{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T04:18:24Z","timestamp":1784953104570,"version":"3.55.0"},"reference-count":48,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2019,4,23]],"date-time":"2019-04-23T00:00:00Z","timestamp":1555977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2016YFD0300601"],"award-info":[{"award-number":["2016YFD0300601"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41501468, 41601466"],"award-info":[{"award-number":["41501468, 41601466"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Youth Innovation Promotion Association CAS","award":["2017085"],"award-info":[{"award-number":["2017085"]}]},{"name":"the Hainan Provincial Key R&amp;D Program of China","award":["ZDYF2018073"],"award-info":[{"award-number":["ZDYF2018073"]}]},{"name":"the Agricultural Science and Technology Innovation of Sanya","award":["2015KJ04"],"award-info":[{"award-number":["2015KJ04"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Leaf chlorophyll content (LCC) provides valuable information about the nutrition and photosynthesis statuses of crops. Vegetation index-based methods have been widely used in crop management studies for the non-destructive estimation of LCC using remote sensing technology. However, many published vegetation indices are sensitive to crop canopy structure, especially the leaf area index (LAI), when crop canopy spectra are used. Herein, to address this issue, we propose four new spectral indices (The red-edge-chlorophyll absorption index (RECAI), the red-edge-chlorophyll absorption index\/optimized soil-adjusted vegetation index (RECAI\/OSAVI), the red-edge-chlorophyll absorption index\/ the triangular vegetation index (RECAI\/TVI), and the red-edge-chlorophyll absorption index\/the modified triangular vegetation index(RECAI\/MTVI2)) and evaluate their performance for LCC retrieval by comparing their results with those of eight published spectral indices that are commonly used to estimate LCC. A total of 456 winter wheat canopy spectral data corresponding to physiological parameters in a wide range of species, growth stages, stress treatments, and growing seasons were collected. Five regression models (linear, power, exponential, polynomial, and logarithmic) were built to estimate LCC in this study. The results indicated that the newly proposed integrated RECAI\/TVI exhibited the highest LCC predictive accuracy among all indices, where R2 values increased by more than 13.09% and RMSE values reduced by more than 6.22%. While this index exhibited the best association with LCC (0.708** \u2264 r \u2264 0.819**) among all indices, RECAI\/TVI exhibited no significant relationship with LAI (0.029 \u2264 r \u2264 0.167), making it largely insensitive to LAI changes. In terms of the effects of different field management measures, the LCC predictive accuracy by RECAI\/TVI can be influenced by erective winter wheat varieties, low N fertilizer application density, no water application, and early sowing dates. In general, the newly developed integrated RECAI\/TVI was sensitive to winter wheat LCC with a reduction in the influence of LAI. This index has strong potential for monitoring winter wheat nitrogen status and precision nitrogen management. However, further studies are required to test this index with more diverse datasets and different crops.<\/jats:p>","DOI":"10.3390\/rs11080974","type":"journal-article","created":{"date-parts":[[2019,4,24]],"date-time":"2019-04-24T03:14:28Z","timestamp":1556075668000},"page":"974","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":99,"title":["A New Integrated Vegetation Index for the Estimation of Winter Wheat Leaf Chlorophyll Content"],"prefix":"10.3390","volume":"11","author":[{"given":"Bei","family":"Cui","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation, Sanya 572029, Hainan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianjun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Bureau of Science &amp; Technology for Development, Chinese Academy of Sciences, Beijing 100864, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1710-8301","authenticated-orcid":false,"given":"Wenjiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Earth Observation, Sanya 572029, Hainan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0294-5705","authenticated-orcid":false,"given":"Xiaoyu","family":"Song","sequence":"additional","affiliation":[{"name":"Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7836-497X","authenticated-orcid":false,"given":"Huichun","family":"Ye","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Earth Observation, Sanya 572029, Hainan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianfeng","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1080\/01431169408954109","article-title":"Ratios of leaf reflectances in narrow wavebands as indicators of plant stress","volume":"15","author":"Carter","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.1080\/014311697217558","article-title":"Remote estimation of chlorophyll content in higher plant leaves","volume":"18","author":"Gitelson","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1469-185X.1986.tb00425.x","article-title":"Light absorption by plants and its implications for photosynthesis","volume":"61","author":"Osborne","year":"1986","journal-title":"Biol. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1093\/treephys\/7.1-2-3-4.33","article-title":"Exploring the relationship between reflectance red edge and chlorophyll content in slash pine","volume":"7","author":"Curran","year":"1990","journal-title":"Tree Physiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1104\/pp.85.2.355","article-title":"The Nitrogen Use Efficiency of C3 and C4 Plants","volume":"85","author":"Sage","year":"1987","journal-title":"Plant Physiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s11119-008-9091-z","article-title":"Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn","volume":"10","author":"Miao","year":"2008","journal-title":"Precis. Agric."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1109\/JSTARS.2011.2176468","article-title":"Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content","volume":"5","author":"Clevers","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_8","first-page":"47","article-title":"Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels","volume":"25","author":"Schlemmer","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1093\/jxb\/erl231","article-title":"Quantification of plant stress using remote sensing observations and crop models: The case of nitrogen management","volume":"58","author":"Baret","year":"2007","journal-title":"J. Exp. Bot."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.rse.2014.01.004","article-title":"Relationships between gross primary production, green LAI, and canopy chlorophyll content in maize: Implications for remote sensing of primary production","volume":"144","author":"Gitelson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Gitelson, A.A., Vi\u00f1a, A., Ciganda, V., Rundquist, D.C., and Arkebauer, T.J. (2005). Remote estimation of canopy chlorophyll content in crops. Geophys. Res. Lett., 32.","DOI":"10.1029\/2005GL022688"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"S67","DOI":"10.1016\/j.rse.2008.10.019","article-title":"Retrieval of foliar information about plant pigment systems from high resolution spectroscopy","volume":"113","author":"Ustin","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.fcr.2013.12.018","article-title":"Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices","volume":"157","author":"Li","year":"2014","journal-title":"Field Crops Res."},{"key":"ref_14","first-page":"84","article-title":"Monitoring Winter Wheat SPAD Based on Red Edge Parameter Derived from Hyperspectral Reflectance","volume":"3","author":"Yao","year":"2015","journal-title":"China Rural Water Hydropower"},{"key":"ref_15","first-page":"1128","article-title":"A hyperspectral assessment model for leaf chlorophyll content of Pinus massoniana based on neural network","volume":"28","author":"Liu","year":"2017","journal-title":"Chin. J. Appl. Ecol."},{"key":"ref_16","first-page":"149","article-title":"Crop Ground Cover Fraction and Canopy Chlorophyll Content Mapping using RapidEye imagery","volume":"40","author":"Zillmann","year":"2015","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_17","unstructured":"Kim, M., Daughtry, C., Chappelle, E., McMurtrey, J., and Walthall, C. (1994, January 17\u201321). The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation (Apar). Proceedings of the 6th Symposium on Physical Measurements and Signatures in Remote Sensing, Val D\u2019Isere, France."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/S0034-4257(00)00113-9","article-title":"Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance","volume":"74","author":"Daughtry","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S0034-4257(02)00018-4","article-title":"Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture","volume":"81","author":"Haboudane","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","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_21","first-page":"L11402","article-title":"Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves","volume":"33","author":"Gitelson","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jplph.2008.03.004","article-title":"Non-destructive determination of maize leaf and canopy chlorophyll content","volume":"166","author":"Ciganda","year":"2009","journal-title":"J. Plant Physiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5403","DOI":"10.1080\/0143116042000274015","article-title":"The MERIS terrestrial chlorophyll index","volume":"25","author":"Dash","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2003.09.004","article-title":"Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements","volume":"89","author":"Maire","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4589","DOI":"10.1109\/JSTARS.2014.2360069","article-title":"Newly Combined Spectral Indices to Improve Estimation of Total Leaf Chlorophyll Content in Cotton","volume":"7","author":"Jin","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.1080\/01431160110114529","article-title":"Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: Theoretical modelling and experimental observations","volume":"23","author":"Lamb","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.rse.2012.04.002","article-title":"Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons","volume":"123","author":"Liu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.rse.2015.04.032","article-title":"Estimation of crop LAI using hyperspectral vegetation indices and a hybrid inversion method","volume":"165","author":"Liang","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1080\/2150704X.2016.1171925","article-title":"Estimating potato leaf chlorophyll content using ratio vegetation indices","volume":"7","author":"Kooistra","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Clevers, J., Kooistra, L., and Marnix, V.D.B. (2017). Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop. Remote Sens., 9.","DOI":"10.3390\/rs9050405"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s12145-016-0281-3","article-title":"A comparison of the predictive potential of various vegetation indices for leaf chlorophyll content","volume":"10","author":"Cui","year":"2017","journal-title":"Earth Sci. Inf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TGRS.2007.904836","article-title":"Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data","volume":"46","author":"Haboudane","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1023\/A:1020470224740","article-title":"The chequered history of the development and use of simultaneous equations for the accurate determination of chlorophylls a and b","volume":"73","author":"Porra","year":"2002","journal-title":"Photosynth. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2289","DOI":"10.1080\/00103620500250650","article-title":"Estimation of Nitrogen Status in Middle and Bottom Layers of Winter Wheat Canopy by Using Ground-Measured Canopy Reflectance","volume":"36","author":"Wang","year":"2005","journal-title":"Commun. Soil Sci. Plant Anal."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.1016\/j.agrformet.2008.03.005","article-title":"Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation","volume":"148","author":"Wu","year":"2008","journal-title":"Agric. For. Meteorol."},{"key":"ref_36","first-page":"24","article-title":"Assessment of leaf carotenoids content with a new carotenoid index: Development and validation on experimental and model data","volume":"57","author":"Zhou","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/0034-4257(95)00186-7","article-title":"Optimization of soil-adjusted vegetation indices","volume":"55","author":"Rondeaux","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/S0034-4257(00)00197-8","article-title":"Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density","volume":"76","author":"Broge","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1364\/AO.4.000011","article-title":"Spectral Properties of Plants","volume":"4","author":"Gates","year":"1965","journal-title":"Appl. Opt."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1080\/01431168308948546","article-title":"The red edge of plant leaf reflectance","volume":"4","author":"Horler","year":"1983","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/S0176-1617(99)80314-9","article-title":"New Reflectance Index for Remote Sensing of Chlorophyll Content in Higher Plants: Tests using Eucalyptus Leaves","volume":"154","author":"Datt","year":"1999","journal-title":"J. Plant Physiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1093\/jxb\/erl123","article-title":"Hyperspectral remote sensing of plant pigments","volume":"58","author":"Blackburn","year":"2007","journal-title":"J. Exp. Bot."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"S117","DOI":"10.2134\/agronj2006.0370c","article-title":"Application of Spectral Remote Sensing for Agronomic Decisions","volume":"100","author":"Hatfield","year":"2008","journal-title":"Agron. J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"063557","DOI":"10.1117\/1.JRS.6.063557","article-title":"Derivation of biophysical variables from Earth observation data: Validation and statistical measures","volume":"6","author":"Richter","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.ecocom.2013.11.005","article-title":"The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures","volume":"17","author":"Croft","year":"2014","journal-title":"Ecol. Complex."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/S0034-4257(01)00332-7","article-title":"Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data","volume":"81","author":"Brogea","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rse.2005.09.002","article-title":"Assessing vineyard condition with hyperspectral indices: leaf and canopy reflectance simulation in a row-structured discontinuous canopy","volume":"99","author":"Miller","year":"2005","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/8\/974\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:46:35Z","timestamp":1760186795000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/8\/974"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,23]]},"references-count":48,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["rs11080974"],"URL":"https:\/\/doi.org\/10.3390\/rs11080974","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,23]]}}}