how do i know what wavelength to use in a spectrometer
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ABSTRACT
The measurement of color in biology has become increasingly common. These measurements are not limited to colour vision research, merely are also constitute in studies of advice, signaling, camouflage, evolution and beliefs, and in the exam of ecology, artificial and biogenic light. Although the recent availability of portable spectrometers has made information technology simpler to measure colour, guidance on how to make these measurements has non kept footstep. Because nigh biologists receive picayune training in optics, many measure the incorrect thing, or measure the right thing in the wrong way. This Commentary attempts to give biologists a cursory overview of how to mensurate light and colour using spectrometers and calibrated photographs. It focuses in detail on the inherent ambiguities of many optical measurements, and how these can be addressed.
Introduction
To begin at the beginning, one does not measure out color. Color is a perceptual quality, and measuring it makes no more than sense than measuring verse. So, when we discuss the measurement of colour, nosotros are in fact talking most measuring variation in optical properties such as intensity, reflectance and transmittance (see Glossary) over a spectral range – usually the ultraviolet and human-visible portions of the electromagnetic spectrum. Typically, this measurement is performed at a fine wavelength resolution and is chosen a spectrum (east.grand. spectral reflectance, spectral radiance; see Glossary), but there are cases where it is sufficient to mensurate the variation between a few broad spectral regions. In either state of affairs, the resulting data are often integrated into one of the diverse models of color vision to create an estimate of color as perceived by humans or other animals (Endler, 1990; Kelber et al., 2003; Endler and Mielke, 2005; Kemp et al., 2015). This Commentary addresses the beginning part of this process, focusing on the physical act of measuring spectral variation using spectrometers or calibrated photographs.
There are two primary classes of spectra. The kickoff grade compares what an object does to calorie-free relative to what some standard does to it and falls into 2 types, reflectance spectra and transmittance spectra. In the erstwhile, the amount of light reflected from an object is compared – wavelength by wavelength – with the corporeality of light reflected from a standard object, usually a flat white surface. In the latter, the amount of calorie-free transmitted by an object is compared – once more wavelength by wavelength – with the corporeality of light transmitted by a standard medium, commonly air or h2o. The second class of spectra measures lite itself, for example, photon flux every bit a function of wavelength. These spectra are over again of two dissimilar types, radiance and irradiance (encounter Glossary). Radiance measures the amount of light arriving from a certain small region, and irradiance measures the amount of light arriving at a certain small region.
Although these two classes of spectra appear similar, they are fundamentally unlike. Nigh importantly, reflectance and transmittance – considering they are normalized by standards – are unitless ratios, whereas radiance and irradiance measure power or photon flux. This means that measurements of the latter have to be done using calibrated instrumentation. It likewise ways that the measured values depend on the units (e.grand. Watts versus photons), including whether you retrieve of low-cal in terms of wavelength or frequency. On the ane hand, this can make measuring radiance and irradiance complicated. On the other hand, radiance and irradiance have well-defined meanings, whereas reflectance and transmittance practise non. For example, a foliage does not have a unmarried reflectance spectrum, even at just one spot. Instead, information technology has many reflectance spectra, which depend on the angle of the light hitting the leaf and the angle of the detector viewing the leaf. Similarly, a single spot on a leaf does not accept 1 transmittance spectrum, merely an infinite number, depending on how y'all measure it.
Depending on the property that one wants to characterize, measurement of any of these spectra may be a valid arroyo, but choosing ane requires clear-mindedness about what whatsoever given measurement ways and what properties are important to your system. Therefore, although this Commentary does requite a cursory tutorial on how to measure spectra, it mostly focuses on how to be more thoughtful. As with all instrumentation, a spectrometer will happily spit out numbers. The fox is knowing what those numbers mean.
Glossary
Azimuth
In a polar coordinate system, the azimuth is the horizontal angle, as opposed to elevation, which is the vertical bending. For example, the azimuth of the rising dominicus in an equatorial region is East, whereas the summit of the sunday is close to cipher.
Collimation
The shaping of lite into a parallel beam. This is usually done by putting a convex lens one focal distance away from a light source.
Lambertian surface
A surface that reflects light evenly in all directions. The radiance of the surface is equal to the irradiance striking it multiplied by the reflectance of the surface, divided past π. Good examples of approximately Lambertian surfaces are cotton textile and matte paint.
Irradiance
The corporeality of light striking a surface or intersecting a pocket-size volume of space. The showtime, most commonly used by biologists, is termed vector irradiance, the second is termed scalar irradiance. Irradiance measurements are most oft used to quantify the overall illumination level.
Radiance
The amount of light reaching a viewer (or a detector) divided by the (typically small-scale) angular area of the sampled region. For example, to measure the radiance of the sunday using a light detector, one would showtime measure the corporeality of low-cal entering the detector and and so split it by the athwart expanse of the sun in steradians (∼0.00006 sr).
Reflectance
The amount of light leaving a surface divided by the amount of lite that strikes information technology. There is no single value for this, because it depends on the angle of the incident lite and the angle of the reflected lite.
Spectrum
The amount of light (or reflectance or transmittance) as a loftier-resolution function of the wavelength or frequency of the lite.
Specular surface
A surface that reflects low-cal similar a mirror.
Transmittance
The amount of light that passes through a substance divided by the corporeality of lite that entered it. As with reflectance, the value depends on the geometry of the entering light and how much of the exiting light is measured.
Measuring reflectance spectra
As mentioned to a higher place, at that place is no such thing as the 'reflectance spectrum' of a surface, even a surface as uniform as blank paper. For nearly all surfaces, the measured reflectance depends on the angle of the incident calorie-free and the angle of the detector viewing the reflected low-cal. Because both of these can vary over the entire hemisphere of angles above the surface, the true reflectance of an object (fifty-fifty at but 1 wavelength) is a four-dimensional object known every bit the bidirectional reflectance distribution function (BRDF), the 4 dimensions being the angle and azimuth (see Glossary) of both the incident light and the detector. The variation in reflectance over the BRDF can be large, even for unproblematic surfaces at but i angle of incidence (Fig. ane) – a fact that is ignored by almost all biology studies that measure reflectance, including many of the author'south own.
Fig. 1.
Sample bidirectional reflectance distribution function (BRDF) of i location on the savannah near Skukuza, South Africa (25.0°S, 31.v°E), for half dozen visible and near-infrared wavelengths. In each polar plot, the distance from the heart represents the angle of the reflected lite relative to the perpendicular to the ground. The angle and azimuth of the incident sunlight is constant and roughly at the location of the brightest spot on nearly all six plots (zenith angle 67 deg, azimuth 180 deg, marked past a small white circumvolve in the upper left plot only). Annotation that the savannah is strongly backscattering at almost-infrared wavelengths. Reprinted from Gatebe et al. (2003), with permission.
Fig. 1.
Sample bidirectional reflectance distribution function (BRDF) of one location on the savannah most Skukuza, South Africa (25.0°Due south, 31.5°E), for half-dozen visible and near-infrared wavelengths. In each polar plot, the distance from the center represents the angle of the reflected lite relative to the perpendicular to the basis. The angle and azimuth of the incident sunlight is constant and roughly at the location of the brightest spot on most all six plots (zenith bending 67 deg, azimuth 180 deg, marked by a small white circle in the upper left plot simply). Annotation that the savannah is strongly backscattering at nearly-infrared wavelengths. Reprinted from Gatebe et al. (2003), with permission.
Experimental prepare-ups for measuring reflectance
Unfortunately, measuring the BRDF for even a sheet of paper is hard, and for biological samples information technology is impractical at best. So what can exist washed? Sure surfaces, termed Lambertian (run across Glossary), reflect light every bit in all directions and besides take a reflectance that does not depend on the angle of incidence. Commercial reflectance standards approach this platonic and cotton cloth is not a bad approximation to it, only biological surfaces tend to be more complicated. So the researcher is left with iii options, none of which are ideal: (1) measuring reflectance using an established geometry (i.e. an established experimental set up-upward); (2) using a measurement geometry that mimics the biological situation of interest; or (three) studying only Lambertian or mirrored surfaces.
First and most commonly, one tin can mensurate reflectance using a geometry that has been used many times earlier. Although this does not measure the one true reflectance, it does allow 1 to compare new data with previous work. Two common geometries are: (1) illuminate the surface from straight above and place the detector at a 45 deg angle (Fig. 2A) and (2) illuminate the surface at 45 deg and employ an integrating sphere to collect all the reflected light (Fig. 2B). The integrating sphere is coated with a highly cogitating inner surface that scrambles the light to the betoken where its original direction of reflection is lost. Sure companies sell integrating spheres with built-in light sources and a switchable light trap at only the correct angle so that specularly reflected light (equally from a mirror or moisture surface) tin can be included or excluded with the flip of a lever. A third mutual geometry is to illuminate the surface and measure it at the aforementioned angle, using a reflection probe (Fig. 2C). This generally consists of a parallel packet of cobweb optic cables, some of which carry light from a source that illuminates the surface (unremarkably at 45 deg), and some of which carry the reflected light back to a spectrometer. These iii measurement methods may give different answers for many natural surfaces. For instance, in the example shown in Fig. 1, a reflectance probe at 67 deg from the perpendicular would mensurate the reflectance of the savannah footing at 870 nm as approximately 75%, whereas an integrating sphere measurement of the aforementioned location (with the incident light too at 67 deg) would instead measure a value averaged over all reflected angles (∼40%).
Fig. two.
Three common geometries for measuring reflectance. The direction of the calorie-free is indicated using gray arrows. (A) Light is passed from the source (box with dominicus) through a fiber optic cable and and so illuminates a sample (orangish rectangle). A fraction of the reflected light (orange lines) is nerveless by a 2d fiber optic cable that is coupled to a spectrometer (box with spectrum). (B) Low-cal from the source is collimated (run across Glossary) into a beam (shown in xanthous) that then strikes the sample, which covers the opening of an inverted integrating sphere. The black line within the sphere denotes a baffle that prevents direct reflected light from reaching the exit port of the sphere. A fraction of the reflected calorie-free, which is scattered about the inside of the sphere, is collected by a 2nd fiber optic cable that again is coupled to a spectrometer. The light that is reflected in a mirror-like manner (shown in ruby) is oft caught in a light trap so that it can be excluded. (C) Calorie-free from the source runs through a fiber optic cable that is parallel to and bundled with a second fiber optic cable that is connected to the spectrometer, and so that the angle of incidence equals the angle of detection.
Fig. 2.
Three common geometries for measuring reflectance. The direction of the light is indicated using gray arrows. (A) Light is passed from the source (box with lord's day) through a fiber optic cablevision and so illuminates a sample (orange rectangle). A fraction of the reflected low-cal (orange lines) is collected past a second fiber optic cablevision that is coupled to a spectrometer (box with spectrum). (B) Light from the source is collimated (see Glossary) into a beam (shown in yellow) that then strikes the sample, which covers the opening of an inverted integrating sphere. The black line inside the sphere denotes a baffle that prevents direct reflected light from reaching the leave port of the sphere. A fraction of the reflected calorie-free, which is scattered most the inside of the sphere, is collected by a 2d cobweb optic cablevision that once again is coupled to a spectrometer. The light that is reflected in a mirror-similar way (shown in ruby-red) is often defenseless in a light trap so that it can be excluded. (C) Light from the source runs through a fiber optic cablevision that is parallel to and bundled with a second fiber optic cablevision that is connected to the spectrometer, and then that the angle of incidence equals the angle of detection.
A 2nd choice for dealing with the unavoidable ambiguity of reflectance spectra is to utilise a measurement geometry that mimics the ecological situation existence studied. For example, if i is interested in how a ladybug looks to another ladybug itch behind it on a sunny 24-hour interval, one tin can illuminate from higher up and mensurate from the angle of the potential viewer. However, unfortunately, illumination and viewing geometries in nature are seldom constant. A third selection is restricting oneself to studying nearly Lambertian or highly mirrored surfaces, both of which are easily characterized. Unfortunately again, these are uncommon. So, in full general, one must take that reflectance is in the eye of the beholder and be clear-minded and explicit about what is beingness measured.
Instrumentation and standards
Aside from the critical event of reflectance geometry, the measurement of spectral reflectance is not difficult, but it does crave attending to detail. The illumination source can be anything, and so long as information technology provides adequate intensity over the required spectral range. The light source as well needs to provide even and stable illumination over the region seen by the detector and non movement during the actual measurement. The detector is typically a cobweb optic cablevision coupled to a portable spectrometer. The fiber optic cable allows the user to easily choose the viewing bending and region to exist viewed, and the spectrometer measures the entire spectrum at in one case, unremarkably in a small fraction of a second and to a resolution of ∼one nm. The issues of purchasing and using a spectrometer are given in detail in Johnsen (2012), but most spectrometers are uncomplicated to employ in reflectance mode. The best fashion to know whether the fiber optic cable is truly viewing the correct region of your sample is to temporarily unplug it from your spectrometer and plug it into a light source. Because calorie-free travels the same path frontwards and backward, what is now illuminated on your sample is what is being viewed by the spectrometer.
The spectrum of the reflected low-cal is not reflectance. Instead it is reflected radiance, which is discussed in the penultimate section of this Commentary. In order to convert it into spectral reflectance – thus making information technology independent of the spectrum of the illumination – it must be normalized wavelength past wavelength by the reflected radiance from a standard. As mentioned above, this standard is usually a white Lambertian surface with a reflectance that is substantially 100% in the ultraviolet and visible portions of the spectrum. This surface is typically made of an expensive, proprietary plastic known as Spectralon that is formed into a disk, although barium sulfate and magnesium oxide coatings are sometimes used. One can apply a sail of white paper for a standard, but at some point the reflectance of the paper itself will demand to be measured, which requires a genuine standard. In add-on, most paper strongly absorbs ultraviolet radiation (UVR) and often fluoresces equally well. White Teflon plumber's tape also works and typically does not absorb UVR or fluoresce, simply at some point still needs to exist calibrated.
The operating software that is packaged with almost spectrometers automatically divides the reflected radiance from the sample past the reflected radiance from the standard to create a reflectance spectrum. However, information technology is essential that the geometry of the standard measurement exactly matches that of the sample measurement. In other words, the standard's surface must exist in the aforementioned spot (relative to the lite source and the detector) equally the sample surface to within a millimeter. The relative angles must besides friction match to inside a degree or and so, which is difficult considering few biological surfaces are apartment. This means clamping everything down, which tin be tricky because fiber optic cables and biological samples do not clamp well. This cannot be overstressed, and it is instructive to measure out a sample (or the standard) multiple times to come across how much variation can upshot from fifty-fifty pocket-size changes in geometry (or from drift in the output of the illuminating low-cal source). This requirement for technical rigidity in the face up of biological fluidity is the biggest challenge of reflectance measurement. Often, a person measuring reflectance of biological samples spends 95% of the time designing and building an adequate set-up and 5% of the time performing the actual measurements (come across Meadows et al., 2011).
You lot must ensure that your light source emits light at all the wavelengths you crave, otherwise both your sample measurement and your standard measurement will be approximately equal because both are only the electrical racket of the spectrometer, and your calculated reflectance (which is a quotient of the two numbers) will be nearly 100%. At that place are many papers that erroneously written report loftier reflectance in the ultraviolet because the illuminating tungsten bulb did non emit plenty ultraviolet lite. Xenon sources are better for this. Also, if you are measuring something that is not opaque, be sure to identify it on a matte black surface, otherwise the reflectance of the material under your sample will artificially inflate the values. Ecology lite may do the same, so shielding the set-upwards is sometimes necessary. Finally, because the refractive index of the medium relative to the sample affects reflectance (see Johnsen, 2012), equally does just being wet (consider wet sand relative to dry sand; Bohren and Clothiaux, 2006), aquatic samples are best measured within water, ideally with the source and detector probes within the water as well to avoid refraction and reflection at the h2o surface. This means that the reflectance standard must also exist measured in water. Spectralon is hydrophobic, so one must wipe off any bubbles to get an authentic reading of its reflectance. After this is done, the reflectance of the underwater standard is not likewise unlike from the reflectance in air (Voss and Zhang, 2006).
Measuring transmittance spectra
Every bit with reflectance, in that location is no single transmittance spectrum for an object. Transmittance of form depends on the thickness of the sample, just even for a compatible material of one thickness, in that location are an infinite number of transmittances. In this case, the variation does not ascend from the angles of the light source and the detector, only instead from the angular spread of the low-cal that is collected by the detector. This is because the transmittance of calorie-free through an object depends on both calorie-free absorption and light scattering, the quondam not irresolute the management of the incident lite, the latter irresolute it substantially (meet Johnsen, 2012 for further details on the assimilation and scattering of light). In certain cases, i wants to know how much low-cal has passed through an object, regardless of whether the direction of that light has been hopelessly scrambled past scattering inside the object. This is ofttimes known as diffuse transmittance and is useful when one but cares virtually how much light is transmitted (e.g. studies of lite under forest canopies or light deep inside tissue). In other cases, y'all may want to know how much of a parallel axle of calorie-free has made information technology through the object without being absorbed or scattered. This is sometimes referred to as directly transmittance. For instance, frosted drinking glass and clear drinking glass may ultimately permit through the same amount of light, just well-nigh all the light that has passed through the frosted glass has lost its original management, whereas the directionality of the light passing through the articulate glass is preserved. Straight transmittance is especially important for studies involving vision (e.g. image propagation through water or fog, or investigations of the clarity of the cornea and ocular lens).
However, at that place is no clear way to distinguish between low-cal that has gone straight through a substance and light that has been scattered over small angles. The ideal ideal for measuring directly transmittance involves a perfectly parallel and infinitesimally thin axle of light that goes through the material and and then is detected by an infinitesimal (or infinitely far away) detector that thus just collects that low-cal that has not scattered at all, even over the tiniest of angles. In reality, yet, detectors have finite sizes and are non infinitely far away, then they collect both the unaffected beam and some of the forward-scattered light. The ratio of the bore of the detector to its distance from the sample determines how much of this scattered light is collected, and then a bigger or a closer detector collects scattered light over larger angles, making the transmittance larger. For many important biological materials, much of the low-cal is scattered over these small angles, so this is a relevant and unavoidable problem.
For better or worse, at that place is no standard working definition of directly transmittance. So, as with reflectance, this again leaves one making choices. In the case of diffuse transmittance, the best method is to utilize an integrating sphere that collects all the light that has passed through the sample, whether it has been scattered or not (Fig. 3A). In the case of direct transmittance, choosing a detector size and distance and then that all light scattered by <1 deg is collected seems a reasonable, although capricious, choice (Fig. 3B). Just call up that information technology is a choice; in that location is no official direct transmittance, but instead one that depends on the geometry of the measurement system. Every bit with reflectance, in certain cases one can make an ecologically informed pick.
Fig. iii.
Possible geometries for measuring diffuse and direct transmittance. (A) A common geometry for measuring diffuse transmittance. Light from the source that has passed through the orange sample is then reflected many times inside an integrating sphere. A fraction of this light is collected by a fiber optic cablevision that is coupled to a spectrometer. (B) A common geometry for measuring straight transmittance. Light from the source is collimated into a beam by a small lens. This and so passes through the sample (in this case a beroid ctenophore), which both scatters and absorbs information technology. The low-cal that is neither captivated nor scattered over large angles passes through a small hole, is focused onto a fiber optic cablevision and sent to a spectrometer. Adapted from Johnsen (2012).
Fig. 3.
Possible geometries for measuring lengthened and direct transmittance. (A) A common geometry for measuring lengthened transmittance. Light from the source that has passed through the orange sample is then reflected many times within an integrating sphere. A fraction of this low-cal is nerveless by a fiber optic cable that is coupled to a spectrometer. (B) A common geometry for measuring direct transmittance. Calorie-free from the source is collimated into a beam by a minor lens. This so passes through the sample (in this case a beroid ctenophore), which both scatters and absorbs it. The lite that is neither absorbed nor scattered over large angles passes through a small pigsty, is focused onto a cobweb optic cable and sent to a spectrometer. Adapted from Johnsen (2012).
The mechanics of measuring transmittance are much like those of measuring reflectance, with the standards for measures of transmittance being air for terrestrial samples and water for aquatic samples. One must withal worry about the mechanical stability of the set-upwardly, the spectral range of the lite source and whether the sample should be in h2o or not. Designing the ready-up can be peculiarly challenging for measuring straight transmittance because the shape of a transparent object can deflect and even focus the light beam. For example, measuring the direct transmittance of an ocular lens can exist nearly impossible, because, despite its exquisite clarity, information technology completely reshapes the light beam.
Measuring spectral variation from calibrated photographs
Although reflectance and transmittance measurements of artificial substances such as paper and glass can be precise, measuring the optical properties of biological samples is often frustrating. Animals and plants can be squishy, flimsy, small, morphologically circuitous or all of the above. They can too movement. It does not aid that so many organisms and their associated parts are either spheroids or cylinders, both of which tin can focus transmitted calorie-free and ship reflected light in all directions. Repeated measurements of the spectral reflectance of even a dead spider leg, for example, tin can be extremely variable. Finally, individual spectral measurements are a slow and inefficient way to understand the spatial variation of an optically complex tissue, such as a butterfly wing.
Spectral imaging is ane potential solution to many of these problems. An entire tissue or organism illuminated by a diffuse flash can be recorded at one time, eliminating the demand for individual measurements. The downside of this approach is that information technology sacrifices spectral resolution. Instead of obtaining a measurement for every nanometer, all the information is dumped into a few bins, usually the red, green and blue channels of the photographic camera. There are multispectral imaging systems with high spectral resolution, merely they tend to be either custom congenital or extremely expensive (e.g. Chiao et al., 2011), so the remainder of this section focuses on what can be done with a standard camera.
Although a camera but provides three channels, this spectral resolution can be sufficient for many purposes. For example, although color vision models typically demand fine-resolution spectra, many measurements of color are motivated past other factors, such equally the want to classify organisms or tissues [due east.g. comparing the colors of flowers (Muchhala et al., 2014) or assessing the saturation of trunk coloration in guppies relative to immunocompetence (Martin and Johnsen, 2007)]. Information technology is likewise well known that well-nigh variation in natural spectra can be captured using just iii or four principal components (Buchsbaum and Gottschalk, 1983; Chiao et al., 2000). Also, with filters and some cleverness, it is sometimes possible to change the spectral sensitivities of the photographic camera channels so that they guess those of various photoreceptor classes (e.g. Troscianko and Stevens, 2015). Thus, the 3 channels of a commercial digital camera, although designed for human vision, are useful for capturing spectral variation in general, though only in the human-visible portion of the spectrum. Important exceptions to this dominion are the few narrow-band spectra in nature, such every bit bioluminescent emissions or reflections from iridescent tissues. For example, a camera without specialized filters cannot distinguish violet from blue bioluminescence – both will announced blue.
Assuming that three channels exercise suffice for the project at mitt, the main issue is calibration. Unlike a spectrometer, a camera is non designed to deliver calibrated numbers. Earlier one even sees the prototype on the monitor on the back of the camera, it has been tweaked in many unseen and proprietary ways, more often than not to make human faces more appealing. The prototype is also non linear, pregnant that a grayscale value of 200 is not twice as brilliant as a grayscale value of 100. In add-on, lighting tends not to be constant. Tungsten and fluorescent bulbs, and even the on-photographic camera flash, tin vary erratically, and some studies demand outdoor light, which varies even more. Finally, most cameras also have automated white balance settings, which further affect the epitome. The color constancy of our own visual system (Cronin et al., 2014) minimizes the perceptual effects of these changes, but they occur nevertheless and affect whatsoever effort to measure out color.
It is possible to create a highly controlled lighting surroundings and to develop a repeatable photographing procedure, allowing one to calibrate everything alee of time (see Troscianko and Stevens, 2015), but a safer solution is to place a scale standard inside each prototype and then that it tin can never be lost (Tedore and Johnsen, 2012), much like geologists place a hammer or a coin for scale. For example, the scale standard can be a gear up of grey regions that vary from nighttime to light greyness (Fig. 4A). Grayscale standards can be purchased, only they are likewise easy to create on a computer for printing out or can be assembled using paint swatches. The paint swatch approach is especially useful for small standards where information technology becomes obvious that computer-printed grays are only a collection of small black dots. The verbal shades are unimportant, then long as they bridge the range that might appear in the sample. The reflectances of the shades must exist known and are best measured using the integrating sphere procedure described in a higher place (Fig. 2B). The exposure of the photo that includes the sample and the standard needs to exist such that no color channel of the darkest square of the standard in the image reaches zero, and no aqueduct of the lightest square reaches 255. If this does occur, then it is impossible to make up one's mind how light or nighttime that region is. For example, one cannot determine whether the white region is but a little brighter than a grayscale value of 255 or ten times brighter. And then long as the exposure does not saturate the standard in either direction, so information technology does not matter what the camera software has done to the image or whether the lighting inverse from a previous photo, because the standard has been affected in the aforementioned way as the sample. The one exception to this is the saturation control of the camera software, which can leave grays equally gray but brand colors more saturated. For this reason, it is best to use RAW images, which are the data from the sensors prior to any white-point balancing or other non-linear transformation. Another solution is to substitute the grayscale standard series with three series, with increasing intensities of red, light-green and blue.
Fig. 4.
A method of obtaining reflectance from a photograph. (A) A gray standard fix with known reflectances (numbers in pie chart, given as percentage reflectance averaged over 400–700 nm) is placed next to the sample and photographed. The average RGB values for a small square on the toy salamander are shown in the orange box. The image was deliberately left with a poor white balance to prove that this does not affect the success of this process. (B) The RGB values of each greyness shade in the pie nautical chart are recorded and and so plotted against the actual reflectances of the shades in each color aqueduct to create three fitted curves, one for each color. The equations of these curves can then be used to convert the RGB values of any role of the sample into calibrated reflectance values (shown in the green box in A for the sampled region on the salamander).
Fig. 4.
A method of obtaining reflectance from a photo. (A) A gray standard set with known reflectances (numbers in pie nautical chart, given as percentage reflectance averaged over 400–700 nm) is placed next to the sample and photographed. The boilerplate RGB values for a small square on the toy salamander are shown in the orangish box. The image was deliberately left with a poor white balance to show that this does non impact the success of this process. (B) The RGB values of each grey shade in the pie chart are recorded and so plotted against the actual reflectances of the shades in each color aqueduct to create three fitted curves, ane for each color. The equations of these curves can then be used to convert the RGB values of any part of the sample into calibrated reflectance values (shown in the green box in A for the sampled region on the salamander).
To measure the reflectances (averaged over the three color channels of the camera) of a region of the sample, 1 outset obtains the R, Thou and B values of the region using image processing software – generally averaged over a set of adjacent pixels. The R, Thou and B values of each of the gray standards is then plotted and fitted to a bend for each channel, typically an exponential function for near color spaces (Fig. 4B). So, the actual reflectance respective to the RGB values obtained from the sample tin be obtained from the equations of the three fitted curves. This process can exist automatic in a number of unlike ways and gives authentic results regardless of photographic camera software, exposure settings and variation in the illumination – then long as the illumination of the sample is the same as that of the standard.
Measuring spectral radiance and irradiance
Radiance and irradiance
Although almost measurements of 'color' are of reflectance (and occasionally transmittance), at that place are times when one wants to mensurate the actual spectrum – i.e. the power or photon flux as a function of spectral region. These cases commonly involve the measurement of environmental light and bioluminescent emissions, but can also include measurements of reflected or transmitted light. For instance, although many researchers model the appearance of an object by multiplying the spectral reflectance past the spectrum of the light illuminating the object, for all the reasons discussed in this Commentary information technology is more than accurate to measure the actual reflected lite.
However, in that location are a number of issues to consider. First, every bit with reflectance and transmittance, one must make a decision about measurement geometry, in this case the angular region over which the light is nerveless. Although one can collect calorie-free from regions of an infinite multifariousness of shapes and sizes, two limiting cases are most normally used – termed radiance and irradiance. Radiance measurements collect light from a region in space, usually a small one, and are divided past the solid angle of the region viewed. They are used when one wants to measure out the 'brightness' or 'color' of an object. Irradiance measurements, past dissimilarity, collect calorie-free from a large region of space, unremarkably an entire hemisphere and sometimes over the complete sphere. The most common form of irradiance in biology is termed 'vector irradiance', and involves the collection of light over the entire hemisphere above the surface of the detector. This light is weighted so that calorie-free perpendicular to the surface counts the about, and light parallel to the surface does non count at all. In between these 2 angles, the weight of light depends on the cosine of the angle. Although this seems arbitrary, the integrated end result is an accurate measure of the amount of calorie-free energy imparted to a surface. Irradiance measurements are used when one wants to measure the overall illumination spectrum in a habitat or the amount of low-cal entering an centre.
A spectrometer can simply measure how much free energy enters it; information technology does non know what it is looking at. And so setting a spectrometer to measure radiance or irradiance depends on what are called the 'sampling eyes', in nigh cases something screwed onto the end of the fiber optic cable that determines the field of view. If the sampling optic is a Gershun tube (Fig. 5A), which is a device used to limit the field of view of the fiber to a small athwart area, and so the spectrometer is measuring radiance (and so long as the measurement is divided by this area). If the sampling optic is a cosine corrector (a small, expensive piece of white plastic) or an integrating sphere (Fig. 5B), then the spectrometer is measuring vector irradiance. The 'vector' in vector irradiance is in that location to remind y'all that the irradiance depends on the orientation of the sampling eyes. For case, pointing the cosine corrector upwardly will measure out downwelling irradiance and pointing it sideways will measure sidewelling irradiance.
Fig. 5.
Sampling eyes for the measurement of radiance and irradiance. (A) A Gershun tube used to measure radiance. The normally large field of view of the fiber optic cable is reduced by a small opening at the end of the cylinder. (B) 3 dissimilar, only functionally equivalent, sampling eyes for measuring vector irradiance. The left panel shows a cosine corrector that diffuses lite that passes through it. In the eye is an integrating sphere that collects light from all directions. The correct console shows a Spectralon surface that is viewed by a fiber optic cable. The inwards-pointing arrows in all three images depict the incident light. Adapted from Johnsen (2012).
Fig. five.
Sampling eyes for the measurement of radiance and irradiance. (A) A Gershun tube used to mensurate radiance. The normally large field of view of the cobweb optic cable is reduced by a pocket-sized opening at the terminate of the cylinder. (B) Three different, but functionally equivalent, sampling optics for measuring vector irradiance. The left panel shows a cosine corrector that diffuses light that passes through it. In the middle is an integrating sphere that collects light from all directions. The right console shows a Spectralon surface that is viewed by a fiber optic cablevision. The inward-pointing arrows in all three images depict the incident light. Adapted from Johnsen (2012).
Calibration
The second major consequence related to measurements of spectra is calibration. Because reflectance and transmittance spectra are ratios relative to a standard and non measurements of light itself, they practise not accept units and thus do non require calibration. Radiance and irradiance, still, practise require this. Well-nigh spectrometer software will guide you through the tedious calibration process, and some spectrometers fifty-fifty come pre-calibrated. This can be a time-saver, simply it is important to realize that anything you attach to your spectrometer – for example, a fiber optic cable – will modify this calibration. Short lengths of these cables do non affect visible lite significantly, just long lengths (>5 m) will, and any length tin bear upon calibration in the ultraviolet, because the glass in the cablevision significantly absorbs radiations in this region. These pre-set calibrations too drift over fourth dimension, usually requiring you to send the spectrometer back to the company for re-scale.
Although calibration is straightforward, information technology is connected to the of import concept that the shapes of low-cal spectra are not universal, merely instead depend on the units used (Fig. 6). Get-go, because short-wavelength photons are more energetic than long-wavelength photons, a spectrum calibrated in photon flux (e.g. for a vision study) is shifted to longer wavelengths than a spectrum calibrated in power units (e.g. for a thermoregulation study). Second, all calorie-free spectra are histograms. Biologists nearly always calibrate them in bins of equal wavelength – i.east. the spectrum is 'per nanometer'. However, information technology is merely as reasonable, arguably more than so, to bin spectra in equal frequency units (Hertz), which dramatically changes the shape of the spectrum. This is important, because the spectral sensitivity curves of cameras and optics do non suffer from this trouble – they stay the same. Therefore, one cannot simply choose Watts versus photon flux and nanometers versus Hertz and assume that at least the relative shapes and positions of the relevant curves volition stay the same – the radiance or irradiance will change, simply the spectral sensitivity curve will not. This ways that common statements such equally 'human spectral sensitivity peaks near the pinnacle wavelength of daylight' have no merit. See Soffer and Lynch (1999), Heald (2003), Bohren and Clothiaux (2006) and Johnsen (2012) for lively discussions of this subtle and far-reaching consequence. Also, the oft-used concept of a 'neutral spectrum' equally an experimental control similarly has no meaning. A flat spectrum in Watts nm−1 will not exist flat in photons nm−1 and volition be steeply sloped in Watts Hz−1 or photons Hz−ane. This is inescapable.
Fig. six.
The shape of a light spectrum depends on the units used. The aforementioned daylight spectrum is shown plotted equally Watts nm−1, photons nm−1 and photons Hz−1. The spectra are all normalized to the same pinnacle for clarity.
Fig. 6.
The shape of a light spectrum depends on the units used. The same daylight spectrum is shown plotted as Watts nm−1, photons nm−1 and photons Hz−i. The spectra are all normalized to the same top for clarity.
Conclusion
The recent improvements in spectrometers and cameras, combined with the growth of the field of visual environmental and the marvelous, slow-motility merger of biology and physics, mean that measurements of calorie-free and color in biology volition become ever more common. As with all measurements, one must be careful that the property that is beingness measured is both the i that the measurer thinks is beingness measured and i that is relevant to the experimental organisation at hand. This is especially true for measuring spectra, considering humans in general take piddling intuition for light levels. All the same, exercising some intendance, getting advice and explicitly reporting how a measurement was made (rather than, for case, stating 'reflectance was measured' in a methods section) will solve most problems, allowing usa to explore the fascinating intersection of calorie-free and life in a meaningful and satisfying manner.
Acknowledgements
Laura Bagge, Eleanor Caves, Kate Thomas and Drs Jamie Baldwin-Fergus, Christine Bedore, Arielle Cooley, Tom Cronin, Innes Cuthill, Marie Dacke, Tamara Frank, Yakir Gagnon, Alon Gorodetsky, Steve Haddock, Robin Hopkins, Manuel Leal, Justin Marshall, Nathan Morehouse, Dan-Eric Nilsson, Nicholas Roberts, Stacey Smith, Daniel Speiser, Martin Stevens, Alison Sweeney and Eric Warrant commented on an earlier version of the manuscript. Almut owes me a beer for writing this.
Competing interests
The author declares no competing or fiscal interests.
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