{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T09:07:52Z","timestamp":1765357672530,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T00:00:00Z","timestamp":1725321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan","award":["2019YFD1000104","31901963","32060653","32060646"],"award-info":[{"award-number":["2019YFD1000104","31901963","32060653","32060646"]}]},{"name":"National Natural Fund Project","award":["2019YFD1000104","31901963","32060653","32060646"],"award-info":[{"award-number":["2019YFD1000104","31901963","32060653","32060646"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding canopy nitrogen (N) and phosphorus (P) differences is crucial for optimizing plant nutrient distribution and management. This study evaluated leaf N and P content in citrus trees across three cultivation modes: traditional mode (TM), wide-row and narrow-plant mode (WRNPM), and fenced mode (FM). We used hyperspectral data for non-destructive quantification and compared 1080 leaf samples from upper, middle, and lower canopy layers. Four models\u2014Random Forest (RF), Backpropagation Neural Network (BPNN), Partial Least Squares (PLS), and Support Vector Machine (SVM)\u2014were employed for leaf N and P estimation. Results showed that the TM had significantly lower N content compared to the WRNPM and FM, while the WRNPM exhibited higher P content. The canopy layer had minimal impact on N and P in the FM, and leaves in the upper layer had higher nutrient content in the WRNPM and TM. RF provided the best estimation accuracy, with R2 values of 0.66 for N and 0.72 for P. The cultivation mode and canopy layer significantly influenced the estimation accuracy, with the TM yielding the highest R2, followed by the WRNPM and FM obtaining the lowest accuracy. The labor-saving cultivation mode had different nutrient utilization efficiency compared to the TM. The cultivation mode and canopy layer should be considered when hyperspectral data were used for estimating the leaf N and P content. The study can offer new insights for precise fertilization strategies in fruit trees.<\/jats:p>","DOI":"10.3390\/rs16173261","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T04:06:41Z","timestamp":1725336401000},"page":"3261","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Leaf Nitrogen and Phosphorus Variation and Estimation of Citrus Tree under Two Labor-Saving Cultivation Modes Using Hyperspectral Data"],"prefix":"10.3390","volume":"16","author":[{"given":"Dasui","family":"Li","sequence":"first","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"}]},{"given":"Qingqing","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3820-889X","authenticated-orcid":false,"given":"Jinzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"},{"name":"National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Wuhan 430070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4957-3681","authenticated-orcid":false,"given":"Yuanyong","family":"Dian","sequence":"additional","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"},{"name":"Hubei Engineering Technology Research Center for Forestry Information, Wuhan 430070, China"}]},{"given":"Chungen","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"},{"name":"National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Wuhan 430070, China"}]},{"given":"Jingjing","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China"},{"name":"Hubei Engineering Technology Research Center for Forestry Information, Wuhan 430070, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2489","DOI":"10.1093\/jxb\/erx037","article-title":"Molecular Fundamentals of Nitrogen Uptake and Transport in Trees","volume":"68","author":"Pascual","year":"2017","journal-title":"J. Exp. Bot."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.envexpbot.2019.04.013","article-title":"Growth Performance, Photosynthesis, and Root Characteristics Are Associated with Nitrogen Use Efficiency in Six Poplar Species","volume":"164","author":"Luo","year":"2019","journal-title":"Environ. Exp. Bot."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.envexpbot.2019.03.003","article-title":"Morphological and Physiological Responses to Contrasting Nitrogen Regimes in Populus Cathayana Is Linked to Resources Allocation and Carbon\/Nitrogen Partition","volume":"162","author":"Luo","year":"2019","journal-title":"Environ. Exp. Bot."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1111\/jipb.13090","article-title":"Root Developmental Responses to Phosphorus Nutrition","volume":"63","author":"Liu","year":"2021","journal-title":"J. Integr. Plant Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105367","DOI":"10.1016\/j.envexpbot.2023.105367","article-title":"Proteomic Reconfigurations Underlying Physiological Alterations in Poplar Roots in Acclimation to Changing Nitrogen Availability","volume":"211","author":"Li","year":"2023","journal-title":"Environ. Exp. Bot."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"118978","DOI":"10.1016\/j.indcrop.2024.118978","article-title":"Wood Formation in Trees Responding to Nitrogen Availability","volume":"218","author":"Lu","year":"2024","journal-title":"Ind. Crops Prod."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1146\/annurev.environ.032108.105046","article-title":"Nitrogen in Agriculture: Balancing the Cost of an Essential Resource","volume":"34","author":"Robertson","year":"2009","journal-title":"Annu. Rev. Environ. Resour."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1038\/ngeo2693","article-title":"Long-Term Accumulation and Transport of Anthropogenic Phosphorus in Three River Basins","volume":"9","author":"Powers","year":"2016","journal-title":"Nat. Geosci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/nature11909","article-title":"Using Membrane Transporters to Improve Crops for Sustainable Food Production","volume":"497","author":"Schroeder","year":"2013","journal-title":"Nature"},{"key":"ref_10","first-page":"1264","article-title":"Fruit scientific research in New China in the past 70 years: Citrus","volume":"36","author":"Guo","year":"2019","journal-title":"J. Fruit Sci."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Osco, L.P., Ramos, A.P.M., Pereira, D.R., Moriya, \u00c9.A.S., Imai, N.N., Matsubara, E.T., Estrabis, N., de Souza, M., Junior, J.M., and Gon\u00e7alves, W.N. (2019). Predicting Canopy Nitrogen Content in Citrus-Trees Using Random Forest Algorithm Associated to Spectral Vegetation Indices from UAV-Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11242925"},{"key":"ref_12","first-page":"96","article-title":"Physiological Effects of Nitrogen on Fruit Trees","volume":"33","author":"Li","year":"2002","journal-title":"J. Shandong Agric. Univ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1111\/aab.12014","article-title":"Nitrogen Losses from the Soil\/Plant System: A Review","volume":"162","author":"Cameron","year":"2013","journal-title":"Ann. Appl. Biol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Osco, L.P., Ramos, A.P.M., Faita Pinheiro, M.M., Moriya, \u00c9.A.S., Imai, N.N., Estrabis, N., Ianczyk, F., Ara\u00fajo, F.F., Liesenberg, V., and Jorge, L.A.d.C. (2020). A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements. Remote Sens., 12.","DOI":"10.3390\/rs12060906"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Rom\u00e1n, J.R., Rodr\u00edguez-Caballero, E., Rodr\u00edguez-Lozano, B., Roncero-Ramos, B., Chamizo, S., \u00c1guila-Carricondo, P., and Cant\u00f3n, Y. (2019). Spectral Response Analysis: An Indirect and Non-Destructive Methodology for the Chlorophyll Quantification of Biocrusts. Remote Sens., 11.","DOI":"10.3390\/rs11111350"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1007\/s11119-014-9348-7","article-title":"Using Hyperspectral Remote Sensing Techniques to Monitor Nitrogen, Phosphorus, Sulphur and Potassium in Wheat (Triticum aestivum L.)","volume":"15","author":"Mahajan","year":"2014","journal-title":"Precis. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.biosystemseng.2022.05.001","article-title":"Improving Rice Nitrogen Stress Diagnosis by Denoising Strips in Hyperspectral Images via Deep Learning","volume":"219","author":"Zhu","year":"2022","journal-title":"Biosyst. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Guan, M., Wang, L., Cui, X., Li, T., and Zhang, F. (2024). In Situ Nondestructive Detection of Nitrogen Content in Soybean Leaves Based on Hyperspectral Imaging Technology. Agronomy, 14.","DOI":"10.3390\/agronomy14040806"},{"key":"ref_19","first-page":"80","article-title":"Prediction of Nitrogen and Phosphorus Contents in Citrus Leaves Based on Hyperspectral Imaging","volume":"8","author":"Liu","year":"2015","journal-title":"Int. J. Agric. Biol. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Siedliska, A., Baranowski, P., Pastuszka-Wo\u017aniak, J., Zubik, M., and Krzyszczak, J. (2021). Identification of Plant Leaf Phosphorus Content at Different Growth Stages Based on Hyperspectral Reflectance. BMC Plant Biol., 21.","DOI":"10.1186\/s12870-020-02807-4"},{"key":"ref_21","first-page":"158","article-title":"Nitrogen estimation and spatial analysis of orchard canopy based on UAV remote sensing","volume":"42","author":"Li","year":"2023","journal-title":"J. Huazhong Agric. Univ."},{"key":"ref_22","first-page":"108","article-title":"Analyzing fruit quality of Newhall navel oranges with different cultivation patterns","volume":"41","author":"Hu","year":"2022","journal-title":"J. Huazhong Agric. Univ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"uhad018","DOI":"10.1093\/hr\/uhad018","article-title":"Characteristics of Photosynthesis and Vertical Canopy Architecture of Citrus Trees under Two Labor-Saving Cultivation Modes Using Unmanned Aerial Vehicle (UAV)-Based LiDAR Data in Citrus Orchards","volume":"10","author":"Dian","year":"2023","journal-title":"Hortic. Res."},{"key":"ref_24","first-page":"160","article-title":"Effects of tree shape on the quality of leaf and fruit and the yield in peach","volume":"38","author":"Zhao","year":"2010","journal-title":"J. Northwest Agric. For. Univ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"440","DOI":"10.5958\/0974-0112.2017.00085.8","article-title":"Effect of Training System and in Row Spacing on Yield and Fruit Quality of Peach in the Sub-Tropical Regions","volume":"74","author":"Sharma","year":"2017","journal-title":"Ind. J. Hort."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"171","DOI":"10.17660\/ActaHortic.2021.1303.25","article-title":"Yield and Fruit Quality of Japanese Pear in \u201cJoint V-Shaped Trellis\u201d","volume":"1303","author":"Seki","year":"2021","journal-title":"Acta Hortic."},{"key":"ref_27","first-page":"36","article-title":"Effects of tree shapes on growth, yield and quality of peach","volume":"39","author":"Liu","year":"2022","journal-title":"J. Fruit Sci."},{"key":"ref_28","first-page":"126","article-title":"Spatial distribution of spring shoot, leaf nutrition and fruit in citrus canopy with different tree shapes","volume":"58","author":"Liu","year":"2023","journal-title":"J. Gansu Agric. Univ."},{"key":"ref_29","first-page":"1159","article-title":"Forestland Site Quality and Productivity Potential in Ganzhou City","volume":"36","author":"Wang","year":"2014","journal-title":"J. Jiangxi Agric. Univ."},{"key":"ref_30","first-page":"982","article-title":"Assessing the Loss Value of Soil and Water Conservation Resulted from the Mining of Rare Earth Ore in Ganzhou, Jiangxi Province","volume":"31","author":"Zhou","year":"2016","journal-title":"J. Nat. Resour."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6173","DOI":"10.1093\/jxb\/ers271","article-title":"N-Fertilization Has Different Effects on the Growth, Carbon and Nitrogen Physiology, and Wood Properties of Slow- and Fast-Growing Populus Species","volume":"63","author":"Li","year":"2012","journal-title":"J. Exp. Bot."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"118705","DOI":"10.1016\/j.indcrop.2024.118705","article-title":"Nitrogen Assimilation Genes in Poplar: Potential Targets for Improving Tree Nitrogen Use Efficiency","volume":"216","author":"Li","year":"2024","journal-title":"Ind. Crops Prod."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1007\/s11104-010-0414-2","article-title":"Litterfall Production, Decomposition and Nutrient Use Efficiency Varies with Tropical Forest Types in Xishuangbanna, SW China: A 10-Year Study","volume":"335","author":"Tang","year":"2010","journal-title":"Plant Soil"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1562\/0031-8655(2001)0740038OPANEO2.0.CO2","article-title":"Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves","volume":"74","author":"Gitelson","year":"2007","journal-title":"Photochem. Photobiol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture","volume":"90","author":"Haboudane","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_36","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_37","doi-asserted-by":"crossref","first-page":"2360","DOI":"10.1016\/j.rse.2011.04.036","article-title":"Assessing Structural Effects on PRI for Stress Detection in Conifer Forests","volume":"115","author":"Morales","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/36.134076","article-title":"Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS","volume":"30","author":"Kaufman","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/S0034-4257(98)00046-7","article-title":"Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll A + b, and Total Carotenoid Content in Eucalyptus Leaves","volume":"66","author":"Datt","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Shah, S.H., Angel, Y., Houborg, R., Ali, S., and McCabe, M.F. (2019). A Random Forest Machine Learning Approach for the Retrieval of Leaf Chlorophyll Content in Wheat. Remote Sens., 11.","DOI":"10.3390\/rs11080920"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4995","DOI":"10.1080\/0143116031000080769","article-title":"A Comparison of Methods to Relate Grass Reflectance to Soil Metal Contamination","volume":"24","author":"Kooistra","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.envexpbot.2016.06.006","article-title":"Effects of Nitrogen and Phosphorus Supply on Growth and Physiological Traits of Two Larix Species","volume":"130","author":"Li","year":"2016","journal-title":"Environ. Exp. Bot."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.scienta.2018.05.034","article-title":"Canopy Characteristics and Light Distribution in Sapindus Mukorossi Gaertn. Are Influenced by Crown Architecture Manipulation in the Hilly Terrain of Southeast China","volume":"240","author":"Gao","year":"2018","journal-title":"Sci. Hortic."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/S0304-3800(99)00232-X","article-title":"A 3D Peach Canopy Model Used to Evaluate the Effect of Tree Architecture and Density on Photosynthesis at a Range of Scales","volume":"128","author":"Baret","year":"2000","journal-title":"Ecol. Model."},{"key":"ref_45","first-page":"1180","article-title":"Effect of Canopy Structure on Foliar Photosynthetic Characteristics and Fruit Quality of Pears","volume":"40","author":"Peng","year":"2020","journal-title":"Acta Bot. Boreal.-Occident. Sin."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"103873","DOI":"10.1016\/j.chemolab.2019.103873","article-title":"A Comparative Study between a New Method and Other Machine Learning Algorithms for Soil Organic Carbon and Total Nitrogen Prediction Using near Infrared Spectroscopy","volume":"195","author":"Reda","year":"2019","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"e02812","DOI":"10.1002\/ecy.2812","article-title":"A Global Database of Paired Leaf Nitrogen and Phosphorus Concentrations of Terrestrial Plants","volume":"100","author":"Tian","year":"2019","journal-title":"Ecology"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Peng, X., Chen, D., Zhou, Z., Zhang, Z., Xu, C., Zha, Q., Wang, F., and Hu, X. (2022). Prediction of the Nitrogen, Phosphorus and Potassium Contents in Grape Leaves at Different Growth Stages Based on UAV Multispectral Remote Sensing. Remote Sens., 14.","DOI":"10.3390\/rs14112659"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Kviklys, D., Vi\u0161kelis, J., Liaudanskas, M., Janulis, V., Lau\u017eik\u0117, K., Samuolien\u0117, G., Uselis, N., and Lanauskas, J. (2022). Apple Fruit Growth and Quality Depend on the Position in Tree Canopy. Plants, 11.","DOI":"10.3390\/plants11020196"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Kau\u010di\u0107, M., Vukovi\u0107, M., Ga\u0161par, L., Fruk, G., Vidrih, R., Ne\u010demer, M., Fruk, M., Jatoi, M.A., Fu, D., and Kobav, M.B. (2023). The Effect of Canopy Position on the Fruit Quality Parameters and Contents of Bioactive Compounds and Minerals in \u2018Braeburn\u2019 Apples. Agronomy, 13.","DOI":"10.3390\/agronomy13102523"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3261\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:47:40Z","timestamp":1760111260000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3261"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,3]]},"references-count":50,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["rs16173261"],"URL":"https:\/\/doi.org\/10.3390\/rs16173261","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,9,3]]}}}