COMBINING NEW TECHNOLOGIES FOR DETERMINATION OF PHYTOPLANKTON COMMUNITY STRUCTURE IN THE NORTHERN GULF OF MEXICO 1

In situ analysis of phytoplankton community structure was determined at five stations along the Texas Gulf coast using two instruments, the Fluoroprobe and FlowCAM. Results were compared with traditional methods to determine community structure (pigment analysis and microscopy). Diatoms and small nanoplankton (most likely haptophytes) dominated the phytoplankton community at all stations. Estimated chl concentrations for diatoms+dinoflagellates obtained via the Fluoroprobe were not significantly different for three of the five stations sampled when compared with HPLC‐chemical taxonomy analysis, whereas the concentrations of green algal and cryptophyte chl were overestimated. The FlowCAM estimates of overall nanoplankton and microplankton cell abundance were not significantly different when compared with epifluorescence microscopy, and recorded images of phytoplankton cells provided a representative population of the phytoplankton community at each station. The Fluoroprobe and FlowCAM, when used in tandem, are potentially capable of determining the general characteristics of phytoplankton community structure in situ and could be an important addition to biological observing systems in the coastal ocean.     

The CountEm software: simple,efficient and unbiased population size estimation

Population size estimation is essential in ecology and conservation studies. Aerial photography can facilitate this laborious task with high resolution images. However, in images with thousands of individuals exhaustive manual counting is tedious, slow and difficult to verify. Computer vision software may work under some particular conditions but they are generally biased and known to fail in several situations. The CountEm software is a simple alternative based on geometric sampling. It provides a fast and unbiased size estimation for all sorts of populations. The only requirement is that the discrete objects (e.g. animals) in the target population are unambiguously distinguishable for counting in a still image. Typical relative standard errors in the 5–10% range are obtained after counting ~200 properly sampled animals in about 5 min irrespective of population size. The CountEm ver. 1.4.1 is presented here, which includes a guided mode with a simple software interface.     

基于性诱和深度学习的草地贪夜蛾成虫自动识别计数方法

【目的】探究深度学习在草地贪夜蛾Spodoptera frugiperda成虫自动识别计数上的可行性,并评估模型的识别计数准确率,为害虫机器智能监测提供图像识别与计数方法。【方法】设计一种基于性诱的害虫图像监测装置,定时自动采集诱捕到的草地贪夜蛾成虫图像,结合采集船形诱捕器粘虫板上草地贪夜蛾成虫图像,构建数据集;应用YOLOv5深度学习目标检测模型进行特征学习,通过草地贪夜蛾原始图像、清除边缘残缺目标、增加相似检测目标(斜纹夜蛾成虫)、无检测目标负样本等不同处理的数据集进行模型训练,得到Yolov5s-A1, Yolov5s-A2, Yolov5s-AB, Yolov5s-ABC 4个模型,对比在不同遮挡程度梯度下的测试样本不同模型检测结果,用准确率(P)、召回率(R)、F1值、平均准确率(average precision, AP)和计数准确率(counting accuracy, CA)评估各模型的差异。【结果】通过原始图像集训练的模型Yolov5s-A1的识别准确率为87.37%,召回率为90.24%,F1值为88.78;清除边缘残缺目标图像集训练得到的模型Yolov5s-A2的识别准确率为93.15%,召回率为84.77%,F1值为88.76;增加斜纹夜蛾成虫样本图像训练的模型Yolov5s-AB的识别准确率为96.23%,召回率为91.85%,F1值为93.99;增加斜纹夜蛾成虫和无检测对象负样本训练的模型Yolov5s-ABC的识别准确率为94.76%,召回率为88.23%,F1值为91.38。4个模型的AP值从高到低排列如下：Yolov5s-AB>Yolov5s-ABC> Yolov5s-A2>Yolov5s-A1,其中Yolov5s-AB与Yolov5s-ABC结果相近;CA值从高到低排列如下：Yolov5s-AB>Yolov5s-ABC>Yolov5s-A2>Yolov5s-A1。【结论】结果表明本文提出的方法应用于控制条件下害虫图像监测设备及诱捕器粘虫板上草地贪夜蛾成虫的识别计数是可行的,深度学习技术对于草地贪夜蛾成虫的识别和计数是有效的。基于深度学习的草地贪夜蛾成虫自动识别与计数方法对虫体姿态变化、杂物干扰等有较好的鲁棒性,可从各种虫体姿态及破损虫体中自动统计出草地贪夜蛾成虫的数量,在害虫种群监测中具有广阔的应用前景。     

Monitoring cell‐specific neutral lipid accumulation in Phaeodactylum tricornutum (Bacillariophyceae) with Nile Red staining – a new method for FlowCAM

With the fluorescent stain Nile Red (NR), phytoplankton lipid accumulation can be monitored quickly and in situ. In the light of recent results in phytoplankton diversity research, there is also a need for cell‐ and species‐specific lipid measurement techniques. The objective of this work was to investigate whether cell‐specific phytoplankton lipid accumulation could be monitored with the image‐based particle analyzer FlowCAM? and NR staining. Applying Phaeodactylum tricornutum as a model species, we compared the FlowCAM method to two established lipid quantification methods: spectrofluorometric NR fluorescence measurement and total lipid analysis by gas chromatography. The experiment was carried out in batch cultures under nitrogen limitation to induce lipid accumulation. We showed significant correlation between the three different lipid quantification methods confirming the applicability of the novel FlowCAM method in cell‐specific and near real‐time lipid quantification. Furthermore, with the method described here, the lipid content of taxonomically distinguished cells can eventually be measured from multispecies cultures, opening several new possibilities to study species‐specific responses to stress conditions and the complementarity effect.     

CellProfiler: free, versatile software for automated biological image analysis

Careful visual examination of biological samples is quite powerful, but many visual analysis tasks done in the laboratory are repetitive, tedious, and subjective. Here we describe the use of the open-source software, CellProfiler, to automatically identify and measure a variety of biological objects in images. The applications demonstrated here include yeast colony counting and classifying, cell microarray annotation, yeast patch assays, mouse tumor quantification, wound healing assays, and tissue topology measurement. The software automatically identifies objects in digital images, counts them, and records a full spectrum of measurements for each object, including location within the image, size, shape, color intensity, degree of correlation between colors, texture (smoothness), and number of neighbors. Small numbers of images can be processed automatically on a personal computer and hundreds of thousands can be analyzed using a computing cluster. This free, easy-to-use software enables biologists to comprehensively and quantitatively address many questions that previously would have required custom programming, thereby facilitating discovery in a variety of biological fields of study.     

Comparison of techniques used to count single-celled viable phytoplankton

Four methods commonly used to count phytoplankton were evaluated based upon the precision of concentration estimates: Sedgewick Rafter and membrane filter direct counts, flow cytometry, and flow-based imaging cytometry (FlowCAM). Counting methods were all able to estimate the cell concentrations, categorize cells into size classes, and determine cell viability using fluorescent probes. These criteria are essential to determine whether discharged ballast water complies with international standards that limit the concentration of viable planktonic organisms based on size class. Samples containing unknown concentrations of live and UV-inactivated phytoflagellates (Tetraselmis impellucida) were formulated to have low concentrations (<100?mL^?1) of viable phytoplankton. All count methods used chlorophyll a fluorescence to detect cells and SYTOX fluorescence to detect nonviable cells. With the exception of one sample, the methods generated live and nonviable cell counts that were significantly different from each other, although estimates were generally within 100% of the ensemble mean of all subsamples from all methods. Overall, percent coefficient of variation (CV) among sample replicates was lowest in membrane filtration sample replicates, and CVs for all four counting methods were usually lower than 30% (although instances of ~60% were observed). Since all four methods were generally appropriate for monitoring discharged ballast water, ancillary considerations (e.g., ease of analysis, sample processing rate, sample size, etc.) become critical factors for choosing the optimal phytoplankton counting method.     

γH2AX foci as a measure of DNA damage: a computational approach to automatic analysis

The γH2AX focus assay represents a fast and sensitive approach for the detection of one of the critical types of DNA damage - double-strand breaks (DSB) induced by various cytotoxic agents including ionising radiation. Apart from research applications, the assay has a potential in clinical medicine/pathology, such as assessment of individual radiosensitivity, response to cancer therapies, as well as in biodosimetry. Given that generally there is a direct relationship between numbers of microscopically visualised γH2AX foci and DNA DSB in a cell, the number of foci per nucleus represents the most efficient and informative parameter of the assay. Although computational approaches have been developed for automatic focus counting, the tedious and time consuming manual focus counting still remains the most reliable way due to limitations of computational approaches. We suggest a computational approach and associated software for automatic focus counting that minimises these limitations. Our approach, while using standard image processing algorithms, maximises the automation of identification of nuclei/cells in complex images, offers an efficient way to optimise parameters used in the image analysis and counting procedures, optionally invokes additional procedures to deal with variations in intensity of the signal and background in individual images, and provides automatic batch processing of a series of images. We report results of validation studies that demonstrated correlation of manual focus counting with results obtained using our computational algorithm for mouse jejunum touch prints, mouse tongue sections and human blood lymphocytes as well as radiation dose response of γH2AX focus induction for these biological specimens.     

High-resolution spatio-temporal distribution of a coastal phytoplankton bloom using laser in situ scattering and transmissometry (LISST)

Development of optical observation technologies provides new insights into harmful algal bloom (HAB) detection and assessment of HAB species dynamics. Based on preliminary laboratory tests, a laser in situ scattering and transmissometry instrument (LISST-100X) was used to monitor a high-biomass phytoplankton proliferation in the field. Short-term spatial and temporal changes in particle size distribution were measured during a recurrent Alexandrium taylori outbreak. Since the bloom was not monospecific, a size-fraction method to discriminate particular species from LISST-100X measurements was proposed. The results were validated to simultaneous microscopic counts of phytoplankton, and the significantly positive correlation obtained between the two methodologies confirmed the instrument's ability to discriminate phytoplankton at the group and species level. The LISST-100X obtains high-resolution in situ data, and is therefore a better alternative than the traditional microscope for assessing temporal and spatial evolution of HABs. Field observations showed high variability over a short time scale associated with diel vertical migration of A. taylori and the whole phytoplankton population (nanoplankton and microplankton). A numerical circulation model was used to investigate the influence of beach hydrodynamics in the observed horizontal variability. Simulations of the model suggested an important role of daily coastal circulation in determining the distribution of A. taylori in coastal environments.     

QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting

We report the development and testing of software called QuantiFly: an automated tool to quantify Drosophila egg laying. Many laboratories count Drosophila eggs as a marker of fitness. The existing method requires laboratory researchers to count eggs manually while looking down a microscope. This technique is both time-consuming and tedious, especially when experiments require daily counts of hundreds of vials. The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. The QuantiFly software, which includes the refined algorithm, has been designed to be immediately accessible to scientists through an intuitive and responsive user-friendly graphical interface. The software is also open-source, self-contained, has no dependencies and is easily installed (https://github.com/dwaithe/quantifly). Compared to manual egg counts made from digital images, QuantiFly achieved average accuracies of 94% and 85% for eggs laid on transparent (defined) and opaque (yeast-based) fly media. Thus, the software is capable of detecting experimental differences in most experimental situations. Significantly, the advanced feature recognition capabilities of the software proved to be robust to food surface artefacts like bubbles and crevices. The user experience involves image acquisition, algorithm training by labelling a subset of eggs in images of some of the vials, followed by a batch analysis mode in which new images are automatically assessed for egg numbers. Initial training typically requires approximately 10 minutes, while subsequent image evaluation by the software is performed in just a few seconds. Given the average time per vial for manual counting is approximately 40 seconds, our software introduces a timesaving advantage for experiments starting with as few as 20 vials. We also describe an optional acrylic box to be used as a digital camera mount and to provide controlled lighting during image acquisition which will guarantee the conditions used in this study.     

Laboratory sources of error for algal community attributes during sample preparation and counting

Applied algal studies typically require enumeration of preserved cells. As applications of algal assessments proliferate, understanding sources of variability inherent in the methods by which abundance and species composition data are obtained becomes even more important for precision of measurements. We performed replicate counts of diatoms on permanently fixed coverglasses and all algae in Palmer–Maloney chambers to assess precision and accuracy of measurements derived from common counting methods. We counted diatoms and all algae with transects and random fields. Variability estimates (precision) of diatom density, species diversity, and species composition on permanent coverglasses were low between replicate subsamples and between replicate transects. However, average density estimates of diatoms settled on coverglasses determined with transect methods were 42–52% greater than density estimates made with random fields. This bias was due to a predictable, nonrandom distribution of diatoms on the coverglass with few diatoms near edges. Despite bias in density when counting diatoms along coverglass transects, no bias was observed in estimates of species composition. Estimates of density and taxa richness of all-algae in Palmer–Maloney chambers also had low variability among multiple transects and high similarity in species composition between transects. In addition, counting method in Palmer–Maloney chambers did not affect estimates of algal cell density, taxa richness, and species composition, which suggested that counting units were distributed randomly in the chambers. Thus, most sources of variability in sample preparation and analysis are small; however, transect counts should not be used to estimate cell density, and sufficient numbers of random fields must be counted to account for edge effects on cell distribution with material settled on permanently fixed coverglasses.     

Intercalibration of classical and molecular techniques for identification of Alexandrium fundyense (Dinophyceae) and estimation of cell densities

A workshop with the aim to compare classical and molecular techniques for phytoplankton enumeration took place at Kristineberg Marine Research Station, Sweden, in August 2005. Seventeen different techniques – nine classical microscopic-based and eight molecular methods – were compared. Alexandrium fundyense was the target organism in four experiments. Experiment 1 was designed to determine the range of cell densities over which the methods were applicable. Experiment 2 tested the species specificity of the methods by adding Alexandrium ostenfeldii, to samples containing A. fundyense. Experiments 3 and 4 tested the ability of the methods to detect the target organism within a natural phytoplankton community. Most of the methods could detect cells at the lowest concentration tested, 100 cells L⁻¹, but the variance was high for methods using small volumes, such as counting chambers and slides. In general, the precision and reproducibility of the investigated methods increased with increased target cell concentration. Particularly molecular methods were exceptions in that their relative standard deviation did not vary with target cell concentration. Only two of the microscopic methods and three of the molecular methods had a significant linear relationship between their cell count estimates and the A. fundyense concentration in experiment 2, where the objective was to discriminate that species from a morphologically similar and genetically closely related species. None of the investigated methods were affected by the addition of a natural plankton community background matrix in experiment 3. The results of this study are discussed in the context of previous intercomparisons and the difficulties in defining the absolute, true target cell concentration.     

Counting pollen grains using readily available, free image processing and analysis software

Background and Aims

Although many methods exist for quantifying the number of pollen grains in a sample, there are few standard methods that are user-friendly, inexpensive and reliable. The present contribution describes a new method of counting pollen using readily available, free image processing and analysis software.

Methods

Pollen was collected from anthers of two species, Carduus acanthoides and C. nutans (Asteraceae), then illuminated on slides and digitally photographed through a stereomicroscope. Using ImageJ (NIH), these digital images were processed to remove noise and sharpen individual pollen grains, then analysed to obtain a reliable total count of the number of grains present in the image. A macro was developed to analyse multiple images together. To assess the accuracy and consistency of pollen counting by ImageJ analysis, counts were compared with those made by the human eye.

Key Results and Conclusions

Image analysis produced pollen counts in 60 s or less per image, considerably faster than counting with the human eye (5–68 min). In addition, counts produced with the ImageJ procedure were similar to those obtained by eye. Because count parameters are adjustable, this image analysis protocol may be used for many other plant species. Thus, the method provides a quick, inexpensive and reliable solution to counting pollen from digital images, not only reducing the chance of error but also substantially lowering labour requirements.     

Quantitative PCR Method for Enumeration of Cells of Cryptic Species of the Toxic Marine Dinoflagellate Ostreopsis spp. in Coastal Waters of Japan

Monitoring of harmful algal bloom (HAB) species in coastal waters is important for assessment of environmental impacts associated with HABs. Co-occurrence of multiple cryptic species such as toxic dinoflagellate Ostreopsis species make reliable microscopic identification difficult, so the employment of molecular tools is often necessary. Here we developed new qPCR method by which cells of cryptic species can be enumerated based on actual gene number of target species. The qPCR assay targets the LSU rDNA of Ostreopsis spp. from Japan. First, we constructed standard curves with a linearized plasmid containing the target rDNA. We then determined the number of rDNA copies per cell of target species from a single cell isolated from environmental samples using the qPCR assay. Differences in the DNA recovery efficiency was calculated by adding exogenous plasmid to a portion of the sample lysate before and after DNA extraction followed by qPCR. Then, the number of cells of each species was calculated by division of the total number of rDNA copies of each species in the samples by the number of rDNA copies per cell. To test our procedure, we determined the total number of rDNA copies using environmental samples containing no target cells but spiked with cultured cells of several species of Ostreopsis. The numbers estimated by the qPCR method closely approximated total numbers of cells added. Finally, the numbers of cells of target species in environmental samples containing cryptic species were enumerated by the qPCR method and the total numbers also closely approximated the microscopy cell counts. We developed a qPCR method that provides accurate enumeration of each cryptic species in environments. This method is expected to be a powerful tool for monitoring the various HAB species that occur as cryptic species in coastal waters.     

Dye free automated cell counting and analysis

We have developed an automated cell counting method that uses images obtained at multiple focal heights to enumerate cells in confluent culture. By taking the derivative of image intensity with respect to focal height using two complementary images, we are able to count high‐density monolayers of cells over a large image area. Our method resists errors arising from variability in the focal plane caused by flatness or tilt non‐uniformities with a minimal amount of focal plane alignment, allowing the automated collection of images across a large area. Biotechnol. Bioeng. © 2013 Wiley Periodicals, Inc.     

A rapid analysis of copepod feeding using FlowCAM

This study addressed the usefulness and reliability of usinga new plankton image analyzer, FlowCAM, for rapid analysis ofcopepod feeding by comparison with the conventional microscopicanalysis. We carried out bottle incubation experiments withtwo copepod species in the Oyashio region and analyzed the preyabundance prior to and after the incubation with a FlowCAM.From the volume-specific fluorescence intensity of particles,the FlowCAM successfully distinguished between zooplankton andphytoplankton and allowed an adequate evaluation of the copepodfeeding on zooplankton and phytoplankton. The analysis timefor one plankton sample was about 10 min, which was less thanone-tenth of the time required for microscopic enumeration.The FlowCAM is considered to be an efficient tool for rapidanalysis of copepod feeding particularly in studies of omnivory.     

Fiber-Optic Microarray for Simultaneous Detection of Multiple Harmful Algal Bloom Species

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 μm) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.     

Determination of the filamentous cyanobacteria Planktothrix rubescens in environmental water samples using an image processing system

Cyanobacteria occur in surface waters worldwide. Many of these produce peptides and/or alkaloids, which can present a risk for animal and human health. Effective risk assessment and management requires continuous and precise observation and quantification of cyanobacterial cell densities. In this respect, quantification of filamentous Planktothrix species is problematic. The aim of this study was to develop an automated system to count filamentous Planktothrix rubescens using image processing. Furthermore, this study aimed to assess optimum sample volumes and filament density for measurement precision and to validate image processing measurement of P. rubescens for an effective risk assessment.Three environmental samples and one cultured sample of P. rubescens were collected by filtration onto nitrocellulose filters. Filament lengths were determined using fluorescence microscopy combined with an image processor. Cell density could be calculated from the resulting images. Cyanobacteria could easily be discriminated from algae via their fluorescence properties. The results were found to be independent of the mode of image acquisition. The precision of total filament length determination was dependent on the total filament length on the filter, i.e. analyses of highest precision could be expected for filters containing 2000–20,000 μm filaments per mm². When using suitable filtration volumes, the detection limits of the described method are sufficient for an effective risk assessment. To summarise, this procedure is a fast, easy and accurate method to determine cell densities of filamentous P. rubescens in water samples without costly and tedious manual handling.     

Determination of Mammalian Cell Counts,Cell Size and Cell Health Using the Moxi Z Mini Automated Cell Counter

Particle and cell counting is used for a variety of applications including routine cell culture, hematological analysis, and industrial controls^1-5. A critical breakthrough in cell/particle counting technologies was the development of the Coulter technique by Wallace Coulter over 50 years ago. The technique involves the application of an electric field across a micron-sized aperture and hydrodynamically focusing single particles through the aperture. The resulting occlusion of the aperture by the particles yields a measurable change in electric impedance that can be directly and precisely correlated to cell size/volume. The recognition of the approach as the benchmark in cell/particle counting stems from the extraordinary precision and accuracy of its particle sizing and counts, particularly as compared to manual and imaging based technologies (accuracies on the order of 98% for Coulter counters versus 75-80% for manual and vision-based systems). This can be attributed to the fact that, unlike imaging-based approaches to cell counting, the Coulter Technique makes a true three-dimensional (3-D) measurement of cells/particles which dramatically reduces count interference from debris and clustering by calculating precise volumetric information about the cells/particles. Overall this provides a means for enumerating and sizing cells in a more accurate, less tedious, less time-consuming, and less subjective means than other counting techniques⁶.Despite the prominence of the Coulter technique in cell counting, its widespread use in routine biological studies has been prohibitive due to the cost and size of traditional instruments. Although a less expensive Coulter-based instrument has been produced, it has limitations as compared to its more expensive counterparts in the correction for "coincidence events" in which two or more cells pass through the aperture and are measured simultaneously. Another limitation with existing Coulter technologies is the lack of metrics on the overall health of cell samples. Consequently, additional techniques must often be used in conjunction with Coulter counting to assess cell viability. This extends experimental setup time and cost since the traditional methods of viability assessment require cell staining and/or use of expensive and cumbersome equipment such as a flow cytometer.The Moxi Z mini automated cell counter, described here, is an ultra-small benchtop instrument that combines the accuracy of the Coulter Principle with a thin-film sensor technology to enable precise sizing and counting of particles ranging from 3-25 microns, depending on the cell counting cassette used. The M type cassette can be used to count particles from with average diameters of 4 - 25 microns (dynamic range 2 - 34 microns), and the Type S cassette can be used to count particles with and average diameter of 3 - 20 microns (dynamic range 2 - 26 microns). Since the system uses a volumetric measurement method, the 4-25 microns corresponds to a cell volume range of 34 - 8,180 fL and the 3 - 20 microns corresponds to a cell volume range of 14 - 4200 fL, which is relevant when non-spherical particles are being measured. To perform mammalian cell counts using the Moxi Z, the cells to be counted are first diluted with ORFLO or similar diluent. A cell counting cassette is inserted into the instrument, and the sample is loaded into the port of the cassette. Thousands of cells are pulled, single-file through a "Cell Sensing Zone" (CSZ) in the thin-film membrane over 8-15 seconds. Following the run, the instrument uses proprietary curve-fitting in conjunction with a proprietary software algorithm to provide coincidence event correction along with an assessment of overall culture health by determining the ratio of the number of cells in the population of interest to the total number of particles. The total particle counts include shrunken and broken down dead cells, as well as other debris and contaminants. The results are presented in histogram format with an automatic curve fit, with gates that can be adjusted manually as needed.Ultimately, the Moxi Z enables counting with a precision and accuracy comparable to a Coulter Z2, the current gold standard, while providing additional culture health information. Furthermore it achieves these results in less time, with a smaller footprint, with significantly easier operation and maintenance, and at a fraction of the cost of comparable technologies.     

A counting method for the number of Sternolophus rufipes and Hydrochara affinis in a noisy trap image

A quantitative survey of water scavenger beetles Sternolophus rufipes and Hydrochara affinis in paddy fields is essential not only for evaluating the impact of climate change on ecosystems but also for quantifying the stability of paddy fields. Many researchers classify insects in insect traps visually and manually count the number of individuals in each species. This manual survey method is time-consuming, fatiguing, and tedious. In this paper, we present a simple method to classify and count beetles in noisy trap images. The proposed method uses the beetles' body size and spots made by the light reflecting off the backs of beetles. We verify the method using images of beetles attached to the insect trap. The results demonstrate that the number of individuals in each species as counted by the proposed method and the manually counted number are statistically identical, which means that our method is sufficient to replace the existing manual counting method. Additionally, we briefly discuss the limitations of this counting method and ideas that could complement them.     

Fiber-optic microarray for simultaneous detection of multiple harmful algal bloom species

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 mum) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.