储粮真菌自动检测仪的研究与开发

Research and Development of Automatic Detection Instrument for Stored Grain Fungi

真菌是危害储粮安全的主要因素之一,储粮真菌的早期快速检测是防控真菌滋生、保障粮食安全的有效手段。2018年粮食行业颁布实施LS/T 6132《粮油检验粮食真菌检测方法孢子计数法》行业标准,为便于标准的推广应用,研究开发储粮真菌自动检测仪。基于大量储粮真菌孢子图片,构建真菌孢子图库,并利用神经网络算法研发真菌孢子图像识别软件;通过显微成像系统的自动对焦算法优化,实现显微镜下真菌孢子图像自动对焦拍照,采用图像识别软件对储粮真菌孢子图像进行孢子自动识别计数,从而实现储粮真菌的自动检测,减少人工操作和图像识别的误差。

Fungus is one of the primary factors endangering the safety of grain storage.The rapid detection of fungi on stored grain in early stage is an effective measure to prevent and control the fungal multiplication and ensure food security.In 2018,an industry standard“LS/T 6132 Inspection of Grain and Oil-Storage fungal examination-Enumeration spores of fungi”was promulgated and implemented in the grain industry.In this study,we developed an automatic detector for the detection of fungi in grain storage to promote the application of this industry standard.During the development of the detector,we built a fungal spore image library based on a large number of stored grain fungal spore pictures,and developed a fungal spore image recognition software using neural network algorithm.By optimizing the auto focusing algorithm of the microscopic imaging system,the fungal spore image under the microscope can be automatically focused and photographed.And the image recognition software was used to recognize and count the spores of the stored grain fungal automatically.This detector can realize the automatic detection of fungi on stored grain and reduce the probability of mistaken in personnel operation and identification.