The authors would like to thank Dr. Richard Richards and Dr. Shek Hossain at CSIRO, Agriculture, and Food for access to and management of the field plots used for this research. This research was supported by the International Wheat Yield Partnership, through a grant provided by the Grains Research and Development Corporation (US00082). TNB was supported by the Australian Research Council (DP150103863 and LP130100183) and the National Science Foundation (Award #1557906). This work was supported by the USDA National Institute of Food and Agriculture, Hatch projects 1016439 and 1001480.

1. Build and calibrate the PARbars
<ol>
	<li>Gather all parts and tools required for the assembly in a clean workspace.</li>
	<li>Drill a 4 mm diameter hole 20 mm from each end of a white acrylic diffuser bar (1,200 mm length x 30 mm width x 4.5 mm thickness). Drill and tap threaded holes 20 mm from each end of a section of aluminum U-bar to secure diffuser. Drill and tap threaded holes to suit mounting hardware (e.g., a tripod mounting plate).</li>
	<li>Obtain a 1.25 m length of bare copper wire (1.25 mm diameter). If the wire came on a roll, then straighten it by securing one end into a vice or clamp and the other end into the grips of a hand drill, and then turning on the drill at a low speed (100-200 rpm). Repeat with a second 1.25 m length of bare copper wire.</li>
	<li>Mark the intended locations of the photodiodes along the edge of the diffuser using a fine-tip permanent marker, beginning with the first photodiode position at 13.5 cm from one end of the diffuser and the other positions located every 2 cm between the first diode and the far end of the diffuser.
	<ol>
		<li>Mark the position of the first copper wire on the diffuser by centering one photodiode on the diffuser bar with its electrical connection tabs pointing towards the sides of the bar, placing the wire underneath one of the tabs, and marking the wire&#39;s location.</li>
		<li>Repeat the preceding step to mark the wire&#39;s position at the center and the opposite end of the bar.</li>
	</ol>
	</li>
	<li>Use cyanoacrylate glue to glue the first straightened copper wire to the diffuser, using the locations marked in the preceding step to align the wire.
	<ol>
		<li>Use cyanoacrylate glue to glue 50 photodiodes face-down along the diffuser at 20 mm intervals (as marked in the preceding step), ensuring that they are in the center of the diffuser and that all are arranged all in the same orientation such that the large tab sits on the copper wire, and the small tab sits opposite.</li>
		<li>Place the second copper wire such that it sits underneath each of the smaller tabs of the photodiodes, and then glue the wire to the diffuser with cyanoacrylate glue.</li>
	</ol>
	</li>
	<li>Wet both tabs of one photodiode, as well as the adjacent and underlying wires, with flux using a solder flux pen. Solder each tab of the diode to the underlying copper wires using a fine tipped soldering iron at a temperature of approximately 350-400 oC. Test the solder connections by shining a light onto the photodiode and checking for a voltage signal across the wires using a multimeter. Repeat this step for all 50 photodiodes. 
	NOTE: Step 1.7 is optional (if the resistor is not soldered into the PARbar, it can instead later be connected in parallel with the PARbar signal inputs on the datalogger).</li>
	<li>Solder a 1.5 &#937; low temperature coefficient precision resistor in parallel across the copper wires.</li>
	<li>Solder the male end of a waterproof DC connector to the ends of the copper wires (the same ends to which the resistor was soldered, if you followed optional step 1.7) and then seal the connections using glue lined heat shrink tubing.</li>
	<li>Create a continuous silicone barrier around the circuity on the diffuser to form a fluid-tight well, by applying a bead of silicone sealant to the surface of the diffuser, near the edge. Inspect the bead closely to ensure that no air gaps remain between the silicone and the diffuser bar, as gaps will permit epoxy to leak out. Once the sealant has cured, fill the well with epoxy resin.</li>
	<li>When the epoxy resin has hardened (overnight), remove the silicone sealant using a razor blade. Bolt the diffuser to the pre-threaded aluminum U-bar using M4 bolts.</li>
	<li>Use masking tape to secure the diffuser to the aluminum along its whole length, and then fill the void inside the ceptometer with polyurethane foam filler. Once the foam filler has set (overnight), remove the masking tape.</li>
	<li>Solder the female end of the DC connector to a length of two-conductor cable and seal the connections with glue lined heat shrink.</li>
	<li>To calibrate the PARbar against a quantum sensor,
	<ol>
		<li>Connect both sensors to a datalogger or voltmeter capable of measuring a differential voltage output (connect a 1.5 &#937; low temperature-coefficient precision resistor in parallel with the PARbar if a resistor was not integrated into the design in step 1.7),</li>
		<li>Set them outside in full sun on a level plane (level with a spirit level or spirit bubble), record the outputs of both sensors across a period during which solar radiation varies widely, such as a full diurnal cycle, and determine the calibration factor for the PARbar as the slope of a linear regression of PAR reported from the quantum sensor (as the dependent variable) vs. raw voltage output (as the independent variable).</li>
	</ol>
	</li>
</ol>
2. Install in the field
<ol>
	<li>To infer effective plant area index (PAIeff), install one PARbar above the canopy (ensuring that it is not shaded by any light-absorbing elements within the canopy) and another below all light-absorbing elements whose absorptance you wish to measure (typically, below the lowest leaves), with both PARbars aligned at a 45&#176; angle to planting rows. Ensure the upper PARbar is positioned so as not to shade the lower PARbar. Level the PARbars using a spirit level or bubble level.</li>
	<li>Connect the PARbars to a datalogger or voltmeter using cables made in step 1.11. If a 1.5 &#937; low temperature-coefficient precision resistor was not integrated into the PARbar circuit during construction (step 1.7), then connect such a resistor in parallel with each PARbar at this stage.</li>
	<li>Convert differential voltage output to PAR using the calibration factor determined for each PARbar in step 1.13.</li>
</ol>
3. Calculate the effective plant area index (PAIeff)
<ol>
	<li>Calculate PAIeff for each pair of above- and below-canopy PAR measurements using the following equations6: 
	(1) <img alt="Equation 1" src="/files/ftp_upload/59447/59447eq1.jpg" />, 
	where A = 0.283 + 0.0785a &#8211; 0.159a2 (in which a is leaf absorptance), &#964; is the ratio of below- to above-canopy PAR, and K and fb are modeled by Equation 24 and Equation 39, respectively: 
	(2) <img alt="Equation 2" src="/files/ftp_upload/59447/59447eq2.jpg" />, 
	where &#967; is a dimensionless parameter describing leaf angle distribution, &#952; is the solar zenith angle, and 
	(3) <img alt="Equation 3" src="/files/ftp_upload/59447/59447eq3.jpg" />, 
	where r is PAR above the canopy (PARabove) as a fraction of its maximum possible value (PARabove,max = 2550&#8729;cos&#952;); i.e. r = PARabove/PARabove,max. Consult the literature for values of a and c appropriate to your study species (we assumed a = 0.9 and c = 0.9610 for the wheat canopies used for trial measurements presented here). 
	NOTE: A sample R script is provided as a supplementary file to assist users in developing code for automated processing of large datasets.</li>
</ol>

<ol><li>Armbrust, D. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Rapid+measurement+of+crop+canopy+cover%5BTitle%5D)+AND+%22Agronomy+Journal%22%5BJournal%5D)">Rapid measurement of crop canopy cover.</a> Agronomy Journal. 82 (6), 1170-1171 (1990).</li>
<li>Breda, N. J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ground-based+measurements+of+leaf+area+index%3A+a+review+of+methods%2C+instruments+and+current+controversies%5BTitle%5D)+AND+%22Journal+of+Experimental+Botany%22%5BJournal%5D)">Ground-based measurements of leaf area index: a review of methods, instruments and current controversies.</a> Journal of Experimental Botany. 54 (392), 2403-2417 (2003).</li>
<li>Francone, C., Pagani, V., Foi, M., Cappelli, G., Confalonieri, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparison+of+leaf+area+index+estimates+by+ceptometer+and+PocketLAI+smart+app+in+canopies+with+different+structures%5BTitle%5D)+AND+%22Field+Crops+Research%22%5BJournal%5D)">Comparison of leaf area index estimates by ceptometer and PocketLAI smart app in canopies with different structures.</a> Field Crops Research. 155, 38-41 (2014).</li>
<li>Campbell, G. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Extinction+coefficients+for+radiation+in+plant+canopies+calculated+using+an+ellipsoidal+inclination+angle+distribution%5BTitle%5D)+AND+%22Agricultural+and+Forest+Meteorology%22%5BJournal%5D)">Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution.</a> Agricultural and Forest Meteorology. 36 (4), 317-321 (1986).</li>
<li>Cohen, S., Rao, R. S., Cohen, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Canopy+transmittance+inversion+using+a+line+quantum+probe+for+a+row+crop%5BTitle%5D)+AND+%22Agricultural+and+Forest+Meteorology%22%5BJournal%5D)">Canopy transmittance inversion using a line quantum probe for a row crop.</a> Agricultural and Forest Meteorology. 86 (3-4), 225-234 (1997).</li>
<li><a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22AccuPAR+PAR%2FLAI+Ceptometer+Model+LP-80+Operator%27s+Manual%22">AccuPAR PAR/LAI Ceptometer Model LP-80 Operator's Manual</a>. , Decagon Devices, Inc.. (2017).</li>
<li>Salter, W. T., Gilbert, M. E., Buckley, T. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Time-dependent+bias+in+instantaneous+ceptometry+caused+by+row+orientation%5BTitle%5D)+AND+%22The+Plant+Phenome+Journal%22%5BJournal%5D)">Time-dependent bias in instantaneous ceptometry caused by row orientation.</a> The Plant Phenome Journal. , (2018).</li>
<li>Huang, X. H., Han, B. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aHuang%2C+XH+%22Annual+Review+of+Plant+Biology%22">Annual Review of Plant Biology</a>. Merchant, S. S. 65, Annual Reviews. 531-551 (2014).</li>
<li> <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22Application+Note%3A+Beam+fraction+calculation+in+the+LP80%22">Application Note: Beam fraction calculation in the LP80</a>. , Decagon Devices, Inc. (2009).</li>
<li>Campbell, G. S., Van Evert, F. K. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aCampbell%2C+GS+%22Light+interception+by+plant+canopies+-+efficiency+and+architecture%22">Light interception by plant canopies - efficiency and architecture</a>. , Nottingham University Press. (1994).</li>
<li>Pask, A., Pietragalla, J., Mullan, D., Reynolds, M. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aPask%2C+A+%22Physiological+breeding+II%3A+a+field+guide+to+wheat+phenotyping%22">Physiological breeding II: a field guide to wheat phenotyping</a>. , CIMMYT. (2012).</li>
<li>Murchie, E. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Measuring+the+dynamic+photosynthome%5BTitle%5D)+AND+%22Annals+of+Botany%22%5BJournal%5D)">Measuring the dynamic photosynthome.</a> Annals of Botany. 122 (2), 207-220 (2018).</li>
<li>Beddows, P. A., Mallon, E. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cave+Pearl+Data+Logger%3A+a+flexible+Arduino-based+logging+platform+for+long-term+monitoring+in+harsh+environments%5BTitle%5D)+AND+%22Sensors%22%5BJournal%5D)">Cave Pearl Data Logger: a flexible Arduino-based logging platform for long-term monitoring in harsh environments.</a> Sensors. 18 (2), 26(2018).</li>
<li>Li, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Enhancement+of+crop+photosynthesis+by+diffuse+light%3A+quantifying+the+contributing+factors%5BTitle%5D)+AND+%22Annals+of+Botany%22%5BJournal%5D)">Enhancement of crop photosynthesis by diffuse light: quantifying the contributing factors.</a> Annals of Botany. 114 (1), 145-156 (2014).</li>
<li>Lang, A. R. G., Yueqin, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Estimation+of+leaf-area+index+from+transmission+of+direct+sunlight+in+discontinuous+canopies%5BTitle%5D)+AND+%22Agricultural+and+Forest+Meteorology%22%5BJournal%5D)">Estimation of leaf-area index from transmission of direct sunlight in discontinuous canopies.</a> Agricultural and Forest Meteorology. 37 (3), 229-243 (1986).</li>
<li>Cruse, M. J., Kucharik, C. J., Norman, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Using+a+simple+apparatus+to+measure+direct+and+diffuse+photosynthetically+active+radiation+at+remote+locations%5BTitle%5D)+AND+%22Plos+One%22%5BJournal%5D)">Using a simple apparatus to measure direct and diffuse photosynthetically active radiation at remote locations.</a> Plos One. 10 (2), 19(2015).</li>
<li>Yang, G. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unmanned+aerial+vehicle+remote+sensing+for+field-based+crop+phenotyping%3A+current+status+and+perspectives%5BTitle%5D)+AND+%22Frontiers+in+Plant+Science%22%5BJournal%5D)">Unmanned aerial vehicle remote sensing for field-based crop phenotyping: current status and perspectives.</a> Frontiers in Plant Science. 8, 26(2017).</li>
</ol>

The authors confirm that they have no conflicts of interest and nothing to disclose.

Successful implementation of the protocol outlined here for building ceptometers (PARbars) depends most sensitively on two steps: 1.5 (gluing photodiodes in place) and 1.6 (soldering photodiodes to the copper wire). Step 1.5 is prone to error by aligning the photodiodes incorrectly with respect to their intrinsic polarity. For the photodiodes that we used, and which we recommend as essential specific items, the polarity is identified by virtue of the two electrical connector tabs on the diode having clearly different sizes. Thus, before applying cyanoacrylate glue and soldering the photodiodes in place, it is strongly advised to double-check that all diodes are placed with the large connector tabs facing in one direction and the small tabs facing in the other direction. Step 1.6 is prone to failure due to poor soldering technique and formation of a cold soldered junction. This can be avoided by applying thin solder flux using a flux pen immediately before soldering and ensuring that both the wire and the photodiode tab are heated with the solder tip (at approximately 350-400 oC) before soldering itself is applied to the junction. Problems with electrical connections in a PARbar typically manifest in the form of a calibration slope distinctly different from those of other PARbars. Such problems can be caught early by testing each electrical connection during construction (as described in Step 1.6), and again after all connections have been soldered, but before they have been encased in epoxy (Step 1.9). A third potential source of error arises from the failure to use a low temperature-coefficient precision resistor, whose resistance is insensitive to temperature; using an ordinary resistor will cause the error as the resistance, and hence the voltage output per unit of light absorbed by the diodes, changes with ambient temperature. The final major source of error is not unique to PARbars, but applies to all ceptometry measurements: namely, the inference of effective plant area index or leaf area index from light capture depends on features of canopy structure (notably mean leaf absorptance and leaf angle distribution; a and c in Eqns 1 and 2) that may vary during plant development and between genotypes.
There are two main areas in which the protocol described here could be modified or adapted. First, the PARbars that we present here were designed specifically for use in row crops, such as wheat and barley, but the design could easily be modified for other applications. For example, a shunt resistor with larger resistance could be used to enhance gain (mV output per unit PAR) at lower PAR ranges. For versatility, a low-temperature coefficient precision potentiometer (variable resistor) could be used to modify the PARbar&#39;s sensitivity range as needed or to make small adjustments to gain so that each of many PARbars have identical calibration slopes. Second, the photodiodes could also be used individually as quantum sensors, allowing the user to capture spatial as well as temporal variation within individual canopies for a much lower cost than possible using commercially available quantum sensors. This could be particularly valuable given the growing interest in dynamic photosynthesis under fluctuating light conditions12. Third, although we used a conventional (and expensive) datalogger for the data presented in this study, there is scope for dataloggers to instead be built using off-the-shelf componentry, enabling the creation of a combined ceptometry and datalogger system on a limited budget. The popularity of so-called maker platforms, such as Arduino and Raspberry Pi, offer great promise in this area; we suggest the open-source Arduino-based Cave Pearl project13 as a starter for further development. Cave Pearl dataloggers were designed for environmental monitoring of cave ecosystems, so ruggedness and low power demand were key considerations in their design. Similar considerations are relevant for implementation to plant phenotyping work. Cave Pearl datalogger components are inexpensive (less than USD $50 per unit) and small, which could enable them to be directly incorporated into PARbars.
Application of the PARbars described here faces three main limitations. First, the inference of plant area index or leaf area index from measured light capture is hampered by strong time-dependent biases, particularly in row crops7. This can be overcome by making repeated or continuous measurements over a day. Second, inexpensive photodiodes do not have a spectral output that is exactly proportional to photon flux (the variable of greatest interest in photosynthesis research). This can cause bias when light quality changes greatly through a canopy, although previous estimates of the resulting error indicate that it is on the order of a few percent7. Third, PARbars cannot distinguish between the direct beam and diffuse components of incoming PAR above the canopy. As diffuse radiation penetrates deeper into the canopy than direct sunlight14, transmittance will be increased and PAIeff will be underestimated as the diffuse fraction of total irradiance increases. When all radiation is diffuse, PAIeff is directly proportional to the logarithm of 1/&#964;&#160; rather than the relationship shown in Equation 115. Cruse et al. (2015)16 noted that currently available commercial instruments that can measure direct and diffuse PAR are expensive and require regular maintenance, so they designed a simple and inexpensive apparatus to address this issue. Their system consists of a quantum sensor that is routinely shaded by a motorized, moving shadowband and allows for continuous measurement of total, direct and diffuse PAR. The sensor used in the Cruse et al.16 system could be replaced with the same photodiode used in PARbars to further reduce cost and may be easily incorporated into the existing PARbar setup. These measurements could be integrated into the data processing pipeline and would further enhance the reliability of estimates of PAIeff.
The major advantage of PARbars relative to existing commercial ceptometers is their low cost, which makes it feasible to produce them in large numbers. Recently, there has been a growing interest in novel high-throughput plant phenotyping technologies for the estimation of canopy traits (for review see Yang et al., 201717). Whilst these methods are promising in that they produce huge amounts of data they are typically very indirect and require validation against conventional techniques. PARbars could serve as a cost-effective, ground-based validation tool for these new techniques.
The low production cost of PARbars also make them a viable option for continuous measurements in the field. This could be useful for several reasons. For example, continuous measurements can be used to characterize row-orientation biases to develop time-specific correction functions for instantaneous measurements (for more information see Salter et al. 20187). Continuous ceptometry can also capture short fluctuations in canopy light capture over time (sunflecks and shadeflecks) caused by clouds passing overhead, movement of the canopy, etc. Photosynthesis is known to be highly sensitive to small changes in environmental conditions and &#8216;dynamic&#8217; changes in photosynthesis are now thought to be important in driving crop yield (for review see Murchie et al., 201812). PARbars installed in the field with a suitably short logging interval could be used to capture these short fluctuations and provide better understanding of the dynamic nature of plant canopies.

Ceptometers (linear arrays of light sensors) are used to measure the proportion of photosynthetically active radiation (PAR) intercepted by plant canopies. Ceptometers are used widely for agricultural crop research due to the relatively straightforward nature of measurements and simplicity of data interpretation. The basic principle of ceptometry is that the transmittance of light to the base of a plant canopy (&#964;) is dependent on the projected area of light absorbing materials above. Measurements of PAR above and below the canopy can, therefore, be used to estimate canopy traits such as leaf area index (LAI) and effective plant area index (PAIeff) (which includes stems, culms and reproductive structures in addition to leaves)1,2,3. Reliability of PAIeff estimates inferred from &#964; is improved by modeling the effects of the beam fraction of incoming PAR (fb), the leaf absorptance (a) and the effective canopy extinction coefficient (K); K, in turn, depends on both the solar zenith angle (&#952;) and the leaf angle distribution (&#967;)1,4,5,6. It is a common practice to correct for these effects. However, there are other biases that have not received due consideration in the past due to methodological and cost limitations.
We recently identified significant time-dependent bias in instantaneous ceptometry measurements of row crops, such as wheat and barley7. This bias is caused by an interaction between row planting orientation and solar zenith angle. To overcome this bias, continuously logging ceptometers can be mounted in the field to monitor diurnal cycles of canopy light interception and then daily averages of &#964; and PAIeff can be calculated. However, continuous measurements are often infeasible due to the prohibitively high cost of commercially available ceptometers &#8211; often several thousand US dollars for a single instrument &#8211; and the requirement for measurements of many field plots. The latter is particularly evident in the -omics era where many hundreds of genotypes are required for genomic analyses, such as genome wide association studies (GWAS) and genomic selection (GS) (for review see Huang &#38; Han, 20148). We recognized that there was a need for cost-effective ceptometers that could be produced in large numbers and be used for continuous measurements across many genotypes.
As a solution, we designed easy-to-build, high-accuracy ceptometers (PARbars) at a cost of USD $75 per unit and requiring approximately one hour of labor to construct. PARbars are built using 50 photodiodes that are sensitive only in the PAR waveband (wavelengths 390 &#8211; 700 nm), with very little sensitivity outside this range, obviating the use of costly filters. The photodiodes are connected in parallel across a 1 m length to produce an integrated differential voltage signal that can be recorded with a datalogger. The circuitry is encased in epoxy for waterproofing and the sensors operate over a large temperature range (-40 to +80 &#176;C), allowing the PARbars to be deployed in the field for extended periods of time. With the exception of the photodiodes and a low-temperature-coefficient resistor, all parts required to build a PARbar can be purchased from a hardware store. A full list of required parts and tools is provided in the Table of Materials. Here we present detailed instructions on how to build and use PARbars for the estimation of PAIeff and present representative results from wheat canopies.

<table><tbody><tr><td>1.5 &amp;Omega; low temperature coefficient precision resistor</td><td>TE Connectivity Ltd., Schaffhausen, Switzerland.</td><td>UPW25 series</td><td>Could be made using multiple larger resistors in parallel but they need to have low temperature coefficient (i.e. &amp;plusmn; 3 ppm/&amp;deg;C).&lt;br/&gt; URL for commercial source: https://bit.ly/2DFuPpm</td></tr><tr><td>Acrylic diffuser</td><td>Plastix Australia Pty. Ltd., Arncliffe, NSW, Australia.</td><td>445 - Opal White</td><td>1200 mm length x 30 mm width x 4.5 mm thick.&lt;br/&gt; URL for commercial source: https://bit.ly/2Bq0fyc</td></tr><tr><td>Aluminum U-bar</td><td>Capral Ltd., Bundamba, QLD, Australia.</td><td>EK9160</td><td>1220 mm length x 35 mm width x 25 mm depth.&lt;br/&gt; URL for commercial source: https://bit.ly/2PPfJou</td></tr><tr><td>Bare solid core copper wire</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Bolts</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Clamps</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Clear epoxy potting resin</td><td>Solid Solutions, East Bentleigh, VIC, Australia.</td><td>651 - Universal Epoxy Potting Resin</td><td>Clear epoxy resin for electrical applications.&lt;br/&gt; URL for commercial source: https://bit.ly/2qY0pHa</td></tr><tr><td>Cyanoacrylate glue</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Datalogger</td><td>Campbell Scientific, Logan, Utah, USA.</td><td>CR5000</td><td>Other dataloggers that record differential voltages could be used.&lt;br/&gt; URL for commercial source: https://bit.ly/2U7Io5H</td></tr><tr><td>Drill or drill press</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Glue lined heat shrink</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Heat gun</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>LED torch</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Masking tape</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Photodiodes (50)</td><td>Everlight Americas Inc., Carrollton, Texas, USA.</td><td>EAALSDSY6444A</td><td>It is important that this specific component is used due to spectral response.&lt;br/&gt; URL for commercial source: https://bit.ly/2FzVnuH</td></tr><tr><td>Polyurethane foam filler</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Quantum sensor</td><td>LI-COR, Lincoln, Nebraska, USA.</td><td>LI-190R</td><td>For calibration of PARbars only.&lt;br/&gt; URL for commercial source: https://bit.ly/2HEfKbh</td></tr><tr><td>Screwdrivers</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Silicone sealant</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Solder</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Solder flux pen</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Soldering iron</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Spirit/bubble level</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Tap and die set</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Two-core cable</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Voltmeter</td><td>Non-specific part</td><td></td><td></td></tr><tr><td>Waterproof connectors</td><td>Core Electronics, Adamstown, NSW, Australia.</td><td>ADA743</td><td>2 core waterproof connector. DC power connectors work well.&lt;br/&gt; URL for commercial source: https://bit.ly/2Brcrik</td></tr></tbody></table>

parbars: cheap, easy to build ceptometers for continuous measurement of light interception in plant canopies

Ceptometry is a technique used to measure the transmittance of photosynthetically active radiation through a plant canopy using multiple light sensors connected in parallel on a long bar. Ceptometry is often used to infer properties of canopy structure and light interception, notably leaf area index (LAI) and effective plant area index (PAIeff). Due to the high cost of commercially available ceptometers, the number of measurements that can be taken is often limited in space and time. This limits the usefulness of ceptometry for studying genetic variability in light interception, and precludes thorough analysis of, and correction for, biases that can skew measurements depending on the time of day. We developed continuously logging ceptometers (called PARbars) that can be produced for USD $75 each and yield high quality data comparable to commercially available alternatives. Here we provide detailed instruction on how to build and calibrate PARbars, how to deploy them in the field and how to estimate PAI from collected transmittance data. We provide representative results from wheat canopies and discuss further considerations that should be made when using PARbars.

A schematic for the PARbar build is shown in Figure 1. A representative calibration curve for a PARbar is shown in Figure 2. The differential voltage output of a PARbar is linearly proportional to the PAR output from a quantum sensor, with R2 = 0.9998. PARbars were deployed in wheat canopies and logged every 20 s across the development of the plants. A typical diurnal time course of the canopy light environment collected using a PARbar on a clear sunny day is shown in Figure 3 (raw transmittance data and corrected PAIeff are shown for comparison). Figures 3b and 3c demonstrate the bias that could be introduced by taking instantaneous ceptometry measurements at various times of day (as per Salter et al. 20187). The wheat plots used for the collection of this data had a row planting orientation due north-south with the transmission of light to the lower canopy peaking at 12:30 (Figure 3b). If an instantaneous measurement were to be taken at this point, PAIeff would be underestimated, whereas if it were taken in the morning or afternoon it may be overestimated. The weatherproof PARbars can also be deployed in the field for long time periods; Figure 4 demonstrates how PARbars could be used to monitor how canopy light environment changes as plants develop.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59447/59447fig1.jpg" /> 
Figure 1. Schematics for the PARbar build. (a) Location and arrangement of the waterproof connector and the internal shunt resistor; (b) arrangement and spacing of the photodiodes; (c) drilling locations on the acrylic diffuser bar; (d) drilling locations on the aluminum U-bar; and (e) electronic circuit diagram of a PARbar. <a href="https://www.jove.com/files/ftp_upload/59447/59447fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59447/59447fig2.jpg" /> 
Figure 2. Representative PARbar calibration curve. The relationship between the differential voltage output of a PARbar (mV) and the photosynthetic photon flux density or PAR (&#956;mol m-2 s-1) from a quantum sensor. Each point represents a single pair of measurements from the PARbar and quantum sensor, recorded once every 20 seconds over a period of 4 hours for one day. <a href="https://www.jove.com/files/ftp_upload/59447/59447fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59447/59447fig3.jpg" /> 
Figure 3. Representative daily timecourse of PARbar output. Data collected on a clear day using PARbars in wheat canopies at anthesis in Canberra, Australia (-35&#176;12&#39;00.1008&#34;, 149&#176;05&#39;17.0988&#34;). (a) PAR measured above the canopy (&#956;mol m-2 s-1), (b) uncorrected transmittance (the ratio of PARabove/PARbelow) (unitless), and (c) the effective plant area index (PAIeff, m2 m-2), calculated from Equation 1. Data points shown in (b) and (c) are means (n = 30), solid lines are LOESS local regressions fitted in R (a = 0.5), shaded areas are standard errors of the fit and the dashed horizontal lines represent the daily means. The shaded area between the dotted lines is the time window (1100 &#8211; 1400h) recommended for instantaneous ceptometer measurements in wheat by CIMMYT11. <a href="https://www.jove.com/files/ftp_upload/59447/59447fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59447/59447fig4.jpg" /> 
Figure 4. Representative data collected across a growing season. PARbar data collected from early tillering to anthesis in wheat canopies in Canberra, Australia (-35&#176;12&#39;00.1008&#34;, 149&#176;05&#39;17.0988&#34;). (a) Uncorrected transmittance data (unitless), and (b) effective plant area index (PAIeff, m2 m-2) calculated from Equation 1. Data points shown represent daily means for the period 1,000 &#8211; 1,400h (n = 30). Solid lines are LOESS local regressions fitted in R (a = 0.75), shaded areas are standard errors of the fit. Raw data was not included in further analysis if PARabove was &#60; 1,500 &#181;mol m-2 s-1 and if PARbelow/PARabove was &#62; 1. <a href="https://www.jove.com/files/ftp_upload/59447/59447fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about PARbars: Cheap, Easy to Build Ceptometers for Continuous Measurement of Light Interception in Plant Canopies at JoVE.com

PARbars: Cheap, Easy to Build Ceptometers for Continuous Measurement of Light Interception in Plant Canopies

Here, we present detailed instructions on how to build and calibrate research quality ceptometers (light sensors that integrate light intensity across many sensors arrayed linearly along a horizontal bar).

Ceptometry is a technique used to measure the transmittance of photosynthetically active radiation through a plant canopy using multiple light sensors ...

parbars-cheap-easy-to-build-ceptometers-for-continuous-measurement

Research

JoVE Journal

Environment

9.4K Views.  University of Sydney. Here, we present detailed instructions on how to build and calibrate research quality ceptometers (light sensors that integrate light intensity across many sensors arrayed linearly along a horizontal bar).

Video: PARbars: Cheap, Easy to Build Ceptometers for Continuous Measurement of Light Interception in Plant Canopies

A Rapid Laser Probing Method Facilitates the Non-invasive and Contact-free Determination of Leaf Thermal Properties

Plants can produce valuable substances such as secondary metabolites and recombinant proteins. The purification of the latter from plant biomass can be streamlined by heat treatment (blanching). A blanching apparatus can be designed more precisely if the thermal properties of the leaves are known in detail, i.e., the specific heat capacity and thermal conductivity. The measurement of these properties is time consuming and labor intensive, and usually requires invasive methods that contact the sample directly. This can reduce the product yield and may be incompatible with containment requirements, e.g., in the context of good manufacturing practice. To address these issues, a non-invasive, contact-free method was developed that determines the specific heat capacity and thermal conductivity of an intact plant leaf in about one minute. The method involves the application of a short laser pulse of defined length and intensity to a small area of the leaf sample, causing a temperature increase that is measured using a near infrared sensor. The temperature increase is combined with known leaf properties (thickness and density) to determine the specific heat capacity. The thermal conductivity is then calculated based on the profile of the subsequent temperature decline, taking thermal radiation and convective heat transfer into account. The associated calculations and critical aspects of sample handling are discussed.

A method was developed to determine the specific heat capacity and thermal conductivity of leaf tissue by non-invasive, contact-free near infrared laser probing, which requires less than 1 min per sample.

Plants can produce valuable substances such as secondary metabolites and recombinant proteins. The purification of the latter from plant biomass can be ...

Biochemistry

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Better understanding of plant root dynamics is essential to improve resource use efficiency of agricultural systems and increase the resistance of crop cultivars against environmental stresses. An experimental protocol is presented for RGB and hyperspectral imaging of root systems. The approach uses rhizoboxes where plants grow in natural soil over a longer time to observe fully developed root systems. Experimental settings are exemplified for assessing rhizobox plants under water stress and studying the role of roots. An RGB imaging setup is described for cheap and quick quantification of root development over time. Hyperspectral imaging improves root segmentation from the soil background compared to RGB color based thresholding. The particular strength of hyperspectral imaging is the acquisition of chemometric information on the root-soil system for functional understanding. This is demonstrated with high resolution water content mapping. Spectral imaging however is more complex in image acquisition, processing and analysis compared to the RGB approach. A combination of both methods can optimize a comprehensive assessment of the root system. Application examples integrating root and aboveground traits are given for the context of plant phenotyping and plant physiological research. Further improvement of root imaging can be obtained by optimizing RGB image quality with better illumination using different light sources and by extension of image analysis methods to infer on root zone properties from spectral data.

An experimental protocol is presented for assessment of soil grown plant root systems with RGB and hyperspectral imaging. Combination of RGB image time series with chemometric information from hyperspectral scans optimizes insights into plant root dynamics.

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Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

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Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

The presented protocol uses the eddy covariance method at non-typical locations, applicable to all types of short-canopy ecosystems with limited area, on a currently reforested windthrow site in Poland. Details of measuring site setup rules, flux calculations and quality control, and final result analysis, are described.

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Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

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An accurate estimation of leaf area index (LAI) is crucial for many models of material and energy fluxes within plant ecosystems and between an ecosystem and the atmospheric boundary layer. Therefore, three methods (litter traps, needle technique, and PCA) for taking precise LAI measurements were in the presented protocol.

Accurate estimations of leaf area index (LAI), defined as half of the total leaf surface area per unit of horizontal ground surface area, are crucial for ...

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass (ADG) Fresnel Lens for Concentrating Photovoltaics

We present a method to characterize achromatic Fresnel lenses for photovoltaic applications. The achromatic doublet on glass (ADG) Fresnel lens is composed of two materials, a plastic and an elastomer, whose dispersion characteristics (refractive index variation with wavelength) are different. We first designed the lens geometry and then used ray-tracing simulation, based on the Monte Carlo method, to analyze its performance from the point of view of both optical efficiency and the maximum attainable concentration. Afterwards, ADG Fresnel lens prototypes were manufactured using a simple and reliable method. It consists of a prior injection of plastic parts and a consecutive lamination, together with the elastomer and a glass substrate to fabricate the parquet of ADG Fresnel lenses. The accuracy of the manufactured lens profile is examined using an optical microscope while its optical performance is evaluated using a solar simulator for concentrator photovoltaic systems. The simulator is composed of a xenon flash lamp whose emitted light is reflected by a parabolic mirror. The collimated light has a spectral distribution and an angular aperture similar to the real Sun. We were able to assess the optical performance of the ADG Fresnel lenses by taking photographs of the irradiance spot cast by the lens using a charge-coupled device (CCD) camera and measuring the photocurrent generated by several types of multi junction (MJ) solar cells, which have been previously characterized at a solar simulator for concentrator solar cells. These measurements have demonstrated the achromatic behavior of ADG Fresnel lenses and, as a consequence, the suitability of the modelling and manufacturing methods.

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

The achromatic doublet on glass (ADG) Fresnel lens makes use of two materials with differing dispersion to reduce chromatic aberration and increase attainable concentration. In this paper, a protocol for the complete characterization of the ADG Fresnel lens is presented.

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Engineering

Field Measurement of Effective Leaf Area Index using Optical Device in Vegetation Canopy

Leaf area index (LAI) is an essential canopy variable describing the amount of foliage in an ecosystem. The parameter serves as the interface between green components of plants and the atmosphere, and many physiological processes occur there, primarily photosynthetic uptake, respiration, and transpiration. LAI is also an input parameter for many models involving carbon, water, and the energy cycle. Moreover, ground-based in situ measurements serve as the calibration method for LAI obtained from remote sensing products. Therefore, straightforward indirect optical methods are necessary for making precise and rapid LAI estimates. The methodological approach, advantages, controversies, and future perspectives of the newly developed LP 110 optical device based on the relation between radiation transmitted through the vegetation canopy and canopy gaps were discussed in the protocol. Furthermore, the instrument was compared to the world standard LAI-2200 Plant Canopy Analyzer. The LP 110 enables more rapid and more straightforward processing of data acquired in the field, and it is more affordable than the Plant Canopy Analyzer. The new instrument is characterized by its ease of use for both above- and below-canopy readings due to its greater sensor sensitivity, in-built digital inclinometer, and automatic logging of readings at the correct position. Therefore, the hand-held LP 110 device is a suitable gadget for performing LAI estimation in forestry, ecology, horticulture, and agriculture based on the representative results. Moreover, the same device also enables the user to take accurate measurements of incident photosynthetically active radiation (PAR) intensity.

Fast and precise leaf area index (LAI) estimation in terrestrial ecosystems is crucial for a wide range of ecological studies and calibrating remote sensing products. Presented here is the protocol for using the new LP 110 optical device for taking ground-based in situ LAI measurements.

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Evaluation of Photosynthetic Behaviors by Simultaneous Measurements of Leaf Reflectance and Chlorophyll Fluorescence Analyses

Chlorophyll a fluorescence analysis is widely used to measure photosynthetic behaviors in intact plants, and has resulted in the development of many parameters that efficiently measure photosynthesis. Leaf reflectance analysis provides several vegetation indices in ecology and agriculture, including the photochemical reflectance index (PRI), which can be used as an indicator of thermal energy dissipation during photosynthesis because it correlates with non-photochemical quenching (NPQ). However, since NPQ is a composite parameter, its validation is required to understand the nature of the PRI parameter. To obtain physiological evidence for evaluation of the PRI parameter, we simultaneously measured chlorophyll fluorescence and leaf reflectance in xanthophyll cycle defective mutant (npq1) and wild-type Arabidopsis plants. Additionally, the qZ parameter, which likely reflects the xanthophyll cycle, was extracted from the results of chlorophyll fluorescence analysis by monitoring relaxation kinetics of NPQ after switching the light off. These simultaneous measurements were carried out using a pulse-amplitude modulation (PAM) chlorophyll fluorometer and a spectral radiometer. The fiber probes from both instruments were positioned close to each other to detect signals from the same leaf position. An external light source was used to activate photosynthesis, and the measuring lights and saturated light were provided from the PAM instrument. This experimental system enabled us to monitor light-dependent PRI in the intact plant and revealed that light-dependent changes in PRI differ significantly between the wild type and npq1 mutant. Furthermore, PRI was strongly correlated with qZ, meaning that qZ reflects the xanthophyll cycle. Together, these measurements demonstrated that simultaneous measurement of leaf reflectance and chlorophyll fluorescence is a valid approach for parameter evaluation.

We describe a new technical approach to study photosynthetic responses in higher plants involving simultaneous measurements of chlorophyll a fluorescence and leaf reflectance using a PAM and a spectral radiometer for the detection of signals from the same leaf area in Arabidopsis.

Chlorophyll a fluorescence analysis is widely used to measure photosynthetic behaviors in intact plants, and has resulted in the development of many ...

Bioengineering

Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants

Developmental and environmental cues induce Ca2+ fluctuations in plant cells. Stimulus-specific spatial-temporal Ca2+ patterns are sensed by cellular Ca2+ binding proteins that initiate Ca2+ signaling cascades. However, we still know little about how stimulus specific Ca2+ signals are generated. The specificity of a Ca2+ signal may be attributed to the sophisticated regulation of the activities of Ca2+ channels and/or transporters in response to a given stimulus. To identify these cellular components and understand their functions, it is crucial to use systems that allow a sensitive and robust recording of Ca2+ signals at both the tissue and cellular levels. Genetically encoded Ca2+ indicators that are targeted to different cellular compartments have provided a platform for live cell confocal imaging of cellular Ca2+ signals. Here we describe instructions for the use of two Ca2+ detection systems: aequorin based FAS (film adhesive seedlings) luminescence Ca2+ imaging and case12 based live cell confocal fluorescence Ca2+ imaging. Luminescence imaging using the FAS system provides a simple, robust and sensitive detection of spatial and temporal Ca2+ signals at the tissue level, while live cell confocal imaging using Case12 provides simultaneous detection of cytosolic and nuclear Ca2+ signals at a high resolution.

Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants

Ca2+ signaling regulates diverse biological processes in plants. Here we present approaches for monitoring abiotic stress induced spatial and temporal Ca2+ signals in Arabidopsis cells and tissues using the genetically encoded Ca2+ indicators Aequorin or Case12.

Developmental and environmental cues induce Ca2+ fluctuations in plant cells. Stimulus-specific spatial-temporal Ca2+ patterns are sensed by cellular Ca2+ ...

Biology

High-Throughput Analysis of Non-Photochemical Quenching in Crops Using Pulse Amplitude Modulated Chlorophyll Fluorometry

Photosynthesis is not optimized in modern crop varieties, and therefore provides an opportunity for improvement. Speeding up the relaxation of non-photochemical quenching (NPQ) has proven to be an effective strategy to increase photosynthetic performance. However, the potential to breed for improved NPQ and a complete understanding of the genetic basis of NPQ relaxation is lacking due to limitations of oversampling and data collection from field-grown crop plants. Building on previous reports, we present a high-throughput assay for analysis of NPQ relaxation rates in Glycine max (soybean) using pulse amplitude modulated (PAM) chlorophyll fluorometry. Leaf disks are sampled from field-grown soybeans before transportation to a laboratory where NPQ relaxation is measured in a closed PAM-fluorometer. NPQ relaxation parameters are calculated by fitting a bi-exponential function to the measured NPQ values following a transition from high to low light. Using this method, it is possible to test hundreds of genotypes within a day. The procedure has the potential to screen mutant and diversity panels for variation in NPQ relaxation, and can therefore be applied to both fundamental and applied research questions.

The protocol introduces a high-throughput method for measuring the relaxation of non-photochemical quenching by pulse amplitude modulated chlorophyll fluorometry. The method is applied to field-grown Glycine max and can be adapted to other species to screen for genetic diversity or breeding populations.

Photosynthesis is not optimized in modern crop varieties, and therefore provides an opportunity for improvement. Speeding up the relaxation of ...

High-Resolution Imaging of Chlorophyll Biosynthesis in Arabidopsis Seedling

Non-invasive Assay for Chlorophyll Biosynthesis Kinetics Determination during Early Stages of Arabidopsis De-etiolation

Chlorophyll biosynthesis is a hallmark of de-etiolation, one of the most dramatic stages in the plant life cycle. The tightly controlled and highly dynamic process of chlorophyll biosynthesis is triggered during the shift from the dark to the light in flowering plants. At the moment when etiolated seedlings are exposed to the first traces of sunlight, rapid (in order of seconds) conversion of protochlorophyllide into chlorophyllide is mediated by unique light-accepting protein complexes, leading via subsequent metabolic steps to the production of fully functional chlorophyll. Standard techniques for chlorophyll content analysis include pigment extraction from detached plant tissues, which does not apply to studying such fast processes. To investigate chlorophyll kinetics in vivo with high accuracy and spatiotemporal resolution in the first hours after light-induced de-etiolation, an instrument and protocol were developed. Here, we present a detailed procedure designed for statistically robust quantification of chlorophyll in the early stages of Arabidopsis de-etiolation.

Author Spotlight: Non-Invasive High-Resolution Measurement of Chlorophyll Synthesis During De-Etiolation

Here, we describe an advanced tool designed for chlorophyll biosynthesis monitoring during the early stages of Arabidopsis seedling de-etiolation. The novel methodology provides non-invasive real-time chlorophyll fluorescence imaging at high spatial and temporal resolution.

Chlorophyll biosynthesis is a hallmark of de-etiolation, one of the most dramatic stages in the plant life cycle. The tightly controlled and highly ...

PARbars: Cheap, Easy to Build Ceptometers for Continuous Measurement of Light Interception in Plant Canopies

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