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通过自动化图像分析对真菌球进行分类和测量。

Classification and measurement of fungal pellets by automated image analysis.

机构信息

School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.

出版信息

Biotechnol Bioeng. 1992 Apr 15;39(9):945-52. doi: 10.1002/bit.260390909.

Abstract

An automated image analysis method for classifying and measuring pellets of filamentous fungi growing in submerged fermentations has been developed. The method discriminates between pelleted mycelial growth and loose aggregates of dispersed hyphae. Pellets are classified into smooth and hairy types. In both cases, the core of the pellet is identified and its shape and size characterized. For hairy pellets the annular region is also characterized. The method was tested on pellets of Aspergillus niger ATCC 11414 grown in a defined medium in shake flasks. This rapid method makes practical extensive studies on the morphology of pellets in submerged fermentations and the influence of fermentation conditions on that morphology.

摘要

已经开发出一种用于对在液体发酵中生长的丝状真菌颗粒进行分类和测量的自动化图像分析方法。该方法可区分颗粒状菌丝生长和分散菌丝的松散聚集。将颗粒分为光滑型和多毛型。在这两种情况下,都会识别颗粒的核心,并对其形状和大小进行特征描述。对于多毛颗粒,还会对环状区域进行特征描述。该方法在摇瓶中使用限定培养基培养的黑曲霉 ATCC 11414 颗粒上进行了测试。这种快速方法使得在液体发酵中的颗粒形态以及发酵条件对其形态的影响的广泛研究变得切实可行。

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