{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:19:38Z","timestamp":1783037978537,"version":"3.54.6"},"reference-count":164,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFD2400400"],"award-info":[{"award-number":["2023YFD2400400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFD2400401"],"award-info":[{"award-number":["2023YFD2400401"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers and Electronics in Agriculture"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.compag.2026.111828","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T04:19:25Z","timestamp":1777349965000},"page":"111828","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Image-Based, 3D reconstruction for smart farming Applications: A review"],"prefix":"10.1016","volume":"248","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7415-4753","authenticated-orcid":false,"given":"Haihua","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayin","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shulong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyuan","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daoliang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2026.111828_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109033","article-title":"Unlocking plant secrets: a systematic review of 3D imaging in plant phenotyping techniques","volume":"222","author":"Akhtar","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2021.100429","article-title":"Review: Precision Livestock Farming technologies in pasture-based livestock systems","volume":"16","author":"Aquilani","year":"2022","journal-title":"Animal"},{"issue":"3","key":"10.1016\/j.compag.2026.111828_b0015","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1007\/s42853-024-00237-w","article-title":"Development and Application of a Low-cost 3-Dimensional (3D) Reconstruction System based on the Structure from Motion (SfM) Approach for Plant Phenotyping","volume":"49","author":"Arief","year":"2024","journal-title":"J. Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0020","doi-asserted-by":"crossref","first-page":"0235","DOI":"10.34133\/plantphenomics.0235","article-title":"Evaluating Neural Radiance Fields for 3D Plant Geometry Reconstruction in Field Conditions","volume":"6","author":"Arshad","year":"2024","journal-title":"Plant Phenomics"},{"key":"10.1016\/j.compag.2026.111828_b0025","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.compag.2017.01.024","article-title":"Using 3D vision camera system to automatically assess the level of inactivity in broiler chickens","volume":"135","author":"Aydin","year":"2017","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"10.1016\/j.compag.2026.111828_b0030","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1002\/rob.21830","article-title":"Field-based robotic phenotyping of sorghum plant architecture using stereo vision","volume":"36","author":"Bao","year":"2019","journal-title":"J. Field Rob."},{"key":"10.1016\/j.compag.2026.111828_b0035","doi-asserted-by":"crossref","unstructured":"Bernotas, G. et al. (2019) \u201cA photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth,\u201d GigaScience, 8(5), p. giz056. https:\/\/doi.org\/10.1093\/gigascience\/giz056.","DOI":"10.1093\/gigascience\/giz056"},{"key":"10.1016\/j.compag.2026.111828_b0040","unstructured":"Bian, J. et al. (2019) \u201cUnsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video,\u201d Advances in Neural Information Processing Systems. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2019\/hash\/6364d3f0f495b6ab9dcf8d3b5c6e0b01-Abstract.html (Accessed: March 14, 2026)."},{"issue":"5","key":"10.1016\/j.compag.2026.111828_b0045","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1007\/s10457-023-00865-9","article-title":"Assessing canopy structure in andean (agro)forests using 3D UAV remote sensing","volume":"98","author":"Bol\u00edvar-Santamar\u00eda","year":"2024","journal-title":"Agrofor. Syst."},{"key":"10.1016\/j.compag.2026.111828_b0050","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.biosystemseng.2023.08.010","article-title":"The added value of 3D point clouds for digital plant phenotyping \u2013 a case study on internode length measurements in cucumber","volume":"234","author":"Boogaard","year":"2023","journal-title":"Biosyst. Eng."},{"issue":"4","key":"10.1016\/j.compag.2026.111828_b0055","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1093\/aob\/mcaa097","article-title":"Estimation of maize plant height and leaf area index dynamics using an unmanned aerial vehicle with oblique and nadir photography","volume":"126","author":"Che","year":"2020","journal-title":"Ann. Bot."},{"key":"10.1016\/j.compag.2026.111828_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110225","article-title":"High-fidelity 3D reconstruction of peach orchards using a 3DGS-Ag model","volume":"234","author":"Chen","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0065","series-title":"Advances in Computational Intelligence Systems","first-page":"390","article-title":"Fast and Accurate 3D Reconstruction ofPlants using MVSNet andMulti-View Images","author":"Chen","year":"2022"},{"key":"10.1016\/j.compag.2026.111828_b0070","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2024.1439086","article-title":"NeRF-based 3D reconstruction pipeline for acquisition and analysis of tomato crop morphology","volume":"15","author":"Choi","year":"2024","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2026.111828_b0075","doi-asserted-by":"crossref","unstructured":"Choy, C.B. et al. (2016) \u201c3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction,\u201d in B. Leibe et al. (eds.) Computer Vision \u2013 ECCV 2016. Cham: Springer International Publishing (Lecture Notes in Computer Science), pp. 628\u2013644. https:\/\/doi.org\/10.1007\/978-3-319-46484-8_38.","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"10.1016\/j.compag.2026.111828_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.109899","article-title":"A pose-versatile imaging system for comprehensive 3D modeling of planar-canopy fruit trees for automated orchard operations","volume":"230","author":"Churuvija","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"6","key":"10.1016\/j.compag.2026.111828_b0085","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1002\/rob.22077","article-title":"Recent developments and applications of simultaneous localization and mapping in agriculture","volume":"39","author":"Ding","year":"2022","journal-title":"J. Field Rob."},{"key":"10.1016\/j.compag.2026.111828_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.cag.2025.104277","article-title":"GRPE: High-fidelity 3D Gaussian reconstruction for plant entities","volume":"130","author":"Ding","year":"2025","journal-title":"Comput. Graph."},{"issue":"3","key":"10.1016\/j.compag.2026.111828_b0095","first-page":"189","article-title":"Reconstruction method of the 3D model for sheep based on multi-angle Kinect v2","volume":"45","author":"Fan","year":"2024","journal-title":"Journal of Chinese Agricultural Mechanization"},{"key":"10.1016\/j.compag.2026.111828_b0100","series-title":"A Point Set Generation Network for 3D Object Reconstruction from a Single Image","first-page":"2463","author":"Fan","year":"2017"},{"key":"10.1016\/j.compag.2026.111828_b0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108248","article-title":"3D reconstruction of plants using probabilistic voxel carving","volume":"213","author":"Feng","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"5","key":"10.1016\/j.compag.2026.111828_b0110","first-page":"43","article-title":"Measurement Method of Vegetable Seedling Leaf Morphology based on Photometric Stereo","volume":"49","author":"Feng","year":"2018","journal-title":"Transactions of the Chinese Society for Agricultural Machinery"},{"issue":"10","key":"10.1016\/j.compag.2026.111828_b0115","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1007\/s12524-022-01576-x","article-title":"Estimation of Walnut Structure Parameters using Terrestrial Photogrammetry based on Structure-from-Motion (SfM)","volume":"50","author":"Fern\u00e1ndez-Sarr\u00eda","year":"2022","journal-title":"J. Indian Soc. Remote Sens."},{"key":"10.1016\/j.compag.2026.111828_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.micpro.2024.105063","article-title":"FPGA-based stereo matching for crop height measurement using monocular camera","volume":"108","author":"Firmansyah","year":"2024","journal-title":"Microprocess. Microsyst."},{"key":"10.1016\/j.compag.2026.111828_b0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108341","article-title":"A method for obtaining maize phenotypic parameters based on improved QuickShift algorithm","volume":"214","author":"Gao","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0130","series-title":"2024 36th Chinese Control and Decision Conference (CCDC). 2024 36th Chinese Control and Decision Conference (CCDC)","first-page":"2656","article-title":"A Method for estimating fish Biomass based on Underwater Binocular Vision","author":"Gao","year":"2024"},{"key":"10.1016\/j.compag.2026.111828_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2019.105165","article-title":"Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry","volume":"169","author":"Gen\u00e9-Mola","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106343","article-title":"In-field apple size estimation using photogrammetry-derived 3D point clouds: Comparison of 4 different methods considering fruit occlusions","volume":"188","author":"Gen\u00e9-Mola","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105818","article-title":"Pose estimation and adaptable grasp configuration with point cloud registration and geometry understanding for fruit grasp planning","volume":"179","author":"Guo","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107560","article-title":"An improved PointNet++ point cloud segmentation model applied to automatic measurement method of pig body size","volume":"205","author":"Hao","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0155","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s13007-023-01031-z","article-title":"How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques","volume":"19","author":"Harandi","year":"2023","journal-title":"Plant Methods"},{"issue":"12","key":"10.1016\/j.compag.2026.111828_b0160","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.3390\/rs8121031","article-title":"High Throughput Field Phenotyping of Wheat Plant Height and Growth Rate in Field Plot Trials using UAV based Remote Sensing","volume":"8","author":"Holman","year":"2016","journal-title":"Remote Sens. (Basel)"},{"issue":"12","key":"10.1016\/j.compag.2026.111828_b0165","doi-asserted-by":"crossref","first-page":"5038","DOI":"10.1007\/s11947-024-03435-8","article-title":"Real-Time Morphological Measurement of oriental Melon Fruit through Multi-Depth Camera Three-Dimensional Reconstruction","volume":"17","author":"Hong","year":"2024","journal-title":"Food Bioproc. Tech."},{"key":"10.1016\/j.compag.2026.111828_b0170","unstructured":"Horn, B.K.P. (1970) SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW. Technical Report. USA: Massachusetts Institute of Technology."},{"key":"10.1016\/j.compag.2026.111828_b0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107020","article-title":"Modeling realistic 3D agricultural vegetations using a photometric-based approach and its application to weed detection","volume":"198","author":"Hu","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108848","article-title":"High-fidelity 3D reconstruction of plants using Neural Radiance Fields","volume":"220","author":"Hu","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111828_b0185","doi-asserted-by":"crossref","first-page":"806","DOI":"10.3390\/s18030806","article-title":"Automatic Non-Destructive Growth Measurement of Leafy vegetables based on Kinect","volume":"18","author":"Hu","year":"2018","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111828_b0190","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.compag.2014.09.021","article-title":"In-field crop row phenotyping from 3D modeling performed using Structure from Motion","volume":"110","author":"Jay","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0195","doi-asserted-by":"crossref","unstructured":"Jiang, L. et al. (2024) \u201cEstimation of Cotton Boll Number and Main Stem Length Based on 3D Gaussian Splatting.\u201d 2024 ASABE Annual International Meeting, St. Joseph, MI: ASABE (ASABE Paper No. 2400898), p. 1. https:\/\/doi.org\/10.13031\/aim.202400898.","DOI":"10.13031\/aim.202400898"},{"key":"10.1016\/j.compag.2026.111828_b0200","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110293","article-title":"Cotton3DGaussians: Multiview 3D Gaussian Splatting for boll mapping and plant architecture analysis","volume":"234","author":"Jiang","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0205","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.biosystemseng.2024.09.008","article-title":"PointStack based 3D automatic body measurement for goat phenotypic information acquisition","volume":"248","author":"Jin","year":"2024","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0210","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.biosystemseng.2024.12.009","article-title":"In situ volume measurement of dairy cattle via neural radiance fields-based 3D reconstruction","volume":"250","author":"Jing","year":"2025","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0215","article-title":"Remote sensing image fusion on 3D scenarios: a review of applications for agriculture and forestry","volume":"112","author":"Jurado","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.compag.2026.111828_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.livsci.2021.104442","article-title":"Application of depth sensor to estimate body mass and morphometric assessment in Nellore heifers","volume":"245","author":"Kamchen","year":"2021","journal-title":"Livest. Sci."},{"issue":"4","key":"10.1016\/j.compag.2026.111828_b0225","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3592433","article-title":"3D Gaussian Splatting for Real-Time Radiance Field Rendering","volume":"42","author":"Kerbl","year":"2023","journal-title":"ACM Trans. Graph."},{"issue":"12","key":"10.1016\/j.compag.2026.111828_b0230","doi-asserted-by":"crossref","first-page":"1975","DOI":"10.1093\/pcp\/pcab068","article-title":"A Three-Dimensional Scanning System for Digital Archiving and Quantitative Evaluation of Arabidopsis Plant Architectures","volume":"62","author":"Kunita","year":"2021","journal-title":"Plant Cell Physiol."},{"key":"10.1016\/j.compag.2026.111828_b0235","doi-asserted-by":"crossref","unstructured":"Kutulakos, K.N. and Seitz, S.M. (1999) \u201cA theory of shape by space carving,\u201d Proceedings of the Seventh IEEE International Conference on Computer Vision. Proceedings of the Seventh IEEE International Conference on Computer Vision, pp. 307\u2013314 vol.1. https:\/\/doi.org\/10.1109\/ICCV.1999.791235.","DOI":"10.1109\/ICCV.1999.791235"},{"key":"10.1016\/j.compag.2026.111828_b0240","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107903","article-title":"Deep learning-based weight estimation using a fast-reconstructed mesh model from the point cloud of a pig","volume":"210","author":"Kwon","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0245","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106996","article-title":"Iterative offset-based method for reconstructing a mesh model from the point cloud of a pig","volume":"198","author":"Kwon","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111828_b0250","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.inpa.2022.05.005","article-title":"Depth distortion correction for consumer-grade depth cameras in crop reconstruction","volume":"10","author":"Lao","year":"2023","journal-title":"Information Processing in Agriculture"},{"key":"10.1016\/j.compag.2026.111828_b0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106553","article-title":"A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees","volume":"191","author":"Lavaquiol","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0260","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106987","article-title":"Multi-view real-time acquisition and 3D reconstruction of point clouds for beef cattle","volume":"197","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0265","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.biosystemseng.2023.04.014","article-title":"A posture-based measurement adjustment method for improving the accuracy of beef cattle body size measurement based on point cloud data","volume":"230","author":"Li","year":"2023","journal-title":"Biosyst. Eng."},{"issue":"6","key":"10.1016\/j.compag.2026.111828_b0270","doi-asserted-by":"crossref","first-page":"563","DOI":"10.3390\/agriculture11060563","article-title":"Impact of Camera Viewing Angle for estimating Leaf Parameters of Wheat Plants from 3D Point Clouds","volume":"11","author":"Li","year":"2021","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.111828_b0275","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.ecolind.2016.03.036","article-title":"Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system","volume":"67","author":"Li","year":"2016","journal-title":"Ecol. Ind."},{"key":"10.1016\/j.compag.2026.111828_b0280","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106712","article-title":"A single view leaf reconstruction method based on the fusion of ResNet and differentiable render in plant growth digital twin system","volume":"193","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0285","series-title":"2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"5480","article-title":"Photorealistic arm Robot simulation for 3D Plant Reconstruction and Automatic Annotation using Unreal Engine 5","author":"Li","year":"2024"},{"key":"10.1016\/j.compag.2026.111828_b0290","series-title":"2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV). 2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","first-page":"7765","article-title":"BioNet and NeFF: Crop Biomass Prediction from Point Clouds to Drone Imagery","author":"Li","year":"2025"},{"key":"10.1016\/j.compag.2026.111828_b0295","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108149","article-title":"Automatic reconstruction and modeling of dormant jujube trees using three-view image constraints for intelligent pruning applications","volume":"212","author":"Li","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0300","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106107","article-title":"Three-dimensional reconstruction of guava fruits and branches using instance segmentation and geometry analysis","volume":"184","author":"Lin","year":"2021","journal-title":"Comput. Electron. Agric."},{"issue":"8","key":"10.1016\/j.compag.2026.111828_b0305","doi-asserted-by":"crossref","first-page":"1975","DOI":"10.3390\/agronomy13081975","article-title":"RepC-MVSNet: a Reparameterized Self-Supervised 3D Reconstruction Algorithm for Wheat 3D Reconstruction","volume":"13","author":"Liu","year":"2023","journal-title":"Agronomy"},{"key":"10.1016\/j.compag.2026.111828_b0310","series-title":"2018 IEEE International Conference on Information and Automation (ICIA). 2018 IEEE International Conference on Information and Automation (ICIA)","first-page":"1072","article-title":"Point cloud based iterative segmentation technique for 3D plant phenotyping","author":"Liu","year":"2018"},{"key":"10.1016\/j.compag.2026.111828_b0315","series-title":"2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). 2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","first-page":"4263","article-title":"Bird-View 3D Reconstruction for Crops with Repeated Textures","author":"Lu","year":"2023"},{"key":"10.1016\/j.compag.2026.111828_b0320","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110017","article-title":"Automatic coarse-to-fine method for cattle body measurement based on improved GCN and 3D parametric model","volume":"231","author":"Lu","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.compag.2026.111828_b0325","doi-asserted-by":"crossref","first-page":"17315","DOI":"10.1007\/s11042-020-10069-3","article-title":"3D plant root system reconstruction based on fusion of deep structure-from-motion and IMU","volume":"80","author":"Lu","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"10.1016\/j.compag.2026.111828_b0330","doi-asserted-by":"crossref","first-page":"4883","DOI":"10.1109\/TIP.2021.3069578","article-title":"Simultaneous Direct Depth Estimation and Synthesis Stereo for Single image Plant root Reconstruction","volume":"30","author":"Lu","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.compag.2026.111828_b0335","series-title":"Complex, Intelligent, and Software Intensive Systems","first-page":"768","article-title":"3D Model Generation of cattle using Multiple Depth-Maps for ICT Agriculture","author":"Maki","year":"2018"},{"key":"10.1016\/j.compag.2026.111828_b0340","unstructured":"Marinello, F. et al. (2015) \u201cApplication of Kinect-Sensor for three-dimensional body measurements of cows.\u201d European Conference on Precision Livestock Farming. https:\/\/www.research.unipd.it\/handle\/11577\/3171362 (Accessed: January 4, 2025)."},{"key":"10.1016\/j.compag.2026.111828_b0345","series-title":"2022 International Conference on Robotics and Automation (ICRA). 2022 International Conference on Robotics and Automation (ICRA)","first-page":"2259","article-title":"Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching","author":"Marks","year":"2022"},{"key":"10.1016\/j.compag.2026.111828_b0350","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109141","article-title":"Improving 3D reconstruction for accurate measurement of appearance characteristics in shiny fruits using post-harvest particle film: a case study on tomatoes","volume":"224","author":"Masoudi","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0355","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1038\/s41598-023-32167-6","article-title":"High-precision plant height measurement by drone with RTK-GNSS and single camera for real-time processing","volume":"13","author":"Matsuura","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.111828_b0360","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2020.111666","article-title":"Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS","volume":"239","author":"Meinen","year":"2020","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0365","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1145\/3503250","article-title":"NeRF: representing scenes as neural radiance fields for view synthesis","volume":"65","author":"Mildenhall","year":"2021","journal-title":"Commun. ACM"},{"key":"10.1016\/j.compag.2026.111828_b0370","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.biosystemseng.2023.01.005","article-title":"Towards rapid weight assessment of finishing pigs using a handheld, mobile RGB-D camera","volume":"226","author":"Nguyen","year":"2023","journal-title":"Biosyst. Eng."},{"issue":"8","key":"10.1016\/j.compag.2026.111828_b0375","doi-asserted-by":"crossref","first-page":"18587","DOI":"10.3390\/s150818587","article-title":"Structured Light-based 3D Reconstruction System for Plants","volume":"15","author":"Nguyen","year":"2015","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111828_b0380","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.isprsjprs.2020.11.010","article-title":"Three-dimensional photogrammetry with deep learning instance segmentation to extract berry fruit harvestability traits","volume":"171","author":"Ni","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0385","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1270\/jsbbs.21074","article-title":"3D modeling and reconstruction of plants and trees: a cross-cutting review across computer graphics, vision, and plant phenotyping","volume":"72","author":"Okura","year":"2022","journal-title":"Breed. Sci."},{"issue":"47","key":"10.1016\/j.compag.2026.111828_b0390","doi-asserted-by":"crossref","first-page":"34955","DOI":"10.1007\/s11042-020-08854-1","article-title":"Non-destructive and cost-effective 3D plant growth monitoring system in outdoor conditions","volume":"79","author":"Paturkar","year":"2020","journal-title":"Multimed. Tools Appl."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0395","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1186\/s13007-022-00889-9","article-title":"Plant trait measurement in 3D for growth monitoring","volume":"18","author":"Paturkar","year":"2022","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2026.111828_b0400","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110631","article-title":"UAVO-NeRF: 3D reconstruction of orchards and semantic segmentation of fruit trees based on neural radiance field in UAV images","volume":"237","author":"Peng","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.compag.2026.111828_b0405","doi-asserted-by":"crossref","first-page":"3603","DOI":"10.3390\/s18113603","article-title":"On-Barn Pig Weight Estimation based on Body Measurements by Structure-from-Motion (SfM)","volume":"18","author":"Pezzuolo","year":"2018","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0410","article-title":"A comparison of low-cost techniques for three-dimensional animal body measurement in livestock buildings","volume":"275","author":"Pezzuolo","year":"2019","journal-title":"IOP Conf. Ser.: Earth Environ. Sci"},{"key":"10.1016\/j.compag.2026.111828_b0415","article-title":"High-throughput 3D reconstruction of plants and its application to plant feature segmentation","volume":"12","author":"Pham","year":"2025","journal-title":"Smart Agric. Technol."},{"issue":"11","key":"10.1016\/j.compag.2026.111828_b0420","doi-asserted-by":"crossref","first-page":"2713","DOI":"10.11834\/jig.200475","article-title":"3D reconstruction of a single plant leaf image","volume":"26","author":"Ren","year":"2021","journal-title":"Journal of Image and Graphics"},{"key":"10.1016\/j.compag.2026.111828_b0425","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109000","article-title":"Evaluating geometric measurement accuracy based on 3D model reconstruction of nursery tomato plants by Agisoft photoscan software","volume":"221","author":"Roshan","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.compag.2026.111828_b0430","doi-asserted-by":"crossref","first-page":"3150","DOI":"10.3390\/s20113150","article-title":"Performances Evaluation of a Low-cost Platform for High-Resolution Plant Phenotyping","volume":"20","author":"Rossi","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111828_b0435","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106937","article-title":"Implementation of an algorithm for automated phenotyping through plant 3D-modeling: a practical application on the early detection of water stress","volume":"197","author":"Rossi","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0440","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105821","article-title":"Accurate body measurement of live cattle using three depth cameras and non-rigid 3-D shape recovery","volume":"179","author":"Ruchay","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0445","article-title":"Accurate 3D shape recovery of live cattle with three depth cameras","volume":"341","author":"Ruchay","year":"2019","journal-title":"IOP Conf. Ser.: Earth Environ. Sci"},{"key":"10.1016\/j.compag.2026.111828_b0450","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"6254","article-title":"PeanutNeRF: 3D Radiance Field for Peanuts","author":"Saeed","year":"2023"},{"key":"10.1016\/j.compag.2026.111828_b0455","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.biosystemseng.2017.03.001","article-title":"A multi-Kinect cow scanning system: calculating linear traits from manually marked recordings of Holstein-Friesian dairy cows","volume":"157","author":"Salau","year":"2017","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0460","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2017.01680","article-title":"Fast High Resolution volume Carving for 3D Plant Shoot Reconstruction","volume":"8","author":"Scharr","year":"2017","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2026.111828_b0465","doi-asserted-by":"crossref","unstructured":"Scharstein, D., Szeliski, R. and Zabih, R. (2001) \u201cA taxonomy and evaluation of dense two-frame stereo correspondence algorithms,\u201d Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001). Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp. 131\u2013140. https:\/\/doi.org\/10.1109\/SMBV.2001.988771.","DOI":"10.1109\/SMBV.2001.988771"},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0470","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1038\/s41598-024-84375-3","article-title":"Irregular seeds DEM parameters prediction based on 3D point cloud and GA-BP-GA optimization","volume":"15","author":"Shao","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.111828_b0475","volume":"arXiv","author":"Shen","year":"2024","journal-title":"\u201cbiomass Phenotyping of Oilseed Rape through UAV Multi-View Oblique Imaging with 3DGS and SAM Model\u201d."},{"key":"10.1016\/j.compag.2026.111828_b0480","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110320","article-title":"Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model","volume":"235","author":"Shen","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0485","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.compag.2016.08.012","article-title":"An approach of pig weight estimation using binocular stereo system based on LabVIEW","volume":"129","author":"Shi","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0490","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105543","article-title":"Research on 3D surface reconstruction and body size measurement of pigs based on multi-view RGB-D cameras","volume":"175","author":"Shuai","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0495","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.compind.2018.02.002","article-title":"Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field","volume":"97","author":"Smith","year":"2018","journal-title":"Comput. Ind."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0500","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1109\/LRA.2023.3338515","article-title":"PAg-NeRF: Towards Fast and Efficient End-to-End Panoptic 3D Representations for Agricultural Robotics","volume":"9","author":"Smitt","year":"2024","journal-title":"IEEE Rob. Autom. Lett."},{"key":"10.1016\/j.compag.2026.111828_b0505","series-title":"2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","first-page":"5180","article-title":"In-field segmentation and identification of plant structures using 3D imaging","author":"Sodhi","year":"2017"},{"issue":"9","key":"10.1016\/j.compag.2026.111828_b0510","doi-asserted-by":"crossref","first-page":"2981","DOI":"10.3390\/s18092981","article-title":"Structured-Light based 3D Reconstruction System for Cultural Relic packaging","volume":"18","author":"Song","year":"2018","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111828_b0520","doi-asserted-by":"crossref","unstructured":"Stuart, L.A.G. et al. (2025) \u201cHigh-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields,\u201d GigaScience, 14, p. giaf022. https:\/\/doi.org\/10.1093\/gigascience\/giaf022.","DOI":"10.1093\/gigascience\/giaf022"},{"key":"10.1016\/j.compag.2026.111828_b0525","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.isprsjprs.2019.12.011","article-title":"Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering","volume":"160","author":"Sun","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2026.111828_b0530","doi-asserted-by":"crossref","DOI":"10.1016\/j.biosystemseng.2025.104214","article-title":"A multi-posture adaptive method for measuring goat bodies dimensions using 3D point clouds in real-world applications","volume":"257","author":"Sun","year":"2025","journal-title":"Biosyst. Eng."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0535","doi-asserted-by":"crossref","first-page":"10030","DOI":"10.1038\/s41598-022-14325-4","article-title":"Cassava root crown phenotyping using three-dimension (3D) multi-view stereo reconstruction","volume":"12","author":"Sunvittayakul","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.111828_b0540","doi-asserted-by":"crossref","DOI":"10.7717\/peerj.12628","article-title":"3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves","volume":"9","author":"Tross","year":"2021","journal-title":"PeerJ"},{"key":"10.1016\/j.compag.2026.111828_b0545","series-title":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","first-page":"1","article-title":"Underwater 3D Object Reconstruction for fish Length Estimation using Convolutional Neural Networks","author":"Ubi\u00f1a","year":"2021"},{"key":"10.1016\/j.compag.2026.111828_b0550","article-title":"Canopy height estimation using drone-based RGB images","volume":"4","author":"Valluvan","year":"2023","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.111828_b0555","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.biosystemseng.2023.08.016","article-title":"Sim2real flower detection towards automated Calendula harvesting","volume":"234","author":"Vierbergen","year":"2023","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0515","article-title":"Precision farming for sustainability: An agricultural intelligence model","volume":"226","author":"Vinod Chandra","year":"2024","journal-title":"Computers and Electronics in Agriculture"},{"key":"10.1016\/j.compag.2026.111828_b0560","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107419","article-title":"An RGB-D multi-view perspective for autonomous agricultural robots","volume":"202","author":"Vulpi","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0565","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110459","article-title":"ET-PatchNet: a low-memory, efficient model for Multi-view Stereo with a case study on the 3D reconstruction of fruit tree branches","volume":"237","author":"Wan","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0570","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109255","article-title":"Stereo matching and 3D reconstruction with NeRF supervision for accurate weight estimation in free-swimming fish","volume":"225","author":"Wang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0575","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128275","article-title":"Automatic fish weight estimation and 3D surface reconstruction with a lightweight instance segmentation model","volume":"288","author":"Wang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111828_b0580","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109661","article-title":"Benchmarking of monocular camera UAV-based localization and mapping methods in vineyards","volume":"227","author":"Wang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0585","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109682","article-title":"Single-view-based high-fidelity three-dimensional reconstruction of leaves","volume":"227","author":"Wang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0590","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"52","article-title":"Pixel2Mesh: generating 3D Mesh Models from Single RGB Images","author":"Wang","year":"2018"},{"key":"10.1016\/j.compag.2026.111828_b0595","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110582","article-title":"Real-time semantic SLAM-based 3D reconstruction robot for greenhouse vegetables","volume":"237","author":"Wang","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"16","key":"10.1016\/j.compag.2026.111828_b0600","first-page":"243","article-title":"Segmentation and measurement of key phenotype for chinese cabbage sprout using multi-view geometry","volume":"38","author":"Wang","year":"2022","journal-title":"Transactions of the Chinese Society of Agricultural Engineering (transactions of the CSAE)"},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0605","doi-asserted-by":"crossref","first-page":"63","DOI":"10.3390\/rs11010063","article-title":"Maize Plant Phenotyping: Comparing 3D Laser Scanning, Multi-View Stereo Reconstruction, and 3D Digitizing estimates","volume":"11","author":"Wang","year":"2019","journal-title":"Remote Sens. (Basel)"},{"key":"10.1016\/j.compag.2026.111828_b0610","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107687","article-title":"A review of three-dimensional computer vision used in precision livestock farming for cattle growth management","volume":"206","author":"Wang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0615","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110978","article-title":"Automatic measurement method of sheep body size based on 3D reconstruction and point cloud segmentation","volume":"239","author":"Wei","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0620","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.biosystemseng.2023.09.006","article-title":"Modelling wine grapevines for autonomous robotic cane pruning","volume":"235","author":"Williams","year":"2023","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0625","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108328","article-title":"3D grape bunch model reconstruction from 2D images","volume":"215","author":"Woo","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0630","series-title":"\u201cPhotometric method for determining surface orientation from multiple images,\u201d Shape from shading","first-page":"513","author":"Woodham","year":"1989"},{"issue":"5","key":"10.1016\/j.compag.2026.111828_b0635","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.1016\/j.cj.2022.02.007","article-title":"Panicle-3D: a low-cost 3D-modeling method for rice panicles based on deep learning, shape from silhouette, and supervoxel clustering","volume":"10","author":"Wu","year":"2022","journal-title":"The Crop Journal"},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0640","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s13007-023-00988-1","article-title":"Quantification of the three-dimensional root system architecture using an automated rotating imaging system","volume":"19","author":"Wu","year":"2023","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2026.111828_b0645","doi-asserted-by":"crossref","DOI":"10.34133\/2020\/1848437","article-title":"(2020) \u201cMVS-Pheno: a Portable and Low-cost Phenotyping Platform for Maize Shoots using Multiview Stereo 3D Reconstruction,","author":"Wu","year":"2020","journal-title":"Plant Phenomics"},{"key":"10.1016\/j.compag.2026.111828_b0650","article-title":"A miniaturized phenotyping platform for individual plants using multi-view stereo 3D reconstruction","volume":"13","author":"Wu","year":"2022","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2026.111828_b0655","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109259","article-title":"Using high-throughput phenotyping platform MVS-Pheno to decipher the genetic architecture of plant spatial geometric 3D phenotypes for maize","volume":"225","author":"Wu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0660","article-title":"A 3D reconstruction platform for complex plants using OB-NeRF","volume":"16","author":"Wu","year":"2025","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2026.111828_b0665","doi-asserted-by":"crossref","unstructured":"Xiang, L. et al. (2020) \u201cPhenoStereo: a high-throughput stereo vision system for field-based plant phenotyping - with an application in sorghum stem diameter estimation,\u201d 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020, American Society of Agricultural and Biological Engineers. https:\/\/doi.org\/10.13031\/aim.202001190.","DOI":"10.13031\/aim.202001190"},{"key":"10.1016\/j.compag.2026.111828_b0670","article-title":"A review of three-dimensional vision techniques in food and agriculture applications","volume":"5","author":"Xiang","year":"2023","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.111828_b0675","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.compag.2018.11.022","article-title":"Behavior-induced health condition monitoring of caged chickens using binocular vision","volume":"156","author":"Xiao","year":"2019","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"10.1016\/j.compag.2026.111828_b0680","doi-asserted-by":"crossref","first-page":"269","DOI":"10.3390\/rs12020269","article-title":"Image-based Dynamic Quantification of Aboveground Structure of Sugar Beet in Field","volume":"12","author":"Xiao","year":"2020","journal-title":"Remote Sens. (Basel)"},{"key":"10.1016\/j.compag.2026.111828_b0685","doi-asserted-by":"crossref","DOI":"10.1016\/j.eja.2021.126378","article-title":"Estimating economic benefit of sugar beet based on three-dimensional computer vision: a case study in Inner Mongolia, China","volume":"130","author":"Xiao","year":"2021","journal-title":"Eur. J. Agron."},{"key":"10.1016\/j.compag.2026.111828_b0690","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.isprsjprs.2023.05.016","article-title":"High-throughput calculation of organ-scale traits with reconstructed accurate 3D canopy structures using a UAV RGB camera with an advanced cross-circling oblique route","volume":"201","author":"Xiao","year":"2023","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2026.111828_b0695","doi-asserted-by":"crossref","first-page":"0082","DOI":"10.34133\/plantphenomics.0082","article-title":"The Importance of using Realistic 3D Canopy Models to Calculate Light Interception in the Field","volume":"5","author":"Xiao","year":"2023","journal-title":"Plant Phenomics"},{"key":"10.1016\/j.compag.2026.111828_b0700","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.isprsjprs.2024.01.027","article-title":"3D reconstruction and characterization of cotton bolls in situ based on UAV technology","volume":"209","author":"Xiao","year":"2024","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2026.111828_b0705","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105731","article-title":"A review on plant high-throughput phenotyping traits using UAV-based sensors","volume":"178","author":"Xie","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111828_b0710","doi-asserted-by":"crossref","first-page":"343","DOI":"10.3390\/agriculture15030343","article-title":"A Skeleton-based Method of root System 3D Reconstruction and Phenotypic Parameter Measurement from Multi-View image Sequence","volume":"15","author":"Xu","year":"2025","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.111828_b0715","doi-asserted-by":"crossref","DOI":"10.1016\/j.biosystemseng.2025.104171","article-title":"A reconstruction method for incomplete pig point clouds based on stepwise hole filling and its applications","volume":"255","author":"Xu","year":"2025","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111828_b0720","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108866","article-title":"Research on automatic 3D reconstruction of plant phenotype based on Multi-View images","volume":"220","author":"Yang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0725","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107218","article-title":"Automated measurement of dairy cows body size via 3D point cloud data analysis","volume":"200","author":"Yang","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0730","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108512","article-title":"3D-based precise evaluation pipeline for maize ear rot using multi-view stereo reconstruction and point cloud semantic segmentation","volume":"216","author":"Yang","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"21","key":"10.1016\/j.compag.2026.111828_b0735","doi-asserted-by":"crossref","first-page":"6068","DOI":"10.3390\/s20216068","article-title":"A Low-cost 3D Phenotype Measurement Method of Leafy vegetables using Video Recordings from Smartphones","volume":"20","author":"Yang","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111828_b0740","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.109957","article-title":"Facility of tomato plant organ segmentation and phenotypic trait extraction via deep learning","volume":"231","author":"Yao","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0745","doi-asserted-by":"crossref","unstructured":"Yao, Y. et al. (2018) \u201cMVSNet: Depth Inference for Unstructured Multi-view Stereo,\u201d in V. Ferrari et al. (eds.) Computer Vision \u2013 ECCV 2018. Cham: Springer International Publishing (Lecture Notes in Computer Science), pp. 785\u2013801. https:\/\/doi.org\/10.1007\/978-3-030-01237-3_47.","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"10.1016\/j.compag.2026.111828_b0750","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109229","article-title":"Sensors, systems and algorithms of 3D reconstruction for smart agriculture and precision farming: a review","volume":"224","author":"Yu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0755","series-title":"Time-of-Flight and Structured Light Depth Cameras: Technology and applications","author":"Zanuttigh","year":"2016"},{"key":"10.1016\/j.compag.2026.111828_b0760","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.126220","article-title":"MT-MVSNet: a lightweight and highly accurate convolutional neural network based on mobile transformer for 3D reconstruction of orchard fruit tree branches","volume":"268","author":"Zeng","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111828_b0765","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5399","article-title":"Wheat3DGS: In-field 3D Reconstruction, Instance Segmentation and Phenotyping of Wheat Heads with Gaussian Splatting","author":"Zhang","year":"2025"},{"key":"10.1016\/j.compag.2026.111828_b0770","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108307","article-title":"Automatic method for quantitatively analyzing the body condition of livestock from 3D shape","volume":"214","author":"Zhang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0775","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108629","article-title":"Neural radiance fields for multi-scale constraint-free 3D reconstruction and rendering in orchard scenes","volume":"217","author":"Zhang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111828_b0780","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.compind.2018.02.006","article-title":"Photometric stereo for three-dimensional leaf venation extraction","volume":"98","author":"Zhang","year":"2018","journal-title":"Comput. Ind."},{"key":"10.1016\/j.compag.2026.111828_b0785","doi-asserted-by":"crossref","unstructured":"Zhang, X.\/ et al. (2021) \u201c3D reconstruction of chicken based on color and thermal images,\u201d 2021 ASABE Annual International Virtual Meeting, July 12-16, 2021 [Preprint]. https:\/\/doi.org\/10.13031\/aim.202100079.","DOI":"10.13031\/aim.202100079"},{"key":"10.1016\/j.compag.2026.111828_b0790","first-page":"1","article-title":"Phenotypic Parameters Estimation of Plants using Deep Learning-based 3-D Reconstruction from Single RGB image","volume":"19","author":"Zhao","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"4","key":"10.1016\/j.compag.2026.111828_b0795","first-page":"783","article-title":"FGPointKAN++ point cloud segmentation and adaptive key cutting plane recognition for cow body size measurement","volume":"15","author":"Zhou","year":"2025","journal-title":"Artif. Intell. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111828_b0800","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1093\/aob\/mcaa046","article-title":"Quantification of light interception within image-based 3-D reconstruction of sole and intercropped canopies over the entire growth season","volume":"126","author":"Zhu","year":"2020","journal-title":"Ann. Bot."},{"issue":"1","key":"10.1016\/j.compag.2026.111828_b0805","doi-asserted-by":"crossref","first-page":"7055","DOI":"10.1038\/s41598-020-63720-2","article-title":"Analysing the phenotype development of soybean plants using low-cost 3D reconstruction","volume":"10","author":"Zhu","year":"2020","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.111828_b0810","series-title":"2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN). 2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN)","first-page":"130","article-title":"A General Video Surveillance Framework for Animal Behavior Analysis","author":"Zin","year":"2016"},{"issue":"2","key":"10.1016\/j.compag.2026.111828_b0815","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1111\/cgf.13386","article-title":"State of the Art on 3D reconstruction with RGB\u2010D Cameras","volume":"37","author":"Zollh\u00f6fer","year":"2018","journal-title":"Comput. Graphics Forum"},{"key":"10.1016\/j.compag.2026.111828_b0820","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107626","article-title":"Density estimation method of mature wheat based on point cloud segmentation and clustering","volume":"205","author":"Zou","year":"2023","journal-title":"Comput. Electron. Agric."}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926004230?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926004230?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T23:58:09Z","timestamp":1783036689000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169926004230"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":164,"alternative-id":["S0168169926004230"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2026.111828","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Image-Based, 3D reconstruction for smart farming Applications: A review","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2026.111828","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111828"}}