Dataset Information

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

ABSTRACT: This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS). A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar plates and stored at 28°C and 85% RH. The fungi were analyzed every 12 h over two days during growth, and optimal simulation models were built based on HIS parameters. The results showed that the coefficients of determination (R2) of simulation models for testing datasets were 0.7223 to 0.9914, and the sum square error (SSE) and root mean square error (RMSE) were in a range of 2.03-53.40×10(-4) and 0.011-0.756, respectively. The correlation coefficients between the HIS parameters and colony forming units of fungi were high from 0.887 to 0.957. In addition, fungi species was discriminated by partial least squares discrimination analysis (PLSDA), with the classification accuracy of 97.5% for the test dataset at 36 h. The application of this method in real food has been addressed through the analysis of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum inoculated in peaches, demonstrating that the HIS technique was effective for simulation of fungal infection in real food. This paper supplied a new technique and useful information for further study into modeling the growth of fungi and detecting fruit spoilage caused by fungi based on HIS.

SUBMITTER: Sun Y

PROVIDER: S-EPMC4671615 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

Sun Ye Y Gu Xinzhe X Wang Zhenjie Z Huang Yangmin Y Wei Yingying Y Zhang Miaomiao M Tu Kang K Pan Leiqing L

PloS one 20151207 12

This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS). A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar plates and stored at 28°C and 85% RH. The fungi were analyzed every 12 h over two days during growth, and optimal simulation models were built ...[more]

PMID: 26642054

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Project description:Worldwide, 20-25% of all harvested fruit and vegetables are lost annually in the field and throughout the postharvest supply chain due to rotting by fungal pathogens. Most postharvest pathogens exhibit necrotrophic or saprotrophic lifestyles, resulting in decomposition of the host tissues and loss of marketable commodities. Necrotrophic fungi can readily infect ripe fruit leading to the rapid establishment of disease symptoms. However, these pathogens generally fail to infect unripe fruit or remain quiescent until host conditions stimulate a successful infection. Previous research on infections of fruit has mainly been focused on the host's genetic and physicochemical factors that inhibit or promote disease. Here, we investigated if fruit pathogens can modify their own infection strategies in response to the ripening stage of the host. To test this hypothesis, we profiled global gene expression of three fungal pathogens that display necrotrophic behavior-Botrytis cinerea, Fusarium acuminatum, and Rhizopus stolonifer-during interactions with unripe and ripe tomato fruit. We assembled and functionally annotated the transcriptomes of F. acuminatum and R. stolonifer as no genomic resources were available. Then, we conducted differential gene expression analysis to compare each pathogen during inoculations versus in vitro conditions. Through characterizing patterns of overrepresented pathogenicity and virulence functions (e.g., phytotoxin production, cell wall degradation, and proteolysis) among the differentially expressed genes, we were able to determine shared strategies among the three fungi during infections of compatible (ripe) and incompatible (unripe) fruit tissues. Though each pathogen's strategy differed in the details, interactions with unripe fruit were commonly characterized by an emphasis on the degradation of cell wall components, particularly pectin, while colonization of ripe fruit featured more heavily redox processes, proteolysis, metabolism of simple sugars, and chitin biosynthesis. Furthermore, we determined that the three fungi were unable to infect fruit from the non-ripening (nor) tomato mutant, confirming that to cause disease, these pathogens require the host tissues to undergo specific ripening processes. By enabling a better understanding of fungal necrotrophic infection strategies, we move closer to generating accurate models of fruit diseases and the development of early detection tools and effective management strategies.

Project description:Worldwide, 20-25% of all harvested fruit and vegetables are lost annually in the field and throughout the postharvest supply handling chain due to spoilage by fungal pathogens. Most impactful postharvest pathogens exhibit necrotrophic lifestyles, resulting in rotting of the host tissues and complete loss of marketable commodities. Necrotrophic fungi can readily infect ripe fruit leading to the rapid establishment of disease symptoms. However, these pathogens generally fail to infect unripe fruit, or remain quiescent until host and environmental conditions stimulate a successful infection. Current research on necrotrophic infections of fruit was mainly focused on the host by characterizing genetic and physicochemical factors that inhibit or promote the disease. However, the pathogenicity and virulence strategies employed by necrotrophic pathogens in ripe and unripe fruit are mostly understudied. Here, we provide a first comparative transcriptomics study of fungal postharvest pathogens: Botrytis cinerea, Rhizopus stolonifer and Fusarium acuminatum, all of which display necrotrophic behavior when infecting fruit. We de novo assembled and annotated the transcriptomes of R. stolonifer, and F. acuminatum and performed a differential gene expression analysis comparing the three fungal transcriptomes during fruit infection with that of fungal in-vitro growth. Analysis of the differentially expressed genes for enrichment of functional annotations revealed shared strategies of the three fungi during infection of compatible (ripe fruit) and incompatible (unripe fruit) hosts. We furthermore selected candidate genes that are involved in these strategies to characterize their expression during infection of unripe and ripe-like fruit of the non-ripening (nor) tomato mutant, both of which are physiologically and biochemically similar to unripe wildtype fruit. By enabling a better understanding of fungal necrotrophic infection strategies, we move closer to generating accurate models of fruit diseases and development of early detection tools and effective management strategies.

Project description:UNLABELLED:Colletotrichum acutatum is known as an important anthracnose pathogen of a wide range of host plants worldwide. Numerous studies have reported subgroups within the C. acutatum species complex. Multilocus molecular phylogenetic analysis (ITS, ACT, TUB2, CHS-1, GAPDH, HIS3) of 331 strains previously identified as C. acutatum and other related taxa, including strains from numerous hosts with wide geographic distributions, confirmed the molecular groups previously recognised and identified a series of novel taxa. Thirty-one species are accepted, of which 21 have not previously been recognised. Colletotrichum orchidophilum clusters basal to the C. acutatum species complex. There is a high phenotypic diversity within this complex, and some of the species appear to have preferences to specific hosts or geographical regions. Others appear to be plurivorous and are present in multiple regions. In this study, only C. salicis and C. rhombiforme formed sexual morphs in culture, although sexual morphs have been described from other taxa (especially as laboratory crosses), and there is evidence of hybridisation between different species. One species with similar morphology to C. acutatum but not belonging to this species complex was also described here as new, namely C. pseudoacutatum. TAXONOMIC NOVELTIES:New combinations - Colletotrichum limetticola (R.E. Clausen) Damm, P.F. Cannon & Crous, C. lupini (Bondar) Damm, P.F. Cannon & Crous, C. salicis (Fuckel) Damm, P.F. Cannon & Crous. New species - C. acerbum Damm, P.F. Cannon & Crous, C. australe Damm, P.F. Cannon & Crous, C. brisbanense Damm, P.F. Cannon & Crous, C. cosmi Damm, P.F. Cannon & Crous, C. costaricense Damm, P.F. Cannon & Crous, C. cuscutae Damm, P.F. Cannon & Crous, C. guajavae Damm, P.F. Cannon & Crous, C. indonesiense Damm, P.F. Cannon & Crous, C. johnstonii Damm, P.F. Cannon & Crous, C. kinghornii Damm, P.F. Cannon & Crous, C. laticiphilum Damm, P.F. Cannon & Crous, C. melonis Damm, P.F. Cannon & Crous, C. orchidophilum Damm, P.F. Cannon & Crous, C. paxtonii Damm, P.F. Cannon & Crous, C. pseudoacutatum Damm, P.F. Cannon & Crous C. pyricola Damm, P.F. Cannon & Crous, C. rhombiforme Damm, P.F. Cannon & Crous, C. scovillei Damm, P.F. Cannon & Crous, C. sloanei Damm, P.F. Cannon & Crous, C. tamarilloi Damm, P.F. Cannon & Crous, C. walleri Damm, P.F. Cannon & Crous. Typifications: Epitypifications - C. acutatum J.H. Simmonds, C. limetticola (R.E. Clausen) Damm, P.F. Cannon & Crous, C. nymphaeae (Pass.) Aa, C. phormii (Henn.) D.F. Farr & Rossman, C. salicis (Fuckel) Damm, P.F. Cannon & Crous. Lectotypifications - C. nymphaeae (Pass.) Aa, C. orchidearum Allesch.

Dataset Information

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

Publications

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

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