Differentiating Biological Colours with Few and Many Sensors: Spectral Reconstruction with RGB and Hyperspectral Cameras

Background

The ability to discriminate between two similar or progressively dissimilar colours is important for many animals as it allows for accurately interpreting visual signals produced by key target stimuli or distractor information. Spectrophotometry objectively measures the spectral characteristics of these signals, but is often limited to point samples that could underestimate spectral variability within a single sample. Algorithms for RGB images and digital imaging devices with many more than three channels, hyperspectral cameras, have been recently developed to produce image spectrophotometers to recover reflectance spectra at individual pixel locations. We compare a linearised RGB and a hyperspectral camera in terms of their individual capacities to discriminate between colour targets of varying perceptual similarity for a human observer.

Main Findings

(1) The colour discrimination power of the RGB device is dependent on colour similarity between the samples whilst the hyperspectral device enables the reconstruction of a unique spectrum for each sampled pixel location independently from their chromatic appearance. (2) Uncertainty associated with spectral reconstruction from RGB responses results from the joint effect of metamerism and spectral variability within a single sample.

Conclusion

(1) RGB devices give a valuable insight into the limitations of colour discrimination with a low number of photoreceptors, as the principles involved in the interpretation of photoreceptor signals in trichromatic animals also apply to RGB camera responses. (2) The hyperspectral camera architecture provides means to explore other important aspects of colour vision like the perception of certain types of camouflage and colour constancy where multiple, narrow-band sensors increase resolution.     

Colorimetric Grading Scale Can Promote the Standardization of Experiential and Sensory Evaluation in Quality Control of Traditional Chinese Medicines

Experiential and sensory evaluation is an ancient method that remains important in the current quality control system of Traditional Chinese Medicines (TCMs). The process is rapid and convenient when evaluating the quality of crude materials in TCM markets. However, sensory evaluation has been met with skepticism because it is mainly based on experience and lacks a scientific basis. In this study, rhubarb was selected to demonstrate how color-based sensory evaluation could differentiate the quality of herbal medicines objectively. The colors of the rhubarb samples, expressed as RGB values, were obtained from different parts and forms of the plant, including the plant’s surface, fracture surface color, and a powdered form with or without treatment with a color-developing reagent. We first divided the rhubarb samples into three grades based on the total content of five hydroxyanthraquinone derivatives, the major pharmacological components in rhubarb. Then, a three-layer back-propagation artificial neural network (BP-ANN), calibrated with selected training samples, was used to correlate the quality of the rhubarb with its color. The color of the rhubarb powder after coloration attained the highest accuracy (92.3%) in predicting the quality grade of the test samples with the established artificial neural networks. Finally, a standardized colorimetric grading scale was created based on the spatial distribution of the rhubarb samples in a two-dimensional chromaticity diagram according to the colors of the powdered rhubarb after color enhancement. By comparing the color between the scale and the tested samples, similar to performing a pH test with indicator paper, subjects without sensory evaluation experience could quickly determine the quality grade of rhubarb. This work illustrates the technical feasibility of the color-based grading of rhubarb quality and offers references for quantifying and standardizing the sensory evaluation of TCMs, foods and other products.     

Color image analysis of cervical neoplasia using RGB computer color specification

OBJECTIVE: To establish quantitative color image analysis for cytology, red, green and blue (RGB) color specification was applied to Papanicolaou-stained cervical smears. STUDY DESIGN: Cell samples used in this study was those from 300 cervical specimens. We analyzed the color tone of nuclei and cytoplasm of the squamous cells in the cervical smear by means of computer image analysis. RESULTS: Papanicolaou stained nuclei displayed basophilic blue to purple. When they were hyperchromatic and deeply stained, B and G values decreased in value. The RGB values of cytoplasm and nuclei decreased significantly (P < .01) as their degree of cellular atypia increased. CONCLUSION: Using RGB color specification to analyze Papanicolaou-stained cervical smears, a significant difference was perceived in the nucleus and cytoplasm between different groups of squamous cells, from normal, dysplastic and squamous cell carcinoma. These findings may help to establish automated cytology.     

Quantitative and qualitative analysis of stain color using RGB computer color specification

OBJECTIVE: To establish standardized Papanicolaou stain for cytology using RGB color specification. This new method was formerly used in DTP software application for computer color specification. STUDY DESIGN: RGB color specification was taken from a color film, optical constituents of which were made into computer software. Cell samples used in this study were from 100 sputum specimens stained with Papanicolaou stain. We analyzed the color tone of the cytoplasm of squamous cells in the smear. RESULTS: The R and B value of eosinophilic cells were demonstrated statistically by different values between normal, borderline atypical and malignant squamous cells. G and B values of light green-philic cells demonstrated a statistical difference between normal, borderline atypical and malignant squamous cells. No significant differences were found in RGB value between normal, borderline atypical and malignant squamous orangeophilic cells. CONCLUSION: Using our own method of analyzing Papanicolaou-stained sputum, a new quantitative and qualitative analysis of stain color for standardized Papanicolaou stain was introduced.     

The tissue composition of<Emphasis Type="Italic"> Montastraea franksi</Emphasis> during a natural bleaching event in the Florida Keys

In this study, we used a correlative approach to (1) test for an association between bleaching and host tissue composition during a natural bleaching event, and (2) assess whether bleaching susceptibility varies between years. In August 1997, Montastraea franksi at 15-m depth on Conch Reef, Florida, bleached and the severity of the response varied among individuals. Seventy-five randomly selected colonies were quantified for bleaching using both an ordinal scale, assigned by eye, and a continuous scale, assessed using red, green, and blue (RGB) spectral analysis of photographs. Zooxanthella density and chlorophyll a content were evaluated as measures of bleaching, and coral tissue was analyzed for glycerol, free amino acids (FAA), protein, and mycosporine-like amino acids (MAAs); collectively, these are described as the "tissue composition." In 1998, most of the same coral colonies were analyzed for color and zooxanthella density to determine whether colony color in 1997 was correlated with color in 1998. In 1997, colonies of M. franksi that were ranked by color differed significantly in RGB brightness, zooxanthella density, and chlorophyll a content, but not in tissue composition. Similarly, a multivariate test for a linear relationship between color and tissue composition did not reveal a significant association. Analyses of corals in 1997 and 1998 revealed a significant positive relationship between color in both years (i.e., the same colonies were similarly colored in each year). These results are discussed in the context of the temporal scale of the sampling regime, the nature of the measured traits, and the adaptive bleaching hypothesis.     

Primate Fruit Color: Useful Concept or Alluring Myth?

While the importance of frugivorous primates as seed dispersers is well established, the question of the extent to which they exert selective pressure on fruit color phenotypes is contested. Numerous studies have identified suites of primate fruit colors, but the lack of agreement among them illustrates the difficulty of identifying the match between primate foraging behavior and the extent of primate–plant coevolution. This may indicate that primates do not shape fruit traits, at least in a consistent direction, or that the evolution of fruit color is affected by a complex array of selection pressures in which primates play only a part. Here, we review the role of primates in shaping fruit color in the context of primate color vision phenotypes, and fruit phenotypic constraints and selective pressures. To test the hypothesis that fruit color is subjected to selection pressures by primates, we offer six testable predictions aimed at disentangling the complex array of factors that can contribute to fruit color phenotypes, including animal mutualists, animal antagonists, and developmental and phylogenetic constraints of fruits. We conclude that identifying the importance of primate seed dispersers in shaping fruit visual traits is possible, but more complex than previously thought.     

Quantification of histochemical staining by color deconvolution

OBJECTIVE: To develop a flexible method of separation and quantification of immunohistochemical staining by means of color image analysis. STUDY DESIGN: An algorithm was developed to deconvolve the color information acquired with red-green-blue (RGB) cameras and to calculate the contribution of each of the applied stains based on stain-specific RGB absorption. The algorithm was tested using different combinations of diaminobenzidine, hematoxylin and eosin at different staining levels. RESULTS: Quantification of the different stains was not significantly influenced by the combination of multiple stains in a single sample. The color deconvolution algorithm resulted in comparable quantification independent of the stain combinations as long as the histochemical procedures did not influence the amount of stain in the sample due to bleaching because of stain solubility and saturation of staining was prevented. CONCLUSION: This image analysis algorithm provides a robust and flexible method for objective immunohistochemical analysis of samples stained with up to three different stains using a laboratory microscope, standard RGB camera setup and the public domain program NIH Image.     

Multiplexing clonality: combining RGB marking and genetic barcoding

RGB marking and DNA barcoding are two cutting-edge technologies in the field of clonal cell marking. To combine the virtues of both approaches, we equipped LeGO vectors encoding red, green or blue fluorescent proteins with complex DNA barcodes carrying color-specific signatures. For these vectors, we generated highly complex plasmid libraries that were used for the production of barcoded lentiviral vector particles. In proof-of-principle experiments, we used barcoded vectors for RGB marking of cell lines and primary murine hepatocytes. We applied single-cell polymerase chain reaction to decipher barcode signatures of individual RGB-marked cells expressing defined color hues. This enabled us to prove clonal identity of cells with one and the same RGB color. Also, we made use of barcoded vectors to investigate clonal development of leukemia induced by ectopic oncogene expression in murine hematopoietic cells. In conclusion, by combining RGB marking and DNA barcoding, we have established a novel technique for the unambiguous genetic marking of individual cells in the context of normal regeneration as well as malignant outgrowth. Moreover, the introduction of color-specific signatures in barcodes will facilitate studies on the impact of different variables (e.g. vector type, transgenes, culture conditions) in the context of competitive repopulation studies.     

The biological basis of a universal constraint on color naming: cone contrasts and the two-way categorization of colors

Many studies have provided evidence for the existence of universal constraints on color categorization or naming in various languages, but the biological basis of these constraints is unknown. A recent study of the pattern of color categorization across numerous languages has suggested that these patterns tend to avoid straddling a region in color space at or near the border between the English composite categories of "warm" and "cool". This fault line in color space represents a fundamental constraint on color naming. Here we report that the two-way categorization along the fault line is correlated with the sign of the L- versus M-cone contrast of a stimulus color. Moreover, we found that the sign of the L-M cone contrast also accounted for the two-way clustering of the spatially distributed neural responses in small regions of the macaque primary visual cortex, visualized with optical imaging. These small regions correspond to the hue maps, where our previous study found a spatially organized representation of stimulus hue. Altogether, these results establish a direct link between a universal constraint on color naming and the cone-specific information that is represented in the primate early visual system.     

A novel method for the estimation of soybean chlorophyll content using a smartphone and image analysis

The development of smartphones, specifically their cameras, and imaging technologies has enabled their use as sensors/measurement tools. Here we aimed to evaluate the applicability of a fast and noninvasive method for the estimation of total chlorophyll (Chl), Chl a, Chl b, and carotenoids (Car) content of soybean plants using a smartphone camera. Single leaf disc images were obtained using a smartphone camera. Subsequently, for the same leaf discs, a Chl meter was used to obtain the relative index of Chl and the photosynthetic pigments were then determined using a classic method. The RGB, HSB and CIELab color models were extracted from the smartphone images and correlated to Chl values obtained using a Chl meter and by a standard laboratory protocol. The smartphone camera was sensitive enough to capture successfully a broad range of Chl and Car contents seen in soybean leaves. Although there was a variation between color models, some of the proposed regressions (e.g., the S and b index from HSB and Lab color models and NRI [RGB model]) were very close to the Chl meter values. Based on our findings, smartphones can be used for rapid and accurate estimation of soybean and Car contents in soybean leaves.     

The primate palette: The evolution of primate coloration

Flip through The Pictorial Guide to the Living Primates¹ and you will notice a striking yet generally underappreciated aspect of primate biology: primates are extremely colorful. Primate skin and pelage coloration were highlighted examples in Darwin's² original discussions of sexual selection but, surprisingly, the topic has received little research attention since. Here we summarize the patterns of color variation observed across the primate order and examine the selective forces that might drive and maintain this aspect of primate phenotypic diversity. We discuss how primate color patterns might be adaptive for physiological function, crypsis, and communication. We also briefly summarize what is known about the genetic basis of primate pigmentation and argue that understanding the proximate mechanisms of primate coloration will be essential, not only for understanding the evolutionary forces shaping phenotypic variation, but also for clarifying primate taxonomies and conservation priorities.     

A global risk assessment of primates under climate and land use/cover scenarios

Primates are facing an impending extinction crisis, driven by extensive habitat loss, land use change and hunting. Climate change is an additional threat, which alone or in combination with other drivers, may severely impact those taxa unable to track suitable environmental conditions. Here, we investigate the extent of climate and land use/cover (LUC) change‐related risks for primates. We employed an analytical approach to objectively select a subset of climate scenarios, for which we then calculated changes in climatic and LUC conditions for 2050 across primate ranges (N = 426 species) under a best‐case scenario and a worst‐case scenario. Generalized linear models were used to examine whether these changes varied according to region, conservation status, range extent and dominant habitat. Finally, we reclassified primate ranges based on different magnitudes of maximum temperature change, and quantified the proportion of ranges overall and of primate hotspots in particular that are likely to be exposed to extreme temperature increases. We found that, under the worst‐case scenario, 74% of Neotropical forest‐dwelling primates are likely to be exposed to maximum temperature increases up to 7°C. In contrast, 38% of Malagasy savanna primates will experience less pronounced warming of up to 3.5°C. About one quarter of Asian and African primates will face up to 50% crop expansion within their range. Primary land (undisturbed habitat) is expected to disappear across species' ranges, whereas secondary land (disturbed habitat) will increase by up to 98%. With 86% of primate ranges likely to be exposed to maximum temperature increases >3°C, primate hotspots in the Neotropics are expected to be particularly vulnerable. Our study highlights the fundamental exposure risk of a large percentage of primate ranges to predicted climate and LUC changes. Importantly, our findings underscore the urgency with which climate change mitigation measures need to be implemented to avert primate extinctions on an unprecedented scale.     

Segmentation of transitional cell carcinoma nuclei by nonsupervised thresholding in different color spaces

OBJECTIVE: To develop a method for nonsupervised thresholding of transitional cell carcinoma nuclei of hematoxylin-eosin-stained histologic sections. STUDY DESIGN: For grayscale, RGB, HSL and L*a*b* thresholding we used an extension of a clustering method, based on a between-class/within-class criterion, applying optimal gray-level thresholding to distributions of R, G, B, or H and S or L* color domains. Algorithms were tested on 20 hematoxylin-eosin-stained sections of bladder carcinomas. RESULTS: Results were compared with corresponding results of manually selected nuclear areas. Images were compared pixel to pixel with matching reference images. Grayscale automatic thresholding presented unacceptably low pixel specificity, which complicated further nuclear segmentation. Nonsupervised thresholding in RGB or HSL, as well as semimanual thresholding in L*a*b* color space demonstrated significantly better accuracy and high values of pixel specificity and sensitivity, which permitted errors of only 4.27-5.83% in the subsequent mean area estimation of the transitional cell carcinoma nuclei. CONCLUSION: Nonsupervised multispectral thresholding in RGB or HSL color space extends single graylevel thresholding techniques to multilevel thresholding. This seems to be an effective, relatively simple and fast alternative to the widely used automatic grayscale or manual color thresholding for segmentation of nuclei in routine histologic sections.     

Different selective pressures shape the molecular evolution of color vision in chimpanzee and human populations

A population genetic analysis of the long-wavelength opsin (OPN1LW, "red") color vision gene in a global sample of 236 human nucleotide sequences had previously discovered nine amino acid replacement single nucleotide polymorphisms, which were found at high frequencies in both African and non-African populations and associated with an unusual haplotype diversity. Although this pattern of nucleotide diversity is consistent with balancing selection, it has been argued that a recombination "hot spot" or gene conversion within and between X-linked color vision genes alone may explain these patterns. The current analysis investigates a closely related primate with trichromatism to determine whether color vision gene amino acid polymorphism and signatures of adaptive evolution are characteristic of humans alone. Our population sample of 56 chimpanzee (Pan troglodytes) OPN1LW sequences shows three singleton amino acid polymorphisms and no unusual recombination or linkage disequilibrium patterns across the approximately 5.5-kb region analyzed. Our comparative population genetic approach shows that the patterns of OPN1LW variation in humans and chimpanzees are consistent with positive and purifying selection within the two lineages, respectively. Although the complex role of color vision has been greatly documented in primate evolution in general, it is surprising that trichromatism has followed very different selective trajectories even between humans and our closest relatives.     

丝光绿蝇蛹壳颜色变化及其对死后间隔时间推断的意义

【目的】研究不同恒温下丝光绿蝇Lucilia sericata蛹期蛹壳颜色变化,并利用提取的蛹壳RGB值绘制标准色板,为法医学中死后间隔时间(postmortem interval, PMI)的推断提供科学依据。【方法】在16, 20, 24, 28和32℃恒温下分别饲养丝光绿蝇待其发育至蛹期,选取10头蛹为观察样本,每隔12 h定期观察蛹壳的颜色变化,拍照并利用图像分析软件提取蛹期各观察时间点蛹壳颜色的RGB值,再将分析计算后的RGB值还原为标准色板,并采用R软件对蛹发育时间与蛹壳颜色RGB值中的R值的关系进行多元回归分析和拟合。【结果】不同恒温下,丝光绿蝇蛹壳颜色随发育时间均呈现出不均衡的加深趋势,尤其在化蛹初期和临近羽化时变化明显。根据各发育时间的标准RGB值可制作出对应不同恒温的5个丝光绿蝇蛹壳颜色标准色板。【结论】在案发现场,可将检获到的蝇蛹与本研究得到的相近温度下的蛹壳颜色标准色板进行比色鉴定,初步估算蛹期,为死后间隔时间的推断提供科学依据。     

瓜实蝇对虚拟波长下不同颜色的趋性（英文）

利用害虫对不同颜色的趋性进行害虫防治, 如利用黄板对实蝇的监测和防治已有很长的历史, 然而尚未见把颜色量化进行实蝇对颜色偏嗜性研究的报道。为探明对瓜实蝇Bactrocera cucurbitae最具吸引力的颜色及其虚拟波长, 本试验应用Dan Bruton的虚拟波长与RGB值的函数关系, 把RGB值转换为虚拟波长; 选择RGB值［(0, 213, 255), (0, 255, 146), (54, 255, 0), (129, 255, 0), (195, 255, 0), (255, 255, 0), (255, 190, 0)和 (255, 119, 0)］的颜色进行打印, 这些颜色对应的虚拟波长分别是480, 500, 520, 540, 560, 580, 560和600 nm; 在八面体内进行瓜实蝇对8种颜色的偏嗜性试验。结果表明： 波长在520~560 nm 之间对应的颜色对瓜实蝇的吸引率高于其他虚拟波长对应的颜色, 而540 nm (黄绿色, RGB值为 129, 255, 0)对应的颜色纸对瓜实蝇的吸引率最大。此外田间颜色偏嗜性试验也证实了黄绿色对瓜实蝇有最强的引诱作用。结果说明, 黄绿色（虚拟波长540 nm）是吸引瓜实蝇的关键颜色, 黄绿色粘虫板可作为监测与防治瓜实蝇的一种有效方法。     

Characterization of the fecal microbiome from non-human wild primates reveals species specific microbial communities

Background

Host-associated microbes comprise an integral part of animal digestive systems and these interactions have a long evolutionary history. It has been hypothesized that the gastrointestinal microbiome of humans and other non-human primates may have played significant roles in host evolution by facilitating a range of dietary adaptations. We have undertaken a comparative sequencing survey of the gastrointestinal microbiomes of several non-human primate species, with the goal of better understanding how these microbiomes relate to the evolution of non-human primate diversity. Here we present a comparative analysis of gastrointestinal microbial communities from three different species of Old World wild monkeys.

Methodology/Principal Findings

We analyzed fecal samples from three different wild non-human primate species (black-and-white colobus [Colubus guereza], red colobus [Piliocolobus tephrosceles], and red-tailed guenon [Cercopithecus ascanius]). Three samples from each species were subjected to small subunit rRNA tag pyrosequencing. Firmicutes comprised the vast majority of the phyla in each sample. Other phyla represented were Bacterioidetes, Proteobacteria, Spirochaetes, Actinobacteria, Verrucomicrobia, Lentisphaerae, Tenericutes, Planctomycetes, Fibrobacateres, and TM7. Bray-Curtis similarity analysis of these microbiomes indicated that microbial community composition within the same primate species are more similar to each other than to those of different primate species. Comparison of fecal microbiota from non-human primates with microbiota of human stool samples obtained in previous studies revealed that the gut microbiota of these primates are distinct and reflect host phylogeny.

Conclusion/Significance

Our analysis provides evidence that the fecal microbiomes of wild primates co-vary with their hosts, and that this is manifested in higher intraspecies similarity among wild primate species, perhaps reflecting species specificity of the microbiome in addition to dietary influences. These results contribute to the limited body of primate microbiome studies and provide a framework for comparative microbiome analysis between human and non-human primates as well as a comparative evolutionary understanding of the human microbiome.     

Design and selection of trap color for capture of the tea leafhopper,Empoasca vitis,by orthogonal optimization

The tea leafhopper, Empoasca vitis (Göthe) (Hemiptera: Cicadellidae), is a major pest of the tea plant, Camellia sinensis (L.) O. Kuntze (Theaceae). In this study, the RGB color model was used to describe the colors of sticky traps. The most effective color for attraction of E. vitis was investigated by orthogonal optimization. The selected color was verified in tea gardens and the most effective height for positioning of color sticky traps for capturing tea leafhoppers was investigated. After the determination of the effect of the three color parameters and their interactions by orthogonal optimization, the color gold (RGB: 255, 215, 0) was selected as the most effective color to trap tea leafhoppers. In tea gardens, more leafhoppers were captured using gold sticky traps (RGB: 226, 204, 4) than using commercially available yellow sticky traps. The most effective height of gold sticky traps for trapping leafhoppers was 40–60 cm above the tea canopy. Few lady beetles were captured at this height. We conclude that the orthogonal optimization method is a convenient and efficient method to screen digitally generated colors for attracting and trapping of pests.     

Network measures for dyadic interactions: stability and reliability

Social network analysis (SNA) is a general heading for a collection of statistical tools that aim to describe social interactions and social structure by representing individuals and their interactions as graph objects. It was originally developed for the social sciences, but more recently it was also adopted by behavioral ecologists. However, although SNA offers a full range of exciting possibilities for the study of animal societies, some authors have raised concerns about the correct application and interpretation of network measures. In this article, we investigate how reliable and how stable network measures are (i.e. how much variation they show under re-sampling and how much they are influenced by erroneous observations). For this purpose, we took a data set of 44 nonhuman primate grooming networks and studied the effects of re-sampling at lower re-sampling rates than the originally observed ones and the inclusion of two types of errors, "mis-identification" and "mis-classification," on six different network metrics, i.e. density, degree variance, vertex strength variance, edge weight disparity, clustering coefficient, and closeness centrality. Although some measures were tolerant toward reduced sample sizes, others were sensitive and even slightly reduced samples could yield drastically different results. How strongly a metric is affected seems to depend on both the sample size and the structure of the specific network. The same general effects were found for the inclusion of sampling errors. We, therefore, emphasize the importance of calculating valid confidence intervals for network measures and, finally, we suggest a rough research plan for network studies.     

Using Delaunay triangulation to sample whole‐specimen color from digital images

1. Color variation is one of the most obvious examples of variation in nature, but biologically meaningful quantification and interpretation of variation in color and complex patterns are challenging. Many current methods for assessing variation in color patterns classify color patterns using categorical measures and provide aggregate measures that ignore spatial pattern, or both, losing potentially important aspects of color pattern.
2. Here, we present Colormesh, a novel method for analyzing complex color patterns that offers unique capabilities. Our approach is based on unsupervised color quantification combined with geometric morphometrics to identify regions of putative spatial homology across samples, from histology sections to whole organisms. Colormesh quantifies color at individual sampling points across the whole sample.
3. We demonstrate the utility of Colormesh using digital images of Trinidadian guppies (Poecilia reticulata), for which the evolution of color has been frequently studied. Guppies have repeatedly evolved in response to ecological differences between up‐ and downstream locations in Trinidadian rivers, resulting in extensive parallel evolution of many phenotypes. Previous studies have, for example, compared the area and quantity of discrete color (e.g., area of orange, number of black spots) between these up‐ and downstream locations neglecting spatial placement of these areas. Using the Colormesh pipeline, we show that patterns of whole‐animal color variation do not match expectations suggested by previous work.
4. Colormesh can be deployed to address a much wider range of questions about color pattern variation than previous approaches. Colormesh is thus especially suited for analyses that seek to identify the biologically important aspects of color pattern when there are multiple competing hypotheses or even no a priori hypotheses at all.