New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil

The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of soybeans in the United States. To assess the severity of nematode infestations in the field, SCN egg population densities are determined. Cysts (dead females) of the nematode must be extracted from soil samples and then ground to extract the eggs within. Sucrose centrifugation commonly is used to separate debris from suspensions of extracted nematode eggs. We present a method using OptiPrep as a density gradient medium with improved separation and recovery of extracted eggs compared to the sucrose centrifugation technique. Also, computerized methods were developed to automate the identification and counting of nematode eggs from the processed samples. In one approach, a high-resolution scanner was used to take static images of extracted eggs and debris on filter papers, and a deep learning network was trained to identify and count the eggs among the debris. In the second approach, a lensless imaging setup was developed using off-the-shelf components, and the processed egg samples were passed through a microfluidic flow chip made from double-sided adhesive tape. Holographic videos were recorded of the passing eggs and debris, and the videos were reconstructed and processed by custom software program to obtain egg counts. The performance of the software programs for egg counting was characterized with SCN-infested soil collected from two farms, and the results using these methods were compared with those obtained through manual counting.大豆胞囊线虫（soybean cyst nematode, SCN），学名Heterodera glycines，是美国大豆生产中危害最严重的病原线虫。为评估田间线虫侵染的严重程度，需测定SCN的卵种群密度。该线虫的胞囊（即死亡的雌成虫）需从土壤样本中提取，随后经研磨以释放其中的卵。蔗糖离心法通常用于从提取出的线虫卵悬浮液中分离杂质。本研究提出一种以OptiPrep作为密度梯度介质的方法，相较于蔗糖离心法，该方法可提升提取卵的分离效果与回收率。此外，本研究还开发了自动化方法，可对处理后的样本中的线虫卵进行自动识别与计数。第一种方法中，使用高分辨率扫描仪对滤纸上的提取卵与杂质拍摄静态图像，随后训练深度学习网络以在杂质背景中识别并计数卵粒。第二种方法中，利用市售组件搭建了无透镜成像装置，并将处理后的卵样本通过由双面胶带制成的微流控流道芯片。研究记录了流经样本的卵与杂质的全息视频，随后通过定制软件对视频进行重构与处理，以获取卵粒计数结果。本研究使用从两座农场采集的受SCN侵染的土壤，对两款卵计数软件的性能进行了表征，并将上述两种方法的计数结果与人工计数结果进行了对比。