Detection Of Pine Wood Nematode Research Articles

Integrating Multi-Scale Remote-Sensing Data to Monitor Severe Forest Infestation in Response to Pine Wilt Disease

Pine wilt disease (PWD) is one of the most destructive forest diseases that has led to rapid wilting and mortality in susceptible host pine trees. Spatially explicit detection of pine wood nematode (PWN)-induced infestation is important for forest management, policy making, and practices. Previous studies have mapped forest disturbances in response to various forest diseases and/or insects over large areas using remote-sensing techniques, but these efforts were often constrained by the limited availability of ground truth information needed for the calibration and validation of moderate-resolution satellite algorithms in the process of linking plot-scale measurements to satellite data. In this study, we proposed a two-level up-sampling strategy by integrating unmanned aerial vehicle (UAV) surveys and high-resolution Radarsat-2 satellite imagery for expanding the number of training samples at the 30-m resampled Sentinel-1 resolution. Random forest algorithms were separately used in the prediction of the Radarsat-2 and Sentinel-1 infestation map induced by PWN. After data acquisition in Muping District during August and September 2021, we first verified the ability of a deep-learning-based object detection algorithm (i.e., YOLOv5 model) in the detection of infested trees from coregistered UAV-based RGB images (Average Precision (AP) of larger than 70% and R2 of 0.94). A random forest algorithm trained using the up-sampling UAV infestation map reference and corresponding Radarsat-2 pixel values was then used to produce the Radarsat-2 infestation map, resulting in an overall accuracy of 72.57%. Another random forest algorithm trained using the Radarsat-2 infestation pixels with moderate and high severity (i.e., an infestation severity of larger than 0.25, where the value was empirically set based on a trade-off between classification accuracy and infection detectability) and corresponding Sentinel-1 pixel values was subsequently used to predict the Sentinel-1 infestation map, resulting in an overall accuracy of 87.63%, where the validation data are Radarsat-2 references rather than UAV references. The Sentinel-1 map was also validated by independent UAV surveys, with an overall accuracy of 76.30% and a Kappa coefficient of 0.45. We found that the expanded training samples by the integration of UAV and Radarsat-2 strengthened the medium-resolution Sentinel-1-based prediction model of PWD. This study demonstrates that the proposed method enables effective PWN infestation mapping over multiple scales.

Sampling design for efficient detection of pine wood nematode, Bursaphelenchus xylophilus, in diseased trees using a DNA detection kit: variation across branch, trunk and tree

Summary Detection of pine wood nematode, Bursaphelenchus xylophilus, is fundamental for effective control of pine wilt disease. Recent molecular techniques, such as DNA detection, have enhanced detectability of the nematodes whereas appropriate field sampling has received less attention. In order to elucidate a sampling design that most efficiently detects B. xylophilus using a commercially-distributed DNA detection kit, we compared detection levels of B. xylophilus using wood chips taken from various positions on dead trees. Results showed that the DNA kit had a higher detection level than the conventional method, and that trunk samples had higher levels than branch samples. Statistical model revealed that among-tree variation influenced the detectability more strongly than within-tree variation. Our results suggest that, in practice, with limited resources for control, it is more efficient to take samples from many trees with a minimum number from each tree, rather than taking many samples from a small number of trees.

Mark-recapture of Monochamus galloprovincialis with semiochemical-baited traps: population density, attraction distance, flight behaviour and mass trapping efficiency

The pine sawyer Monochamus galloprovincialis is considered the most efficient vector in Europe of the pine wood nematode (PWN), the causal agent of the pine wilt disease. The detection of PWN in Europe generated great concern by the EU which, in response, implemented strong quarantine and phytosanitary measures. Among them, the improvement of monitoring and control of pine sawyer is imperative, for which better understanding of behavioural, ecological and operational factors affecting catchability is needed. In 2012–2013, we investigated with mark-recapture methods the population density, trap attraction distance, flight behaviour and mass trapping efficiency in M. galloprovincialis. Population density ranged from 96 to 474 adults ha−1. Trap attraction distance averaged 50 m. Lifetime adult dispersal was 107–122 m on average. A logarithmic diffusion model fitted to recapture data yielded a maximum dispersal of 464 m (95 per cent confidence limits: 121–2365 m). Sawyer flights were significantly more frequent downslope in the plot. Catch concentration (i.e. the ratio between the radius r of the effective trapping area S and the maximum dispersal distance rm) ranged from 0.32 to 0.41 depending on sex. Mass trapping efficiency (i.e. the ratio of the total number of adults caught in the plot (excluding recaptures) over the estimated population size) was consistently low (0.08–0.36). We conclude from an applied perspective that available lures and traps are highly effective for monitoring, but their implementation in mass trapping requires substantial improving.

A rapid staining‐assisted wood sampling method for PCR‐based detection of pine wood nematode Bursaphelenchus xylophilus in Pinus massoniana wood tissue

SummaryFor reasons of unequal distribution of more than one nematode species in wood, and limited availability of wood samples required for the PCR‐based method for detecting pinewood nematodes in wood tissue of Pinus massoniana, a rapid staining‐assisted wood sampling method aiding PCR‐based detection of the pine wood nematode Bursaphelenchus xylophilus (Bx) in small wood samples of P. massoniana was developed in this study. This comprised a series of new techniques: sampling, mass estimations of nematodes using staining techniques, and lowest limit Bx nematode mass determination for PCR detection. The procedure was undertaken on three adjoining 5‐mg wood cross‐sections, of 0.5 × 0.5 × 0.015 cm dimension, that were cut from a wood sample of 0.5 × 0.5 × 0.5 cm initially, then the larger wood sample was stained by acid fuchsin, from which two 5‐mg wood cross‐sections (that adjoined the three 5‐mg wood cross‐sections, mentioned above) were cut. Nematode‐staining‐spots (NSSs) in each of the two stained sections were counted under a microscope at 100× magnification. If there were eight or more NSSs present, the adjoining three sections were used for PCR assays. The B. xylophilus– specific amplicon of 403 bp (DQ855275) was generated by PCR assay from 100.00% of 5‐mg wood cross‐sections that contained more than eight Bx NSSs by the PCR assay. The entire sampling procedure took only 10 min indicating that it is suitable for the fast estimation of nematode numbers in the wood of P. massonina as the prelimary sample selections for other more expensive Bx‐detection methods such as PCR assay.

Application of a real-time PCR method for the detection of pine wood nematode, Bursaphelenchus xylophilus, in wood samples from lodgepole pine

Abstract A real-time PCR polymerase chain reaction (real-time PCR) method was developed to detect and differentiate Bursaphelenchus xylophilus (pine wood nematode, PWN) from other wood-inhabiting nematode species. A primer set and a specific Taqman® fluorescent probe were designed to amplify target B. xylophilus heat shock protein 70 sequences. After optimization, this real-time PCR assay was shown to be highly specific and sensitive, detecting at least 0.005 ng of B. xylophilus genomic DNA, as well as DNA extracted from single nematodes. The practical application of this real-time PCR diagnostic method for the detection of B. xylophilus from actual wood samples of lodgepole pine (Pinus contorta, Dougl. var. latifolia) trees containing a heterogeneous population of nematodes, rather than pure cultures or individual nematodes, is demonstrated. This method works well in the presence of potential inhibitors associated with wood after Baermann extraction and thus eliminates the need to produce pure nematode samples through further culturing and/or isolation of nematodes with a high-power microscope.