivar postinoculation. The combination of fruitlet anatomy and lignification plays a role in the mechanism of host resistance to fruitlet core rot.

SUBMITTER: Barral B

PROVIDER: S-EPMC6747042 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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An Imaging Approach to Identify Mechanisms of Resistance to Pineapple Fruitlet Core Rot.

Barral Bastien B Chillet Marc M Léchaudel Mathieu M Lartaud Marc M Verdeil Jean-Luc JL Conéjéro Geneviève G Schorr-Galindo Sabine S

Frontiers in plant science 20190910

Fruitlet core rot is one of the major postharvest disease of pineapple (<i>Ananas comosus</i> var. <i>comosus</i>). In the past, control strategies were designed to eliminate symptoms without addressing their causes or mechanisms, thus achieving only moderate success. In this study, (i) we focused on the anatomy of the fruitlets in the resistant "MD-2" and susceptible "Queen" pineapple cultivars; (ii) we identified the key role of the carpel margin in the infection process; (iii) we identified t ...[more]

PMID: 31552069

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Project description:Aphanomyces root rot (ARR) is a soil-borne disease that results in severe yield losses in lentil. The development of resistant cultivars is one of the key strategies to control this pathogen. However, the evaluation of disease severity is limited to visual scores that can be subjective. This study utilized image-based phenotyping approaches to evaluate Aphanomyces euteiches resistance in lentil genotypes in greenhouse (351 genotypes from lentil single plant/LSP derived collection and 191 genotypes from recombinant inbred lines/RIL using digital Red-Green-Blue/RGB and hyperspectral imaging) and field (173 RIL genotypes using unmanned aerial system-based multispectral imaging) conditions. Moderate to strong correlations were observed between RGB, multispectral, and hyperspectral derived features extracted from lentil shoots/roots and visual scores. In general, root features extracted from RGB imaging were found to be strongly associated with disease severity. With only three root traits, elastic net regression model was able to predict disease severity across and within multiple datasets (R 2 = 0.45-0.73 and RMSE = 0.66-1.00). The selected features could represent visual disease scores. Moreover, we developed twelve normalized difference spectral indices (NDSIs) that were significantly correlated with disease scores: two NDSIs for lentil shoot section - computed from wavelengths of 1170, 1160, 1270, and 1280 nm (0.12 ≤ |r| ≤ 0.24, P < 0.05) and ten NDSIs for lentil root sections - computed from wavelengths in the range of 630-670, 700-840, and 1320-1530 nm (0.10 ≤ |r| ≤ 0.50, P < 0.05). Root-derived NDSIs were more accurate in predicting disease scores with an R 2 of 0.54 (RMSE = 0.86), especially when the model was trained and tested on LSP accessions, compared to R 2 of 0.25 (RMSE = 1.64) when LSP and RIL genotypes were used as train and test datasets, respectively. Importantly, NDSIs - computed from wavelengths of 700, 710, 730, and 790 nm - had strong positive correlations with disease scores (0.35 ≤r ≤ 0.50, P < 0.0001), which was confirmed in field phenotyping with similar correlations using vegetation index with red edge wavelength (normalized difference red edge, 0.36 ≤ |r| ≤ 0.57, P < 0.0001). The adopted image-based phenotyping approaches can help plant breeders to objectively quantify ARR resistance and reduce the subjectivity in selecting potential genotypes.

Dataset Information

An Imaging Approach to Identify Mechanisms of Resistance to Pineapple Fruitlet Core Rot.

Publications

An Imaging Approach to Identify Mechanisms of Resistance to Pineapple Fruitlet Core Rot.

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