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24 pages, 4328 KiB  
Article
Construction of Composite Microorganisms and Their Physiological Mechanisms of Postharvest Disease Control in Red Grapes
by Jingwei Chen, Kaili Wang, Esa Abiso Godana, Dhanasekaran Solairaj, Qiya Yang and Hongyin Zhang
Foods 2025, 14(3), 408; https://doi.org/10.3390/foods14030408 - 26 Jan 2025
Viewed by 330
Abstract
Red grapes often suffer from postharvest diseases like blue mold and black mold caused by Penicillium expansum and Aspergillus niger. Biological control using beneficial yeasts and bacteria is an effective method to manage these diseases. Rhodotorula sp. and Bacillus sp. are effective [...] Read more.
Red grapes often suffer from postharvest diseases like blue mold and black mold caused by Penicillium expansum and Aspergillus niger. Biological control using beneficial yeasts and bacteria is an effective method to manage these diseases. Rhodotorula sp. and Bacillus sp. are effective microorganisms for the control of postharvest diseases of red grapes. This study combined two yeast strains (Rhodotorula graminis and Rhodotorula babjevae) and two bacterial strains (Bacillus licheniformis and Bacillus velezensis) to investigate their biological control effects on major postharvest diseases of red grapes and explore the underlying physiological mechanisms. Research showed that compound microorganism W3 outperformed the others; it reduced spore germination and germ tube growth of P. expansum and A. niger, while its volatiles further inhibited pathogen growth. Additionally, the treatment enhanced the antioxidant capacity of grapes and increased resistance to pathogens by boosting peroxidase activities, superoxide dismutase, catalase and ascorbate peroxidase, phenylalanine ammonolyase, and polyphenol oxidase. Furthermore, the combined treatment increased the activity and accumulation of antifungal compounds such as total phenols and flavonoids, thereby improving disease resistance and reducing decay. Therefore, composite microorganisms combining various antagonistic strains may offer a viable substitute for tackling postharvest diseases in red grapes. Full article
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<p>Affinity test between antagonistic strains. Note: Different letters represent different strains, Y1 (<span class="html-italic">Rhodotorula graminis</span>), Y2 (<span class="html-italic">Rhodotorula babjevae</span>), B2 (<span class="html-italic">Bacillus licheniformis</span>), and B4 (<span class="html-italic">Bacillus velezensis</span>).</p>
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<p>Optimal proportion construction of complex microorganisms that inhibit blue mold disease of red grapes. Note: CK is sterile water control group. (<b>A</b>,<b>B</b>) represent combination of strain Y1 with B2, (<b>C</b>,<b>D</b>) represent combination of strain W1 with Y2, and (<b>E</b>,<b>F</b>) represent combination of strain W2 with B4. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
Full article ">Figure 2 Cont.
<p>Optimal proportion construction of complex microorganisms that inhibit blue mold disease of red grapes. Note: CK is sterile water control group. (<b>A</b>,<b>B</b>) represent combination of strain Y1 with B2, (<b>C</b>,<b>D</b>) represent combination of strain W1 with Y2, and (<b>E</b>,<b>F</b>) represent combination of strain W2 with B4. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Optimal proportion construction of complex microorganisms that inhibit black mold disease of red grapes. Note: CK is sterile water control group. (<b>A</b>,<b>B</b>) represent combination of strain Y1 with B2, (<b>C</b>,<b>D</b>) represent combination of strain Q1 with Y2, (<b>E</b>,<b>F</b>) represent combination of strain Q2 with B4. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
Full article ">Figure 3 Cont.
<p>Optimal proportion construction of complex microorganisms that inhibit black mold disease of red grapes. Note: CK is sterile water control group. (<b>A</b>,<b>B</b>) represent combination of strain Y1 with B2, (<b>C</b>,<b>D</b>) represent combination of strain Q1 with Y2, (<b>E</b>,<b>F</b>) represent combination of strain Q2 with B4. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Control effects of different treatment groups blue mold (<b>A</b>,<b>B</b>) and black mold (<b>C</b>,<b>D</b>) of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, W3, and Q3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of different treatments on spore germination rate and germ tube length of <span class="html-italic">P. expansum</span> (<b>A</b>,<b>B</b>) and <span class="html-italic">A. niger</span> (<b>C</b>,<b>D</b>). Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of volatile metabolites produced by different treatments on <span class="html-italic">P. expansum</span> (<b>A</b>,<b>B</b>) and <span class="html-italic">A. niger</span> (<b>C</b>,<b>D</b>). Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
Full article ">Figure 7
<p>Effects of volatile metabolites produced by different treatments on blue mold (<b>A</b>,<b>B</b>) and black mold (<b>C</b>,<b>D</b>) of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p><span class="html-italic">In vitro</span> inhibition of <span class="html-italic">P. expansum</span> (<b>A</b>) and <span class="html-italic">A. niger</span> (<b>B</b>) by non-volatile metabolites treated with different treatments. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
Full article ">Figure 8 Cont.
<p><span class="html-italic">In vitro</span> inhibition of <span class="html-italic">P. expansum</span> (<b>A</b>) and <span class="html-italic">A. niger</span> (<b>B</b>) by non-volatile metabolites treated with different treatments. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of non-volatile metabolites produced by different treatments on blue mold (<b>A</b>,<b>B</b>) and black mold (<b>C</b>,<b>D</b>) of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of different treatments on POD (<b>A</b>), SOD (<b>B</b>) and CAT (<b>C</b>) activities of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of different treatments on PPO (<b>A</b>), APX (<b>B</b>), and PAL (<b>C</b>) activities of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
Full article ">Figure 11 Cont.
<p>Effects of different treatments on PPO (<b>A</b>), APX (<b>B</b>), and PAL (<b>C</b>) activities of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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<p>Effects of different treatments on total phenol (<b>A</b>) and flavonoid (<b>B</b>) contents of red grapes. Note: CK is sterile water control group; Y1, Y2, B2, B4, and W3 represent different treatment groups. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05) according to Duncan’s multiple-range mean comparison test.</p>
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14 pages, 1767 KiB  
Article
Sensitivity to the Demethylation Inhibitor Difenoconazole Among Baseline Populations of Various Penicillium spp. Causing Blue Mold of Apples and Pears
by Madan Pandey, Clayton L. Haskell, Juliette D. Cowell and Achour Amiri
J. Fungi 2025, 11(1), 61; https://doi.org/10.3390/jof11010061 - 15 Jan 2025
Viewed by 445
Abstract
Difenoconazole (DIF), a demethylation inhibitor fungicide, was registered in 2016 for the control of postharvest diseases of pome fruits. In this study, 162 isolates from P. expansum (n = 31) and 13 other “non-expansumPenicillium spp., i.e., P. solitum ( [...] Read more.
Difenoconazole (DIF), a demethylation inhibitor fungicide, was registered in 2016 for the control of postharvest diseases of pome fruits. In this study, 162 isolates from P. expansum (n = 31) and 13 other “non-expansumPenicillium spp., i.e., P. solitum (n = 52), P. roqueforti (n = 32), P. commune (n = 15), P. paneum (n = 9), P. psychrosexuale (n = 8), P. crustosum (n = 5), P. carneum (n = 3), P. palitans (n = 2), along with one isolate each of P. citrinum, P. griseofulvum, P. raistrickii, P. ribium, and P. viridicatum, were collected from multiple packinghouses in the U.S. Pacific Northwest. In vitro sensitivity assays showed similar sensitivities of spores and mycelia across species with the mean EC50 values ranging from 0.01 for P. psychrosexuale (n = 8) to 1.33 μg mL−1 for P. palitans (n = 2), whereas the mean EC50s were 0.03, 0.12, 0.19, and 0.51 μg mL−1 for P. expansum (n = 31), P. paneum (n = 9), P. solitum (n = 52), and P. crustosum (n = 5), respectively. The recommended rate of DIF controlled P. expansum and P. roqueforti isolates but not all isolates of four other Penicillium spp. on Fuji apples after five months at 1.5 °C. The mixture of DIF + fludioxonil (FDL) (AcademyTM) controlled all the dual-sensitive isolates (DIFSFDLS) and DIF single-resistant (DIFR) isolates among the six species tested but not the FDLR and dual DIFRFDLR isolates. Notable polymorphism was detected in the CYP51 gene of the “non-expansum” species with four mutations located at four residues. Although the isolates analyzed in this study had not previously been exposed to DIF, the findings indicate variable sensitivity levels among the Penicillium spp. Full article
(This article belongs to the Section Fungal Pathogenesis and Disease Control)
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<p>Frequency distribution of the effective concentrations of difenoconazole inhibiting 50% germination and germ tube (EC<sub>50</sub>) among seven <span class="html-italic">Penicillium</span> spp. (<b>a</b>) and correlation between logarithmically transformed EC<sub>50</sub> values for spore germination and mycelial growth inhibition (<b>b</b>). The numbers in brackets indicate the number of isolates tested for each species.</p>
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<p>Blue mold incidence after five months of storage at 1.5 °C on untreated (control) and DIF-treated Fuji apples then inoculated with spore suspensions of <span class="html-italic">Penicillium</span> spp. isolates with different EC<sub>50</sub> values shown in brackets. Bars indicate the standard deviations of the means, and an asterisk indicates a significant difference between the incidence in the control and DIF for each isolate based on Tukey’s HSD test at <span class="html-italic">p</span> &lt; 0.05. Dashed black and blue lines indicate regression between EC<sub>50</sub> values and blue mold incidence (%) for each <span class="html-italic">Penicillium</span> spp., for the control and DIF treatments, respectively.</p>
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<p>(<b>a</b>) Blue mold lesions after five months of storage at 1.5 °C on untreated (control) and DIF-treated Fuji apples then inoculated with spore suspensions (10<sup>5</sup> spores mL<sup>−1</sup>) of each isolate. An asterisk indicates the EC<sub>50</sub> value (µg mL<sup>−1</sup>) of each isolate; (<b>b</b>) Growth of <span class="html-italic">Penicillium expansum</span>, <span class="html-italic">P. roqueforti</span>, <span class="html-italic">P. palitans</span>, <span class="html-italic">P. crustosum</span>, <span class="html-italic">P. solitum</span>, and <span class="html-italic">P. commune</span> isolates after 7 days at 22 °C on malt extract agar medium supplemented with different DIF concentrations.</p>
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28 pages, 2437 KiB  
Article
Omics-Based Comparison of Fungal Virulence Genes, Biosynthetic Gene Clusters, and Small Molecules in Penicillium expansum and Penicillium chrysogenum
by Holly P. Bartholomew, Christopher Gottschalk, Bret Cooper, Michael R. Bukowski, Ronghui Yang, Verneta L. Gaskins, Dianiris Luciano-Rosario, Jorge M. Fonseca and Wayne M. Jurick
J. Fungi 2025, 11(1), 14; https://doi.org/10.3390/jof11010014 - 28 Dec 2024
Viewed by 537
Abstract
Penicillium expansum is a ubiquitous pathogenic fungus that causes blue mold decay of apple fruit postharvest, and another member of the genus, Penicillium chrysogenum, is a well-studied saprophyte valued for antibiotic and small molecule production. While these two fungi have been investigated [...] Read more.
Penicillium expansum is a ubiquitous pathogenic fungus that causes blue mold decay of apple fruit postharvest, and another member of the genus, Penicillium chrysogenum, is a well-studied saprophyte valued for antibiotic and small molecule production. While these two fungi have been investigated individually, a recent discovery revealed that P. chrysogenum can block P. expansum-mediated decay of apple fruit. To shed light on this observation, we conducted a comparative genomic, transcriptomic, and metabolomic study of two P. chrysogenum (404 and 413) and two P. expansum (Pe21 and R19) isolates. Global transcriptional and metabolomic outputs were disparate between the species, nearly identical for P. chrysogenum isolates, and different between P. expansum isolates. Further, the two P. chrysogenum genomes revealed secondary metabolite gene clusters that varied widely from P. expansum. This included the absence of an intact patulin gene cluster in P. chrysogenum, which corroborates the metabolomic data regarding its inability to produce patulin. Additionally, a core subset of P. expansum virulence gene homologues were identified in P. chrysogenum and were similarly transcriptionally regulated in vitro. Molecules with varying biological activities, and phytohormone-like compounds were detected for the first time in P. expansum while antibiotics like penicillin G and other biologically active molecules were discovered in P. chrysogenum culture supernatants. Our findings provide a solid omics-based foundation of small molecule production in these two fungal species with implications in postharvest context and expand the current knowledge of the Penicillium-derived chemical repertoire for broader fundamental and practical applications. Full article
(This article belongs to the Special Issue Plant Pathogens and Mycotoxins)
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<p>Genome macrosynteny between <span class="html-italic">P. expansum</span> R19 (blue), <span class="html-italic">P. expansum</span> Pe21 (orange) <span class="html-italic">P. chrysogenum</span> 404 (green), and <span class="html-italic">P. chrysogenum</span> 413 (pink) chromosomes (chr). Gray lines represent regions of synteny and connect to similar areas across chromosomal regions.</p>
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<p>Principal Component analysis of transcriptomic data for each <span class="html-italic">Penicillium</span> spp. isolate. <span class="html-italic">P. chrysogenum</span> isolates 404 (red circles) and 413 (red triangles), <span class="html-italic">P. expansum</span> isolates R19 (blue triangles) and Pe21 (blue circles) across four replicates.</p>
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<p>Principal Component analysis of metabolomic data for each <span class="html-italic">Penicillium</span> spp. isolate. <span class="html-italic">P. chrysogenum</span> isolates 404 (navy blue) and 413 (orange), <span class="html-italic">P. expansum</span> isolates R19 (green) and Pe21 (brown), and the PDB control samples (teal). Samples were analyzed in both positive ion mode (<b>left</b>) and negative ion mode (<b>right</b>).</p>
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<p>Patulin genomic, transcriptomic, and metabolomic presence in each <span class="html-italic">Penicillium</span> isolate. (<b>A</b>) Complete 15-gene patulin biosynthetic gene cluster in <span class="html-italic">P. expansum</span> found localized to one location in R19 and Pe21 (top, orange line). In 404 and 413, the native orthologous cluster only contains 6 genes (bottom, star), with the remaining orthologues found across the four chromosomes (blue lines). (<b>B</b>) Expression (Log2 TPM) of each patulin cluster gene orthologue across the four isolates. Darker red indicates higher expression, and gray means transcript levels were below the threshold. TPM = transcripts per million. (<b>C</b>) Average patulin production detected in each isolate over the average potato dextrose broth (PDB) control. Values are average peak area ratios across replicates.</p>
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<p>Penicillin G genomic, transcriptomic, and metabolomic presence in each <span class="html-italic">Penicillium</span> isolate. (<b>A</b>) Penicillin G biosynthetic gene cluster in <span class="html-italic">P. chrysogenum</span> (top, orange line) chromosome 1, which were absent in R19 and Pe21. The 404 <span class="html-italic">pcbC</span> gene shows a larger segment that suggests a tandem repeat compared to the 413 genome. (<b>B</b>) Expression (Log2 TPM) of each penicillin G cluster gene orthologue across the two isolates. Darker red indicates higher expression, and gray means transcript levels were below the threshold. TPM = transcripts per million. (<b>C</b>) Average penicillin G production detected in each isolate over the average potato dextrose broth (PDB) control. Values are average peak area ratios across replicates.</p>
Full article ">
14 pages, 3213 KiB  
Article
Antifungal Activity of Ethanolic Extracts from Aeroponically Grown Cape Gooseberry (Physalis peruviana L.) with LED Lights and In Vitro Habituated Roots
by Daniel Eduardo Avila-Avila, Martha Alicia Rodríguez-Mendiola, Carlos Arias-Castro, Laura Isabel Arias-Rodríguez, Martin Eduardo Avila-Miranda and Norma Alejandra Mancilla-Margalli
Plants 2024, 13(24), 3586; https://doi.org/10.3390/plants13243586 - 23 Dec 2024
Viewed by 669
Abstract
Green mold caused by Penicillium digitatum is a major post-harvest disease in citrus fruits. Therefore, the search for sustainable and low-environmental-impact alternatives for the management of these fungi is of utmost importance. Physalis peruviana L. is a native fruit of the Peruvian Andes [...] Read more.
Green mold caused by Penicillium digitatum is a major post-harvest disease in citrus fruits. Therefore, the search for sustainable and low-environmental-impact alternatives for the management of these fungi is of utmost importance. Physalis peruviana L. is a native fruit of the Peruvian Andes with rich bioactive components present throughout the plant. Its antifungal activity stands out, attributed to its high content of phenols, coupled with its antioxidant capacity and antimicrobial activity. Plants were cultivated aeroponically under a combination of red, mixed (50% red, 50% blue), and green LED lights. Additionally, in vitro-habituated roots free of plant growth regulators were also cultivated. An ethanol extraction assisted by ultrasound for 30 min followed by maceration for 72 h was performed, and the extract was filtrated and evaporated in an extraction hood. Antioxidant activity was assessed using the DPPH method, total polyphenols were measured using the Folin–Ciocâlteu method, and an antifungal test in vitro by the poisoned food method was conducted against P. digitatum. In vitro assays revealed that extracts from leaves, roots, and fruits exerted a significant inhibitory effect on the growth of P. digitatum, as evidenced by a reduction in colony radius when cultured employing the poisoned food method, with IC50 values of 62.17, 53.15, and 286.34 µg·mL−1, respectively, compared to 2297 µg·mL−1 for the commercial fungicide Captan 50WP. Although leaves had higher total polyphenol content, no direct correlation with antifungal activity was found. Colored LEDs enhanced phenol accumulation, antioxidant capacity, and antifungal properties in plant parts compared to white LEDs and in vitro roots. These findings suggest P. peruviana as a new alternative biological production system to provide natural compounds for post-harvest disease management. Full article
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<p>Relationship of Trolox equivalent antioxidant capacity (TEAC) of ethanolic extracts of <span class="html-italic">P. peruviana</span> at a concentration of 5 mg·mL<sup>−1</sup>. Fruit (F), leaf in white LED light (LW), leaf mixed LED light (LM), <span class="html-italic">in vitro</span>-habituated root (RIV), root white LED light (RW), root mixed light (RM). Statistically significant differences are indicated by different letters LSD, (<span class="html-italic">p</span> ≤ 0.05). The error bars in the figure represent the standard error of the mean.</p>
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<p>Total polyphenol content (TPC) in extracts of <span class="html-italic">P. peruviana.</span> Extracts of <span class="html-italic">in vitro</span>-habituated root (RIV), Leaf in white light (LW), Root in white light (RM), Leaf in mixed light (LM), Root in mixed light (RM), Fruit (F). Significant differences are denoted by different letters. LSD (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Growth radius in millimeters (mm) of <span class="html-italic">P. digitatum</span> in medium poisoned by extracts of <span class="html-italic">P. peruviana</span>. Control (C−), control with dimethyl sulfoxide (C+ DMSO), <span class="html-italic">in vitro</span>-habituated root (RIV), leaf in white light (LW), root in white light (RW), leaf in mixed light (LM), root in mixed light (RM), fruit (F), Captan 50 WP (C50). The error bars in the figure represent the standard error of the mean. Statistically significant differences are marked by different letters, based on LSD (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Percentage of growth inhibition of <span class="html-italic">P. digitatum</span> using ethanolic extracts of <span class="html-italic">in vitro</span>-habituated root (RIV), leaf in white light (LW), root in white light (RW), leaf in mixed light (LM), root in mixed light (RM), fruit (F), Captan 50 WP (C50). The error bars in the figure represent the standard error of the mean.</p>
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<p>Antifungal activity results in 7 days post-inoculation of <span class="html-italic">P. peruviana</span> extracts in <span class="html-italic">P. digitatum</span>: Control absolute (C−), control with dimethyl sulfoxide (C + DMSO), positive control with fungicide Captan 50 (C50), fruit (F), leaf white light (LW), leaf mixed light (LM), root in white light (RW), Leaf in mixed light (LM), root in mixed light (RM), <span class="html-italic">in vitro</span>-habituated root (RIV).</p>
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<p><span class="html-italic">P. peruviana</span> cultivated aeroponically: (<b>A</b>) cultivated with white LED light and (<b>B</b>) with mixed LED light.</p>
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<p>Habituated <span class="html-italic">in vitro</span> root culture of <span class="html-italic">P. peruviana</span>. (<b>A</b>) Germination and growth <span class="html-italic">in vitro</span> in solid medium. (<b>B</b>) Root growth in solid medium. (<b>C</b>) Transfer of roots to liquid medium. (<b>D</b>) Habituated roots <span class="html-italic">in vitro</span> at 45 days.</p>
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10 pages, 8354 KiB  
Article
Replication of Leaf Surface Structures on Flat Phosphor-Converted LEDs for Enhanced Angular Color Uniformity
by Bing-Mau Chen, Chiu-Hsiang Chen, Shang-Ping Ying and Yu-Kang Chang
Micromachines 2024, 15(11), 1399; https://doi.org/10.3390/mi15111399 - 20 Nov 2024
Viewed by 684
Abstract
We explored the use of biomimetic structures, including those that mimic leaf structures, to enhance the angular color uniformity of flat phosphor-converted light-emitting diodes (pcLEDs). The distinct microstructures found on natural leaf surfaces, such as micro-scale bumps, ridges, and hierarchical patterns, have inspired [...] Read more.
We explored the use of biomimetic structures, including those that mimic leaf structures, to enhance the angular color uniformity of flat phosphor-converted light-emitting diodes (pcLEDs). The distinct microstructures found on natural leaf surfaces, such as micro-scale bumps, ridges, and hierarchical patterns, have inspired the design of artificial microstructures that can improve light extraction, scattering, and overall optical performance in LED applications. The effects of these leaf surface microstructures on the phosphor layer of flat pcLEDs were evaluated. An imprinting technique was employed to directly replicate the surface morphology structures from fresh plant leaves. The results indicated that this method provided excellent scattering capability and reduced the disparity in light output between blue and yellow light emissions from flat pcLEDs at various angles. Subsequently, uniform correlated color temperature in the flat pcLEDs was achieved, reducing the yellow ring effect. Furthermore, the availability of diverse wrinkle and surface patterns from a wide range of natural prototypes could reduce design costs compared with traditional mold fabrication, making the method suitable for application in mass production. Full article
(This article belongs to the Special Issue Innovative Progression of Light-Emitting Diodes (LED))
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<p>Schematic cross-sectional view of flat pcLED.</p>
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<p>Photographs of the leaves used in the study. (<b>a</b>) <span class="html-italic">Epipremnum aureum</span> and (<b>b</b>) <span class="html-italic">Acer serrulatum</span>, with marked regions indicating areas selected for surface microstructure analysis.</p>
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<p>Optical microscope images of the surface morphologies of (<b>a</b>–<b>c</b>) Regions A, B, and C from <span class="html-italic">Epipremnum aureum</span>, (<b>d</b>–<b>f</b>) their respective inverse UV-curable resin replicas, and (<b>g</b>–<b>i</b>) their respective positive replicated PDMS films.</p>
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<p>Optical microscope images of the surface morphologies of (<b>a</b>–<b>c</b>) Regions A, B, and C from <span class="html-italic">Acer serrulatum</span>, (<b>d</b>–<b>f</b>) their respective inverse UV-curable resin replicas, and (<b>g</b>–<b>i</b>) their respective positive replicated PDMS films.</p>
Full article ">Figure 4 Cont.
<p>Optical microscope images of the surface morphologies of (<b>a</b>–<b>c</b>) Regions A, B, and C from <span class="html-italic">Acer serrulatum</span>, (<b>d</b>–<b>f</b>) their respective inverse UV-curable resin replicas, and (<b>g</b>–<b>i</b>) their respective positive replicated PDMS films.</p>
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<p>Schematic demonstrating the procedure used to produce lead surface microstructure on pcLEDs.</p>
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<p>(<b>a</b>) Angular CCT and (<b>b</b>) ΔCCT of pcLED with and without <span class="html-italic">Epipremnum aureum</span> surface microstructures applied to phosphor layer.</p>
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<p>(<b>a</b>) Angular CCT and (<b>b</b>) ΔCCT of pcLED with and without <span class="html-italic">Acer serrulatum</span> surface microstructures applied to phosphor layer.</p>
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<p>Optical power according to the injection current of pcLED with and without (<b>a</b>) <span class="html-italic">Epipremnum aureum</span> and (<b>b</b>) <span class="html-italic">Acer serrulatum</span> surface microstructures applied to phosphor layer.</p>
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16 pages, 1956 KiB  
Article
In Vitro Assessment of Penicillium expansum Sensitivity to Difenoconazole
by Mohammed Khadiri, Hassan Boubaker, Abdelaaziz Farhaoui, Said Ezrari, Mohammed Radi, Rachid Ezzouggari, Fouad Mokrini, Essaid Ait Barka and Rachid Lahlali
Microorganisms 2024, 12(11), 2169; https://doi.org/10.3390/microorganisms12112169 - 28 Oct 2024
Cited by 1 | Viewed by 845
Abstract
Penicillium expansum causes blue mold, a major post-harvest disease affecting apples. This disease is commonly managed using fungicides, including Difenoconazole (Dif), a demethylation inhibitor (DMI) approved for its control. This investigation aims to evaluate the baseline sensitivity of 100 P. expansum isolates to [...] Read more.
Penicillium expansum causes blue mold, a major post-harvest disease affecting apples. This disease is commonly managed using fungicides, including Difenoconazole (Dif), a demethylation inhibitor (DMI) approved for its control. This investigation aims to evaluate the baseline sensitivity of 100 P. expansum isolates to Difenoconazole. The isolates were collected from symptomatic apples in 34 storage warehouses across the Fes-Meknes and Draa-Tafilalet regions over three years (2020, 2021, and 2022). The study revealed an increase in the percentage of inhibition of mycelial growth and spore germination of P. expansum proportional to the increasing concentration of the fungicide. Moreover, the results indicate that 46 isolates were able to develop even at a concentration of 5 µg/mL of Dif (the suggested discriminatory dose), indicating reduced sensitivity to this fungicide. The analysis of the values of the effective concentration to inhibit 50% (EC50) of mycelial growth of P. expansum ranging from 0.027 to 1.673 µg/mL (mean: 0.263 µg/mL, variation factor: 62.507) and for spore germination from 0.0002 to 0.787 µg/mL (mean: 0.048 µg/mL, variation factor: 4113.835). The wide variation in EC50 values indicates significant variability in the isolates’ responses to Dif, likely due to diverse sampling in space and time. Our results showed that some P. expansum isolates could grow even at high concentrations of Dif, indicating limited efficacy of this treatment. The EC50 of five isolates exceeded 0.92 µg/mL, suggesting potential resistance. This study indicates reduced sensitivity and possible emergence of resistant strains. Notably, it is the first evaluation of P. expansum sensitivity to Dif in Morocco. Full article
(This article belongs to the Section Antimicrobial Agents and Resistance)
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<p>Sampling areas in the Fes-Meknes and Draa-Tafilalet regions of Morocco. This map was generated using ArcGIS Pro version 2.6. The black crosses indicate the locations of <span class="html-italic">P. expansum</span> isolates resistant to difenoconazole.</p>
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<p>Agarose gel electrophoresis profiles (1.5%) showing PCR-amplified products with <span class="html-italic">P. expansum</span>-specific primers; patF-F and patF-R of the patF gene. Lane M: GeneRuler 100 bp DNA Ladder (Thermo Scientific). Lane C-: negative control. Lane C+ (Aby4): positive control with the Aby4 strain of <span class="html-italic">P. expensum</span> identified through molecular sequencing of the internal transcribed spacer (ITS) region of rDNA (accession number: OR426630).</p>
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<p>Effect of different difenoconazole concentrations on Mycelial Growth of <span class="html-italic">P. expansum</span>.</p>
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<p>Distribution of EC50 values for mycelial growth and spore germination of 100 isolates of <span class="html-italic">P. expansum</span>.</p>
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13 pages, 2934 KiB  
Article
Recovery and Restructuring of Fine and Coarse Soil Fractions as Earthen Construction Materials
by Mazhar Hussain, Ines Lamrous, Antony Provost, Nathalie Leblanc, Hafida Zmamou, Daniel Levacher and Abdoulaye Kane
Sustainability 2024, 16(20), 8952; https://doi.org/10.3390/su16208952 - 16 Oct 2024
Viewed by 911
Abstract
Excessive consumption of natural resources to meet the growing demands of building and infrastructure projects has put enormous stress on these resources. On the other hand, a significant quantity of soil is excavated for development activities across the globe and is usually treated [...] Read more.
Excessive consumption of natural resources to meet the growing demands of building and infrastructure projects has put enormous stress on these resources. On the other hand, a significant quantity of soil is excavated for development activities across the globe and is usually treated as waste material. This study explores the potential of excavated soils in the Brittany region of France for its reuse as earthen construction materials. Characterization of soil recovered from building sites was carried out to classify the soils and observe their suitability for earthen construction materials. These characteristics include mainly Atterberg limits, granulometry, organic matter and optimum moisture content. Soil samples were separated into fine and coarse particles through wet sieving. The percentage of fines (particles smaller than 0.063 mm) in studied soil samples range from 28% to 65%. The methylene blue value (MBV) for Lorient, Bruz and Polama soils is 1, 1.2 and 1.2 g/100 g, and French classification (Guide de terrassements des remblais et des couches de forme; GTR) of soil samples is A1, B5 and A1, respectively. The washing of soils with lower fine content helps to recover excellent-quality sand and gravel, which are a useful and precious resource. However, residual fine particles are a waste material. In this study, three soil formulations were used for manufacturing earth blocks. These formulations include raw soil, fines and restructured soil. In restructured soil, a fine fraction of soil smaller than 0.063 mm was mixed with 15% recycled sand. Restructuring of soil fine particles helps to improve soil matrix composition and suitability for earth bricks. Compressed-earth blocks of 4 × 4 × 16 cm were manufactured at a laboratory scale for flexural strength testing by using optimum molding moisture content and compaction through Proctor normal energy. Compressive strength tests were performed on cubic blocks of size 4 × 4 × 4 cm. Mechanical testing of bricks showed that bricks with raw soil had higher resistance with a maximum of 3.4 MPa for Lorient soil. Removal of coarse particles from soil decreased the strength of bricks considerably. Restructuring of fines with recycled sand improves their granular skeleton and increases the compressive strength and durability of bricks. Full article
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<p>Brittany soil samples: Lorient (<b>a</b>), Polama (<b>b</b>) and Bruz (<b>c</b>).</p>
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<p>Wet processing of excavated soils.</p>
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<p>Raw soil (<b>a</b>), mixing soil with water (<b>b</b>), wet sieving of soil (<b>c</b>) and fine particles of soil (<b>d</b>).</p>
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<p>Samples of prismatic earth blocks.</p>
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<p>Granulometry of recycled sand.</p>
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<p>Minerology of recycled sand.</p>
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<p>Flexural and compressive strength (MPa) of earth blocks. Note: S = raw soil; F = fine soil; RS = restructured soil; Fc = compressive strength; Ft = flexural strength.</p>
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19 pages, 5203 KiB  
Article
New Trichoderma Strains Suppress Blue Mold in Oranges by Damaging the Cell Membrane of Penicillium italicum and Enhancing Both Enzymatic and Non-Enzymatic Defense Mechanisms in Orange Fruits
by Asmaa El-Nagar, Yasser S. A. Mazrou, Mansour M. El-Fawy, Mohamed K. Abou-Shlell, Mohamed A. A. Seleim, Abeer H. Makhlouf and Mohamed G. A. Hegazy
Horticulturae 2024, 10(10), 1076; https://doi.org/10.3390/horticulturae10101076 - 8 Oct 2024
Viewed by 923
Abstract
Blue mold disease, caused by Penicillium italicum (P. italicum), presents a significant challenge to orange fruits (Citrus sinensis L.) and other citrus crops globally. Biological control, particularly Trichoderma species, offers a promising alternative to synthetic fungicides. Therefore, this study aimed [...] Read more.
Blue mold disease, caused by Penicillium italicum (P. italicum), presents a significant challenge to orange fruits (Citrus sinensis L.) and other citrus crops globally. Biological control, particularly Trichoderma species, offers a promising alternative to synthetic fungicides. Therefore, this study aimed to isolate, identify, and evaluate the antagonistic activities of two Trichoderma isolates against P. italicum. These isolates were molecularly identified and assigned accession numbers PP002254 and PP002272, respectively. Both isolates demonstrated significant antifungal activity in dual culture assays. Moreover, the culture filtrates (CFs) of Trichoderma longibrachiatum PP002254 and Trichoderma harzianum PP002272 suppressed the mycelial growth of P. italicum by 77.22% and 71.66%, respectively. Additionally, CFs reduced the severity of blue mold on orange fruits by 26.85% and 53.81%, compared to 100% in the control group. Scanning electron microscopy revealed that treated P. italicum hyphae were shrunken and disfigured. Enzyme activities (catalase, peroxidase, polyphenol oxidase, and phenylalanine ammonia-lyase) in treated oranges increased, along with total soluble phenolics and flavonoids. Conversely, malondialdehyde (MDA) levels decreased in treated fruits. These findings suggest that T. longibrachiatum PP002254 and T. harzianum PP002272 could be effective biocontrol agents for managing blue mold and other citrus postharvest diseases. Full article
(This article belongs to the Special Issue Biological Control of Pre and Postharvest Diseases II)
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<p>Morphological characteristics of <span class="html-italic">T. longibrachiatum</span> PP002254 and <span class="html-italic">T. harzianum</span> isolates PP002272 on PDA plates on the front side (<b>a</b>,<b>b</b>) and the back side (<b>c</b>,<b>d</b>), respectively, after incubation for 7 days at 25 ± 2 °C. (<b>e</b>,<b>f</b>) Maximum-likelihood phylogenetic tree using ITS-5.8S rDNA sequence of <span class="html-italic">T. longibrachiatum</span> Isolate AE 2023 and <span class="html-italic">T. harzianum</span> Isolate AE 2023 (GenBank Accession No. PP002254 and PP002272, respectively) (highlighted in bold) in comparison with other 20 <span class="html-italic">Trichoderma</span> strains/isolates retrieved from recent available data in the National Center for Biotechnology Information (NCBI) GenBank (<a href="https://www.ncbi.nlm.nih.gov/" target="_blank">https://www.ncbi.nlm.nih.gov/</a>; accessed on 21 December 2023).</p>
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<p>In vitro, the antifungal activity of <span class="html-italic">T. longibrachiatum</span> PP0022542 and <span class="html-italic">T. harzianum</span> PP002272 against <span class="html-italic">P. italicum</span> using a dual culture plate assay after 7 days of incubation at 25 °C.</p>
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<p>The antifungal activity of <span class="html-italic">T. longibrachiatum</span> PP002254 and <span class="html-italic">T. harzianum</span> PP002272 culture filtrate against <span class="html-italic">P. italicum</span>.</p>
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<p>Morphological changes of <span class="html-italic">T. longibrachiatum</span> PP002254 and <span class="html-italic">T.harzianum</span> PP002272 culture filtrate on <span class="html-italic">P. italicum</span> hyphae by scanning electron microscope (SEM) examinations (JEOL, Tokyo, Japan).</p>
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<p>Effect of <span class="html-italic">T. longibrachiatum</span> PP002254 and <span class="html-italic">T. harzianum</span> PP002272 CFs on (<b>a</b>) Disease symptoms of blue mold in oranges fruit inoculated with <span class="html-italic">P. italicum</span> 7 days post inoculation (<b>b</b>) Lesion diameter (mm) and (<b>c</b>) disease severity (%). Values are mean ± standard error (SE).Different letters indicate statistically significant differences among the treatments, as determined by the Tukey Honestly Significant Difference (HSD) test at a significance level of (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of <span class="html-italic">T. longibrachiatum</span> PP002254 and <span class="html-italic">T. harzianum</span> PP002272 CFs on enzyme activity including catalase, peroxidase, polyphenoloxidase, and phenylalanine ammonia-lyase of orange fruit at 24, 48, 72 and 96 h post-treatment (hpt). (<b>a</b>) Catalase (CAT), (<b>b</b>) peroxidase (POX), (<b>c</b>) polyphenoloxidase (PPO), and (<b>d</b>) phenylalanine ammonia-lyase (PAL). Values represent mean ± standard error (SE). Tukey’s HSD test at <span class="html-italic">p</span> &lt; 0.05 indicates that bars with different letters are statistically different.</p>
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17 pages, 12686 KiB  
Article
Online Public Feedback on Mid- to High-Rise Biophilic Buildings: A Study of the Asia–Pacific Region over the Past Decade
by Yue Liu and Xiangmin Guo
Buildings 2024, 14(8), 2394; https://doi.org/10.3390/buildings14082394 - 2 Aug 2024
Viewed by 981
Abstract
Over the past decade, biophilic architecture has been widely developed across the Asia–Pacific region. However, there is a notable lack of research based on online public reviews focusing on mid- to high-rise biophilic buildings, especially quantitative studies combining traditional architectural design features. This [...] Read more.
Over the past decade, biophilic architecture has been widely developed across the Asia–Pacific region. However, there is a notable lack of research based on online public reviews focusing on mid- to high-rise biophilic buildings, especially quantitative studies combining traditional architectural design features. This study aims to fill this gap by analyzing the typical floor plans and online public reviews of nine renowned biophilic buildings in the Asia–Pacific region. Using space syntax and natural language processing tools, the design features of typical floor plans and public feedback will be analyzed separately, and their correlation will be evaluated. Additionally, the content of negative and low-score reviews will be categorized to identify issues in current biophilic building designs. The findings suggest that biophilic design can stimulate widespread public discussion, with large direct blue–green elements receiving overwhelming attention. However, biophilic elements can also lead to negative sentiments due to factors like humidity, high temperatures, mold, and insects. This study provides insights and design recommendations for future biophilic buildings, demonstrating the value of biophilic design in public reviews and emphasizing the need to balance these factors to enhance public satisfaction and acceptance. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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<p>Flow chart of research process.</p>
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<p>Number of related sentences for sentiment analysis.</p>
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<p>Sentiment analysis results.</p>
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<p>Clustering analysis results of architecture- and design-related texts.</p>
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<p>Pearson correlation matrix.</p>
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11 pages, 232 KiB  
Article
Ozone Treatment as a Sustainable Alternative for Suppressing Blue Mold in Mandarins and Extending Shelf Life
by Darija Lemic, Marija Andrijana Galešić, Mario Bjeliš and Helena Viric Gasparic
Agriculture 2024, 14(7), 1196; https://doi.org/10.3390/agriculture14071196 - 20 Jul 2024
Viewed by 1576
Abstract
Citrus fruits, particularly mandarins, are highly valued globally for their nutritional benefits and versatile culinary uses. However, the challenge of post-harvest decay, primarily due to blue mold (Penicillium italicum) infections, results in significant food losses and necessitates effective preservation strategies. Traditional [...] Read more.
Citrus fruits, particularly mandarins, are highly valued globally for their nutritional benefits and versatile culinary uses. However, the challenge of post-harvest decay, primarily due to blue mold (Penicillium italicum) infections, results in significant food losses and necessitates effective preservation strategies. Traditional methods often rely on fungicides, raising concerns about chemical residues and environmental impact. This study investigates the efficacy of ozone as an alternative approach to controlling blue mold in mandarins. Various gaseous ozone treatments were tested, including single, double, and triple treatments, with durations ranging from 10 to 60 min and concentrations from 3.3 to 20 ppm. Additionally, ozonated water treatments were evaluated with concentrations of 2, 4, and 6 ppm. To simulate a realistic infestation scenario, mandarins were artificially infected with P. italicum spores before undergoing both gaseous ozone and ozonated water treatments. The storage conditions for the mandarins were meticulously controlled, maintaining a humidity level of 50–60% and a temperature range of 10–12 °C. Each fruit was analyzed, and the presence of P. italicum infection was determined two and three weeks after the ozonation. Results indicated that ozone treatments significantly reduced mold growth, with gaseous ozone demonstrating efficacy rates up to 97.5% and ozonated water treatments achieving preservation rates between 95% and 97%. These results underscore ozone’s potential as a safe, efficient, and sustainable alternative to conventional fungicides, offering promising solutions for extending the shelf life of mandarins. Further research is recommended to optimize ozone treatment parameters, assess long-term effects on fruit quality and nutritional content, and refine application techniques to harness ozone’s potential in citrus fruit preservation fully. This approach not only addresses food security challenges but also aligns with global efforts to reduce chemical inputs in agriculture and promote environmentally sustainable practices. Full article
(This article belongs to the Section Agricultural Product Quality and Safety)
16 pages, 8893 KiB  
Article
SntB Affects Growth to Regulate Infecting Potential in Penicillium italicum
by Chunyan Li, Shuzhen Yang, Meihong Zhang, Yanting Yang, Zhengzheng Li and Litao Peng
J. Fungi 2024, 10(6), 368; https://doi.org/10.3390/jof10060368 - 21 May 2024
Viewed by 1499
Abstract
Penicillium italicum, a major postharvest pathogen, causes blue mold rot in citrus fruits through the deployment of various virulence factors. Recent studies highlight the role of the epigenetic reader, SntB, in modulating the pathogenicity of phytopathogenic fungi. Our research revealed that [...] Read more.
Penicillium italicum, a major postharvest pathogen, causes blue mold rot in citrus fruits through the deployment of various virulence factors. Recent studies highlight the role of the epigenetic reader, SntB, in modulating the pathogenicity of phytopathogenic fungi. Our research revealed that the deletion of the SntB gene in P. italicum led to significant phenotypic alterations, including delayed mycelial growth, reduced spore production, and decreased utilization of sucrose. Additionally, the mutant strain exhibited increased sensitivity to pH fluctuations and elevated iron and calcium ion stress, culminating in reduced virulence on Gannan Novel oranges. Ultrastructural analyses disclosed notable disruptions in cell membrane integrity, disorganization within the cellular matrix, and signs of autophagy. Transcriptomic data further indicated a pronounced upregulation of hydrolytic enzymes, oxidoreductases, and transport proteins, suggesting a heightened energy demand. The observed phenomena were consistent with a carbon starvation response potentially triggering apoptotic pathways, including iron-dependent cell death. These findings collectively underscored the pivotal role of SntB in maintaining the pathogenic traits of P. italicum, proposing that targeting PiSntB could offer a new avenue for controlling citrus fungal infections and subsequent fruit decay. Full article
(This article belongs to the Special Issue Control of Postharvest Fungal Diseases)
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<p>Effects of the <span class="html-italic">SntB</span> gene deficiency on the growth and pathogenicity of <span class="html-italic">P. italicum</span>. (<b>A</b>,<b>B</b>) Colony morphology and colony radial growth under solid culture conditions. (<b>C</b>) Spore production and spore germination rate. (<b>D</b>) Incidence of <span class="html-italic">P. italicum</span> of navel oranges at 5d. (<b>E</b>) Mean diameters of disease lesions at inoculation sites developed with time. Different letters (a, b, c, d or e) above the columns indicate significant differences between the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Radial growth of <span class="html-italic">P. italicum</span> stains under stress environment. (<b>A</b>) Mycelial mass at different pH (2, 4, 6, 8, and 10) conditions, where group 0 is normal PSB medium. (<b>B</b>) Colony diameter of two strains at low, medium, and high sucrose concentrations, where the CK group is normal PSA medium. (<b>C</b>,<b>D</b>) Colony diameter and colony state in media containing metal ion and cell wall disrupters. Different letters (a, b, c, d, e or f) above the columns indicate significant differences between the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Ultrastructure of <span class="html-italic">P. italicum</span> hyphae observed by transmission electron microscopy (TEM). (<b>A</b>,<b>B</b>) <span class="html-italic">PiKu70</span>, (<b>C</b>,<b>D</b>) of <span class="html-italic">ΔPiSntB</span>. Green arrow: degradation of the nuclear membrane and release of nucleoplasm; red arrow: thickening of the cell wall; blue arrow: increase in autophagic vesicles; yellow arrow: mitochondrial expansion; orange arrow: cell membrane invaginations, as if the cell wall skeleton collapsed.</p>
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<p>Analysis of differentially expressed genes (DEGs) in <span class="html-italic">ΔPiSntB. (</span><b>A</b>) Cluster heat map of DEGs in <span class="html-italic">ΔPiSntB</span> and <span class="html-italic">PiKu70</span>. (<b>B</b>): Gene Ontology enrichment analysis of differentially expressed genes in <span class="html-italic">P. italicum</span>. (<b>C</b>) KEGG enrichment analysis of differentially expressed genes in <span class="html-italic">P. italicum</span>.</p>
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<p>Analysis of differentially expressed genes (DEGs) in <span class="html-italic">ΔPiSntB. (</span><b>A</b>) Cluster heat map of DEGs in <span class="html-italic">ΔPiSntB</span> and <span class="html-italic">PiKu70</span>. (<b>B</b>): Gene Ontology enrichment analysis of differentially expressed genes in <span class="html-italic">P. italicum</span>. (<b>C</b>) KEGG enrichment analysis of differentially expressed genes in <span class="html-italic">P. italicum</span>.</p>
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<p>RT-qPCR verification of DEGs in RNA-Seq.</p>
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25 pages, 10099 KiB  
Article
Antifungal Activities of Biogenic Silver Nanoparticles Mediated by Marine Algae: In Vitro and In Vivo Insights of Coating Tomato Fruit to Protect against Penicillium italicum Blue Mold
by Ragaa A. Hamouda, Fatimah Q. Almaghrabi, Ohoud M. Alharbi, Abla D. M. Al-Harbi, Rahaf M. Alsulami and Abrar M. Alhumairi
Mar. Drugs 2024, 22(5), 225; https://doi.org/10.3390/md22050225 - 16 May 2024
Cited by 3 | Viewed by 2050
Abstract
In an attempt to reduce such decay induced by pathogenic causes, several studies investigated the effectiveness of nanoparticles (NPs) that play a vital role in saving food products, especially fruits. Current research delves into biogenic silver nanoparticles (using marine alga Turbinaria turbinata (Tt/Ag-NPs) [...] Read more.
In an attempt to reduce such decay induced by pathogenic causes, several studies investigated the effectiveness of nanoparticles (NPs) that play a vital role in saving food products, especially fruits. Current research delves into biogenic silver nanoparticles (using marine alga Turbinaria turbinata (Tt/Ag-NPs) and their characterization using FT-IR, TEM, EDS, and zeta potential. Some pathogenic fungi, which cause fruit spoilage, were isolated. We studied the impact of using Tt/Ag-NPs to protect against isolated fungi in vitro, and the influence of Tt/Ag-NPs as a coating of tomato fruit to protect against blue mold caused by Penicillium italicum (OR770486) over 17 days of storage time. Five treatments were examined: T1, healthy fruits were used as the positive control; T2, healthy fruits sprayed with Tt/Ag-NPs; T3, fruits infected with P. italicum followed by coating with Tt/Ag-NPs (pre-coating); T4, fruits coated with Tt/Ag-NPs followed by infection by P. italicum (post-coating); and T5, the negative control, fruits infected by P. italicum. The results displayed that Tt/Ag-NPs are crystalline, spherical in shape, with size ranges between 14.5 and 39.85 nm, and negative charges. Different concentrations of Tt/Ag-NPs possessed antifungal activities against Botrytis cinerea, Rhodotorula mucilaginosa, Penicillium expansum, Alternaria alternate, and Stemphylium vesicarium. After two days of tomatoes being infected with P. italicum, 55% of the fruits were spoilage. The tomato fruit coated with Tt/Ag-NPs delayed weight loss, increased titratable acidity (TA%), antioxidant%, and polyphenol contents, and decreased pH and total soluble solids (TSSs). There were no significant results between pre-coating and post-coating except in phenol contents increased in pre-coating. A particular focus is placed on the novel and promising approach of utilizing nanoparticles to combat foodborne pathogens and preserve commodities, with a spotlight on the application of nanoparticles in safeguarding tomatoes from decay. Full article
(This article belongs to the Special Issue Nanoparticle Synthesis with Marine Substances, 2nd Edition)
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<p>FT-IR analysis of active compounds derived from marine alga <span class="html-italic">Turbinaria turbinata</span>.</p>
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<p>FT-IR analysis of Tt/Ag-NPs derived from marine alga <span class="html-italic">Turbinaria turbinata</span>.</p>
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<p>XRD patterns of Tt-AgNPS derived from marine alga <span class="html-italic">T. turbinata</span>; the intense peak at 32.321° represents preferential growth in the (110) direction.</p>
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<p>Energy-dispersive X-ray (EDX) of Tt-AgNPS derived from marine alga <span class="html-italic">T. turbinata</span>.</p>
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<p>Zeta potential of Tt-AgNPS derived from marine alga <span class="html-italic">Turbinaria turbinata</span>.</p>
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<p>(<b>a</b>) TEM image of Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>. (<b>b</b>) Particle size distribution of Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>.</p>
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<p>Phylogenetic tree structure built on the Clustral W alignment of ITS sequences of the isolated fungi <span class="html-italic">Penicillium italicum</span> RH12 OR770486, with homologue sequences attained from the NCBI GenBank. Orange circle: fungal strain.</p>
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<p>Images of antifungal activates of Tt/Ag-NPs derived from marine alga <span class="html-italic">T. turbinata</span>.</p>
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<p>Change in (<b>a</b>) chilling injury index, and (<b>b</b>) chilling injury incidence %, of postharvest tomato coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span> during storage periods at ambient temperatures. (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; and post-coating: spraying with Tt-AgNPs, followed by infection).</p>
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<p>Change in (<b>a</b>) weight loss (%), (<b>b</b>) pH, and (<b>c</b>) TA (%) of postharvest tomato, coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>, during storage periods at ambient temperatures. Values with the same letter are not significantly different (<span class="html-italic">p</span> &lt; 0.05). (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; and post-coating: spraying with Tt-AgNPs, followed by infection). Bars represent error bars.</p>
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<p>Change in (<b>a</b>) lycopene (mg/Kg), (<b>b</b>) carotenoids (mg/Kg), and (<b>c</b>) antioxidant % of postharvest tomato, coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>, during storage time at ambient temperatures. Values with the same letter are not significantly different (<span class="html-italic">p</span> &lt; 0.05). (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; and post-coating: sprayed with Tt-AgNPs, followed by infection). Bars represent error bars.</p>
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<p>Change in (<b>a</b>) lycopene (mg/Kg), (<b>b</b>) carotenoids (mg/Kg), and (<b>c</b>) antioxidant % of postharvest tomato, coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>, during storage time at ambient temperatures. Values with the same letter are not significantly different (<span class="html-italic">p</span> &lt; 0.05). (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; and post-coating: sprayed with Tt-AgNPs, followed by infection). Bars represent error bars.</p>
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<p>Change in (<b>a</b>) phenolic contents (mg/g) and (<b>b</b>) TSS% of postharvest tomato, coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>, during storage time at ambient temperatures. Values with the same letter are not significantly different (<span class="html-italic">p</span> &lt; 0.05). (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; post-coating: sprayed with Tt-AgNPs, followed by infection). Bars represent error bars.</p>
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<p>Change in (<b>a</b>) phenolic contents (mg/g) and (<b>b</b>) TSS% of postharvest tomato, coated with Tt-AgNPs derived from marine alga <span class="html-italic">T. turbinata</span>, during storage time at ambient temperatures. Values with the same letter are not significantly different (<span class="html-italic">p</span> &lt; 0.05). (Coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; post-coating: sprayed with Tt-AgNPs, followed by infection). Bars represent error bars.</p>
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<p>(<b>a</b>) Pearson’s correlation coefficient heat map for measured parameters of postharvest tomato during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>b</b>) Pearson’s correlation coefficient heat map for measured parameters of postharvest tomatoes coated with Tt-AgNPs during storage times (positive correlations are displayed green and negative correlations are displayed in white); (<b>c</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato pre-coated with Tt-AgNPs during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>d</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato post-coated with Tt-AgNPs during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>e</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato during storage times (positive correlations are displayed in green and negative correlations are displayed in white (upper direction arrows are positive correlation, lower direction negative correlation).</p>
Full article ">Figure 13 Cont.
<p>(<b>a</b>) Pearson’s correlation coefficient heat map for measured parameters of postharvest tomato during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>b</b>) Pearson’s correlation coefficient heat map for measured parameters of postharvest tomatoes coated with Tt-AgNPs during storage times (positive correlations are displayed green and negative correlations are displayed in white); (<b>c</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato pre-coated with Tt-AgNPs during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>d</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato post-coated with Tt-AgNPs during storage times (positive correlations are displayed in green and negative correlations are displayed in white); (<b>e</b>) Pearson’s correlation coefficient heat map for measured parameters of infected postharvest tomato during storage times (positive correlations are displayed in green and negative correlations are displayed in white (upper direction arrows are positive correlation, lower direction negative correlation).</p>
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<p>Visual appearance of treated tomato during storage periods at ambient temperatures (coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; post-coating: sprayed with Tt-AgNPs, followed by infection).</p>
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<p>Visual appearance of treated tomato during storage periods at ambient temperatures (coating: sprayed with nanoparticles; pre-coating: infected, followed by spraying with Tt-AgNPs; post-coating: sprayed with Tt-AgNPs, followed by infection).</p>
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14 pages, 2465 KiB  
Article
Ozone Application Suppressed the Blue Mold Development and Maintained the Main Active Ingredients Content of Postharvest Fresh Codonopsis pilosula during Storage
by Jiangyang Chen, Zhiguang Liu, Qili Liu, Dan Zhang, Huali Xue, Suqin Shang and Yang Bi
J. Fungi 2024, 10(3), 163; https://doi.org/10.3390/jof10030163 - 20 Feb 2024
Cited by 1 | Viewed by 1478
Abstract
Penicillium expansum is the predominant causal agent causing blue mold in postharvest fresh Codonopsis pilosula during storage. The pathogen reduces the yield and affects the quality of C. pilosula and even generates patulin, threatening human health. In this study, postharvest fresh, healthy C. [...] Read more.
Penicillium expansum is the predominant causal agent causing blue mold in postharvest fresh Codonopsis pilosula during storage. The pathogen reduces the yield and affects the quality of C. pilosula and even generates patulin, threatening human health. In this study, postharvest fresh, healthy C. pilosula was sprayed with P. expansum, and the control effect of ozone on postharvest diseases of C. pilosula was studied, and the effect of ozone on the contents in the main active ingredients of C. pilosula was compared; finally, the effect of ozone on reactive oxygen species (ROS) metabolism in C. pilosula was analyzed. The results showed that 2 mg L−1 ozone application significantly inhibited the occurrence of postharvest blue mold caused by P. expansum, reduced weight loss rate, controlled the accumulation of patulin and maintained the contents of the main active components in C. pilosula. The study will provide a theoretical basis for ozone treatment to control the occurrence of postharvest diseases of C. pilosula. Full article
(This article belongs to the Special Issue Biological Control of Fungal Diseases)
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<p>Effects of ozone treatment on the disease incidence and disease index of the blue mold of <span class="html-italic">C. pilosula</span> during different storage periods. (<b>A</b>): Pictures of disease symptoms of <span class="html-italic">C. pilosula</span> samples during different storage periods; (<b>B</b>): Disease incidence; (<b>C</b>): Disease index. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of ozone treatment on weight loss rate of <span class="html-italic">C. pilosula</span> inoculated with <span class="html-italic">P. expansum</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of ozone treatment on patulin accumulation in <span class="html-italic">C. pilosulain</span> inoculated with <span class="html-italic">P. expansum</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of ozone treatment on the content of the main active ingredients of the blue mold of <span class="html-italic">C. pilosula</span>. (<b>A</b>) Thermography; (<b>B</b>) Analysis of relationship.</p>
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<p>Effect of ozone treatment on the content of four main active ingredients of the blue mold of <span class="html-italic">C. pilosula</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). (<b>A</b>) lobetyolin; (<b>B</b>) lobetyolin I; (<b>C</b>) syringin; (<b>D</b>) atractylenolide III.</p>
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<p>PCA score scatter plot of <span class="html-italic">C. pilosula</span> samples. (<b>A</b>). Load chart. (<b>B</b>). Score chart.</p>
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<p>Effects of ozone treatment on O<sub>2</sub><sup>−.</sup> production content (<b>A</b>) and H<sub>2</sub>O<sub>2</sub> content (<b>B</b>) in <span class="html-italic">C. pilosula</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of ozone treatment on the activities of NOX (<b>A</b>), SOD (<b>B</b>), CAT (<b>C</b>) and POD (<b>D</b>) in <span class="html-italic">C. pilosula</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of ozone treatment on cell membrane permeability (<b>A</b>) and MDA content (<b>B</b>) in <span class="html-italic">C. pilosula</span>. Bars indicate standard error. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Schematic diagram of active ingredient transformation of <span class="html-italic">C. pilosula</span>.</p>
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20 pages, 3985 KiB  
Article
Unlocking Nature’s Secrets: Molecular Insights into Postharvest Pathogens Impacting Moroccan Apples and Innovations in the Assessment of Storage Conditions
by Mohammed Khadiri, Hassan Boubaker, Salah-Eddine Laasli, Abdelaaziz Farhaoui, Said Ezrari, Nabil Radouane, Mohammed Radi, Latifa Askarne, Essaid Ait Barka and Rachid Lahlali
Plants 2024, 13(4), 553; https://doi.org/10.3390/plants13040553 - 18 Feb 2024
Cited by 3 | Viewed by 1915
Abstract
Apple production holds a prominent position in Morocco’s Rosaceae family. However, annual production can fluctuate due to substantial losses caused by fungal diseases affecting stored apples. Our findings emphasize that the pre-storage treatment of apples, disinfection of storage facilities, box type, and fruit [...] Read more.
Apple production holds a prominent position in Morocco’s Rosaceae family. However, annual production can fluctuate due to substantial losses caused by fungal diseases affecting stored apples. Our findings emphasize that the pre-storage treatment of apples, disinfection of storage facilities, box type, and fruit sorting are pivotal factors affecting apple losses during storage. Additionally, the adopted preservation technique was significantly correlated with the percentage of damage caused by fungal infections. Blue mold accounts for nearly three-quarters of the diseases detected, followed by gray rot with a relatively significant incidence. This study has revealed several fungal diseases affecting stored apples caused by pathogens such as Penicillium expansum, Botrytis cinerea, Alternaria alternata, Trichothecium roseum, Fusarium avenaceum, Cadophora malorum, and Neofabraea vagabunda. Notably, these last two fungal species have been reported for the first time in Morocco as pathogens of stored apples. These data affirm that the high losses of apples in Morocco, attributed primarily to P. expansum and B. cinerea, pose a significant threat in terms of reduced production and diminished fruit quality. Hence, adopting controlled atmosphere storage chambers and implementing good practices before apple storage is crucial. Full article
(This article belongs to the Special Issue Pathogenesis and Disease Control in Crops—2nd Edition)
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<p>Multiple Component Analysis (MCA) highlighting the relationship between apple storage conditions and the observed damage (low = 110%; moderate =10−20%; high = 20−30%; very high = 30−40%). The arrow direction indicates the correlation between each variable and the correspondence axes (F1 and F2). The arrow length shows the relative contribution of the variables to the axes and storage conditions. The numbers above circles represent the attributes of each variable studied in Table 3. Abbreviations: PHT, postharvest treatment; CCD, cold chamber disinfection; BD, box disinfection; BT, box type; FSBS, fruit sorting before storage; ST, storage temperature; SD, storage duration.</p>
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<p>Redundancy analysis (RDA) showing the distribution trend of Moroccan apple conservation stations in terms of observed damage. The codes represent the stations studied. Red−colored stations represent severely damaged entities (high to very high damage = 20−40%). Green-colored stations represent entities with less damage (low to moderate damage = 1−20%). The circled entities represent the controlled atmosphere conservation stations.</p>
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<p>Morphological characteristics of the main diseases affecting apples during storage. (<b>A</b>,<b>D</b>,<b>G</b>,<b>J</b>,<b>M</b>,<b>P</b>,<b>S</b>): appearance of apple (Golden Delicious) rot after inoculation with spore solution (10<sup>4</sup> spores/mL) and incubation for 14 days at 25 °C. (<b>B</b>,<b>E</b>,<b>H</b>,<b>K</b>,<b>N</b>,<b>Q</b>,<b>T</b>): pathogen colonies on Potato Dextrose Agar (PDA) medium after incubation for 7 to 14 days at 25 °C. (<b>C</b>,<b>F</b>,<b>I</b>,<b>L</b>,<b>O</b>,<b>R</b>,<b>U</b>): microscopic observation (×40) of conidia and mycelium of pathogens. A, B, and C: blue mold caused by <span class="html-italic">Penicillium expansum.</span> (<b>D</b>,<b>E</b>,<b>F</b>): gray mold caused by <span class="html-italic">Botrytis cinerea</span>. (<b>G</b>,<b>H</b>,<b>I</b>): Alternaria rot caused by <span class="html-italic">Alternaria alternata.</span> (<b>J</b>,<b>K</b>,<b>L</b>): bitter rot caused by <span class="html-italic">Trichothecium roseum.</span> (<b>M</b>,<b>N</b>,<b>O</b>): Fusarium rot caused by <span class="html-italic">Fusarium avenaceum</span>. (<b>P</b>,<b>Q</b>,<b>R</b>): side rot caused by <span class="html-italic">Cadophora malorum.</span> (<b>S</b>,<b>T</b>,<b>U</b>): gloeosporiosis caused by <span class="html-italic">Neofabraea vagabunda</span>. Scale bar = 10 μm.</p>
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<p>Phylogenetic tree generated in MEGA11 software (version 11.0.8 build 210914) using a Kimura two-parameter model based on maximum likelihood analysis of nucleotide sequences of the ITS gene of the main pathogens affecting apple on storage.</p>
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<p>Diameter of apple (cv. Golden Delicious) rots inoculated with spore solution (1 × 10<sup>4</sup> spores/mL) and sterile distilled water (control) after incubation for 14 days at 25 °C. Diameters with the same letter are not significantly different according to Duncan test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Map of Morocco showing the location of apple conservation stations where sampling was performed in the two regions of Fez−Meknes and Draa−Tafilalet, prepared using ArcGIS 10.3.1 software.</p>
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28 pages, 5258 KiB  
Article
The Influence of Long-Term Storage on the Epiphytic Microbiome of Postharvest Apples and on Penicillium expansum Occurrence and Patulin Accumulation
by Reem Al Riachy, Caroline Strub, Noël Durand, Vincent Chochois, Félicie Lopez-Lauri, Angélique Fontana and Sabine Schorr-Galindo
Toxins 2024, 16(2), 102; https://doi.org/10.3390/toxins16020102 - 12 Feb 2024
Cited by 1 | Viewed by 2148
Abstract
Patulin is a secondary metabolite primarily synthesized by the fungus Penicillium expansum, which is responsible for blue mold disease on apples. The latter are highly susceptible to fungal infection in the postharvest stages. Apples destined to produce compotes are processed throughout the [...] Read more.
Patulin is a secondary metabolite primarily synthesized by the fungus Penicillium expansum, which is responsible for blue mold disease on apples. The latter are highly susceptible to fungal infection in the postharvest stages. Apples destined to produce compotes are processed throughout the year, which implies that long periods of storage are required under controlled atmospheres. P. expansum is capable of infecting apples throughout the whole process, and patulin can be detected in the end-product. In the present study, 455 apples (organically and conventionally grown), destined to produce compotes, of the variety “Golden Delicious” were sampled at multiple postharvest steps. The apple samples were analyzed for their patulin content and P. expansum was quantified using real-time PCR. The patulin results showed no significant differences between the two cultivation techniques; however, two critical control points were identified: the long-term storage and the deck storage of apples at ambient temperature before transport. Additionally, alterations in the epiphytic microbiota of both fungi and bacteria throughout various steps were investigated through the application of a metabarcoding approach. The alpha and beta diversity analysis highlighted the effect of long-term storage, causing an increase in the bacterial and fungal diversity on apples, and showed significant differences in the microbial communities during the different postharvest steps. The different network analyses demonstrated intra-species relationships. Multiple pairs of fungal and bacterial competitive relationships were observed. Positive interactions were also observed between P. expansum and multiple fungal and bacterial species. These network analyses provide a basis for further fungal and bacterial interaction analyses for fruit disease biocontrol. Full article
(This article belongs to the Special Issue Toxins: 15th Anniversary)
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<p>Boxplot representing the <span class="html-italic">P. expansum</span> DNA quantities (copies/g of apple) on the surfaces of 450 apples collected at various postharvest stages. The abundance of <span class="html-italic">P. expansum</span> within each stage was assessed through qPCR in three replicates. (<b>A</b>) DNA amounts of <span class="html-italic">P. expansum</span> on the surfaces of conventional apples. The levels were consistent between the three first steps and were more important in the last two steps. (<b>B</b>) DNA amounts of <span class="html-italic">P. expansum</span> in organic apples. Two steps significantly increased the quantity of <span class="html-italic">P. expansum</span> DNA on the surfaces of organically grown apples: the period of cold storage under CA for 6 months and the transfer of apples from 4 °C to an ambient temperature of 25 ± 5 °C (Tukey HSD test, <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Boxplots depicting variance in Shannon diversity measures of (<b>A</b>) fungal and (<b>B</b>) bacterial communities on the surfaces of organically and conventionally cultivated apples across various postharvest stages. The distinct letters indicate significant differences among the groups in the analysis after conducting a Tukey’s HSD test.</p>
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<p>Principal coordinate analysis (PCoA) of fungal populations linked to the surfaces of (<b>A</b>) conventionally cultivated apples and (<b>B</b>) organically cultivated apples gathered at the five postharvest stages using the Bray–Curtis beta diversity metric.</p>
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<p>Relative abundance of the top 12 fungal species identified per sample on the surfaces of (<b>A</b>) conventionally harvested apples and (<b>B</b>) organically harvested apples at various postharvest sampling stages. In instances where taxonomic identification could not be performed to the species level, the ASV was identified at the lowest possible level on the phylogenetic tree.</p>
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<p>Principal coordinate analysis (PCoA) of bacterial populations linked to the surfaces of (<b>A</b>) conventionally cultivated apples and (<b>B</b>) organically cultivated apples collected at the five postharvest stages using the Bray–Curtis beta diversity metric.</p>
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<p>Relative abundance of the top 10 bacterial species identified per sampling step on the surfaces of conventionally harvested apples and organically harvested apples at various postharvest sampling stages. Bacterial species constituting less than 0.5% are categorized as “others”. In cases where taxonomic identification could not be established at the species level, the ASV was identified at the lowest possible level on the phylogenetic tree.</p>
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<p>Relative abundance of the top 10 fungal and bacterial species found on the exteriors of conventional and organic apples when patulin was identified and when it was not detected in the samples by HPLC. Bacterial species constituting less than 0.5% are categorized as “others”. In instances where taxonomic identification could not be achieved at the species level, the ASV was identified at the lowest possible level on the phylogenetic tree.</p>
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<p>Co-occurrence network diagram, generated through SPIEC-EASI, depicting fungal and bacterial species present in a minimum of 5 samples and illustrating cooperative associations (positive interactions). Each node represents a microbe within the microbiome, and each gray link signifies pairwise co-occurrence. The thickness of the line indicates the degree of interaction between two species, with thicker lines denoting stronger interactions. In cases where taxonomic identification could not be achieved at the species level, the ASV was identified at the lowest possible level on the phylogenetic tree.</p>
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<p>Co-occurrence network diagram (based on SPIEC-EASI) of the fungal and bacterial species present in at least 5 samples showing competitive associations (negative interactions). Each node represents a microbe from the microbiome and each gray link represents pairwise co-occurrence. When the taxonomic identification was not possible to the species level, the ASV was identified by the lowest possible level of the phylogenetic tree.</p>
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<p>(<b>A</b>) Flow diagram of the different sampling steps, with the duration between two steps and the storage conditions of apples at each step. (<b>B</b>) Illustrations of the storage bins: conventional and organic apple bins. Three levels of sampling were determined per bin (L1, L2 and L3). Each “x” mark represents a sample composed of fives apples picked randomly at each level. After harvest, three bins per cultivation system were selected and followed up throughout the whole production chain. The number of sampled apples at each step, per cultivation system, was <span class="html-italic">n</span> = 45 apples. The sketches are given for illustration purposes and do not reflect the exact location of the sample.</p>
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<p>Overview of the analysis carried out on one sample (composed of 5 apples). The apples are washed with a solution of 0.15 M NaCl + 0.1% Tween 20 (<span class="html-italic">v</span>/<span class="html-italic">v</span>) in sterile conditions. The apples are then removed, ground and analyzed for their patulin content. The washing solution is centrifuged and the pellet is used for DNA extraction, followed by the quantification of <span class="html-italic">P. expansum</span> by q-PCR and the amplification and sequencing of the 16S and ITS regions of the epiphytic DNA of apples.</p>
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