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Yield estimation in vineyards by visual grape detection

S. Nuske, S. Achar, T. Bates, S. Narasimhan, S. Singh
<span title="">2011</span> <i title="IEEE"> 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems </i> &nbsp;
The harvest yield in vineyards can vary significantly from year to year and also spatially within plots due to variations in climate, soil conditions and pests.  ...  Both shape and visual texture are used to detect berries. We demonstrate detection of green berries against a green leaf background.  ...  ACKNOWLEDGEMENTS This work is funded by the National Grape and Wine Initiative, 1415 L Street, Suite 460, Sacramento, California, 95814, USA, info@NGWI.org.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iros.2011.6048830">doi:10.1109/iros.2011.6048830</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bxc6wqr2i5akddjn52uscypi3m">fatcat:bxc6wqr2i5akddjn52uscypi3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812215155/http://www.cs.cmu.edu/~sachar/grape_iros2011.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8c/85/8c85a2930da5790eb481d1d62e91ef4e23615559.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iros.2011.6048830"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Yield estimation in vineyards by visual grape detection

Stephen Nuske, Supreeth Achar, Terry Bates, Srinivasa Narasimhan, Sanjiv Singh
<span title="">2011</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmucnarmarh2fj6syg5jyqs7ny" style="color: black;">2011 IEEE/RSJ International Conference on Intelligent Robots and Systems</a> </i> &nbsp;
The harvest yield in vineyards can vary significantly from year to year and also spatially within plots due to variations in climate, soil conditions and pests.  ...  Both shape and visual texture are used to detect berries. We demonstrate detection of green berries against a green leaf background.  ...  ACKNOWLEDGEMENTS This work is funded by the National Grape and Wine Initiative, 1415 L Street, Suite 460, Sacramento, California, 95814, USA, info@NGWI.org.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iros.2011.6095069">doi:10.1109/iros.2011.6095069</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iros/NuskeABNS11.html">dblp:conf/iros/NuskeABNS11</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jhv4lc4sknd6tdirhjaaniflx4">fatcat:jhv4lc4sknd6tdirhjaaniflx4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812215155/http://www.cs.cmu.edu/~sachar/grape_iros2011.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8c/85/8c85a2930da5790eb481d1d62e91ef4e23615559.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iros.2011.6095069"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Modeling and Calibrating Visual Yield Estimates in Vineyards [chapter]

Stephen Nuske, Kamal Gupta, Srinivasa Narasimhan, Sanjiv Singh
<span title="2013-12-31">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lirc5icuifhy7ln5rynpn4ak2e" style="color: black;">Springer Tracts in Advanced Robotics</a> </i> &nbsp;
Computer vision algorithms are applied to detect grape berries in images that have been registered together to generate high-resolution estimates.  ...  Accurate yield estimates are of great value to vineyard growers to make informed management decisions such as crop thinning, shoot thinning, irrigation and nutrient delivery, preparing for harvest and  ...  Acknowledgements Work funded by the National Grape and Wine Initiative, (info@NGWI.org).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-40686-7_23">doi:10.1007/978-3-642-40686-7_23</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/swvthiwk2jhtnitmitxcln5m3e">fatcat:swvthiwk2jhtnitmitxcln5m3e</a> </span>
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Computer Vision and Machine Learning for Viticulture Technology

Kah Phooi Seng, Li-Minn Ang, Leigh M. Schmidtke, Suzy Y. Rogiers
<span title="">2018</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
We summarize the latest developments in vision systems and techniques with examples from various representative studies, including, harvest yield estimation, vineyard management and monitoring, grape disease  ...  detection, quality evaluation, and grape phenology.  ...  estimation, vineyard management and monitoring, grape disease detection, quality evaluation, and grape phenology.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2018.2875862">doi:10.1109/access.2018.2875862</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ngtf32fvtvdjhjtgpzh4knltje">fatcat:ngtf32fvtvdjhjtgpzh4knltje</a> </span>
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Towards Predicting Vine Yield: Conceptualization of 3D Grape Models and Derivation of Reliable Physical and Morphological Parameters

Thomas Schneider, Gernot Paulus, Karl-Heinrich Anders
<span title="">2020</span> <i title="Osterreichische Akademie der Wissenschaften"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fr7biv72rfen5cxwllnb5w4zxe" style="color: black;">GI_FORUM - Journal for Geographic Information Science</a> </i> &nbsp;
Traditional collection of these data and yield prediction rely on resource-and time-intensive direct visual and manual in-field work by viticulturists.  ...  Thus, only limited sampling in the vineyards is possible, carried out by humans.  ...  Deploying vineyard-related practices in timely fashion, such as the adjustment of canopy and nutrients, or the detection and elimination of diseases and insects, leads to an increased yield, yield quality  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1553/giscience2020_01_s73">doi:10.1553/giscience2020_01_s73</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wuk3w4vaxnez5ggx3jr6u5jtnm">fatcat:wuk3w4vaxnez5ggx3jr6u5jtnm</a> </span>
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Low-Cost, Computer Vision-Based, Prebloom Cluster Count Prediction in Vineyards

Jonathan Jaramillo, Justine Vanden Heuvel, Kirstin H. Petersen
<span title="2021-04-08">2021</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m3uue43vtfbpdh7yvoxszzj75q" style="color: black;">Frontiers in Agronomy</a> </i> &nbsp;
Traditional methods for estimating the number of grape clusters in a vineyard generally involve manually counting the number of clusters per vine in a subset of the vineyard and scaling by the total number  ...  This method detects, tracks, and counts clusters and shoots in videos collected using a smartphone camera that is driven or walked through the vineyard at night.  ...  While many small wine grape growers in the Northeastern U.S. do not use formal methods to generate yield estimate predictions, those who do yield estimation tend to use this manual method due to the limited  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fagro.2021.648080">doi:10.3389/fagro.2021.648080</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vd6nfcovpzhzlitqphaqrlzkbq">fatcat:vd6nfcovpzhzlitqphaqrlzkbq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210409063712/https://fjfsdata01prod.blob.core.windows.net/articles/files/648080/pubmed-zip/.versions/1/.package-entries/fagro-03-648080/fagro-03-648080.pdf?sv=2018-03-28&amp;sr=b&amp;sig=9sErsPv%2BajXUvJBCGTzs8TtRzGfNIi%2FicXQtnVRQA1o%3D&amp;se=2021-04-09T06%3A37%3A42Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fagro-03-648080.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/40/88/40886e0cabcfea4d1faee84b64943479ef28136b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fagro.2021.648080"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a>

A Low-Cost and Unsupervised Image Recognition Methodology for Yield Estimation in a Vineyard

Salvatore Filippo Di Gennaro, Piero Toscano, Paolo Cinat, Andrea Berton, Alessandro Matese
<span title="2019-05-03">2019</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bbmitkj3efgeppizzjrx6w5emu" style="color: black;">Frontiers in Plant Science</a> </i> &nbsp;
Yield prediction is a key factor to optimize vineyard management and achieve the desired grape quality.  ...  The segmentation results in cluster detection showed a performance of over 85% in partially leaf removal and full ripe condition, and allowed grapevine yield to be estimated with more than 84% of accuracy  ...  Moreover, yield evaluation with visual inspection by means of cluster counting and size estimation is subjective resulting in error variations between the results of different people .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fpls.2019.00559">doi:10.3389/fpls.2019.00559</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31130974">pmid:31130974</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6509744/">pmcid:PMC6509744</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/msmr474cejg4zdii2vg7bea3gm">fatcat:msmr474cejg4zdii2vg7bea3gm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191206232513/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6509744&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/80/eb/80ebb9d82b69bebb897d0cc5296a2d1263f422db.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fpls.2019.00559"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509744" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Grape Cluster Detection Using UAV Photogrammetric Point Clouds as a Low-Cost Tool for Yield Forecasting in Vineyards

Jorge Torres-Sánchez, Francisco Javier Mesas-Carrascosa, Luis-Gonzaga Santesteban, Francisco Manuel Jiménez-Brenes, Oihane Oneka, Ana Villa-Llop, Maite Loidi, Francisca López-Granados
<span title="2021-04-28">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
The accuracy achieved in grape detection opens the door to yield prediction in red grape vineyards.  ...  There have been significant advances in automatic yield estimation in vineyards from on-ground imagery, but terrestrial platforms have some limitations since they can cause soil compaction and have problems  ...  Acknowledgments: The authors would like to thank the staff in Bodegas Ochoa for their cooperation with the set-up and maintenance of the vineyards.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21093083">doi:10.3390/s21093083</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33925169">pmid:33925169</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/om6plhtmfzcnnbvl5dvyptqvdi">fatcat:om6plhtmfzcnnbvl5dvyptqvdi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716212917/https://digital.csic.es/bitstream/10261/241435/1/Forecasting_Vineyards.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f5/a1/f5a121d3ed59535b493a86ec5668d686723a803c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21093083"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

A Non-Invasive Method Based on Computer Vision for Grapevine Cluster Compactness Assessment Using a Mobile Sensing Platform under Field Conditions

Palacios, Diago, Tardaguila
<span title="2019-09-02">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
platforms in commercial vineyards.  ...  Thus far, cluster compactness assessment has been based on visual inspection performed by trained evaluators with very scarce application in the wine industry.  ...  In general terms, the T18 model yielded the best results for these two relevant classes, closely followed by the S18 model, in this case only for the "grape" class, and slightly outperformed by the CS18  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19173799">doi:10.3390/s19173799</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pkmryiuinjdordzv6fam7pt34a">fatcat:pkmryiuinjdordzv6fam7pt34a</a> </span>
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Development of a Low-Cost Semantic Monitoring System for Vineyards Using Autonomous Robots

Abhijeet Ravankar, Ankit A. Ravankar, Michiko Watanabe, Yohei Hoshino, Arpit Rawankar
<span title="2020-05-21">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6iatzfbfmfbi5o7oaltji6olja" style="color: black;">Agriculture</a> </i> &nbsp;
Farmers frequently monitor the vineyard to check grape conditions, damage due to infections from pests and insects, grape growth, and to estimate optimal harvest time.  ...  To this end, robots have a big potential to increase productivity in farms by automating various tasks. We propose a low-cost semantic monitoring system for vineyards using autonomous robots.  ...  Yield estimation: Visual estimation is important to estimate an approximate yield estimation of a vineyard.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriculture10050182">doi:10.3390/agriculture10050182</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p5c2c32gifhvzjdnxjozoqvqie">fatcat:p5c2c32gifhvzjdnxjozoqvqie</a> </span>
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Page 511 of The Journal of Applied Ecology Vol. 39, Issue 3 [page]

<span title="">2002</span> <i title="Blackwell Publishing Ltd."> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_journal-of-applied-ecology" style="color: black;">The Journal of Applied Ecology</a> </i> &nbsp;
We used visual estimation techniques and novel data collection and management procedures to detect small-scale spatiotemporal patterns in bird damage to Baco Noir and Vidal (ice-wine) grape varieties in  ...  Starlings foraged by making short forays into vineyards from perches in adjacent vegetation.  ... 
<span class="external-identifiers"> </span>
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3DBunch: A novel iOS-smartphone application to evaluate the number of grape berries per bunch using image analysis techniques

Scarlett Liu, Xiangdong Zeng, Mark Whitty
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Evaluating the number of berries per bunch is a vital step of grape yield estimation in viticulture but is a labour intensive task for traditional manual measurement.  ...  INDEX TERMS Berry counting, bunch analysis, image analysis, iOS application, yield estimation.  ...  This leads to a lack of samples and results in inaccurate grape yield estimation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3003415">doi:10.1109/access.2020.3003415</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kng5vqlcorhjxfbgr5sj7wt42u">fatcat:kng5vqlcorhjxfbgr5sj7wt42u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200723194002/https://ieeexplore.ieee.org/ielx7/6287639/8948470/09120004.pdf?tp=&amp;arnumber=9120004&amp;isnumber=8948470&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/da/ae/daae1e0c79c3e5b25fac9e2634463c4983a13653.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3003415"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Potentials of small, lightweight and low cost Multi-Echo Laser Scanners for detecting Grape Berries

A. Djuricic, M. Weinmann, B. Jutzi
<span title="2014-06-06">2014</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i74shj7anreaxjo327fokng66m" style="color: black;">The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</a> </i> &nbsp;
In this contribution we focus on vineyard monitoring for detecting and counting grape berries with a small, lightweight and low cost multi-echo laser scanner.  ...  The approach performs with a detection accuracy of above 84%. The results reveal the high potential of such close range ranging devices for locating and counting grape berries.  ...  ACKNOWLEDGEMENT Ana Djuricic was supported by the German Academic Exchange Service (DAAD) scholarship. The authors thank Sven Wursthorn for assistance during data acquisition.  ... 
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Vineyard Yield Estimation, Prediction, and Forecasting: A Systematic Literature Review

André Barriguinha, Miguel de Castro Neto, Artur José Freire Gil
<span title="2021-09-07">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yws6xlpwzjf7llvhkn3wayuvfu" style="color: black;">Agronomy</a> </i> &nbsp;
Nevertheless, most of these approaches are still in the research domain and lack practical applicability in real vineyards by the actual farmers.  ...  Purpose—knowing in advance vineyard yield is a critical success factor so growers and winemakers can achieve the best balance between vegetative and reproductive growth.  ...  Reference Data Sources Test Environment Scale Related Variables Estimation [91] RGB images Field/Laboratory local Grape berries recognition and grape bunch detection Grapes bunches detection  ... 
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Natural Inspired Intelligent Visual Computing and Its Application to Viticulture

Li Ang, Kah Seng, Feng Ge
<span title="2017-05-23">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
(AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia.  ...  The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model.  ...  This work was partly funded by CM3 Machine Learning, Faculty of Business, Justice and Behavioural Sciences at Charles Sturt University.  ... 
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