Influence of inoculum preparation on the growth of Penicillium chrysogenum

• Published in: Journal of applied microbiology Vol. 95; no. 5; pp. 1034 - 1038
• Main Authors: Sautour, M., Dantigny, P., Guilhem, M.‐C., Bensoussan, M.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Science Ltd 01-01-2003; Blackwell Science; Oxford University Press
• Subjects: Biological and medical sciences; Culture Media; Food Microbiology; Fundamental and applied biological sciences. Psychology; growth rate; Growth, nutrition, metabolism, transports, enzymes. Molecular biology; Humans; inoculum preparation; lag time; Microbiology; mould; Mycology; Mycology - methods; Penicillium chrysogenum; Penicillium chrysogenum - classification; Penicillium chrysogenum - growth & development; Polysorbates; spores; Spores, Fungal - growth & development; Time Factors; Water; Fungi; Microorganism growth; Growth rate; Fungi Imperfecti; Thallophyta; Inoculum; Penicillium chrysogenum
• ISSN: 1364-5072; 1365-2672
• DOI: 10.1046/j.1365-2672.2003.02073.x

Aims: The influence of the spore preparation on subsequent fungal growth of Penicillium chrysogenum was assessed.
Methods and Results: The influence of four factors [the nature of the diluting solution (physiological water and physiological water added with Tween‐80), the age of the sporulating culture (4, 8 and 12 days), the strain (737, 738 and 740) and the inoculum size (102, 103, 104 and 105 spores ml−1] on two responses (i.e. the radial growth rate, μ, and the lag time, λ) was studied using an experimental screening methodology.
Conclusions: The main conclusion was the strong effect of the inoculum size on λ. In contrast, the diluting solution had no effect on both the experimental responses. In order to obtain the highest growth rates, it is recommended to use 4‐day‐old sporulating cultures with an inoculum size of 102 spores ml−1.
Significance and Impact of the Study: There is a need for standardizing spore preparation in predictive mycology. The screening methodology is a powerful tool to determine the influence of qualitative and quantitative factors on various biological responses and can be applied widely in microbiology.