PDF(Pubmed)
Abstract：
Phenotypic analysis has significant potential for aiding breeding efforts. However, there is a notable lack of studies utilizing phenotypic analysis in the field of edible fungi. Pleurotus geesteranus is a lucrative edible fungus with significant market demand and substantial industrial output, and early-stage phenotypic analysis of Pleurotus geesteranus is imperative during its breeding process. This study utilizes image recognition technology to investigate the phenotypic features of the mycelium of P. geesteranus. We aim to establish the relations between these phenotypic characteristics and mycelial quality. Four groups of mycelia, namely, the non-degraded and degraded mycelium and the 5th and 14th subcultures, are used as image sources. Two categories of phenotypic metrics, outline and texture, are quantitatively calculated and analyzed. In the outline features of the mycelium, five indexes, namely, mycelial perimeter, radius, area, growth rate, and change speed, are proposed to demonstrate mycelial growth. In the texture features of the mycelium, five indexes, namely, mycelial coverage, roundness, groove depth, density, and density change, are studied to analyze the phenotypic characteristics of the mycelium. Moreover, we also compared the cellulase and laccase activities of the mycelium and found that cellulase level was consistent with the phenotypic indices of the mycelium, which further verified the accuracy of digital image processing technology in analyzing the phenotypic characteristics of the mycelium. The results indicate that there are significant differences in these 10 phenotypic characteristic indices ( P < 0.001 ), elucidating a close relationship between phenotypic characteristics and mycelial quality. This conclusion facilitates rapid and accurate strain selection in the early breeding stage of P. geesteranus.
摘要：
表型分析具有帮助育种工作的巨大潜力。然而,在食用菌领域，缺乏利用表型分析的研究。杏鲍菇是一种利润丰厚的食用菌，具有巨大的市场需求和可观的工业产值，并且在其繁殖过程中，对杏鲍菇进行早期表型分析势在必行。本研究利用图像识别技术研究了毕赤酵母菌丝体的表型特征。我们旨在建立这些表型特征与菌丝体质量之间的关系。四组菌丝体，即,未降解和降解的菌丝体以及第5和第14次传代培养，用作图像源。两类表型指标，轮廓和纹理，进行了定量计算和分析。在菌丝体的轮廓特征中，五个指标，即,菌丝体周长，半径,area,增长率，改变速度，建议证明菌丝生长。在菌丝体的质地特征中，五个指标，即,菌丝体覆盖，圆度,凹槽深度,密度,和密度变化，进行菌丝体表型特征分析。此外，我们还比较了菌丝的纤维素酶和漆酶活性，发现纤维素酶水平与菌丝的表型指标一致，进一步验证了数字图像处理技术在菌丝体表型特征分析中的准确性。结果表明,这10个表型特征指标存在显著差异(P<0.001),阐明表型特征与菌丝质量之间的密切关系。该结论有助于在猪的早期育种阶段快速准确地选择菌株。
