IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12908-d937755.html
   My bibliography  Save this article

Antifungal and Antiaflatoxigenic Activities of Different Plant Extracts against Aspergillus flavus

Author

Listed:
  • Said I. Behiry

    (Agricultural Botany Department, Faculty of Agriculture (Saba Basha), Alexandria University, Alexandria 21531, Egypt)

  • Najwa A. Hamad

    (Plant Protection Department, Faculty of Agriculture, Omar Al-Mukhtar University, Al Bayda 00218-84, Libya)

  • Fatimah O. Alotibi

    (Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Abdulaziz A. Al-Askar

    (Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Amr A. Arishi

    (School of Molecular Sciences, The University of Western Australia, Perth 6009, Australia)

  • Ahmed M. Kenawy

    (Genetic Engineering and Biotechnology Research Institute, City of Scientific Research and Technological Applications, New Borg El Arab City 21934, Egypt)

  • Ibrahim A. Elsamra

    (Agricultural Botany Department, Faculty of Agriculture (Saba Basha), Alexandria University, Alexandria 21531, Egypt)

  • Nesrine H. Youssef

    (Microbiology and Mycotoxins Labs, Regional Center for Foods and Feeds, Agricultural Researches Center, Alexandria 12619, Egypt)

  • Mohsen Mohamed Elsharkawy

    (Department of Agricultural Botany, Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt)

  • Ahmed Abdelkhalek

    (Plant Protection and Biomolecular Diagnosis Department, ALCRI, City of Scientific Research and Technological Applications, New Borg El Arab City 21934, Egypt)

  • Ahmed A. Heflish

    (Agricultural Botany Department, Faculty of Agriculture (Saba Basha), Alexandria University, Alexandria 21531, Egypt)

Abstract

In the current study, four organic solvents, including ethanol, methanol, acetone, and diethyl ether, were used to extract turmeric, wheat bran, and taro peel. The efficiency of three different concentrations of each solvent was assessed for their antifungal and anti-mycotoxin production against Aspergillus flavus . The results indicated that 75% ethanolic and 25% methanolic extracts of taro peels and turmeric were active against fungus growth, which showed the smallest fungal dry weight ratios of 1.61 and 2.82, respectively. Furthermore, the 25% ethanolic extract of turmeric showed the best result (90.78%) in inhibiting aflatoxin B 1 production. After 30 days of grain storage, aflatoxin B 1 (AFB 1 ) production was effectively inhibited, and the average inhibition ratio ranged between 4.46% and 69.01%. Simultaneously, the Topsin fungicide resulted in an inhibition ratio of 143.92%. Taro extract (25% acetone) produced the highest total phenolic content (61.28 mg GAE/g dry extract wt.) and showed an antioxidant capacity of 7.45 μg/mL, followed by turmeric 25% ethanol (49.82 mg GAE/g), which revealed the highest antioxidant capacity (74.16 μg/mL). RT-qPCR analysis indicated that the expression of afl D, afl P, and afl Q (structural genes) and afl R and afl S (regulatory genes) was down-regulated significantly compared to both untreated and Topsin-treated maize grains. Finally, the results showed that all three plant extracts could be used as promising source materials for potential products to control aflatoxin formation, thus creating a safer method for grain storage in the environment than the currently used protective method.

Suggested Citation

  • Said I. Behiry & Najwa A. Hamad & Fatimah O. Alotibi & Abdulaziz A. Al-Askar & Amr A. Arishi & Ahmed M. Kenawy & Ibrahim A. Elsamra & Nesrine H. Youssef & Mohsen Mohamed Elsharkawy & Ahmed Abdelkhalek, 2022. "Antifungal and Antiaflatoxigenic Activities of Different Plant Extracts against Aspergillus flavus," Sustainability, MDPI, vol. 14(19), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12908-:d:937755
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12908/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/19/12908/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wafaa M. AbdEl-Rahim & Wagdy K. B. Khalil & Mariam G. Eshak, 2010. "Evaluation of the gene expression changes in Nile tilapia (Oreochromis niloticus) as affected by the bio-removal of toxic textile dyes from aqueous solution in small-scale bioreactor," Environment Systems and Decisions, Springer, vol. 30(3), pages 242-253, September.
    2. Prasad Naik & Michel Wedel & Lynd Bacon & Anand Bodapati & Eric Bradlow & Wagner Kamakura & Jeffrey Kreulen & Peter Lenk & David Madigan & Alan Montgomery, 2008. "Challenges and opportunities in high-dimensional choice data analyses," Marketing Letters, Springer, vol. 19(3), pages 201-213, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Girish Punj, 2013. "Do consumers who conduct online research also post online reviews? A model of the relationship between online research and review posting behavior," Marketing Letters, Springer, vol. 24(1), pages 97-108, March.
    2. Oliver J. Rutz & Garrett P. Sonnier, 2019. "VANISH regularization for generalized linear models," Quantitative Marketing and Economics (QME), Springer, vol. 17(4), pages 415-437, December.
    3. Bruno J.D. Jacobs & Bas Donkers & Dennis Fok, 2016. "Model-Based Purchase Predictions for Large Assortments," Marketing Science, INFORMS, vol. 35(3), pages 389-404, May.
    4. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
    5. Tsukasa Ishigaki & Nobuhiko Terui & Tadahiko Sato & Greg M. Allenby, 2014. "A Large-Scale Marketing Model using Variational Bayes Inference for Sparse Transaction Data," TMARG Discussion Papers 114, Graduate School of Economics and Management, Tohoku University.
    6. Hamsa Bastani & Mohsen Bayati, 2020. "Online Decision Making with High-Dimensional Covariates," Operations Research, INFORMS, vol. 68(1), pages 276-294, January.
    7. Patrick O. Perry, 2017. "Fast moment-based estimation for hierarchical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 267-291, January.
    8. Sam Ransbotham & Gerald C. Kane & Nicholas H. Lurie, 2012. "Network Characteristics and the Value of Collaborative User-Generated Content," Marketing Science, INFORMS, vol. 31(3), pages 387-405, May.
    9. Oliver J. Rutz & Michael Trusov & Randolph E. Bucklin, 2011. "Modeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?," Marketing Science, INFORMS, vol. 30(4), pages 646-665, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12908-:d:937755. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.