Budburst and leaf area expansion measured with a novel mobile camera system and simple color thresholding

Plant phenology relates strongly to primary productivity and the energy that enters into ecological food webs, and thus is vital in understanding ecosystem function and the effects of climate and climate change. The manual collection of phenological data is labor-intensive and not easily scalable, thus the ability to quantify leaf flush and other parameters at many locations requires innovative new methodologies such as the use of visible light digital cameras. Improved imaging performance was obtained by using a cabled, mobile camera system that allowed a repeated image census of branches of Rhododendron occidentale in the understory along a 30 m transect during leaf flush. Automatic division of acquired images into areas of interest (leaves) and background for calculating leaf area was accomplished by thresholding images in different color spaces. Transformation of the color space into the hue, saturation, and luminance (HSL) color space before thresholding resulted in a mean RMS error of 21.2 cm² compared to hand-counts of leaf area. Thresholding in the native red, green, and blue (RGB) color space to isolate leaves resulted in a larger error, as did using algebraic combinations of the color components or color ratios. Relating physiological function to images, as for sap flow for branches of R. occidentale, indicates that the greening and calculated leaf area of a species as detected by imagers requires additional meteorological sensor data for interpretation.     

Using the value of Lin’s concordance correlation coefficient as a criterion for efficient estimation of areas of leaves of eelgrass from noisy digital images

Background

Eelgrass is a cosmopolitan seagrass species that provides important ecological services in coastal and near-shore environments. Despite its relevance, loss of eelgrass habitats is noted worldwide. Restoration by replanting plays an important role, and accurate measurements of the standing crop and productivity of transplants are important for evaluating restoration of the ecological functions of natural populations. Traditional assessments are destructive, and although they do not harm natural populations, in transplants the destruction of shoots might cause undesirable alterations. Non-destructive assessments of the aforementioned variables are obtained through allometric proxies expressed in terms of measurements of the lengths or areas of leaves. Digital imagery could produce measurements of leaf attributes without the removal of shoots, but sediment attachments, damage infringed by drag forces or humidity contents induce noise-effects, reducing precision. Available techniques for dealing with noise caused by humidity contents on leaves use the concepts of adjacency, vicinity, connectivity and tolerance of similarity between pixels. Selection of an interval of tolerance of similarity for efficient measurements requires extended computational routines with tied statistical inferences making concomitant tasks complicated and time consuming. The present approach proposes a simplified and cost-effective alternative, and also a general tool aimed to deal with any sort of noise modifying eelgrass leaves images. Moreover, this selection criterion relies only on a single statistics; the calculation of the maximum value of the Concordance Correlation Coefficient for reproducibility of observed areas of leaves through proxies obtained from digital images.

Results

Available data reveals that the present method delivers simplified, consistent estimations of areas of eelgrass leaves taken from noisy digital images. Moreover, the proposed procedure is robust because both the optimal interval of tolerance of similarity and the reproducibility of observed leaf areas through digital image surrogates were independent of sample size.

Conclusion

The present method provides simplified, unbiased and non-destructive measurements of eelgrass leaf area. These measurements, in conjunction with allometric methods, can predict the dynamics of eelgrass biomass and leaf growth through indirect techniques, reducing the destructive effect of sampling, fundamental to the evaluation of eelgrass restoration projects thereby contributing to the conservation of this important seagrass species.

     

基于遥感图像处理技术胡杨叶气孔密度的估算及其生态意义

拟利用遥感图像处理技术--面向对象分类,计算胡杨叶片气孔密度,采用面向对象分类的专业软件eCognition对气孔图像进行多尺度分割,将生成的分类图像导入ArcGIS中计算气孔密度,最后用R语言编写代码进行批处理。研究结果显示:该方法用于计算叶片气孔的密度精度高;18个样点胡杨气孔密度存在着较大的差异,从76.7 个/mm²到139.4 个/mm²不等,其平均密度为105 个/mm²;随着干旱胁迫加强,气孔密度表现下降上升再下降的趋势。     

Gastrophysa polygoni herbivory on Rumex confertus: single leaf VOC induction and dose dependent herbivore attraction/repellence to individual compounds

We report large induction (>65_fold increases) of volatile organic compounds (VOCs) emitted from a single leaf of the invasive weed mossy sorrel, Rumex confertus Willd. (Polygonaceae), by herbivory of the dock leaf beetle, Gastrophysa polygoni L. (Coleoptera: Chrysomelidae). The R. confertus VOC blend induced by G. polygoni herbivory included two green leaf volatiles ((Z)-3-hexenal, (Z)-3-hexen-1-yl acetate) and three terpenes (linalool, ß-caryophyllene, (E)-ß-farnesene). Uninjured leaves produced small constitutive amounts of the GLVs and barely detectable amounts of the terpenes. A Y-tube olfactometer bioassay revealed that both sexes of adult G. polygoni were attracted to (Z)-3-hexenal and (Z)-3-hexen-1-yl acetate at a concentration of 300 ng h⁻¹. No significant G. polygoni attraction or repellence was detected for any VOC at other concentrations (60 and 1500 ng h⁻¹). Yet, G. polygoni males and females were significantly repelled by (or avoided) at the highest test concentration (7500 ng h⁻¹) of both GLVs and (E)-ß-farnesene. Mated male and female G. polygoni might be attracted to injured R. confertus leaves, but might avoid R. confertus when VOC concentrations (especially the terpene (E)-ß-farnesene) suggest high overall plant injury from conspecifics, G. viridula, or high infestations of other herbivores that release (E)-ß-farnesene (e.g., aphids). Tests in the future will need to examine G. polygoni responses to VOCs emitted directly from uninjured (constitutive) and injured (induced) R. confertus, and examine whether R. confertus VOC induction concentrations increase with greater tissue removal on a single leaf and/or the number of leaves with feeding injury.     

A role for uninjured afferents in neuropathic pain

Diseases and injuries to the nervous system can lead to a devastating chronic pain condition called neuropathic pain. We review changes that occur in the peripheral nervous system that may play a role in this disease. Common animal models for neuropathic pain involve an injury to one or more peripheral nerves. Following such an injury, the nerve fibers that have been injured exhibit many abnormal properties including the development of spontaneous neural activity as well as a change in the expression of certain genes in their cell body. Recent data indicate that adjacent, uninjured nerve fibers also exhibit significant changes. These changes are thought to be driven by injury-induced alterations in the milieu surrounding the uninjured nerve and nerve terminals. Thus, alteration in neural signaling in both injured and uninjured neurons play a role in the development of neuropathic pain after peripheral nerve injury.     

基于数码相片Gamma校正的水稻叶面积指数估算

随着数码相机的日益普及,利用数码相机进行作物叶面积指数(LAI)测量不断得以应用。由于数码相机成像时会对入射光辐射强度进行Gamma编码变换,输出的相片DN(Digital Number)值与入射光辐射强度呈非线性关系,会造成在确定相片中植被叶片与背景的分割阈值时出现误差,并最终导致LAI估算存在较大不确定性。以水稻为研究对象,获取不同生长期水稻冠层相片并结合同步LAI 2000测量的LAI数据,基于相片Gamma校正原理,对水稻不同生长期冠层相片进行Gamma校正,在此基础上利用冠层孔隙率方法,估算不同生长期水稻LAI。结果表明,经过Gamma校正相片估算的水稻LAI总体精度有显著提高,相片估算的IMAGE LAI与LAI-2000测量值比较的决定系数达到0.71(P0.05)。在整个观测期内,两种方法观测的LAI值在时间变化趋势上表现一致,但在不同生长期内存在差别,在水稻分蘖期和拔节期相片估算的IMAGE LAI要高于LAI-2000测量值,孕穗期到抽穗期期间IMAGE LAI低于LAI-2000测量值,乳熟期到成熟期IMAGE LAI又高于LAI-2000的观测结果。     

Development and evaluation of multiple tendon injury models in the mouse

The mouse has proven to be an advantageous animal model system in basic science research focused on aiding in development and evaluation of potential treatments; however, the small size of mouse tendons makes consistent and reproducible injury models and subsequent biomechanical evaluation challenging for studying tendon healing. In this study, we investigated the feasibility and reproducibility of multiple mouse tendon injury models. Our hypothesis was that incisional (using a blade) and excisional (using a biopsy punch) injuries would result in consistent differences in tendon material properties. At 16 weeks of age, 17 C57BL/6 mice underwent surgery to create defects in the flexor digitorum longus, Achilles, or patellar tendon. Each animal received 1-2 full-thickness, central-width incisional or excisional injuries per limb; at least one tendon per limb remained uninjured. The injuries were distributed such that each tendon type had comparable numbers of uninjured, incisionally injured, and excisionally injured specimens. Three weeks after injury, all animals were euthanized and tendons were harvested for mechanical testing. As hypothesized, differences were detected for all three different tendon types at three weeks post-injury. While all models created injuries that produced predictable outcomes, the patellar tendon model was the most consistent in terms of number and size of significant differences in injured tendons compared to native properties, as well as in the overall variance in the data. This finding provides support for its use in fundamental tendon healing studies; however, future work may use any of these models, based on their appropriateness for the specific question under study.     

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.     

Herbivory on Zostera marina by the gastropod Smaragdia viridis

The feeding activity of the gastropod Smaragdia viridis on Zostera marina (eelgrass) was studied under laboratory conditions and from shoots collected in a deep eelgrass bed (12–14 m depth) in southern Spain (Alboran Sea). This gastropod preferentially ingested young leaf tissues, such as those located in the central leaf and first pair of adjacent leaves and at close distances from the junction of the leaves with the sheath. The ingestion rate of this gastropod was size dependent, ingesting up to 40.6 mm² of epidermal tissues in 24 h (for large individuals), however this value generally represented a very low percentage of the area of a single shoot (0.3–2.1%). The absorption of eelgrass tissues, in relation to digested/non-digested eelgrass cells in faecal pellets, was not size dependent and reached high values (75–90% cells digested). The grazing impact in an eelgrass bed, based on the affected area (length of radular marks by leaf width), also represented a very low value (0.3–1.1%) in relation to the total LAI (Leaf Area Index) available. A seasonal trend of herbivory was registered with maximum values in summer together with maximum densities of S. viridis.     

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground.     

Development of a digital image analysis method for real-time estimation of chlorophyll content in micropropagated potato plants

The present work describes a digital image analysis method based on leaf color analysis to estimate chlorophyll content of leaves of micropropagated potato plantlets. For estimation of chlorophyll content, a simple leaf digital analysis procedure using a simple digital still camera was applied in parallel to a SPAD chlorophyll content meter. RGB features were extracted from the image and correlated with the SPAD values. None of the mean brightness parameters (RGB) were correlated with the actual chlorophyll content following simple correlation studies. However, a correlation between the chromaticity co-ordinates ‘r’, ‘b’ and chlorophyll content was observed, while co-ordinate ‘g’ was not significantly correlated with chlorophyll content. Linear regression and artificial neural networks (ANN) were applied for correlating the mean brightness (RGB) and mean brightness ratio (rgb) features to chlorophyll content of plantlet leaves determined through a SPAD meter. The chlorophyll content as determined by the SPAD meter was significantly correlated (RMSE = 3.97 and 3.59, respectively, for linear and ANN models) to the rgb values of leaf image analysis. Both the models indicate successful prediction of chlorophyll content of leaves of micropropagated plants with high correlation. The developed RGB-based digital image analysis has the advantage over conventional subjective methods for being objective, fast, non-invasive, and inexpensive. The system could be utilized for real-time estimation of chlorophyll content and subsequent analysis of photosynthetic and hyperhydric status of the micropropagated plants for better ex vitro survival.     

Chronic Constriction of the Sciatic Nerve and Pain Hypersensitivity Testing in Rats

Chronic neuropathic pain, resulting from damage to the central or peripheral nervous system, is a prevalent and debilitating condition, affecting 7-18% of the population^1,2. Symptoms include spontaneous (tingling, burning, electric-shock like) pain, dysaesthesia, paraesthesia, allodynia (pain resulting from normally non-painful stimuli) and hyperalgesia (an increased response to painful stimuli). The sensory symptoms are co-morbid with behavioural disabilities, such as insomnia and depression. To study chronic neuropathic pain several animal models mimicking peripheral nerve injury have been developed, one of the most widely used is Bennett and Xie''s (1988) unilateral sciatic nerve chronic constriction injury (CCI)³ (Figure 1). Here we present a method for performing CCI and testing pain hypersensitivity.CCI is performed under anaesthesia, with the sciatic nerve on one side exposed by making a skin incision, and cutting through the connective tissue between the gluteus superficialis and biceps femoris muscles. Four chromic gut ligatures are tied loosely around the sciatic nerve at 1 mm intervals, to just occlude but not arrest epineural blood flow. The wound is closed with sutures in the muscle and staples in the skin. The animal is then allowed to recover from surgery for 24 hrs before pain hypersensitivity testing begins.For behavioural testing, rats are placed into the testing apparatus and are allowed to habituate to the testing procedure. The area tested is the mid-plantar surface of the hindpaw (Figure 2), which falls within the sciatic nerve distribution. Mechanical withdrawal threshold is assessed by mechanically stimulating both injured and uninjured hindpaws using an electronic dynamic plantar von Frey aesthesiometer or manual von Frey hairs⁴. The mechanical withdrawal threshold is the maximum pressure exerted (in grams) that triggers paw withdrawal. For measurement of thermal withdrawal latency, first described by Hargreaves et al (1988), the hindpaw is exposed to a beam of radiant heat through a transparent glass surface using a plantar analgesia meter^5,6. The withdrawal latency to the heat stimulus is recorded as the time for paw withdrawal in both injured and uninjured hindpaws. Following CCI, mechanical withdrawal threshold, as well as thermal withdrawal latency in the injured paw are both significantly reduced, compared to baseline measurements and the uninjured paw (Figure 3). The CCI model of peripheral nerve injury combined with pain hypersensitivity testing provides a model system to investigate the effectiveness of potential therapeutic agents to modify chronic neuropathic pain. In our laboratory, we utilise CCI alongside thermal and mechanical sensitivity of the hindpaws to investigate the role of neuro-immune interactions in the pathogenesis and treatment of neuropathic pain.     

Characterization of leaf boron injury in salt-stressed Eucalyptus by image analysis

Symptoms of boron toxicity (i.e., necrosis of leaf tips and margins) have been observed on eucalyptus trees in the San Joaquin Valley of California where the trees are being tested for their effectiveness at reducing the volume of agricultural drainage effluents. In a controlled, outdoor sand-tank study, Eucalyptus camaldulensis Dehn., Clone 4544 trees were grown and irrigated with combinations of salinity and B to determine their influence on tree growth and water use. Irrigation water quality treatments were prepared to simulate the Na-sulfate salinity, high B nature of these drainage effluents. Electrical conductivities (EC_iw) of the waters ranged from 2 to 28 dS m-1 and B concentrations ranging from 1 to 30 mg L-1. As an integral component of this study , we developed a method to quantify and correlate foliar damage with leaf B concentrations. By scanning both injured and uninjured leaves into computer files and processing with image analysis, we were able to simultaneously correlate salinity stress with its overall effect on leaf area as well as to quantify the relative fraction of leaf area affected by specific-ion (i.e., B) injury. Leaf area was unaffected by B stress but was reduced by salinity only in the younger leaves. Boron injury was correlated with increasing irrigation water B only in older leaves. The relative injured area (RIA) of the older leaves was related to the B concentrations of leaves from trees grown at various salinities . A regression equation was developed from injury data obtained from trees grown under boron and salinity stress for 223 days (r2=0.90). From this relationship, we were able to estimate leaf boron concentrations from injury symptoms in leaves selected at random from main trunk branches of trees grown for 333 days under the same stress conditions. The results suggest that this method may have potential as an effective tool for monitoring the response to toxic levels of boron in eucalyptus, once B toxicity has been established by analytical means. The RIA appears to be mitigated by increased salinity of the irrigation water and is consistent with the general reduction in leaf B by salinity. The interactive effects of boron and salinity on foliar injury depends on the physiological age of the leaf.     

Tolerance and compensatory response of rice to sugarcane borer (Lepidoptera: Crambidae) injury

A 3-yr field experiment was conducted to evaluate the tolerance and compensatory response of rice (Oryza sativa L.) to injury caused by sugarcane borer, Diatraea saccharalis (F.), as affected by cultivar (Cocodrie, Francis, and Jefferson), stage of crop growth during which the injury occurred (third tiller stage, panicle differentiation stage, and heading stage), and sugarcane borer density. The proportion of rice tillers with sugarcane borer injury (leaf and leaf sheath injury and/or stem injury) was lower when injury occurred at the third tiller stage (0.05) than at panicle differentiation (0.19) and heading (0.18). When injury occurred at the two latter stages, both the proportion of tillers with injury and the proportion of tillers with stem injury were negatively correlated with rainfall. Rainfall resulted in dislodgement and mortality of sugarcane borer eggs and larvae before the larvae entered the stems. Rice plant density in this study (111.1 plants/m2) was higher than recorded for previous research on rice compensation using potted rice or conducted in low-density hill production systems (26.7-51.3 plants/m2). Two mechanisms of within-plant tolerance/compensation were observed. Stem injured plants produced approximately 0.69 more tillers than uninjured plants, whereas tillers with leaf and leaf sheath injury produced larger panicles, up to 39.5 and 21.0% heavier than uninjured tillers, when injury occurred at third tiller stage and at panicle differentiation, respectively. Rice yield was not reduced with up to 23% injured tiller and up to 10% injured stems at the third tiller stage, 42% injured tillers and 17% injured stems at panicle differentiation, and 28% injured tillers and 14% injured stems at heading. Significant between-plant compensation was not detected, suggesting competition between adjacent plants is not significantly reduced by injury. Our results suggest that rice can tolerate and/or compensate for a level of stem borer injury previously considered to be economically damaging.     

Volatile induction of three cereals: influence of mechanical injury and insect herbivory on injured plants and neighbouring uninjured plants

Herbivore damage and mechanical injury to leaves can stimulate the emission of volatile compounds. It is well known that emission of these volatile organic compounds (VOC) from plants can influence interactions with pests and their natural enemies. In our experiment, we studied the VOC responses of Triticum aestivum cv. ‘Bombona’, Avena sativa cv. ‘Deresz’ and Hordeum vulgare cv. ‘Rastik’ under mechanical injury and/or adult cereal leaf beetle herbivory, Oelema melanopus (Coleoptera: Chrysomelidae). In the first part of our experiment, we confirmed that increased amounts of several green leaf volatiles (GLVs) and terpene VOC were released by tested cereal plants after leaf injury. The quantities of multiple induced VOC varied significantly between our tested cereals. When undamaged wheat, barley and oat plants were positioned near to mechanically injured or insect-damaged wheat plants, these neighbouring uninjured plants of all three test cereals also emitted significantly more VOC than control plants. The degree of VOC induction was significantly greater when an uninjured plant was closer to an injured wheat plant. This phenomenon may be useful for crop protection, as VOC manipulation may result in improved pest management and help reduce the use of harmful pesticides.     

Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components

Leaf chlorophyll content provides valuable information about physiological status of plants; it is directly linked to photosynthetic potential and primary production. In vitro assessment by wet chemical extraction is the standard method for leaf chlorophyll determination. This measurement is expensive, laborious, and time consuming. Over the years alternative methods, rapid and non-destructive, have been explored. The aim of this work was to evaluate the applicability of a fast and non-invasive field method for estimation of chlorophyll content in quinoa and amaranth leaves based on RGB components analysis of digital images acquired with a standard SLR camera. Digital images of leaves from different genotypes of quinoa and amaranth were acquired directly in the field. Mean values of each RGB component were evaluated via image analysis software and correlated to leaf chlorophyll provided by standard laboratory procedure. Single and multiple regression models using RGB color components as independent variables have been tested and validated. The performance of the proposed method was compared to that of the widely used non-destructive SPAD method. Sensitivity of the best regression models for different genotypes of quinoa and amaranth was also checked. Color data acquisition of the leaves in the field with a digital camera was quick, more effective, and lower cost than SPAD. The proposed RGB models provided better correlation (highest R ²) and prediction (lowest RMSEP) of the true value of foliar chlorophyll content and had a lower amount of noise in the whole range of chlorophyll studied compared with SPAD and other leaf image processing based models when applied to quinoa and amaranth.     

Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation

Plant phenology has gained new importance in the context of global change research, stimulating the development of novel technologies for phenological observations. Regular digital cameras have been effectively used as three-channel imaging sensors, providing measures of leaf color change or phenological shifts in plants. We monitored a species rich Brazilian cerrado savanna to assess the reliability of digital images to detect leaf-changing patterns. Analysis was conducted by extracting color information from selected parts of the image named regions of interest (ROIs). We aimed to answer the following questions: (i) Do digital cameras capture leaf changes in cerrado savanna vegetation? (ii) Can we detect differences in phenological changes among species crowns and the cerrado community? (iii) Is the greening pattern detected for each species by digital camera validated by our on-the-ground leafing phenology (direct observation of tree leaf changes)? We analyzed daily sequences of five images per hour, taken from 6:00 to 18:00 h, recorded during the cerrado main leaf flushing season. We defined 24 ROIs in the original digital image, including total or partial regions and crowns of six plant species. Our results indicated that: (i) for the studied period, single plant species ROIs were more sensitive to changes in relative green values than the community ROIs, (ii) three leaf strategies could be depicted from the species' ROI patterns of green color change, and (iii) the greening patterns and leaf functional groups were validated by our on-the-ground phenology. We concluded that digital cameras are reliable tools to monitor high diverse tropical seasonal vegetation and it is sensitive to inter-species differences of leafing patterns.     

A comparison of photographic analyses used to quantify zooxanthella density and pigment concentrations in Cnidarians

Many cnidarians exist in an obligatory mutualism with dinoflagellates commonly called zooxanthellae. When these symbioses are stressed, zooxanthella densities often decrease (i.e., bleaching), resulting in reduced host fitness or mortality. Because zooxanthellae play a prominent role in the coloration of hosts, several analyses of reflected spectra from photographic images have been developed to quantify zooxanthella densities and serve as a proxy for invasive sampling methods. To date these techniques have not been compared. In this study, global information system (GIS) tools, commonly used with aerial and satellite images, and photographs of healthy and bleached sea anemones, Aiptasia pallida (Verrill), were used to compare these image analysis methods. Zooxanthella densities and chlorophyll-a concentrations were correlated with image brightness (i.e., digital number) in: the red, green, and blue bands (RGB); the average of the three RGB bands (RGB/3); intensity and saturation bands (IHS); and using a principal components analysis (PCA) of the RGB bands. RGB brightness correlations with zooxanthella densities and chlorophyll-a concentrations were highest using the blue band, followed by green, then red. Using any one band within RGB, however, restricts comparisons to similar color morphs. RGB/3, IHS or PCA transformations enable intra and inter-specific comparisons where colors may vary. Among these transformations, PCA and intensity had higher correlations, followed by RGB/3, then saturation. RGB/3 and IHS, unlike PCA, ignore the correlations between the three RGB bands, treating each pixel independently. PCA uses these correlations, and in doing so lessens the effects of heteroscedasticity in the data. In addition, the observed reciprocal relationship of intensity and saturation may serve as a standardized criterion for bleaching. Finally, this study demonstrates that GIS has broad interdisciplinary applications for spatial and spectral analyses from the individual colony to reef scale assessments.     

Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software

A digital image analysis method previously used to evaluate leaf color changes due to nutritional changes was modified to measure the severity of several foliar fungal diseases. Images captured with a flatbed scanner or digital camera were analyzed with a freely available software package, Scion Image, to measure changes in leaf color caused by fungal sporulation or tissue damage. High correlations were observed between the percent diseased leaf area estimated by Scion Image analysis and the percent diseased leaf area from leaf drawings. These drawings of various foliar diseases came from a disease key previously developed to aid in visual estimation of disease severity. For leaves of Nicotiana benthamiana inoculated with different spore concentrations of the anthracnose fungus Colletotrichum destructivum, a high correlation was found between the percent diseased tissue measured by Scion Image analysis and the number of leaf spots. The method was adapted to quantify percent diseased leaf area ranging from 0 to 90% for anthracnose of lily-of-the-valley, apple scab, powdery mildew of phlox and rust of golden rod. In some cases, the brightness and contrast of the images were adjusted and other modifications were made, but these were standardized for each disease. Detached leaves were used with the flatbed scanner, but a method using attached leaves with a digital camera was also developed to make serial measurements of individual leaves to quantify symptom progression. This was successfully applied to monitor anthracnose on N. benthamiana leaves. Digital image analysis using Scion Image software is a useful tool for quantifying a wide variety of fungal interactions with plant leaves.