Applicability of optimized hyperspectral indices for estimating Betalain content in Suaeda salsa

References

• Anders, K., G. Nielsen, S. Stærke, R. C. Morten , E. Merete, and J. Bjarke. 2017. “Detection of Glycoalkaloids and Chlorophyll in Potatoes (Solanum tuberosum L.) By Hyperspectral Imaging”. American Journal of Potato Research 94(6):1–10.
   Web of Science ®Google Scholar
• Balestrieri, C., G. Colonna, A. Giovane, G. Irace, and L. Servillo 2010. “Second-derivative Spectroscopy of Proteins. A Method for the Quantitative Determination of Aromatic Amino Acids in Proteins”. FEBS Journal 90(3):433–440.
   Google Scholar
• Banerjee, B. P., S. Raval, H. Zhai, and P. J. Cullen 2017. “Health Condition Assessment for Vegetation Exposed to Heavy Metal Pollution through Airborne Hyperspectral Data”. Environmental Monitoring and Assessment 189(12):604. 10.1007/s10661-017-6333-4
   PubMed Web of Science ®Google Scholar
• Baroni, M., S. Clementi, G. Cruciani, G. Costantino, and D. Ariganelli. 1992. “Predictive Ability of Regression Models. Part II: Selection of the Best Predictive PLS Model”. Journal of Chemometrics 6(6):347–356. 10.1002/cem.1180060605
   Web of Science ®Google Scholar
• Bhadra, S., V. Sagan, M. Maimaitijiang, M. Maimaitiyiming, and T. C. Mockler 2020. “Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning”. Remote Sensing 12(13):2082. 10.3390/rs12132082
   Web of Science ®Google Scholar
• Botha, E. J., B. J. Zebarth, and B. Leblon 2006. “Non-destructive Estimation of Potato Leaf Chlorophyll and Protein Contents from Hyperspectral Measurements Using the Prospect Radiative Transfer Model”. Canadian Journal of Plant Science 86(1):279–291. 10.4141/P05-017
   Web of Science ®Google Scholar
• Cai, Y., and H. Corke 1999. “Amaranthus Betacyanin Pigments Applied in Model Food Systems”. Journal of Food Science, 64: 869–873 5 10.1111/j.1365-2621.1999.tb15930.x
   Web of Science ®Google Scholar
• Cai, Y., M. Sun, and H. Corke 2003. “Antioxidant Activity of Betalains from Plants of the Amaranthaceae”. Journal of Agricultural and Food Chemistry 51(8):2288–2294. 10.1021/jf030045u
   PubMed Web of Science ®Google Scholar
• Cai, Y. Z., M. Sun, and H. Corke 2005. “Characterization and Application of Betalain Pigments from Plants of the Amaranthaceae”. Trends in Food Science & Technology 16(9):0–376. 10.1016/j.tifs.2005.03.020
   Web of Science ®Google Scholar
• Chang, X. Y., Q. R. Chang, X. F. Wang, D. Chu, and R. X. Guo 2019. “Estimation of Maize Leaf Chlorophyll Contents Based on UAV Hyperspectral Drone Image”. Agricultural Research in the Arid Areas 18(30): 1: 12.
   Google Scholar
• Chu, Z., L. Fei, K. Wenwen, and H. Yong 2015. “Application of Visible and Near-infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves”. Sensors 15(7):16576–16588. 10.3390/s150716576
   PubMed Web of Science ®Google Scholar
• Cleemput, E. V., L. Vanierschot, B. Fernández-Castilla, O. Honnay, and B. Somers. 2018. “The Functional Characterization of Grass- and Shrub Land Ecosystems Using Hyperspectral Remote Sensing: Trends, Accuracy and Moderating Variables”. Remote Sensing of Environment 209:747–763. 10.1016/j.rse.2018.02.030
   Web of Science ®Google Scholar
• Delgadovargas, F., A. R. Jimenez, and O. Paredeslopez 2000. “Natural Pigments: Carotenoids, Anthocyanins, and Betalains — Characteristics, Biosynthesis, Processing, and Stability”. Critical Reviews in Food Science and Nutrition 40(3):173–289. 10.1080/10408690091189257
   PubMed Web of Science ®Google Scholar
• Du, L., W. Gong, S. Shi, J. Yang, and S. Song 2016. “Estimation of Rice Leaf Nitrogen Contents Based on Hyperspectral LIDAR”. International Journal of Applied Earth Observation and Geoformation 44:136–143. 10.1016/j.jag.2015.08.008
   Web of Science ®Google Scholar
• Feng, C., Q. Jin, Y. N. Wang, L. N. Zhao, H. Lu, and Y. M. Li 2015. “Remote Sensing Estimation of Chlorophyll-a Concentration in Inland Lakes Based on GOCI Image and Optical Classification of Water Body”. 36(5), 1557–1564. Huan Jing Ke Xue= Huanjing Kexue
   PubMedGoogle Scholar
• Fernández-Buces, N., C. Siebe, S. Cram, and J. L. Palacio.2006. “Mapping Soil Salinity Using a Combined Spectral Response Index for Bare Soil and Vegetation: A Case Study in the Former Lake Texcoco, Mexico”. Journal of Arid Environments, 65(4):0–667. 10.1016/j.jaridenv.2005.08.005
   Web of Science ®Google Scholar
• Filella, I., L. Serrano, J. Serra, and J. Peuelas 1995. “Evaluating Wheat Nitrogen Status with Canopy Reflectance Indices and Discriminant Analysis”. Crop Science, 35:1400–1405. 5 10.2135/cropsci1995.0011183X003500050023x
   Web of Science ®Google Scholar
• George, R., H. Padalia, S. Kumar, and S. K. Sinha 2020. “Evaluating Sensitivity of Hyperspectral Indices for Estimating Mangrove Chlorophyll in Middle Andaman Island, India”. Environmental Monitoring and Assessment 191(S3). Suppl 3 10.1007/s10661-019-7679-6
   Web of Science ®Google Scholar
• Gitelson, A. A. 2011. “Nondestructive Estimation of Foliar Pigment (Chlorophylls, Carotenoids, and Anthocyanins) Contents: Evaluating a Semianalytical Three-Band Model”. Hyperspectral Remote Sensing of Vegetation: 141.
   Google Scholar
• Haaland, D. M., and E. V. Thomas 1988. “Partial Least-squares Methods for Spectral Analyses. Relation to Other Quantitative Calibration Methods and the Extraction of Qualitative Information”. Analytical Chemistry 60(11):1193–1202. 10.1021/ac00162a020
   Web of Science ®Google Scholar
• He, Y. L., Y. Xu, and Q. X. Zhu 2016. “Soft-sensing Model Development Using PLSR-based Dynamic Extreme Learning Machine with an Enhanced Hidden Layer”. Chemo Metrics and Intelligent Laboratory Systems: 101–111. 154 10.1016/j.chemolab.2016.03.014
   Web of Science ®Google Scholar
• Hong, W., S. Run-He, L. Pu-Dong, and G. Wei 2016. “Dual NDVI Ratio Vegetation Index: A Kind of Vegetation Index Assessing Leaf Carotenoid Content Based on Leaf Optical Properties Model”. Spectroscopy and Spectral Analysis 36(7): 2189–2194.
   Web of Science ®Google Scholar
• Huang, M., Q. G. Wang, M. Zhang, and Q. B. Zhu 2014. “Prediction of Color and Moisture Content for Vegetable Soybean during Drying Using Hyperspectral Imaging Technology”. Journal of Food Engineering 128:24–30. 10.1016/j.jfoodeng.2013.12.008
   Web of Science ®Google Scholar
• Jain, G., S. K E, and K. S. Gould 2015. “Betalain Induction by l-DOPA Application Confers Photoprotection to Saline-exposed Leaves of Disphyma Australe”. New Phytologist. 207 4 1075–1083 10.1111/nph.13409
   PubMed Web of Science ®Google Scholar
• Kempeneers, P., P. J. Zarco‐Tejada, N. P. R. J. North, S. D. Backer, S. Delalieux, G. Sepulcre-Canto, F. Morales, J. A. N. Vanaardt, R. Sagardoy, P. Coppin, and P. Scheunders. 2008. “Model Inversion for Chlorophyll Estimation in Open Canopies from Hyperspectral Imagery”. International Journal of Remote Sensing 29(17–18):5093–5111. 10.1080/01431160802036458
   Web of Science ®Google Scholar
• Li, H., S. Jia, and Z. Le 2019. “Quantitative Analysis of Soil Total Nitrogen Using Hyperspectral Imaging Technology with Extreme Learning Machine”. Sensors 19(20):4355. 10.3390/s19204355
   PubMed Web of Science ®Google Scholar
• Li, L., S. Wang, T. Ren, Y. Ma, and J. Lu 2016. “Evaluating Models of Leaf Phosphorus Content of Winter Oilseed Rape Based on Hyperspectral Data”. Transactions of the Chinese Society of Agricultural Engineering, 2016 23(14):209–218.
   Google Scholar
• Lin, H., X. Liu, and X. Xue 2008. “Correlation Analysis between Biochemical Contents of Camphor and in Situ Hyperspectral Measurements”. International Conference on Multimedia & Information Technology. IEEE Computer Society.
   Google Scholar
• Lorente, D., N. Aleixos, J. Gómez-Sanchis, S. Cubero, O. L. García-Navarrete, and J. Blasco.2012. “Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment”. Neuroimage 5(4):1121–1142.
   Google Scholar
• Maimaitijiang, M., A. Ghulam, P. Sidike, S. Hartling, M. Maimaitiyiming, K. Peterson, E. Shavers, J. Fishman, J. Peterson, S. Kadam, J. Burken, and F.Fritschi. 2017. “Unmanned Aerial System (UAS)-based Phenotyping of Soybean Using Multi-sensor Data Fusion and Extreme Learning Machine”. ISPRS Journal of Photogrammetry and Remote Sensing 134(Dec.), 43–58. 10.1016/j.isprsjprs.2017.10.011
   Web of Science ®Google Scholar
• Meggio, F., P. J. Zarco-Tejada, L. C. Núez, G, Sepulcre-Cantó, M. R. González, and P Martín. 2010. “Grape Quality Assessment in Vineyards Affected by Iron Deficiency Chlorosis Using Narrow-band Physiological Remote Sensing Indices”. Remote Sensing of Environment 114(9):1968–1986. 10.1016/j.rse.2010.04.004
   Web of Science ®Google Scholar
• Mei, L. L., N. L. Xiang, L. Mi, H. F. Mei, and X. H. Wen 2010. “Neural-network Model for Estimating Leaf Chlorophyll Concentration in Rice under Stress from Heavy Metals Using Four Spectral Indices”. Biosystems Engineering 106(3), 223–233. 10.1016/j.biosystemseng.2009.12.008
   Web of Science ®Google Scholar
• Merzlyak, M. N., A. A. Gitelson, O. B. Chivkunova, and V. Y. Rakitin 1999. “Non-destructive Optical Detection of Pigment Changes during Leaf Senescence and Fruit Ripening”. Physiologia Plantarum 106,135–141. 1 10.1034/j.1399-3054.1999.106119.x
   Web of Science ®Google Scholar
• Moses, A. A. G., R. L. Perk, D. Gurlin, D. C. Rundquist, B. C. Leavitt, and T. M. Barrow. 2009. “Non-destructive Estimation of Anthocyanins and Chlorophylls in Anthocyanic Leaves”. American Journal of Botany 96, 10:1861–1868. 10.3732/ajb.0800395
   PubMed Web of Science ®Google Scholar
• Muhammad, E. V. R. I., A. K. I. Y. A. M. A. Tsuyoshi, Kensuke, and Kawamura. 2008. “Coupling Hyperspectral Data with Principle Component Regression (PCR) and Partial Least Square Regression (PLSR) to Improve Prediction Accuracy of Rice Crop Variables”. Journal of the Japanese Agricultural Systems Society 24:31–42.
   Google Scholar
• Nemzer, B., Z. Pietrzkowski, A. Spórna,P. Stalica, W. Thresher, T. Michalowski, and W. Slawomir. 2011. “Betalainic and Nutritional Profiles of Pigment-enriched Red Beet Root (Beta Vulgaris L.) Dried Extracts”. Food Chemistry 127(1):42–53. 10.1016/j.foodchem.2010.12.081
   Web of Science ®Google Scholar
• Nijat, K., Q. Shi, J. Wang, S. Rukeya, N. Ilyas, and I. Gulnur. 2017. “Estimation of Spring Wheat Chlorophyll Content Based on Hyperspectral Features and PLSR Model”. Transactions of the Chinese Society of Agricultural Engineering, 33(22):208–216.
   Google Scholar
• Nijat, K., S. Rukeya, A. Abdugheni, S. Qingdong,M. Balati, Y. Ahunaji, and K. Yasenjiang. 2018. “Estimation of the Relative Chlorophyll Content in Spring Wheat Based on an Optimized Spectral Index”. Photogrammetric Engineering &remote Sensing 12(84):801–811.
   Google Scholar
• Pereira, H. M., S. Ferrier, M. Walters, G. N. Geller, R. H. G. Jongman, R. J. Scholes,  M. W. Bruford, et al. 2013. “Essential Biodiversity Variables”. Science 339:277–278. 6117 10.1126/science.1229931
   PubMed Web of Science ®Google Scholar
• Petri, V., R. Miina, and S. Aku 2018. “Bayesian Estimation of Seasonal Course of Canopy Leaf Area Index from Hyperspectral Satellite Data”. Journal of Quantitative Spectroscopy & Radiative Transfer 208:19–28. 10.1016/j.jqsrt.2018.01.008
   Web of Science ®Google Scholar
• Prasad, S. T., G. John, Lyon., and A. Huete. 2012. “Hyperspectral Remote Sensing”. Taylor & Francis group. ISBN:978–1–4398–4537–0.
   Google Scholar
• Qi, F. Z., Y. L. Zhan, and F. H. Jing 2010. “Detection of Nitrogen-over Fertilized Rice Plants with Leaf Positional Difference in Hyperspectral Vegetation Index”. Journal of Zhejiang University Science B 11(6):465–470. 10.1631/jzus.B0900348
   PubMed Web of Science ®Google Scholar
• Qiao, Y. X. 2016. “Estimating Winter Wheat Leaf Area Index from Ground and Hyperspectral Observations Using Vegetation Indices”. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 9(2), 771–780. 10.1109/JSTARS.2015.2489718
   Web of Science ®Google Scholar
• Qin, J., L. Xie, and Y. Ying 2015. “Determination of Tetracycline Hydrochloride by Terahertz Spectroscopy with PLSR Model”. Food Chemistry 170:415–422. 10.1016/j.foodchem.2014.08.050
   PubMed Web of Science ®Google Scholar
• Rong, Z. R., A. Q. Ma, Z. K. Wang, Y. U. Hao, and J. X. Zhang. 2012. “Formation Mechanism of Landscape Pattern Based on Logistic Regression Model in the Wetland of Liaohe”.Periodical of Ocean University of China 42(7–8):138–143.
   Google Scholar
• Rukeya, S., K. Nijat, A. Abdugheni, H. Li, Y. Ahunaji, M. Balati, and Shi, Q. D. 2018. “Possibility of Optimized Indices for the Assessment of Heavy Metal Contents in Soil around an Open Pit Coal Mine Area”. International Journal of Applied Earth Observation & Geoinformation 73:14–25. 10.1016/j.jag.2018.05.018
   Web of Science ®Google Scholar
• Sawicki, T., and W. Wiczkowski.2018. “The Effects of Boiling and Fermentation on Betalain Profiles and Antioxidant Capacities of Red Beetroot Products”. Food Chemistry 259:292–303. 10.1016/j.foodchem.2018.03.143
   PubMed Web of Science ®Google Scholar
• Skidmore, A. K., J. G. Ferwerda,O. Mutanga, W.S.E. Van, M. Peel, R. C. Grant, H. T. P. Herbert, B. B. Filliz, and V. Valentijn. 2010. “Forage Quality of Savannas — Simultaneously Mapping Foliar Protein and Polyphenols for Trees and Grass Using Hyperspectral Imagery”. Remote Sensing of Environment 114 (1):64–72. 10.1016/j.rse.2009.08.010
   Web of Science ®Google Scholar
• Stagakis, S., N. Markos, O. Sykioti, and A. Kyparissis 2010. “Monitoring Canopy Biophysical and Biochemical Parameters in Ecosystem Scale Using Satellite Hyperspectral Imagery: An Application on a Phlomis Fruticosa Mediterranean Ecosystem Using Multiangular Chris/proba Observations”. Remote Sensing of Environment 114(5): 977–994. 10.1016/j.rse.2009.12.006
   Web of Science ®Google Scholar
• Stintzing, F. C., A. Schieber, and R. Carle.2002. “Betacyanins in Fruits from Red-purple Pitaya, Hylocereus polyrhizus (Weber) Britton & Rose”. Food Chemistry 77(1):101–106. 10.1016/S0308-8146(01)00374-0
   Web of Science ®Google Scholar
• Strack, D., T. Vogt, and W. Schliemann 2003. “Recent Advances in Betalain Research”. Phytochemistry 62(3):247–269. 10.1016/S0031-9422(02)00564-2
   PubMed Web of Science ®Google Scholar
• Sun, Y., Y. Wang, H. XiaoX. Gu, L. Pan, and Tu, K. 2017. “Hyperspectral Imaging Detection of Decayed Honey Peaches Based on Their Chlorophyll Content [J]”. Food Chemistry, 235:194–202. 10.1016/j.foodchem.2017.05.064
   PubMed Web of Science ®Google Scholar
• Tanaka, Y., N. Sasaki, and A. Ohmiya 2008. “Biosynthesis of Plant Pigments: Anthocyanins, Betalains and Carotenoids”. Plant Journal 54(4):733–749. 10.1111/j.1365-313X.2008.03447.x
   PubMed Web of Science ®Google Scholar
• Wang, C. Q., H. Song, X. Z. Gong, Q. G. Hu, F. Liu, and B. Wang 2007. “Correlation of Tyrosinase Activity and Betacyanin Biosynthesis Induced by Dark in C3 Halophyte Suaeda Salsa Seedlings”. Plant Science 173(5):0–494. 10.1016/j.plantsci.2007.07.010
   Web of Science ®Google Scholar
• Wang, C. Q., J. Q. Zhao, M. Chen, et al. 2006. “Identification of Betacyanin and Effects of Environmental Factors on Its Accumulation in Halophyte Suaeda salsa”. Journal of Plant Physiology and Molecular Biology 32(2):195–201.
   PubMedGoogle Scholar
• Wang, Q., and P. Li 2012. “Hyperspectral Indices for Estimating Leaf Biochemical Properties in Temperate Deciduous Forests: Comparison of Simulated and Measured Reflectance Data Sets”. Ecological Indicators 14(1):56–65. 10.1016/j.ecolind.2011.08.021
   Web of Science ®Google Scholar
• Wang, X. P., Z. Fei, Hsing-te-kung, and V. C. Johnson. 2018. “New Methods for Improving the Remote Sensing Estimation of Soil Organic Matter Content (SOMC) in the Ebinur Lake Wetland National Nature Reserve (ELWNNR) in Northwest China”. Remote Sensing of Environment 218:104–108. 10.1016/j.rse.2018.09.020
   Web of Science ®Google Scholar
• Wang, X. P., Z. Jie, B. R. Guang, and M. Yi. 2014. “Yellow River Estuary Typical Wetlands Classification Based on Hyperspectral Derivative Transformation”. Proceedings of SPIE-The International Society for Optical Engineering 9142(1):91421O-91421O–12.
   Google Scholar
• Wen, X. J., G. W. Qing, L. Z. Guang, H. B. Jun, and S. Zhang. 2017. “Assessment of Heavy Metals Contamination in Soil Profiles of Roadside Suaeda salsa Wetlands in a Chinese Delta”. Physics & Chemistry of the Earth Parts A/b/c, 97:71–76 10.1016/j.pce.2017.01.001
   Web of Science ®Google Scholar
• Wold, S., M. Sjostrom, and L. Eriksson 2001. “PLS-regression: A Basic Tool of Chemometrics”. Chemometrics and Intelligent Laboratory Systems 58(2): 109–130. 10.1016/S0169-7439(01)00155-1
   Web of Science ®Google Scholar
• Wu, T, 2008. “Study on Extraction Condition of Red Pigment from Suaeda salsa Bunge”.Journal of Anhui Agri 36(21): 8983–8984.
   Google Scholar
• Xiao, Y., and J. G. Yang 2015. “Soil Organic Carbon Mineralization and Its Relation with Salinity in Coastal Wetland of Liao He Estuary”. Chinese Journal of Ecology 34(10):2792–2798.
   Google Scholar
• Yang, Y. C., D.-W. Sun, and -N.-N. Wang.2015. “Rapid Detection of Browning Levels of Lychee Pericarp as Affected by Moisture Contents Using Hyperspectral Imaging”. Computers and Electronics in Agriculture 113:203–212. 10.1016/j.compag.2015.02.008
   Web of Science ®Google Scholar
• Yendrek, C. R., T. Tomaz, C. M. Montes,Y. Cao,and E. A. Ainsworth. 2017. “High-throughput phenotyping of maize leaf physiological and biochemical traits using hyperspectral reflectance„. Plant Physiology, 173(1), 614.
   PubMed Web of Science ®Google Scholar
• Zarco-Tejada, P. J., J. R. Miller, ., A. Morales, and A. Berjón, and J. Agüera. 2004. “Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops„. Remote Sensing of Environment, 90(4), 463–476
   Web of Science ®Google Scholar
• Zarco-Tejada, P. J., M. L. Guillén-Climent, R. Hernández-Clemente, A. Catalina, M. R. González, and P. Martín. 2013. “Estimating Leaf Carotenoid Content in Vineyards Using High Resolution Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle (UAV)”. Agricultural and Forest Meteorology 171-172:281–294. 10.1016/j.agrformet.2012.12.013
   Web of Science ®Google Scholar
• Zhang, C., F. Liu, W. W. Kong, and Y. He 2015. “Application of Visible and Near-infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed”, Rape Leaves. Sensors 15(7):16576–16588.
   PubMed Web of Science ®Google Scholar
• Zhang, H., L. I. Zhi, T. Chen, and B. Qin 2017. “Quantitative Determination of Aura Mine O by Terahertz Spectroscopy with 2dcos-PLSR Model”. Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy 184:335–341. 10.1016/j.saa.2017.05.017
   PubMed Web of Science ®Google Scholar
• Zhang, Y., . S., Q., . X. Xu, H., . X. Li et al.et al. 2015. “Progress of Application and Distribution of Betalains”. Chinese Agricultural Science Bulletin 31(4):149–156.
   Google Scholar