The authors are indebted to the Journal of Forest Science editorial board for encouraging and authorizing us to use the representative results in this protocol from the article published there.
The research was financially supported by the Ministry of Agriculture of the Czech Republic, institutional support MZE-RO0118, National Agency of Agricultural Research (Project No. QK21020307), and the European Union&#39;s Horizon 2020 research and innovation program (grant agreement No. 952314).
The authors also kindly thank three anonymous reviewers for their constructive criticism, which improved the manuscript. In addition, thanks go to Dusan Bartos, Alena Hvezdova, and Tomas Petr for helping with field measurements and Photon Systems Instruments Ltd. company for their collaboration and providing device photos.

<ol>
	<li>Muiruri, E. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Forest+diversity+effects+on+insect+herbivores:+Do+leaf+traits+matter.">Forest diversity effects on insect herbivores: Do leaf traits matter.</a> New Phytologist. 221 (4), 2250-2260 (2018).</li><li>Macfarlane, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+leaf+area+index+in+eucalypt+forest+using+digital+photography.">Estimation of leaf area index in eucalypt forest using digital photography.</a> Agricultural and Forest Meteorology. 143 (3-4), 176-188 (2007).</li><li>Easlon, H. M., Bloom, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Easy+leaf+area:+Automated+digital+image+analysis+for+rapid+and+accurate+measurements+of+leaf+area.">Easy leaf area: Automated digital image analysis for rapid and accurate measurements of leaf area.</a> Applications in Plant Sciences. 2 (7), 1400033 (2014).</li><li>Asner, G. P., Scurlock, J. M. O., Hicke, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+synthesis+of+leaf+area+index+observations:+implications+for+ecological+and+remote+sensing+studies.">Global synthesis of leaf area index observations: implications for ecological and remote sensing studies.</a> Global Ecology and Biogeography. 12, 191-205 (2003).</li><li>Vicari, M. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leaf+and+wood+classification+framework+for+terrestrial+LiDAR+point+clouds.">Leaf and wood classification framework for terrestrial LiDAR point clouds.</a> Methods in Ecology and Evolution. 10 (5), 680-694 (2019).</li><li>Watson, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+physiological+studies+in+the+growth+of+field+crops.+I.+Variation+in+net+assimilation+rate+and+leaf+area+between+species,+varieties,+and+within+and+between+years.">Comparative physiological studies in the growth of field crops. I. Variation in net assimilation rate and leaf area between species, varieties, and within and between years.</a> Annals of Botany. 11, 41-76 (1947).</li><li>Chen, J. M., Black, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Defining+leaf-area+index+for+non-flat+leaves.">Defining leaf-area index for non-flat leaves.</a> Plant, Cell and Environment. 15 (4), 421-429 (1992).</li><li>Welles, J. M., Cohen, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Canopy+structure+measurement+by+gap+fraction+analysis+using+commercial+instrumentation.">Canopy structure measurement by gap fraction analysis using commercial instrumentation.</a> Journal of Experimental Botany. 47 (9), 1335-1342 (1996).</li><li>Br&#233;da, N. J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ground-based+measurements+of+leaf+area+index:+a+review+of+methods,+instruments,+and+current+controversies.">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>Jonckheere, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+methods+for+in+situ+leaf+area+index+determination.+Part+I:+Theories,+sensors+and+hemispherical+photography.">Review of methods for in situ leaf area index determination. Part I: Theories, sensors and hemispherical photography.</a> Agricultural and Forest Meteorology. 121 (1-2), 19-35 (2004).</li><li>Weiss, M., Baret, F., Smith, G. J., Jonckheere, I., Coppin, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+methods+for+in+situ+leaf+area+index+(LAI)+determination.+Part+II.+Estimation+of+LAI,+errors+and+sampling.">Review of methods for in situ leaf area index (LAI) determination. Part II. Estimation of LAI, errors and sampling.</a> Agricultural and Forest Meteorology. 121 (1-2), 37-53 (2004).</li><li>Fang, H., Baret, F., Plummer, S., Schaepman-Strub, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+overview+of+global+leaf+area+index+(LAI):+Methods,+products,+validation,+and+applications.">An overview of global leaf area index (LAI): Methods, products, validation, and applications.</a> Reviews of Geophysics. 57 (3), 739-799 (2019).</li><li>Yan, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+indirect+optical+measurements+of+leaf+area+index:+Recent+advances,+challenges,+and+perspectives.">Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives.</a> Agricultural and Forest Meteorology. 265, 390-411 (2019).</li><li>Parker, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tamm+review:+Leaf+Area+Index+(LAI)+is+both+a+determinant+and+a+consequence+of+important+processes+in+vegetation+canopies.">Tamm review: Leaf Area Index (LAI) is both a determinant and a consequence of important processes in vegetation canopies.</a> Forest Ecology and Management. 477, 118496 (2020).</li><li>Jiapaer, G., Yi, Q., Yao, F., Zhang, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+non-destructive+LAI+determination+methods+and+optimization+of+sampling+schemes+in+an+open+Populus+euphratica+ecosystem.">Comparison of non-destructive LAI determination methods and optimization of sampling schemes in an open Populus euphratica ecosystem.</a> Urban Forestry and Urban Greening. 26, 114-123 (2017).</li><li>Grotti, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+intensity,+image-based+method+to+estimate+gap+fraction,+canopy+openness+and+effective+leaf+area+index+from+phase-shift+terrestrial+laser+scanning.">An intensity, image-based method to estimate gap fraction, canopy openness and effective leaf area index from phase-shift terrestrial laser scanning.</a> Agricultural and Forest Meteorology. 280, 107766 (2020).</li><li>Gower, S. T., Kucharik, C. J., Norman, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+and+indirect+estimation+of+leaf+area+index,+fAPAR,+and+net+primary+production+of+terrestrial+ecosystems.">Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems.</a> Remote Sensing of Environment. 70 (1), 29-51 (1999).</li><li>Morisette, J. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+of+global+moderate-resolution+LAI+products:+a+framework+proposed+within+the+CEOS+land+product+validation+subgroup.">Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup.</a> IEEE Transactions on Geoscience and Remote Sensing. 44 (7), 1804-1817 (2006).</li><li>Pokorn&#253;, R., &#352;alansk&#225;, P., Janou&#353;, D., Pavelka, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ALAI-02D+-+a+new+instrument+in+forest+practice.">ALAI-02D - a new instrument in forest practice.</a> Journal of Forest Science. 47, 164-169 (2001).</li><li>&#268;ern&#253;, J., Krejza, J., Pokorn&#253;, R., Bedn&#225;&#345;, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LaiPen+LP+100+-+a+new+device+for+estimating+forest+ecosystem+leaf+area+index+compared+to+the+etalon:+A+methodologic+case+study.">LaiPen LP 100 - a new device for estimating forest ecosystem leaf area index compared to the etalon: A methodologic case study.</a> Journal of Forest Science. 64 (11), 455-468 (2018).</li><li>Larcher, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Physiological plant ecology. Ecophysiology and Stress Physiology of Functional Groups. , (2003).</li><li>Taiz, L., Zeiger, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Plant Physiology. 5th edition. , 623 (2010).</li><li>Pokorn&#253;, R., Tom&#225;&#353;kov&#225;, I., Havr&#225;nkov&#225;, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+variation+and+efficiency+of+leaf+area+index+in+young+mountain+Norway+spruce+stand.">Temporal variation and efficiency of leaf area index in young mountain Norway spruce stand.</a> European Journal of Forest Research. 127, 359-367 (2008).</li><li>Chen, J. M., Black, T. A., Adams, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+hemispherical+photography+for+determining+plant+area+index+and+geometry+of+a+forest+stand.">Evaluation of hemispherical photography for determining plant area index and geometry of a forest stand.</a> Agricultural and Forest Meteorology. 56, 129-143 (1991).</li><li>Black, T. A., Chen, J. M., Lee, X. H., Sagar, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characteristics+of+shortwave+and+longwave+irradiances+under+a+Douglas-fir+forest+stand.">Characteristics of shortwave and longwave irradiances under a Douglas-fir forest stand.</a> Canadian Journal of Forest Research. 21 (7), 1020-1028 (1991).</li><li>Hirose, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+the+Monsi-Saeki+theory+on+canopy+structure+and+function.">Development of the Monsi-Saeki theory on canopy structure and function.</a> Annals of Botany. 95 (3), 483-494 (2005).</li><li>Pierce, L., Running, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=rapid+estimation+of+coniferous+forest+leaf+area+index+using+a+portable+integrating+radiometer.">rapid estimation of coniferous forest leaf area index using a portable integrating radiometer.</a> Ecology. 69 (6), 1762-1767 (1988).</li><li>Lang, A. R. G., McMurtrie, R. E., Benson, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validity+of+surface-area+indexes+of+Pinus+radiata+estimated+from+transmittance+of+sun's+beam.">Validity of surface-area indexes of Pinus radiata estimated from transmittance of sun's beam.</a> Agricultural and Forest Meteorology. 57 (1-3), 157-170 (1991).</li><li>Zou, J., Yan, G., Zhu, L., Zhang, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Woody-to-total+area+ratio+determination+with+a+multispectral+canopy+imager.">Woody-to-total area ratio determination with a multispectral canopy imager.</a> Tree Physiology. 29 (8), 1069-1080 (2009).</li><li>Stenberg, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correcting+LAI-2000+estimates+for+the+clumping+of+needles+in+shoots+of+conifer.">Correcting LAI-2000 estimates for the clumping of needles in shoots of conifer.</a> Agricultural and Forest Meteorology. 79 (1-2), 1-8 (1996).</li><li>Chianucci, F., MacFarlane, C., Pisek, J., Cutini, A., Casa, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+foliage+clumping+from+the+LAI-2000+Plant+Canopy+Analyser:+effect+of+view+caps.">Estimation of foliage clumping from the LAI-2000 Plant Canopy Analyser: effect of view caps.</a> Trees-Structure and Function. 29, 355-366 (2015).</li><li>Zou, J., Yan, G., Chen, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+canopy+and+woody+components+clumping+indices+at+three+mature+Picea+crassifolia+forest+stands.">Estimation of canopy and woody components clumping indices at three mature Picea crassifolia forest stands.</a> IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8 (4), 1413-1422 (2015).</li><li>Bao, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+tree+trunks+on+estimation+of+clumping+index+and+LAI+from+HemiView+and+Terrestrial+LiDAR.">Effects of tree trunks on estimation of clumping index and LAI from HemiView and Terrestrial LiDAR.</a> Forests. 9 (3), 144 (2018).</li><li>Zhu, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improving+leaf+area+index+(LAI)+estimation+by+correcting+for+clumping+and+woody+effects+using+terrestrial+laser+scanning.">Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning.</a> Agricultural and Forest Meteorology. 263, 276-286 (2018).</li><li>Photon Systems Instruments Ltd. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> PSI LaiPen LP 110 Manual and User Guide. , 45 (2016).</li><li>&#268;ern&#253;, J., Pokorn&#253;, R., Haninec, P., Bedn&#225;&#345;, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leaf+area+index+estimation+using+three+distinct+methods+in+pure+deciduous+stands.">Leaf area index estimation using three distinct methods in pure deciduous stands.</a> Journal of Visualized Experiments: JoVE. (150), e59757 (2019).</li><li>Fleck, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leaf+area+measurements.+Manual+Part+XVII.+In:+UNECE+ICP+Forests+Programme+Co-ordinating+Centre+(Ed.)+Manual+of+methods+and+criteria+for+harmonized+sampling,+assessment,+monitoring+and+analysis+of+the+effects+of+air+pollution+on+forests.">Leaf area measurements. Manual Part XVII. In: UNECE ICP Forests Programme Co-ordinating Centre (Ed.) Manual of methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests.</a> Th&#252;nen Institute of Forest Ecosystems. , (2016).</li><li>&#268;ern&#253;, J., Pokorn&#253;, R., Haninec, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leaf+area+index+estimated+by+direct,+semi-direct,+and+indirect+methods+in+European+beech+and+sycamore+maple+stands.">Leaf area index estimated by direct, semi-direct, and indirect methods in European beech and sycamore maple stands.</a> Journal of Forestry Research. 31, 827-836 (2020).</li><li>Leblanc, S. G., Chen, J. M., Kwong, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracing+radiation+and+architecture+of+canopies.">Tracing radiation and architecture of canopies.</a> TRAC MANUAL Version 2.1.3. , 25 (2002).</li><li>Sommer, K. J., Lang, A. R. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+analysis+of+two+indirect+methods+of+measuring+leaf+area+index+as+applied+to+minimal+and+spur+pruned+grape+vines.">Comparative analysis of two indirect methods of measuring leaf area index as applied to minimal and spur pruned grape vines.</a> Australian Journal of Plant Physiology. 21 (2), 197-206 (1994).</li><li>Leblanc, S. G., Chen, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+practical+scheme+for+correcting+multiple+scattering+effects+on+optical+LAI+measurements.">A practical scheme for correcting multiple scattering effects on optical LAI measurements.</a> Agricultural and Forest Meteorology. 110 (2), 125-139 (2001).</li></ol>

The authors have nothing to disclose. The representative results were used from the article &#268;ern&#253;, J., Krejza, J., Pokorn&#253;, R., Bedn&#225;&#345;, P. LaiPen LP 100 - a new device for estimating forest ecosystem leaf area index compared to the etalon: A methodologic case study. Journal of Forest Science.64 (11), 455-468 (2018). DOI: 10.17221/112/2018-JFS based on the Journal of Forest Science editorial board's kind permission.

What are the differences between the LP 110 as a newly presented device for estimating LAI (or taking PAR intensity measurements) and the LAI-2200 PCA as an improved version of the previous standard LAI-2000 PCA for estimating LAI via an indirect method? Beyond the price being about fourfold higher for the Plant Canopy Analyzer compared to the LP 110, the number of output parameters, measurement conditions, methodological approaches, and possibilities of estimating LAI for different canopies, accuracy of results, etc., can be compared.
When comparing the hardware, the LP 110 seems to be more user-friendly. The LP 110 is a lighter device and does not require any cable connections between the sensors and the data-logger. Both sensors (i.e., for LAI and PAR measurements; see Figure 1) are integrated within the body of the device, allowing the operator to move easily throughout the studied ecosystem (e.g., in shrubs or dense forests). To ensure the reading value accuracy, a correct sensor position and value storage are essential. This position (either in the zenith or pre-set angles) is identified by a changing sound frequency if the sensor is close or far from the target position. Even under the most intensive sound (the volume can be corrected), the LP 110 held automatically saves the reading value. Contrariwise, finding the correct sensor position for the Plant Canopy Analyzer must be done with a manual bubble level on a hand-held stick. The operator must press the button to save the reading value simultaneously while checking the bubble level. However, the correct sensor position is routinely lost when pressing the button, resulting in decreased accuracy of the reading value. Since visually checking a bubble level is not necessary for taking LP 110 readings, there is also the possibility to hold the instrument on an extension rod, enabling the user to measure above canopies of natural or artificial regeneration, tall herbaceous or shrub layers. In this case, the correct sensor position can simply be found based on the changing sound frequency.
There are differences between the LP 110 and the Plant Canopy Analyzer in respect of LAI sensor construction, especially with regard to sensor sensitivity and the sensors&#39; fields of view (FOV). If the LAI sensor of the Plant Canopy Analyzer is exposed to open-air, it can fog up under high air humidity conditions, which commonly occur in the early morning in open areas. Contrariwise, the LAI sensor of the LP 110 is fog-free as it is located inside the restrictor view cup (Figure 1). Although the restrictor of the LP 110&#39;s LAI sensor is removable, it has a fixed FOV; however, the FOV of the LAI sensor of the Plant Canopy Analyzer can be modified both in the azimuthal and zenith directions using different restrictors (opaque view caps) and by using a masking procedure during data post-processing, respectively. Even though the FOV of the LP 110&#39;s LAI sensor (Figure 1) is relatively narrow and cannot be manipulated compared to the Plant Canopy Analyzer, the sensitivity of this sensor is about tenfold higher. This higher LAI sensor sensitivity enables the user to take measurements using the LP 110 under conditions of low irradiance and also to take above-canopy (reference) readings on extremely narrow open plots, for instance, on narrow forest roads or lines. Furthermore, the above to below-canopy readings&#39; ratio is higher, leading to increased accuracy of the measured transmittance and thus better LAIe estimation. On the other hand, it is necessary to increase the number of below-canopy readings per transect owing to the narrow FOV of the LP 110&#39;s LAI sensor.
There are some similarities between the LP 110 and the Plant Canopy Analyzer, for instance, in measuring conditions and in modifications of the LAI sensor zenith angle view (in directions of 0&#176;, 16&#176;, 32&#176;, 48&#176;, and 64&#176; for the LP 110; and 7&#176;, 23&#176;, 38&#176;, 53&#176;, and 68&#176; for the Plant Canopy Analyzer) to quantify the inclination angle of canopy elements. Similar to the Plant Canopy Analyzer, the LP 110 diminishes the effect of light reflectance and measures a real light absorption part of the light by foliage due to specific sensor wavelength characteristics. Other optical-based instruments such as SunScan, AccuPAR, TRAC39, or DEMON9,40 (for more details, see Table of Materials) measure under relatively wider light intervals regardless of the light reflectance. In dual sensor mode, it is possible to take automatic measurements with one sensor ordinarily placed in an open area to take above-canopy (reference) readings in time intervals ranging from 10-360 s and 5-3,600 s for the LP 110 and the Plant Canopy Analyzer, respectively, and there is the possibility to add GPS positions to individual measurements. For both the instruments, it is impossible to measure LAIe: i) during and immediately after rain conditions, as wet canopy elements, including stems enhance both light reflectance and transmittance values below the canopy; thus, actual LAIe is underestimated under such conditions; ii) during windy conditions when canopy elements are moving, and transmittance values vary greatly even though the sensor position is stable, and iii) during unstable synoptic situations when light conditions change rapidly. The last condition is not so limiting for the LP 110 due to the sensor&#39;s narrow FOV. Also, a distance of obstacles need to be considered. However, a suitable sensor orientation lessens the problem. For both devices, it is likewise possible to estimate LAIe during a sunny day, mainly close to sunrise or sunset. Except for midday when direct sun rays can enter the LAI sensor through the restrictor cap slot, taking LAIe measurements is feasible throughout the whole day; even if the LAI sensor is perpendicularly oriented toward the sun (relevant for the LP 110) or the back of the operator (relevant for the Plant Canopy Analyzer). However, some correction procedures presented by Leblanc and Chen41 must be applied. If the above-canopy readings vary by more than &#177;20% during a short time span (approximately 1-2 min), continuing to take LAIe measurements is useless due to the expected extremely high LAIe estimation error. That problem could be avoided with a precise synchronous estimation of above- and below-canopy readings in dual sensor mode employing two units with the same accurate time setup and calibration. The next critical step for estimating LAIe using the LP 110 is a selection of a suitable open area for above-canopy readings, especially for single sensor mode (the maximal time lag between above and below-canopy readings, i.e., forest stand and open plot, must be 15-20 min), where the size of the open area must respect the sensor FOV. Besides that, the LP 110 is similar to the Plant Canopy Analyzer, not suitable for accurately estimating LAIe in too dense (i.e., LAIe at stand level over 7.88)23, very low canopies grassland, or the transmittance below 1%.
All the obtained values of incident light and light transmittance below the canopy with a time entry are post-processed using specific software, providing many output parameters, especially with the Plant Canopy Analyzer. Contrariwise, the software for processing the data obtained from LP 110 needs to be improved to be more automatic and user-friendly, such as the software relevant to Plant Canopy Analyzer. Moreover, it is advisable to modify the restriction cup for the LP 110 by the producer to change or adjust the sensor FOV.

Canopies are loci of numerous biological, physical, chemical, and ecological processes. Most of them are affected by canopy structures1. Therefore, accurate, rapid, non-destructive, and reliable in situ&#160;vegetation canopy quantification is crucial for a wide range of studies involving hydrology, carbon and nutrient cycling, and global climate change2,3. Since leaves or needles represent an active interface between the atmosphere and vegetation4, one of the critical canopy structural characteristics is leaf area index (LAI)5, defined as one-half of the total green leaf surface area per unit of horizontal ground surface area or crown projection for individuals, expressed in m2 per m2 as a dimensionless variable6,7.
Various instruments and methodological approaches for estimating terrestrial LAI and their pros and cons in diverse ecosystems have already been presented8,9,10,11,12,13,14,15. There are two main categories of LAI estimation methods: direct and indirect (see comprehensive reviews8,9,10,11,12 for more details). Mainly used in forest stands, ground-based&#160;LAI estimates are routinely obtained using indirect optical methods due to the lack of direct LAI determination, but they usually represented a time-consuming, labor-intensive, and destructive method9,10,12,16. Moreover, indirect optical methods derive LAI from more easily measure related parameters (from the viewpoint of its time-demanding and labor-intense nature)17, such as the ratio between incident irradiation above and below the canopy and the quantification of canopy gaps14. It is evident that Plant Canopy Analyzers have also been widely used to validate satellite LAI retrievals18; therefore, it has been considered a standard for LP 110 comparison (see Table of Materials for more details about employed instruments).
The LP 110, as an updated version of initially self-made simple instrument ALAI-02D19 and later LP 10020, was developed as a close competitor for Plant Canopy Analyzers. As a representative of indirect optical methods, the device is hand-held, lightweight, battery-powered, without any need for a cable connection between the sensor and data-logger that uses a digital inclinometer instead of a bubble level and enables faster and more accurate positioning and value reading. In addition, the device was designed to note immediate readouts. Thus, the time estimate needed for collecting data in the field is shorter for the LP 110 than Plant Canopy Analyzer by approximately &#8531;. After the export of readouts to a computer, the data are available for subsequent processing. The device records irradiance within the blue light wavelengths (i.e., 380-490 nm)21,22 using an LAI sensor for making an LAI calculation. The LAI sensor is masked by an opaque restriction cap with 16&#176; (Z-axis) and 112&#176; (X-axis) fields of view (Figure 1). Thus, light transmittance can be noted using the device held either perpendicularly to the ground surface (i.e., zenith angle 0&#176;), or at five different angles of 0&#176;, 16&#176;, 32&#176;, 48&#176;, and 64&#176; to be able also to deduce canopy elements&#39; inclination.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62802/62802fig01.jpg" /> 
Figure 1: Physical features of the LP 110. The MENU key enables the user shift up and down throughout the display, and the SET button serves as the Enter key (A).The zenith view under different inclination angles (&#177;8 due to the side view) and the horizontal view is fixed for LP 110 to 112&#176; (B) similarly to the Plant Canopy Analyzer&#160;(modified by restrictors). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62802/62802fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Due to the higher sensitivity of the LAI sensor, its restricted field of view, in-built digital inclinometer, automatic logging of reading values at the correct position indicated by sound without a button press, the new instrument is also suitable for above-canopy readings at narrow valleys or even on broader forest roads to measure a wide range of sky conditions. Besides that, it enables quantification of mature stand canopies above the relatively high regeneration, and it attains higher accuracy of irradiance values than Plant Canopy Analyzer. Moreover, the price of LP 110 equals about &#188; of the Plant Canopy Analyzer. Contrariwise, the utilization of LP 110 in dense (i.e.,&#160;LAIe at stand level over 7.88)23 or very low canopies as grassland is limited.
The LP 110 can work within two operating modes: (i) a single sensor mode taking both below-canopy and reference readings (above the studied canopy or in a sufficiently widespread clearing located within the vicinity of the analyzed vegetation) performed before, after, or during below-canopy measurements taken with the same instrument and (ii) a dual sensor mode using the first instrument for taking below-canopy readings, whereas the second one is employed for automatically logging reference readings within a regular predefined time interval (from 10 up to 600 s). The LP 110 can be matched with a compatible GPS device (see Table of Materials) to record each below-canopy measurement point&#39;s coordinates for both the modes mentioned above.
The effective leaf area index (LAIe)24 incorporates the clumping index effect and can be derived from measurements of solar beam irradiance taken above and below the studied vegetation canopy25. Thus, for the following LAIe calculation, transmittance (t) must be calculated from irradiation both transmitted below the canopy (I) and incident above the vegetation (Io) measured by the LP 110 device.
t = I / I0 (1)
Since the irradiation intensity exponentially decreases as it passes through a vegetation canopy, LAIe can be calculated according to the Beer-Lambert extinction law modified by Monsi and Saeki9,26
LAIe = - ln (I / I0) x k-1 (2),
Where, k is the extinction coefficient. The extinction coefficient reflects each element&#39;s shape, orientation, and position in the vegetation canopy with the known canopy element inclination and view direction9,12. The k coefficient (see equation 2) depends on the absorption of irradiance by foliage, and it differs among plant species based on the morphological parameters of canopy elements, their spatial arrangement, and optical properties. Since the extinction coefficient usually fluctuates around 0.59,27, equation 2 can be simplified as presented by Lang et al.28 in a slightly different way for heterogeneous and homogenous canopies:
In a heterogeneous canopy
LAIe = 2 x |<img alt="Equation 1" src="/files/ftp_upload/62802/62802eq01.jpg" />ln t| (3),
or
In a homogeneous canopy
LAIe = 2 x |ln T| (4),
Where, t: is transmittance at each below-canopy measurement point, and T: is the average transmittance of all t values per measured transect or stand.
In forest stands, LAIe must be further corrected due to a clumping effect of the assimilation apparatus within the shoots29,30,31,32,33,34 to obtain the actual LAI value.
The protocol is devoted to the practical utilization of the LP 110 optical device for estimating LAIe in a selected example of Central European conifer forest stands (see Table 2 and Table 3 for the site, structural, and dendrometric characteristics). LAIe estimation in a vegetation canopy using this device is based on a widely used optical method related to the transmittance of photosynthetically active radiation and canopy gap fraction. The paper aims to provide a comprehensive protocol for performing LAIe estimation using the new LP 110 optical device.

<table><tbody><tr><td>AccuPAR</td><td>METER Group, Inc., Pullman, WA, USA</td><td>AccuPaR LP-80</td><td>https://www.metergroup.com/environment/products/accupar-lp-80-leaf-area-index/</td></tr><tr><td>DEMON</td><td>CSIRO, Canberra, Australia</td><td>DEMON</td><td></td></tr><tr><td>File Viewer</td><td>LI-COR Biosciences Inc., NE, USA</td><td>FV2200C Software</td><td>https://www.licor.com/env/products/leaf_area/LAI-2200C/software.html</td></tr><tr><td>FluorPen</td><td>Photon System Instruments Ltd. (PSI), Czech Republic</td><td>FluorPen 1.1.2.3 Sofware</td><td>https://handheld.psi.cz/products/laipen/#download</td></tr><tr><td>Hand-held GPS device</td><td>Garmin Ltd., Czech Republic</td><td>Garmin eTrex 32x Europe46</td><td>https://www.garmin.cz/garmin-etrex-32x-europe46/80117</td></tr><tr><td>Hand-held device for leaf area index estimation(LP 110)</td><td>Photon System Instruments Ltd. (PSI) Czech Republic</td><td>LaiPen LP 110</td><td>https://handheld.psi.cz/products/laipen/#info</td></tr><tr><td>Plant Canopy Analyser</td><td>LI-COR Biosciences Inc., NE, USA</td><td>LAI-2000 PCA</td><td>LAI-2200 PCA or LAI-2200C as improved versions of LAI-2000 PCA can be used, see: https://www.licor.com/env/products/leaf_area/LAI-2200C/</td></tr><tr><td>Statistical software</td><td>Systat Software Inc., CA, USA</td><td>SigmaPlot 13.0</td><td>https://systatsoftware.com/products/sigmaplot/sigmaplot-version-13/?gclid=Cj0KCQjwzYGGBhCTARIs&lt;br/&gt; AHdMTQzgfb42vv0mWmcbVcflNO&lt;br/&gt; UvrLl802Lrhkfh23Qie2mIZfw4O8kp&lt;br/&gt; 7p0aAsoiEALw_wcB</td></tr><tr><td>Statistical software</td><td>StatSoft Inc., OK, USA</td><td>STATISTICA 10.0</td><td>For LAI visualization, wafer-plots in STATISTICA 10.0 were employed.</td></tr><tr><td>SunScan</td><td>Delta-T Devices, Ltd., Cambridge, UK</td><td>SS1 SunScan</td><td>https://www.delta-t.co.uk/product/sunscan</td></tr><tr><td>TRAC</td><td>3&lt;sup&gt;rd&lt;/sup&gt; Wave Engineering, Ontarion Canada</td><td>Tracing Radiation and Architecture of Canopies</td><td>http://faculty.geog.utoronto.ca/Chen/Chen&#039;s%20homepage/res_trac.htm</td></tr><tr><td>Tripod</td><td>Any</td><td>NA</td><td>Tripod with standard nut</td></tr><tr><td>Water level</td><td>Any</td><td>NA</td><td></td></tr></tbody></table>

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.

The spatial structure obtained from both tested devices obviously differed in all studied plots, i.e., thinned from above (A), thinned from below (B) and a control without any silvicultural intervention (C; see Table 2 for more details). At the stand level, similar differences in LAI values obtained from the LP 110 and the Plant Canopy Analyzer were confirmed between thinned plots with various densities (A vs. B) using ANOVA and Tukey&#39;s test. For the Plant Canopy Analyzer, significantly higher LAI values were observed in the control plot with no silvicultural intervention than in the thinned ones (A, B). However, the values significantly exceeded LAI obtained from the LP 110 in the control plot. For the LP 110, LAI did not significantly differ in the C and B treatments. Contrariwise, a significant difference in LAI values between the C and A plots was found. Generally, LAI significantly decreased after applied thinning treatments in the studied stands. LAI estimated using the LP 110 (LaiPen LP110) decreased more evidently in plot A, whereas the LAI values obtained from the Analyzer (LAI-2200 PCA) decreased more in plot B. Nevertheless, these recorded differences were slight (Figure 4).
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62802/62802fig04.jpg" /> 
Figure 4: LAI values estimated using the LP 110 and the Plant Canopy Analyzer optical devices in Norway spruce pole stands under different silvicultural treatments. For estimating LAI, 81 below-canopy readings were taken in each studied stand. A: Thinning from above; B: Thinning from below; C: Control plot. The dots signify the mean LAI value. The whiskers display the standard deviations. Various letters indicate significant differences (p &#60; 0.05) among the silvicultural treatments and different optical instruments using Tukey&#39;s Post-hoc test. This figure has been modified from &#268;ern&#253; et al.20. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62802/62802fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The LAI values&#39; spatial variability is illustrated in Figure 5 for each thinning treatment in pure Norway spruce pole stands.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/62802/62802fig05.jpg" /> 
Figure 5: Spatial heterogeneity of LAI estimated using the LP 110 and the Plant Canopy Analyzer at the level of individual measurement points under studied spruce canopy.&#160;A: Thinning from above; B: Thinning from below; C: Control plot. The numbers above arrows signify the lateral side length and spacing of measurement points within the regular grid. This figure has been modified from &#268;ern&#253; et al.20. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62802/62802fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The LP 110 underestimated LAI by 7.4% and 10.6% in plots A and C, respectively. Contrariwise, this device overestimated the LAI stand value obtained from the Plant Canopy Analyzer in plot B by 3.7%. If the total averages from all LAI values regardless of the thinning treatment applied were calculated and subsequently compared (LP 110 vs. Plant Canopy Analyzer), the LP 110 device underestimated LAI obtained by the Plant Canopy Analyzer by 5.8%. Subsequently, differences in specific LAI values measured above individual points arranged within the regular grid were calculated for both instruments, and these deviations were subsequently expressed as a percentage. Under these circumstances, the LAI values measured by the LP 110 and the Plant Canopy Analyzer differed profoundly (Table 1).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2">Silvicultural treatment</td>
			<td colspan="2">Forest stand LAI</td>
			<td rowspan="2">Relative differences (%) among LAI from LaiPen LP 110 compared to LAI-2200 PCA at the level of individual measurement points</td>
		</tr>
		<tr>
			<td>LaiPen LP 110 (m2 m-2)</td>
			<td>LAI-2200 PCA (m2 m-2)</td>
		</tr>
		<tr>
			<td>A</td>
			<td>7.05 &#177; 1.73</td>
			<td>7.61 &#177; 2.29</td>
			<td>1 &#177; 37 (-58; 156)</td>
		</tr>
		<tr>
			<td>B</td>
			<td>7.76 &#177; 1.36</td>
			<td>7.48 &#177; 1.75</td>
			<td>8 &#177; 30 (-33; 183)</td>
		</tr>
		<tr>
			<td>C</td>
			<td>8.35 &#177; 1.23</td>
			<td>9.34 &#177; 2.51</td>
			<td>-5 &#177; 26 (-48; 115)</td>
		</tr>
	</tbody>
</table>
Table 1: Mean LAI at the stand level and LAI differences expressed as a % between the LP 110 and the Plant Canopy Analyser at the level of individual measurement points. A: Thinning from above; B: Thinning from below; C: Control plot. This table has been modified from &#268;ern&#253; et al.20.
For all LAI data measured at a particular point level using the LP 110 and the Plant Canopy Analyzer, linear regression between both the employed devices was performed. The linear regression of y = 0.8954x (R2 = 0.94; RMSE = 2.11438) was found for all LAI data from both the tested instruments (Figure 6).
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/62802/62802fig06.jpg" /> 
Figure 6: The linear regression among LAI values coming from the LP 110 and the Plant Canopy Analyzer at the level of individual measurement points in studied Norway spruce pole stands.&#160;This figure has been modified from &#268;ern&#253; et al.20. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62802/62802fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Geographic coordinates</td>
			<td>49&#176;29&#39;31&#34; N, 16&#176;43&#39;30&#34; E</td>
		</tr>
		<tr>
			<td>Altitude</td>
			<td>610-625 m a. s. l.</td>
		</tr>
		<tr>
			<td>Mean annual air temperature</td>
			<td>6.5 &#176;C</td>
		</tr>
		<tr>
			<td>Mean annual precipitation</td>
			<td>717 mm</td>
		</tr>
	</tbody>
</table>
Table 2: Characteristics of the study site. This table has been modified from &#268;ern&#253; et al.20.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Plot</td>
			<td>Age of stand (years)</td>
			<td>Stand density (trees ha-1)</td>
			<td>Height (m)</td>
			<td>DBH (cm)</td>
			<td>BA1.3 (m2&#183;ha-1)</td>
			<td>Growing stock (m3&#183;ha-1)</td>
		</tr>
		<tr>
			<td>A</td>
			<td>36</td>
			<td>1.930</td>
			<td>14.14 &#177; 3.73</td>
			<td>14.84 &#177; 6.13</td>
			<td>36.60 &#177; 0.25</td>
			<td>250.02 &#177; 2.00</td>
		</tr>
		<tr>
			<td>B</td>
			<td>36</td>
			<td>1.915</td>
			<td>16.33 &#177; 2.37</td>
			<td>15.81 &#177; 4.47</td>
			<td>43.41 &#177; 0.17</td>
			<td>290.07 &#177; 1.32</td>
		</tr>
		<tr>
			<td>C</td>
			<td>36</td>
			<td>4.100</td>
			<td>12.72 &#177; 2.68</td>
			<td>10.97 &#177; 4.81</td>
			<td>36.96 &#177; 0.19</td>
			<td>287.12 &#177; 1.39</td>
		</tr>
	</tbody>
</table>
Table 3: Dendrometric and structural characteristics of the studied stands covering an area of 25 m x 25 m in 2014. In each studied stand, 81 below-canopy readings were taken within a regular grid (3 m x 3 m) under standard overcast skies (for more details, follow &#268;ern&#253; et al.20). All LAI measurements were conducted in July and August when LAI values are most stable9,38. A: Thinning from above; B: Thinning from below; C: Control plot; DBH: stem diameter at breast height; BA1.3: the basal area at breast height. For BA1.3 at the stand level, the basal areas of each tree presented in the studied stand, calculated as: BA1.3 = (&#8719;*DBH2)/4, was summed up. This table has been modified from &#268;ern&#253; et al.20.

Watch this Scientific Journal Video about Field Measurement of Effective Leaf Area Index using Optical Device in Vegetation Canopy at JoVE.com

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

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.

Leaf area index (LAI) is an essential canopy variable describing the amount of foliage in an ecosystem. The parameter serves as the interface between ...

field-measurement-effective-leaf-area-index-using-optical-device

Nanyang Technological University

Research

JoVE Journal

Environment

3.2K Views.  Research Station at Opočno. 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.

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

Mass Production of Genetically Modified Aedes aegypti for Field Releases in Brazil

New techniques and methods are being sought to try to win the battle against mosquitoes. Recent advances in molecular techniques have led to the development of new and innovative methods of mosquito control based around the Sterile Insect Technique (SIT)1-3. A control method known as RIDL&#160;(Release of Insects carrying a Dominant Lethal)4, is based around SIT, but uses genetic methods to remove the need for radiation-sterilization5-8. A RIDL&#160;strain of Ae. aegypti was successfully tested in the field in Grand Cayman9,10; further field use is planned or in progress in other countries around the world.
Mass rearing of insects has been established in several insect species and to levels of billions a week. However, in mosquitoes, rearing has generally been performed on a much smaller scale, with most large scale rearing being performed in the 1970s and 80s. For a RIDL&#160;program it is desirable to release as few females as possible as they bite and transmit disease. In a mass rearing program&#160;there are several stages to produce the males to be released: egg production, rearing eggs until pupation, and then sorting males from females before release. These males are then used for a RIDL&#160;control program,&#160;released as either pupae or adults11,12.
To suppress a mosquito population using RIDL&#160;a large number of high quality male adults need to be reared13,14. The following describes the methods for the mass rearing of OX513A, a RIDL&#160;strain of Ae. aegypti 8, for release and covers the techniques required for the production of eggs and mass rearing RIDL&#160;males for a control program.

Mass Production of Genetically Modified Aedes aegypti for Field Releases in Brazil

To achieve population suppression of Aedes aegypti using the RIDL&#174; (Release of Insects carrying a Dominant Lethal) system, large numbers of male mosquitoes need to be released. This requires the use of mass rearing techniques and technology to provide reliable systems to obtain the maximum number of high quality male mosquitoes.

New techniques and methods are being sought to try to win the battle against mosquitoes. Recent advances in molecular techniques have led to the ...

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals is often not well understood. Here we demonstrate an integrated field lysimetry and porewater sampling method for evaluating the mobility of chemicals applied to soils and established vegetation. Lysimeters, open columns made of metal or plastic, are driven into bareground or vegetated soils. Porewater samplers, which are commercially available and use vacuum to collect percolating soil water, are installed at predetermined depths within the lysimeters. At prearranged times following chemical application to experimental plots, porewater is collected, and lysimeters, containing soil and vegetation, are exhumed. By analyzing chemical concentrations in the lysimeter soil, vegetation, and porewater, downward leaching rates, soil retention capacities, and plant uptake for the chemical of interest may be quantified. Because field lysimetry and porewater sampling are conducted under natural environmental conditions and with minimal soil disturbance, derived results project real-case scenarios and provide valuable information for chemical management. As chemicals are increasingly applied to land worldwide, the described techniques may be utilized to determine whether applied chemicals pose adverse effects to human health or the environment.

Field lysimetry and porewater sampling allow researchers to evaluate the fate of chemicals applied to soils and established vegetation. The goal of this protocol is to demonstrate how to install required instrumentation and collect samples for chemical analysis during integrated field lysimetry and porewater sampling experiments.

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals ...

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

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.

This article showcases the static chamber-based method for measurement of greenhouse gas flux from soil systems. With relatively modest infrastructure investments, measurements may be obtained from multiple treatments/locations and over timeframes ranging from hours to years.

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the ...

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.

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 ...

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

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 describing the vegetation structure in the fields of ecology, forestry, and agriculture. Therefore, procedures of three commercially used methods (litter traps, needle technique, and a plant canopy analyzer) for performing LAI estimation were presented step-by-step. Specific methodological approaches were compared, and their current advantages, controversies, challenges, and future perspectives were discussed in this protocol. Litter traps are usually deemed as the reference level. Both the needle technique and the plant canopy analyzer (e.g., LAI-2000) frequently underestimate LAI values in comparison with the reference. The needle technique is easy to use in deciduous stands where the litter completely decomposes each year (e.g., oak and beech stands). However, calibration based on litter traps or direct destructive methods is necessary. The plant canopy analyzer is a commonly used device for performing LAI estimation in ecology, forestry, and agriculture, but is subject to potential error due to foliage clumping and the contribution of woody elements in the field of view (FOV) of the sensor. Eliminating these potential error sources was discussed. The plant canopy analyzer is a very suitable device for performing LAI estimations at the high spatial level, observing a seasonal LAI dynamic, and for long-term monitoring of LAI.

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 ...

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

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to achieve a high stomatal conductance (gs) to capture CO2 for photosynthesis, water is lost by transpiration1,2. Water evaporating from the airspaces is replaced from cell walls, in turn drawing water from the xylem of leaf veins, in turn drawing from xylem in the stems and roots. As water is pulled through the system, it experiences hydraulic resistance, creating tension throughout the system and a low leaf water potential (&Psi;leaf). The leaf itself is a critical bottleneck in the whole plant system, accounting for on average 30% of the plant hydraulic resistance3. Leaf hydraulic conductance (Kleaf = 1/ leaf hydraulic resistance) is the ratio of the water flow rate to the water potential gradient across the leaf, and summarizes the behavior of a complex system: water moves through the petiole and through several orders of veins, exits into the bundle sheath and passes through or around mesophyll cells before evaporating into the airspace and being transpired from the stomata. Kleaf is of strong interest as an important physiological trait to compare species, quantifying the effectiveness of the leaf structure and physiology for water transport, and a key variable to investigate for its relationship to variation in structure (e.g., in leaf venation architecture) and its impacts on photosynthetic gas exchange. Further, Kleaf responds strongly to the internal and external leaf environment3. Kleaf can increase dramatically with irradiance apparently due to changes in the expression and activation of aquaporins, the proteins involved in water transport through membranes4, and Kleaf declines strongly during drought, due to cavitation and/or collapse of xylem conduits, and/or loss of permeability in the extra-xylem tissues due to mesophyll and bundle sheath cell shrinkage or aquaporin deactivation5-10. Because Kleaf can constrain gs and photosynthetic rate across species in well watered conditions and during drought, and thus limit whole-plant performance they may possibly determine species distributions especially as droughts increase in frequency and severity11-14.
We present a simple method for simultaneous determination of Kleaf and gs on excised leaves. A transpiring leaf is connected by its petiole to tubing running to a water source on a balance. The loss of water from the balance is recorded to calculate the flow rate through the leaf. When steady state transpiration (E, mmol &bull; m-2 &bull; s-1) is reached, gs is determined by dividing by vapor pressure deficit, and Kleaf by dividing by the water potential driving force determined using a pressure chamber (Kleaf= E /- &Delta;&psi;leaf, MPa)15.
This method can be used to assess Kleaf responses to different irradiances and the vulnerability of Kleaf to dehydration14,16,17.

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method EFM

We describe a relatively rapid (30 min) and realistic method for simultaneously measurement of leaf hydraulic conductance (Kleaf) and stomatal conductance (gs) for transpiring excised leaves. The method can be modified to measure the light and dehydration responses of Kleaf and gs.

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to ...

Biology

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the primary photosynthetic organ, and their size and shape vary developmentally and environmentally within a plant. For these reasons studies on leaf morphology require measurement of multiple parameters from numerous leaves, which is best done by semi-automated phenomics tools5,6. Canopy shade is an important environmental cue that affects plant architecture and life history; the suite of responses is collectively called the shade avoidance syndrome (SAS)7. Among SAS responses, shade induced leaf petiole elongation and changes in blade area are particularly useful as indices8. To date, leaf shape programs (e.g. SHAPE9, LAMINA10, LeafAnalyzer11, LEAFPROCESSOR12) can measure leaf outlines and categorize leaf shapes, but can not output petiole length. Lack of large-scale measurement systems of leaf petioles has inhibited phenomics approaches to SAS research. In this paper, we describe a newly developed ImageJ plugin, called LeafJ, which can rapidly measure petiole length and leaf blade parameters of the model plant Arabidopsis thaliana. For the occasional leaf that required manual correction of the petiole/leaf blade boundary we used a touch-screen tablet. Further, leaf cell shape and leaf cell numbers are important determinants of leaf size13. Separate from LeafJ we also present a protocol for using a touch-screen tablet for measuring cell shape, area, and size. Our leaf trait measurement system is not limited to shade-avoidance research and will accelerate leaf phenotyping of many mutants and screening plants by leaf phenotyping.

Demonstration of key methods for high throughput leaf measurements. These methods can be used to accelerate leaf phenotyping when studying many plant mutants or otherwise screening plants by leaf phenotype.

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the ...

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.

Because larger leaves are more susceptible to water loss, the biggest leaves are typically found in plants where rainfall is plentiful. In the driest environments, chloroplasts of succulents are located in the stem of the plant, minimizing evaporation. The orientation of leaves to the sun can also influence light acquisition. In exceptionally sunny environments, horizontally oriented leaves are susceptible to excessive dehydration. In these environments, like those of grasslands, leaves may be oriented vertically to capture light when the sun is low in the sky, thereby reducing sun damage.

Light capture can also be optimized by the positioning of plant leaves with respect to the stem; the arrangement of leaves on a stem is called phyllotaxy. Alternate phyllotaxy describes the scenario in which a single leaf emerges from a single position on the stem. Some plants demonstrate opposite phyllotaxy, in which two leaves emerge in opposing directions from the same location. Whorled phyllotaxy is when several leaves emerge from the same point on a stem. The plant hormone auxin controls the pattern in which leaves emerge from the plant stem.

The Leaf Area Index (LAI) is a representation of light capture efficiency. By measuring the one-sided, horizontal surface area of the leaves on a plant and dividing that by the horizontal ground area the plant covers, a ratio is generated. Typically, a higher LAI indicates more efficient light capture. However, over a LAI greater than seven appears to cause shading and pruning of lower leaves, having no additional effect on light acquisition. In practice, measurement of LAI is often accomplished via satellite imaging and is used to measure the productivity of an ecosystem.

Light Acquisition, Phyllotaxy and Leaf Area Index

Akwizycja światła

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. ...

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

Podsumowanie

Przeglądaj więcej filmów

Rozdziały w tym wideo

Mass Production of Genetically Modified Aedes aegypti for Field Releases in Brazil

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

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

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

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

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

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

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Akwizycja światła