{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:23:07Z","timestamp":1770747787702,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2016,6,25]],"date-time":"2016-06-25T00:00:00Z","timestamp":1466812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The use of depth cameras in precision agriculture is increasing day by day. This type of sensor has been used for the plant structure characterization of several crops. However, the discrimination of small plants, such as weeds, is still a challenge within agricultural fields. Improvements in the new Microsoft Kinect v2 sensor can capture the details of plants. The use of a dual methodology using height selection and RGB (Red, Green, Blue) segmentation can separate crops, weeds, and soil. This paper explores the possibilities of this sensor by using Kinect Fusion algorithms to reconstruct 3D point clouds of weed-infested maize crops under real field conditions. The processed models showed good consistency among the 3D depth images and soil measurements obtained from the actual structural parameters. Maize plants were identified in the samples by height selection of the connected faces and showed a correlation of 0.77 with maize biomass. The lower height of the weeds made RGB recognition necessary to separate them from the soil microrelief of the samples, achieving a good correlation of 0.83 with weed biomass. In addition, weed density showed good correlation with volumetric measurements. The canonical discriminant analysis showed promising results for classification into monocots and dictos. These results suggest that estimating volume using the Kinect methodology can be a highly accurate method for crop status determination and weed detection. It offers several possibilities for the automation of agricultural processes by the construction of a new system integrating these sensors and the development of algorithms to properly process the information provided by them.<\/jats:p>","DOI":"10.3390\/s16070972","type":"journal-article","created":{"date-parts":[[2016,6,27]],"date-time":"2016-06-27T12:56:01Z","timestamp":1467032161000},"page":"972","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":72,"title":["An Approach to the Use of Depth Cameras for Weed Volume Estimation"],"prefix":"10.3390","volume":"16","author":[{"given":"Dionisio","family":"And\u00fajar","sequence":"first","affiliation":[{"name":"Center for Automation and Robotics, Spanish National Research Council, CSIC-UPM, Arganda del Rey, Madrid 28500, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2268-2562","authenticated-orcid":false,"given":"Jos\u00e9","family":"Dorado","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Sciences, Spanish National Research Council, CSIC, Madrid 28006, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C\u00e9sar","family":"Fern\u00e1ndez-Quintanilla","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Sciences, Spanish National Research Council, CSIC, Madrid 28006, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5807-8132","authenticated-orcid":false,"given":"Angela","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Center for Automation and Robotics, Spanish National Research Council, CSIC-UPM, Arganda del Rey, Madrid 28500, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, Q. (2015). Precision Agriculture Technology for Crop Farming, CRC Press.","DOI":"10.1201\/b19336"},{"key":"ref_2","unstructured":"Oerke, E.C., Dehne, H.W., Schnbeck, F., and Weber, A. (1999). Crop Production and Crop Protection: Estimated Losses in Major Food and Cash Crops, Elsevier."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1111\/j.1365-3180.2006.00523.x","article-title":"Assessing the opportunity for site-specific management of Avena sterilis in winter barley fields in Spain","volume":"46","author":"Ruiz","year":"2006","journal-title":"Weed Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1023\/A:1024517624527","article-title":"Site-specific herbicide decision model to maximize profit in winter wheat","volume":"4","author":"Young","year":"2003","journal-title":"Precis. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1046\/j.1365-3180.2003.00349.x","article-title":"Real-time weed detection, decision making and patch spraying in maize, sugar beet, winter wheat and winter barley","volume":"43","author":"Gerhards","year":"2003","journal-title":"Weed Res."},{"key":"ref_6","first-page":"17","article-title":"Herbicide savings and economic benefits of several strategies to control Sorghum halepense in maize crops","volume":"50","author":"Ribeiro","year":"2003","journal-title":"Crop Prot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s10343-013-0301-x","article-title":"The Nature of Sorghum Halepense (L.) Pers. Spatial Distribution Patterns in Tomato Cropping Fields","volume":"65","author":"Jackenkroll","year":"2013","journal-title":"Gesunde Pflanz."},{"key":"ref_8","first-page":"1","article-title":"Cell to whole-plant phenotyping: The best is yet to come","volume":"8","author":"Dhondt","year":"2013","journal-title":"Trends Plant Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"20078","DOI":"10.3390\/s141120078","article-title":"A Review of Imaging Techniques for Plant Phenotyping","volume":"14","author":"Li","year":"2014","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.compag.2010.08.005","article-title":"Sensing technologies for precision specialty crop production","volume":"74","author":"Lee","year":"2010","journal-title":"Comput. Electron. Agric."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s11370-010-0075-2","article-title":"Applied machine vision of plants: A review with implications for field deployment in automated farming operations","volume":"3","author":"McCarthy","year":"2010","journal-title":"Intel. Serv. Robot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.compag.2007.06.002","article-title":"Ground-based sensing system for weed mapping in cotton","volume":"60","author":"Sui","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2304","DOI":"10.3390\/s110302304","article-title":"Accuracy and feasibility of optoelectronic sensors for weed mapping in wide row crops","volume":"11","author":"Ribeiro","year":"2011","journal-title":"Sensors"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1111\/j.1365-3180.2011.00876.x","article-title":"Weed discrimination using ultrasonic sensors","volume":"51","author":"Escola","year":"2011","journal-title":"Weed Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"14662","DOI":"10.3390\/s131114662","article-title":"Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor","volume":"13","author":"Moreno","year":"2013","journal-title":"Sensors"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1800","DOI":"10.1016\/j.measurement.2013.01.011","article-title":"Metrological evaluation of Microsoft Kinect and Asus Xtion sensors","volume":"46","author":"Riveiro","year":"2013","journal-title":"Measurement"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.compag.2011.12.007","article-title":"On the use of depth camera for 3D phenotyping of entire plants","volume":"82","author":"Rousseau","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.jfoodeng.2014.06.019","article-title":"Size estimation of sweet onions using consumer-grade RGB-depth sensor","volume":"142","author":"Wang","year":"2014","journal-title":"J. Food Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1071\/FP12019","article-title":"SPICY: Towards automated phenotyping of large pepper plants in the greenhouse","volume":"39","author":"Song","year":"2012","journal-title":"Funct. Plant Biol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2830","DOI":"10.3390\/s130302830","article-title":"BreedVision\u2014A multi-sensor platform for non-destructive field-based phenotyping in plant breeding","volume":"13","author":"Busemeyer","year":"2013","journal-title":"Sensors"},{"key":"ref_21","unstructured":"Correa, C., Valero, C., Barreiro, P., Ortiz-Ca\u00f1avate, J., and Gil, J. (2013). VII Congreso Ib\u00e9rico de Agroingenier\u00eda y Ciencias Hort\u00edcolas, UPM. (In Spanish)."},{"key":"ref_22","first-page":"165","article-title":"Identification and location system of multi-operation apple robot based on vision combination","volume":"43","author":"Wang","year":"2012","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_23","unstructured":"Agrawal, D., Long, G.A., Tanke, N., Kohanbash, D., and Kantor, G. (August, January 29). Autonomous robot for small-scale NFT systems. Proceedings of the 2012 ASABE Annual International Meeting, Dallas, TX, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.3390\/s140203001","article-title":"Low-cost 3D systems: Suitable tools for plant phenotyping","volume":"14","author":"Paulus","year":"2014","journal-title":"Sensors"},{"key":"ref_25","unstructured":"Lachat, E., Macher, H., Mittet, M.A., Landes, T., and Grussenmeye, P. (September, January 31). First experiences with kinect v2 sensor for close range 3d modelling. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Conference), Avila, Spain."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Fankhauser, P., Bloesch, M., Rodriguez, D., Kaestner, R., Hutter, M., and Siegwart, R. (2015, January 27\u201331). Kinect v2 for mobile robot navigation: Evaluation and modeling. Proceedings of the 2015 IEEE International Advanced Robotics (ICAR), Istanbul, Turkey.","DOI":"10.1109\/ICAR.2015.7251485"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Nie\u00dfner, M., Zollh\u00f6fer, M., Izadi, S., and Stamminger, M. (2013). Real-time 3d reconstruction at scale using voxel hashing. ACM Trans. Graphics, 32.","DOI":"10.1145\/2508363.2508374"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1111\/j.1744-7348.1991.tb04895.x","article-title":"A uniform decimal code for growth stages of crops and weeds","volume":"119","author":"Lancashire","year":"1991","journal-title":"Ann. Appl. Biol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1046\/j.1365-3180.1997.d01-70.x","article-title":"Use of the extended BBCH scale-general for the descriptions of the growth stages of mono- and dicotyledonous weed species","volume":"37","author":"Hess","year":"1997","journal-title":"Weed Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"12999","DOI":"10.3390\/s150612999","article-title":"Matching the Best Viewing Angle in Depth Cameras for Biomass Estimation Based on Poplar Seedling Geometry","volume":"15","author":"Dorado","year":"2015","journal-title":"Sensors"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2384","DOI":"10.3390\/s130202384","article-title":"Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor","volume":"13","author":"Azzari","year":"2013","journal-title":"Sensors"},{"key":"ref_32","unstructured":"Mirtich, B. Fast and Accurate Computation of Polyhedral Mass Properties, 2007. Available online: http:\/\/www.cs.berkeley.edu\/~jfc\/mirtich\/massProps.html."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1614\/0043-1745(2002)050[0281:RMAIWS]2.0.CO;2","article-title":"Review: Multivariate analysis in weed science research","volume":"50","author":"Kenkel","year":"2002","journal-title":"Weed Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"16216","DOI":"10.3390\/s131216216","article-title":"Assessing the potential of low-cost 3D cameras for the rapid measurement of plant woody structure","volume":"13","author":"Nock","year":"2013","journal-title":"Sensors"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhang, W., Yan, K., Li, X., and Zhou, G. (2012, January 22\u201327). Extracting corn geometric structural parameters using Kinect. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352068"},{"key":"ref_36","unstructured":"Yamamoto, S., Hayashi, S., Saito, S., and Ochiai, Y. (August, January 29). Measurement of growth information of a strawberry plant using a natural interaction device. Proceedings of the American Society of Agricultural and Biological Engineers Annual International Meeting, Dallas, TX, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/7\/972\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:24:48Z","timestamp":1760210688000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/7\/972"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,25]]},"references-count":36,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2016,7]]}},"alternative-id":["s16070972"],"URL":"https:\/\/doi.org\/10.3390\/s16070972","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,6,25]]}}}