{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T04:33:56Z","timestamp":1769747636594,"version":"3.49.0"},"reference-count":102,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T00:00:00Z","timestamp":1675641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2022YFD2200101"],"award-info":[{"award-number":["2022YFD2200101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["31922055"],"award-info":[{"award-number":["31922055"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFD2200101"],"award-info":[{"award-number":["2022YFD2200101"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31922055"],"award-info":[{"award-number":["31922055"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","award":["2022YFD2200101"],"award-info":[{"award-number":["2022YFD2200101"]}]},{"name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","award":["31922055"],"award-info":[{"award-number":["31922055"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The quantitative, accurate and efficient acquisition of tree phenotypes is the basis for forest \u201cgene-phenotype-environment\u201d studies. It also offers significant support for clarifying the genetic control mechanisms of tree traits. The application of unmanned aerial vehicle (UAV) remote sensing technology to the collection of phenotypic traits at an individual tree level quantitatively analyses tree phenology and directionally evaluates tree growth, as well as accelerating the process of forest genetics and breeding. In this study, with the help of high-resolution, high-overlap, multispectral images obtained by an UAV, combined with digital elevation models (DEMs) extracted from point clouds acquired by a backpack LiDAR, a high-throughput tree structure and spectral phenotypic traits extraction and a genetic selection were conducted in a trial of Eucalyptus clones in the State-owned Dongmen Forest Farm in the Guangxi Zhuang Autonomous Region. Firstly, we validated the accuracy of extracting the phenotypic parameters of individual tree growth based on aerial stereo photogrammetry point clouds. Secondly, on this basis, the repeatability of the tree growth traits and vegetation indices (VIs), the genetic correlation coefficients between the traits were calculated. Finally, the eucalypt clones were ranked by integrating a selection index of traits, and the superior genotypes were selected and their genetic gain predicted. The results showed a high accuracy of the tree height (H) extracted from the digital aerial photogrammetry (DAP) point cloud based on UAV images (R2 = 0.91, and RMSE = 0.56 m), and the accuracy of estimating the diameter at breast height (DBH) was R2 = 0.71, and RMSE = 0.75 cm. All the extracted traits were significantly different within the tree species and among the clones. Except for the crown width (CW), the clonal repeatability (Rc) of the traits were all above 0.9, and the individual repeatability values (Ri) were all above 0.5. The genetic correlation coefficient between the tree growth traits and VIs fluctuated from 0.3 to 0.5, while the best clones were EA14-15, EA14-09, EC184, and EC183 when the selection proportion was 10%. The purpose of this study was to construct a technical framework for phenotypic traits extraction and genetic analysis of trees based on unmanned aerial stereo photography point clouds and high-resolution multispectral images, while also exploring the application potential of this approach in the selective breeding of eucalypt clones.<\/jats:p>","DOI":"10.3390\/rs15040899","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T02:56:08Z","timestamp":1675738568000},"page":"899","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Superior Clone Selection in a Eucalyptus Trial Using Forest Phenotyping Technology via UAV-Based DAP Point Clouds and Multispectral Images"],"prefix":"10.3390","volume":"15","author":[{"given":"Shiyue","family":"Tao","sequence":"first","affiliation":[{"name":"Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaojian","family":"Xie","sequence":"additional","affiliation":[{"name":"Research Institute of Fast-Growing Trees, Chinese Academy of Forestry, Zhanjiang 524022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianzhong","family":"Luo","sequence":"additional","affiliation":[{"name":"Research Institute of Fast-Growing Trees, Chinese Academy of Forestry, Zhanjiang 524022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianzhong","family":"Wang","sequence":"additional","affiliation":[{"name":"State-Owned Dongmen Forest Farm of Guangxi Zhuang Autonomous Region, Chongzuo 532199, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State-Owned Dongmen Forest Farm of Guangxi Zhuang Autonomous Region, Chongzuo 532199, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guibin","family":"Wang","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5195-0477","authenticated-orcid":false,"given":"Lin","family":"Cao","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1126\/science.abp8463","article-title":"Managing forests for competing goals","volume":"376","author":"Gurevitch","year":"2022","journal-title":"Science"},{"key":"ref_2","first-page":"107","article-title":"The Predicament and Countermeasures of Development of Global Eucalyptus Plantations","volume":"25","author":"Wen","year":"2018","journal-title":"Guangxi Sci."},{"key":"ref_3","first-page":"45","article-title":"Study on Crown Growth Law of Eucalyptus urophylla \u00d7 E. grandis Clones","volume":"39","author":"Zhang","year":"2022","journal-title":"Eucalypt Sci. Technol."},{"key":"ref_4","unstructured":"Iglesias-Trabado, G., and Wilstermann, D. (2022, December 02). Eucalyptus Universalis, Global Cultivated Eucalypt Forests Map 2008. Available online: http:\/\/www.mfkp.org\/INRMM\/article\/13780278."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"19764","DOI":"10.1038\/s41598-021-97089-7","article-title":"Geographical spatial distribution and productivity dynamic change of eucalyptus plantations in China","volume":"11","author":"Zhang","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_6","first-page":"70","article-title":"Variation in pulp wood traits between eucalypt clones across sites and implications for deployment strategies","volume":"24","author":"Luo","year":"2012","journal-title":"J. Trop. For. Sci."},{"key":"ref_7","unstructured":"Turnbull, J.W. (2007). Development of Sustainable Forestry Plantations in China: A Review, Australian Centre for International Agricultural Research."},{"key":"ref_8","first-page":"25","article-title":"Genetic analysis and selection of Eucalyptus clones growth","volume":"40","author":"Chen","year":"2020","journal-title":"J. Cent. South Univ. For. Technol."},{"key":"ref_9","first-page":"1","article-title":"Study on Multi-characters Genetic Analysis and Selection Index of 93 Eucalyptus urophylla Clones","volume":"27","author":"Lu","year":"2010","journal-title":"Eucalypt Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1080\/00049158.2016.1275948","article-title":"Genetic variation and genetic gain for energy production, growth traits and wood properties in Eucalyptus hybrid clones in China","volume":"80","author":"Wu","year":"2017","journal-title":"Aust. For."},{"key":"ref_11","first-page":"73","article-title":"Genetic variation analysis and early comprehensive selection of 21 Eucalyptus clones in western Guangdong Province, China","volume":"42","author":"Xie","year":"2018","journal-title":"J. Nanjing For. Univ. Nat. Sci."},{"key":"ref_12","first-page":"580","article-title":"Plant phenomics: History, present status and challenges","volume":"41","author":"Zhou","year":"2018","journal-title":"J. Nanjing Agric. Univ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.ufug.2013.07.002","article-title":"Allometric equations for urban ash trees (Fraxinus spp.) in Oakville, Southern Ontario, Canada","volume":"13","author":"Peper","year":"2014","journal-title":"Urban For. Urban Green."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.foreco.2007.02.027","article-title":"Crown structure and biomass allocation patterns modulate aboveground productivity in young loblolly pine and slash pine","volume":"243","author":"Chmura","year":"2007","journal-title":"For. Ecol. Manag."},{"key":"ref_15","first-page":"260","article-title":"The relationship between canopy width, height and trunk size in some tree species growing in the Savana zone of Nigeria","volume":"3","author":"Arzai","year":"2010","journal-title":"Bayero J. Pure Appl. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1007\/s00468-017-1593-8","article-title":"Modelling crown width\u2013diameter relationship for Scots pine in the central Europe","volume":"31","author":"Sharma","year":"2017","journal-title":"Trees"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1611","DOI":"10.13031\/trans.14419","article-title":"Phenotyping Architecture Traits of Tree Species Using Remote Sensing Techniques","volume":"64","author":"Sangjan","year":"2021","journal-title":"Trans. ASABE"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.pbi.2007.12.004","article-title":"Population, quantitative and comparative genomics of adaptation in forest trees","volume":"11","author":"Neale","year":"2008","journal-title":"Curr. Opin. Plant Biol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1038\/nrg2897","article-title":"Phenomics: The next challenge","volume":"11","author":"Houle","year":"2010","journal-title":"Nat. Rev. Genet."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.3389\/fpls.2017.01111","article-title":"Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives","volume":"8","author":"Yang","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2002","DOI":"10.3389\/fpls.2017.02002","article-title":"High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates","volume":"8","author":"Madec","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.fcr.2012.04.003","article-title":"Field-based phenomics for plant genetics research","volume":"133","author":"White","year":"2012","journal-title":"Field Crop. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1016\/j.tplants.2018.08.005","article-title":"Phenotyping Whole Forests Will Help to Track Genetic Performance","volume":"23","author":"Dungey","year":"2018","journal-title":"Trends Plant Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1002\/ajb2.1347","article-title":"The case for remote sensing of individual plants","volume":"106","author":"Kellner","year":"2019","journal-title":"Am. J. Bot."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Krause, S., Sanders, T.G.M., Mund, J.-P., and Greve, K. (2019). UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring. Remote Sens., 11.","DOI":"10.3390\/rs11070758"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Iizuka, K., Yonehara, T., Itoh, M., and Kosugi, Y. (2018). Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest. Remote Sens., 10.","DOI":"10.3390\/rs10010013"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Berninger, A., Lohberger, S., Zhang, D., and Siegert, F. (2019). Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data. Remote Sens., 11.","DOI":"10.3390\/rs11182105"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nezami, S., Khoramshahi, E., Nevalainen, O., P\u00f6l\u00f6nen, I., and Honkavaara, E. (2020). Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks. Remote Sens., 12.","DOI":"10.20944\/preprints202002.0334.v1"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nevalainen, O., Honkavaara, E., Tuominen, S., Viljanen, N., Hakala, T., Yu, X., Hyypp\u00e4, J., Saari, H., P\u00f6l\u00f6nen, I., and Imai, N.N. (2017). Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sens., 9.","DOI":"10.3390\/rs9030185"},{"key":"ref_30","unstructured":"Constantinescu, S.G., and Niculescu, M. (2013). AIP Conference Proceedings, American Institute of Physics."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Camarretta, N., Harrison, P.A., Lucieer, A., Potts, B.M., Davidson, N., and Hunt, M. (2020). From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure. Remote Sens., 12.","DOI":"10.3390\/rs12193184"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kim, J., Kim, K.-S., Kim, Y., and Chung, Y.S. (2021). A short review: Comparisons of high-throughput phenotyping methods for detecting drought tolerance. Sci. Agric., 78.","DOI":"10.1590\/1678-992x-2019-0300"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chang, A., Yeom, J., Jung, J., and Landivar, J. (2020). Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease. Remote Sens., 12.","DOI":"10.3390\/rs12244122"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1111\/j.1749-8198.2008.00182.x","article-title":"Hyperspectral Remote Sensing of Vegetation","volume":"2","author":"Im","year":"2008","journal-title":"Geogr. Compass"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1353691","DOI":"10.1155\/2017\/1353691","article-title":"Significant remote sensing vegetation indices: A review of developments and applications","volume":"2017","author":"Xue","year":"2017","journal-title":"J. Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Tayade, R., Yoon, J., Lay, L., Khan, A.L., Yoon, Y., and Kim, Y. (2022). Utilization of Spectral Indices for High-Throughput Phenotyping. Plants, 11.","DOI":"10.3390\/plants11131712"},{"key":"ref_37","unstructured":"Han, L. (2019). Study on High-Throughput Maize Phenotyping Analysis and Evaluation Based on UAV Quantitative Remote Sensing. [Ph.D. Thesis, China University of Mining & Technology]."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2853","DOI":"10.1007\/s00122-020-03637-6","article-title":"Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize","volume":"133","author":"Anche","year":"2020","journal-title":"Theor. Appl. Genet."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Rabab, S., Breen, E., Gebremedhin, A., Shi, F., Badenhorst, P., Chen, Y.-P., and Daetwyler, H. (2021). A New Method for Extracting Individual Plant Bio-Characteristics from High-Resolution Digital Images. Remote Sens., 13.","DOI":"10.3390\/rs13061212"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Liao, L., Cao, L., Xie, Y., Luo, J., and Wang, G. (2022). Phenotypic Traits Extraction and Genetic Characteristics Assessment of Eucalyptus Trials Based on UAV-Borne LiDAR and RGB Images. Remote Sens., 14.","DOI":"10.3390\/rs14030765"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Liziniewicz, M., Ene, L.T., Malm, J., Lindberg, J., Helmersson, A., and Karlsson, B. (2020). Estimation of Genetic Parameters and Selection of Superior Genotypes in a 12-Year-Old Clonal Norway Spruce Field Trial after Phenotypic Assessment Using a UAV. Forests, 11.","DOI":"10.3390\/f11090992"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"596315","DOI":"10.3389\/fpls.2020.596315","article-title":"Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance","volume":"11","author":"Pont","year":"2021","journal-title":"Front. Plant Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"114073","DOI":"10.1016\/j.indcrop.2021.114073","article-title":"Heritable variation in tree growth and needle vegetation indices of slash pine (Pinus elliottii) using unmanned aerial vehicles (UAVs)","volume":"173","author":"Tao","year":"2021","journal-title":"Ind. Crop. Prod."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1007\/s11676-015-0092-2","article-title":"Genetic variation in growth traits and stem\u2013branch characteristics and their relationships to Eucalyptus clones","volume":"26","author":"Wu","year":"2015","journal-title":"J. For. Res."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1590\/01047760202026032744","article-title":"THE USE OF GENETIC DISTANCE AND GROUPING METHODS TO PREDICT Eucalyptus Pellita F. MUELL GENITORS FOR HYBRIDIZATION","volume":"26","author":"Andrade","year":"2020","journal-title":"Cerne"},{"key":"ref_46","first-page":"45","article-title":"Eucalyptus Clonal Breeding at Guangxi Dongmen Forest Farm","volume":"32","author":"Zhang","year":"2015","journal-title":"Eucalypt Sci. Technol."},{"key":"ref_47","first-page":"53","article-title":"Present Status of Forest Resources and Sustainable Development in Dongmen Forest Farm, Guangxi","volume":"28","author":"Mo","year":"2011","journal-title":"Eucalypt Sci. Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2016.03.016","article-title":"Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas","volume":"117","author":"Zhao","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"923","DOI":"10.14358\/PERS.72.8.923","article-title":"Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data","volume":"72","author":"Chen","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","first-page":"49","article-title":"Individual Tree Crown Extraction based on UAV Visible Light Remote Sensing Technology","volume":"51","author":"Zhang","year":"2022","journal-title":"J. West China For. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Goutte, C., and Gaussier, E. (2005, January 21\u201323). A probabilistic interpretation of precision, recall and F-score, with implication for evaluation. Proceedings of the European Conference on Information Retrieval, Santiago de Compostela, Spain.","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of Leaf-Area Index from Quality of Light on the Forest Floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_53","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W. (1973). Monitoring Vegetation Systems in the Great Plains with ERTS, NASA Special Publications."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0034-4257(97)00162-4","article-title":"Multivariate Alteration Detection (MAD) and MAF Postprocessing in Multispectral, Bitemporal Image Data: New Approaches to Change Detection Studies","volume":"64","author":"Nielsen","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_55","first-page":"65","article-title":"Monitoring annual forest change in Eucalyptus plantation based on RGB-NDVI detection of remote sensing imagery","volume":"41","author":"Zhou","year":"2017","journal-title":"J. Nanjing For. Univ. Nat. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/0034-4257(88)90031-4","article-title":"Relative sensitivity of normalized difference vegetation Index (NDVI) and microwave polarization difference Index (MPDI) for vegetation and desertification monitoring","volume":"24","author":"Becker","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_57","first-page":"125","article-title":"Research Advance of Broadband Vegetation Index Using Remotely Sensed Images","volume":"32","author":"Li","year":"2015","journal-title":"J. Yangtze River Sci. Res."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/0034-4257(92)90074-T","article-title":"Normalization of multidirectional red and NIR reflectances with the SAVI","volume":"41","author":"Huete","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_59","first-page":"117","article-title":"Research on Eucalyptus Extraction Based on Automatic Threshold Decision Tree Classification","volume":"4","author":"Lu","year":"2020","journal-title":"For. Resour. Manag."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1869","DOI":"10.13031\/2013.27665","article-title":"Remote Sensing of Plant Nitrogen Status in Corn","volume":"39","author":"Bausch","year":"1996","journal-title":"Trans. ASAE"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/S1537-5110(03)00097-7","article-title":"Potential Use of Nitrogen Reflectance Index to estimate Plant Parameters and Yield of Maize","volume":"85","author":"Diker","year":"2003","journal-title":"Biosyst. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"956","DOI":"10.2134\/jeq2004.0956","article-title":"Assessment of Crown Condition in Eucalypt Vegetation by Remotely Sensed Optical Indices","volume":"33","author":"Coops","year":"2004","journal-title":"J. Environ. Qual."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1080\/01431160701281056","article-title":"Crown-scale evaluation of spectral indices for defoliated and discoloured eucalypts","volume":"29","author":"Barry","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_65","unstructured":"Zhang, L. (2012). Research on Remote Sensing Biomass Estimate of Eucalyptus Plantation, Guangxi University."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1590\/1678-992x-2015-0477","article-title":"Estimating foliar nitrogen in Eucalyptus using vegetation indexes","volume":"74","author":"Gomes","year":"2017","journal-title":"Sci. Agricola"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Liao, K., Yang, F., Dang, H., Wu, Y., Luo, K., and Li, G. (2022). Detection of Eucalyptus Leaf Disease with UAV Multispectral Imagery. Forests, 13.","DOI":"10.3390\/f13081322"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Duarte, A., Acevedo-Mu\u00f1oz, L., Gon\u00e7alves, C.I., Mota, L., Sarmento, A., Silva, M., Fabres, S., Borralho, N., and Valente, C. (2020). Detection of Longhorned Borer Attack and Assessment in Eucalyptus Plantations Using UAV Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12193153"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Shen, X., Cao, L., Yang, B., Xu, Z., and Wang, G. (2019). Estimation of Forest Structural Attributes Using Spectral Indices and Point Clouds from UAS-Based Multispectral and RGB Imageries. Remote Sens., 11.","DOI":"10.3390\/rs11070800"},{"key":"ref_70","first-page":"1541","article-title":"Distinguishing vegetation from soil background information","volume":"43","author":"Richardsons","year":"1977","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/0034-4257(94)90134-1","article-title":"A modified soil adjusted vegetation index","volume":"48","author":"Qi","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1562\/0031-8655(2001)074<0038:OPANEO>2.0.CO;2","article-title":"Optical properties and nondestructive estimation of anthocyanin content in plant leaves","volume":"74","author":"Gitelson","year":"2001","journal-title":"Photochem. Photobiol."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1078\/0176-1617-00887","article-title":"Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves","volume":"160","author":"Gitelson","year":"2003","journal-title":"J. Plant Physiol."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/1011-1344(93)06963-4","article-title":"Quantitative estimation of chlorophyll-a using reflectance spectra: Experiments with autumn chestnut and maple leaves","volume":"22","author":"Gitelson","year":"1994","journal-title":"J. Photochem. Photobiol. B Biol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/S0034-4257(02)00010-X","article-title":"Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages","volume":"81","author":"Sims","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_79","first-page":"929","article-title":"Genetic Variation and Early Selection Analysis of Open-pollinated Families of Pinus kesiya var. langbianensis","volume":"30","author":"Li","year":"2017","journal-title":"For. Res."},{"key":"ref_80","unstructured":"Xu, J. (2006). Quantitative Genetics in Forestry, China Forestry Publishing House."},{"key":"ref_81","first-page":"97","article-title":"Application of Repeatability in Tree Breeding","volume":"10","author":"Xu","year":"1988","journal-title":"J. Beijing for. Univ."},{"key":"ref_82","first-page":"20","article-title":"Calculation and application of phenotypic correlation coefficient and genetic correlation coefficient","volume":"1","author":"Wang","year":"1982","journal-title":"Liaoning Agric. Sci."},{"key":"ref_83","unstructured":"Wang, D. (2015). Statistical Analysis and Softw are Development of Genetic Model for Half-sib Progeny Test in Forest Trees, Nanjing Forestry University."},{"key":"ref_84","first-page":"72","article-title":"Multiple- trait combined selection of superior Betula alnoides clones in eastern Guangdong","volume":"37","author":"Wang","year":"2017","journal-title":"J. Cent. South Univ. For. Technol."},{"key":"ref_85","first-page":"1","article-title":"Study on integrated selection of provenances-families of Eucalytus tereticornis","volume":"16","author":"Xu","year":"2003","journal-title":"For. Res."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"958106","DOI":"10.3389\/fpls.2022.958106","article-title":"Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes","volume":"13","author":"Luo","year":"2022","journal-title":"Front. Plant Sci."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"112307","DOI":"10.1016\/j.rse.2021.112307","article-title":"Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach","volume":"256","author":"Yun","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"245","DOI":"10.9787\/PBB.2013.1.3.245","article-title":"Estimation of Genetic Parameters for Growth Performance and Survival Rate in a Clonal Test of Peronema canescens","volume":"1","author":"Kang","year":"2013","journal-title":"Plant Breed. Biotechnol."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"118342","DOI":"10.1016\/j.foreco.2020.118342","article-title":"Genetic parameters and genotype \u00d7 environment interaction in Pinus taeda clonal tests","volume":"474","author":"Braga","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s11295-008-0172-y","article-title":"Comparisons of genetic parameters and clonal value predictions from clonal trials and seedling base population trials of radiata pine","volume":"5","author":"Baltunis","year":"2008","journal-title":"Tree Genet. Genomes"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"1673","DOI":"10.1007\/s11676-020-01210-x","article-title":"Growth variations and stability analyses of seven poplar clones at three sites in northeast China","volume":"32","author":"Pei","year":"2020","journal-title":"J. For. Res."},{"key":"ref_92","first-page":"469","article-title":"Genetic parameters for growth and wood density in juvenile Eucalyptus urophylla S. T. Blake","volume":"39","year":"2005","journal-title":"Agrociencia"},{"key":"ref_93","first-page":"2174","article-title":"Genetic Variation Analysis and Selection of 23 Eucalyptus Clones in Southern Guangxi","volume":"32","author":"Wang","year":"2019","journal-title":"Southwest China J. Agric. Sci."},{"key":"ref_94","first-page":"37","article-title":"Comprehensive Analysis of Multiple Traits of Eucalyptus urophylla x Eucalyptus grangdis Clones","volume":"43","author":"Li","year":"2014","journal-title":"J. West China For. Sci."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"103828","DOI":"10.1016\/j.envexpbot.2019.103828","article-title":"Morpho-physiological variability of Pinus nigra populations reveals climate-driven local adaptation but weak water use differentiation","volume":"166","author":"Santini","year":"2019","journal-title":"Environ. Exp. Bot."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1038\/s41438-019-0137-3","article-title":"Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes","volume":"6","author":"Pallas","year":"2019","journal-title":"Hortic. Res."},{"key":"ref_97","unstructured":"Li, C. (2007). Studies on Clone Selection and Silviculture Effect for Sawlog of E. Urophylla\u00d7E. Grangdis. [Master\u2019s Thesis, Guangxi University]."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Natarajan, S., Basnayake, J., Wei, X., and Lakshmanan, P. (2019). High-Throughput Phenotyping of Indirect Traits for Early-Stage Selection in Sugarcane Breeding. Remote Sens., 11.","DOI":"10.3390\/rs11242952"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"39","DOI":"10.18671\/scifor.v45n113.04","article-title":"Acur\u00e1cia preditiva de testes clonais de Eucalyptus spp. utilizando efeitos aditivos do parentesco e valida\u00e7\u00e3o cruzada","volume":"45","author":"Resende","year":"2017","journal-title":"Sci. For."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.1461-9563.2010.00509.x","article-title":"The constraints of selecting for insect resistance in plantation trees","volume":"13","author":"Henery","year":"2010","journal-title":"Agric. For. \u00c8ntomol."},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Gylander, T., Hamann, A., Brouard, J.S., and Thomas, B.R. (2012). The Potential of Aspen Clonal Forestry in Alberta: Breeding Regions and Estimates of Genetic Gain from Selection. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0044303"},{"key":"ref_102","unstructured":"Zobel, B.J., and Talbert, J. (1984). Applied Forest Tree Improvement, John Wiley & Sons."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/899\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:25:50Z","timestamp":1760120750000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/899"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,6]]},"references-count":102,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15040899"],"URL":"https:\/\/doi.org\/10.3390\/rs15040899","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,6]]}}}