{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:27:32Z","timestamp":1772252852667,"version":"3.50.1"},"reference-count":73,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,27]],"date-time":"2022-05-27T00:00:00Z","timestamp":1653609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"U.S. Agency for International Development Middle East Research and Cooperation","award":["#M34-037"],"award-info":[{"award-number":["#M34-037"]}]},{"name":"Dutch Ministry of Foreign Affairs","award":["#M34-037"],"award-info":[{"award-number":["#M34-037"]}]},{"name":"Hebrew University of Jerusalem Intramural Research Fund Career Development","award":["#M34-037"],"award-info":[{"award-number":["#M34-037"]}]},{"name":"Hebrew University Center for Sustainability","award":["#M34-037"],"award-info":[{"award-number":["#M34-037"]}]},{"name":"Hebrew University International School of Agricultural Sciences","award":["#M34-037"],"award-info":[{"award-number":["#M34-037"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To meet the ever-growing global population necessities, integrating climate-change-relevant plant traits into breeding programs is required. Developing new tools for fast and accurate estimation of chlorophyll parameters, chlorophyll a (Chl-a) content, chlorophyll b (Chl-b) content, and their ratio (Chl-a\/b), can promote breeding programs of wheat with enhanced climate adaptability. Spectral reflectance of leaves is affected by changes in pigment concentration and can be used to estimate chlorophyll parameters. The current study identified and validated the top known spectral indices and developed new vegetation indices (VIs) for Chl-a and Chl-b content estimation and used them to non-destructively estimate Chl-a\/b values and compare them to hyperspectral estimations. Three wild emmer introgression lines, with contrasting drought stress responsiveness dynamics, were selected. Well-watered and water-limited irrigation regimes were applied. The wheat leaves were spectrally measured with a handheld spectrometer to acquire their reflectance in the 330 to 790 nm range. Regression models based on calculated VIs as well as all hyperspectral curves were calibrated and validated against chlorophyll extracted values. The developed normalized difference spectral indices (NDSIs) resulted in high accuracy of Chl-a (NDSI415,614) and Chl-b (NDSI406,525) estimation, allowing for indirect non-destructive estimation of Chl-a\/b with root mean square error (RMSE) values that could fit 6 to 10 times in the range of the measured values. They also performed similarly to the hyperspectral models. Altogether, we present here a new tool for a non-destructive estimation of Chl-a\/b, which can serve as a basis for future breeding efforts of climate-resilient wheat as well as other crops.<\/jats:p>","DOI":"10.3390\/rs14112585","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T02:30:06Z","timestamp":1653964206000},"page":"2585","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Spectral Estimation of In Vivo Wheat Chlorophyll a\/b Ratio under Contrasting Water Availabilities"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2935-6233","authenticated-orcid":false,"given":"Gabriel","family":"Mulero","sequence":"first","affiliation":[{"name":"The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5929-7131","authenticated-orcid":false,"given":"Harel","family":"Bacher","sequence":"additional","affiliation":[{"name":"The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1741-7967","authenticated-orcid":false,"given":"Uri","family":"Kleiner","sequence":"additional","affiliation":[{"name":"The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8063-1619","authenticated-orcid":false,"given":"Zvi","family":"Peleg","sequence":"additional","affiliation":[{"name":"The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1136-1883","authenticated-orcid":false,"given":"Ittai","family":"Herrmann","sequence":"additional","affiliation":[{"name":"The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1146\/annurev-publhealth-031816-044356","article-title":"Climate change and global food systems: Potential impacts on food security and undernutrition","volume":"38","author":"Myers","year":"2017","journal-title":"Annu. Rev. Public Health"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sade, N., and Peleg, Z. (2020). Future challenges for global food security under climate change. Plant Sci., 9\u201311.","DOI":"10.1016\/j.plantsci.2020.110467"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3513","DOI":"10.1111\/gcb.13599","article-title":"Leaf chlorophyll content as a proxy for leaf photosynthetic capacity","volume":"23","author":"Croft","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1038\/nchembio.1555","article-title":"Natural strategies for photosynthetic light harvesting","volume":"10","author":"Croce","year":"2014","journal-title":"Nat. Chem. Biol."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Croft, H., and Chen, J.M. (2018). Leaf Pigment Content. Compr. Remote Sens., 117\u2013142.","DOI":"10.1016\/B978-0-12-409548-9.10547-0"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"110207","DOI":"10.1016\/j.plantsci.2019.110207","article-title":"Review: Improving global food security through accelerated plant breeding","volume":"287","author":"Lenaerts","year":"2019","journal-title":"Plant Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1007\/s11099-016-0206-x","article-title":"Effects of drought stress on growth and chlorophyll fluorescence of Lycium ruthenicum Murr. seedlings","volume":"54","author":"Guo","year":"2016","journal-title":"Photosynthetica"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1104\/pp.65.3.478","article-title":"Chlorophyll determination in intact tissues using N,N -Dimethylformamide","volume":"65","author":"Moran","year":"1980","journal-title":"Plant Physiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0176-1617(11)81192-2","article-title":"The Spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution","volume":"144","author":"Wellburn","year":"1994","journal-title":"J. Plant Physiol."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2006GL026457","article-title":"Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves","volume":"33","author":"Gitelson","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.1007\/s12161-017-0853-y","article-title":"Spectral indices for non-destructive determination of lettuce pigments","volume":"10","author":"Lopes","year":"2017","journal-title":"Food Anal. Methods"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.1081\/PLN-120014076","article-title":"Relationship between chlorophyll content in leaves of sorghum and pigeonpea determined by extraction method and by chlorophyll meter (SPAD-502)","volume":"25","author":"Yamamoto","year":"2002","journal-title":"J. Plant Nutr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1111\/pbi.13568","article-title":"Uncovering candidate genes involved in photosynthetic capacity using unexplored genetic variation in Spring Wheat","volume":"19","author":"Joynson","year":"2021","journal-title":"Plant Biotechnol. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1109\/JSTARS.2013.2252601","article-title":"Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral two band vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion\/EO-1 data","volume":"6","author":"Thenkabail","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1017\/S0021859614000483","article-title":"Chlorophyll estimation in field crops: An assessment of handheld leaf meters and spectral reflectance measurements","volume":"153","author":"Casa","year":"2015","journal-title":"J. Agric. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"P\u00e9rez-Patricio, M., Camas-Anzueto, J.L., Sanchez-Alegr\u00eda, A., Aguilar-Gonz\u00e1lez, A., Guti\u00e9rrez-Miceli, F., Escobar-G\u00f3mez, E., Voisin, Y., Rios-Rojas, C., and Grajales-Couti\u00f1o, R. (2018). Optical method for estimating the chlorophyll contents in plant leaves. Sensors, 18.","DOI":"10.3390\/s18020650"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/0034-4257(92)90089-3","article-title":"Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and carotenoids in soybean leaves","volume":"39","author":"Chappelle","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005GL022688","article-title":"Remote estimation of canopy chlorophyll content in crops","volume":"32","author":"Gitelson","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1127\/pfg\/2015\/0253","article-title":"Estimate leaf chlorophyll of rice using reflectance indices and partial least squares","volume":"2015","author":"Yu","year":"2015","journal-title":"Photogramm. Fernerkund. Geoinf."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1104\/pp.52.1.57","article-title":"Optical parameters of leaves of 30 plant species","volume":"52","author":"Gausman","year":"1973","journal-title":"Plant Physiol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/02757259509532298","article-title":"A review of vegetation indices","volume":"13","author":"Bannari","year":"1995","journal-title":"Remote Sens. Rev."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Giovos, R., Tassopoulos, D., Kalivas, D., Lougkos, N., and Priovolou, A. (2021). Remote sensing vegetation indices in viticulture: A critical review. Agriculture, 11.","DOI":"10.3390\/agriculture11050457"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4604","DOI":"10.1093\/jxb\/eraa143","article-title":"High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response","volume":"71","author":"Banerjee","year":"2020","journal-title":"J. Exp. Bot."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3063","DOI":"10.1109\/TGRS.2007.897429","article-title":"A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements","volume":"45","author":"Bannari","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"118786","DOI":"10.1016\/j.saa.2020.118786","article-title":"Hyperspectral characteristics and quantitative analysis of leaf chlorophyll by reflectance spectroscopy based on a genetic algorithm in combination with partial least squares regression","volume":"243","author":"Chen","year":"2020","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Thenkabail, P.S., and Lyon, J.G. (2011). Nondestructive estimation of foliar pigment (chlorophylls, carotenoids, and anthocyanins) contents: Evaluating a semianalytical three-band model. Hyperspectral Remote Sensing of Vegetation, CRC.","DOI":"10.1201\/b11222-42"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1016\/j.isprsjprs.2011.08.001","article-title":"An investigation into robust spectral indices for leaf chlorophyll estimation","volume":"66","author":"Main","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Sonobe, R., Yamashita, H., Mihara, H., Morita, A., and Ikka, T. (2020). Estimation of leaf chlorophyll a, b and carotenoid contents and their ratios using hyperspectral reflectance. Remote Sens., 12.","DOI":"10.3390\/rs12193265"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ray, D., Mueller, N., West, P., and Foley, J. (2013). Yield trends are insufficient to double global crop production by 2050. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0066428"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.tplants.2013.12.002","article-title":"Plant domestication versus crop evolution: A conceptual framework for cereals and grain legumes","volume":"19","author":"Abbo","year":"2014","journal-title":"Trends Plant Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1111\/pce.13138","article-title":"Activation of seminal root primordia during wheat domestication reveals underlying mechanisms of plant resilience","volume":"41","author":"Golan","year":"2018","journal-title":"Plant Cell Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1093\/plphys\/kiab292","article-title":"Wild emmer introgression alters root-to-shoot growth dynamics in durum wheat in response to water stress","volume":"187","author":"Bacher","year":"2021","journal-title":"Plant Physiol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1093\/jxb\/erab500","article-title":"Modifying root-to-shoot ratio improves root water influxes in wheat under drought stress","volume":"73","author":"Bacher","year":"2022","journal-title":"J. Exp. Bot."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1111\/j.1365-3040.2005.01259.x","article-title":"Genetic diversity for drought resistance in wild emmer wheat and its ecogeographical associations","volume":"28","author":"Peleg","year":"2005","journal-title":"Plant Cell Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"5127","DOI":"10.1080\/01431160903283892","article-title":"SWIR-based spectral indices for assessing nitrogen content in potato fields","volume":"31","author":"Herrmann","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.rse.2007.04.011","article-title":"Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice","volume":"112","author":"Inoue","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2180","DOI":"10.1890\/14-2098.1","article-title":"Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties","volume":"25","author":"Singh","year":"2015","journal-title":"Ecol. Appl."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0169-7439(01)00155-1","article-title":"PLS-regression: A basic tool of chemometrics","volume":"58","author":"Wold","year":"2001","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Yang, G., Liu, J., Zhao, C., Li, Z., Huang, Y., Yu, H., Xu, B., Yang, X., Zhu, D., and Zhang, X. (2017). Unmanned aerial vehicle remote sensing for field-based crop phenotyping: Current status and perspectives. Front. Plant Sci., 8.","DOI":"10.3389\/fpls.2017.01111"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"56","DOI":"10.25080\/Majora-92bf1922-00a","article-title":"Data structures for statistical computing in python","volume":"1","author":"McKinney","year":"2010","journal-title":"Proc. 9th Python Sci. Conf."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: Fundamental algorithms for scientific computing in python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nat. Methods"},{"key":"ref_43","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s11099-013-0021-6","article-title":"Photosynthesis under stressful environments: An overview","volume":"51","author":"Ashraf","year":"2013","journal-title":"Photosynthetica"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1093\/oxfordjournals.aob.a087986","article-title":"Variation in mesophyll cell number and size in wheat leaves","volume":"65","author":"Pyke","year":"1990","journal-title":"Ann. Bot."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s40502-017-0281-4","article-title":"Natural variation of top three leaf traits and their association with grain yield in rice hybrids","volume":"22","author":"Guru","year":"2017","journal-title":"Indian J. Plant Physiol."},{"key":"ref_47","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_48","doi-asserted-by":"crossref","first-page":"517","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_49","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.1109\/36.934080","article-title":"Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data","volume":"39","author":"Miller","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","unstructured":"Robert, P.C., Rust, R.H., and Larson, W.E. (2000). Coincident detection of crop water stress, nitrogen status and canopy density using ground-based multispectral data. Proceedings of the Fifth International Conference on Precision Agriculture, Bloomington, MN, USA, 16\u201319 July 2000, American Society of Agronomy."},{"key":"ref_51","first-page":"750","article-title":"High spectral resolution: Determination of spectral shifts between the red and infrared","volume":"11","author":"Guyot","year":"1988","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.2134\/agronj2010.0395","article-title":"Remote sensing leaf chlorophyll content using a visible band index","volume":"103","author":"Daughtry","year":"2011","journal-title":"Agron. J."},{"key":"ref_53","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_54","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_55","doi-asserted-by":"crossref","unstructured":"Cavender-Bares, J., Gamon, J.A., and Townsend, P.A. (2020). How the optical properties of leaves modify the absorption and scattering of energy and enhance leaf functionality. Remote Sensing of Plant Biodiversity, Springer International Publishing.","DOI":"10.1007\/978-3-030-33157-3"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2097","DOI":"10.1007\/s10113-017-1202-9","article-title":"Generality of relationships between leaf pigment contents and spectral vegetation indices in Mallorca (Spain)","volume":"17","author":"Hallik","year":"2017","journal-title":"Reg. Environ. Chang."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2141","DOI":"10.1016\/j.rse.2011.04.018","article-title":"LAI assessment of wheat and potato crops by VEN\u03bcS and Sentinel-2 bands","volume":"115","author":"Herrmann","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_58","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., and Harlan, J.C. (1974). Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation, Texas A&M University Remote Sensing Center."},{"key":"ref_59","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_60","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_61","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1071\/AR9950113","article-title":"Forecasting Wheat Yield in a Mediterranean-Type Environment from the NOAA Satellite","volume":"46","author":"Smith","year":"1995","journal-title":"Crop Pasture Sci."},{"key":"ref_62","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_63","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":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"2727","DOI":"10.1080\/01431169508954588","article-title":"Reflectance Assessment of Mite Effects on Apple Trees","volume":"16","author":"Filella","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/0098-8472(92)90034-Y","article-title":"A Reappraisal of the Use of DMSO for the Extraction and Determination of Chlorophylls a and b in Lichens and Higher Plants","volume":"32","author":"Barnes","year":"1992","journal-title":"Environ. Exp. Bot."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(92)90059-S","article-title":"A Narrow-Waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efficiency","volume":"41","author":"Gamon","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/0034-4257(94)90136-8","article-title":"Reflectance Indices Associated with Physiological Changes in Nitrogen- and Water-Limited Sunflower Leaves","volume":"48","author":"Gamon","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_68","first-page":"4","article-title":"The Stress Concept in Plants: An Introduction","volume":"148","author":"Lichtenthaler","year":"1996","journal-title":"Plant Physiol. Biochem."},{"key":"ref_69","first-page":"221","article-title":"Semi-Empirical Indices to Assess Carotenoids\/Chlorophyll a Ratio from Leaf Spectral Reflectance","volume":"31","author":"Penuelas","year":"1995","journal-title":"Photosynthetica"},{"key":"ref_70","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_71","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1562\/0031-8655(2002)075<0272:ACCIPL>2.0.CO;2","article-title":"Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy","volume":"75","author":"Gitelson","year":"2002","journal-title":"Photochem. Photobiol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR Absorbed by Vegetation from Bidirectional Reflectance Measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1034\/j.1399-3054.1999.106119.x","article-title":"Non-Destructive Optical Detection of Pigment Changes during Leaf Senescence and Fruit Ripening","volume":"106","author":"Merzlyak","year":"1999","journal-title":"Physiol. 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