{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T03:12:41Z","timestamp":1769742761592,"version":"3.49.0"},"publisher-location":"Basel Switzerland","reference-count":57,"publisher":"MDPI","license":[{"start":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T00:00:00Z","timestamp":1696464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.3390\/csac2023-14920","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T01:40:50Z","timestamp":1698025250000},"page":"22","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Enhancing Kiwi Bacterial Canker Leaf Assessment: Integrating Hyperspectral-Based Vegetation Indexes in Predictive Modeling"],"prefix":"10.3390","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6809-008X","authenticated-orcid":false,"given":"Mafalda","family":"Reis-Pereira","sequence":"first","affiliation":[{"name":"Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7017-9323","authenticated-orcid":false,"given":"Renan","family":"Tosin","sequence":"additional","affiliation":[{"name":"Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9058-3147","authenticated-orcid":false,"given":"Rui C.","family":"Martins","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"given":"Filipe Neves","family":"Dos Santos","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9913-1155","authenticated-orcid":false,"given":"Fernando","family":"Tavares","sequence":"additional","affiliation":[{"name":"Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"CIBIO, Centro de Investiga\u00e7\u00e3o em Biodiversidade e Recursos Gen\u00e9ticos, InBIO Laborat\u00f3rio Associado, Campus de Vair\u00e3o, Universidade do Porto, 4485-661 Vair\u00e3o, Portugal"},{"name":"BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vair\u00e3o, 4485-661 Vair\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8299-324X","authenticated-orcid":false,"given":"M\u00e1rio","family":"Cunha","sequence":"additional","affiliation":[{"name":"Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1111\/j.1364-3703.2012.00788.x","article-title":"Pseudomonas Syringae pv. Actinidiae: A Re-Emerging, Multi-Faceted, Pandemic Pathogen","volume":"13","author":"Scortichini","year":"2012","journal-title":"Mol. Plant Pathol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1071\/DN09014","article-title":"Current status of bacterial canker spread on kiwifruit in Italy","volume":"4","author":"Balestra","year":"2009","journal-title":"Australas. Plant Dis. Notes"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"537","DOI":"10.3390\/bios5030537","article-title":"Current and Prospective Methods for Plant Disease Detection","volume":"5","author":"Fang","year":"2015","journal-title":"Biosensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13593-014-0246-1","article-title":"Advanced methods of plant disease detection. A review","volume":"35","author":"Martinelli","year":"2015","journal-title":"Agron. Sustain. Dev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/0034-4257(89)90046-1","article-title":"Detection of changes in leaf water content using Near- and Middle-Infrared reflectances","volume":"30","author":"Hunt","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_6","unstructured":"Jones, H.G., and Vaughan, R.A. (2010). Remote Sensing of Vegetation: Principles, Techniques, and Applications, Oxford University Press."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.biosystemseng.2017.07.003","article-title":"Discrimination of winter wheat disease and insect stresses using continuous wavelet features extracted from foliar spectral measurements","volume":"162","author":"Zhang","year":"2017","journal-title":"Biosyst. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.biosystemseng.2017.02.008","article-title":"Spectral assessment of two-spotted spider mite damage levels in the leaves of greenhouse-grown pepper and bean","volume":"157","author":"Herrmann","year":"2017","journal-title":"Biosyst. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.3389\/fpls.2018.01195","article-title":"Hyperspectral Canopy Sensing of Wheat Septoria Tritici Blotch Disease","volume":"9","author":"Yu","year":"2018","journal-title":"Front. Plant Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Skoneczny, H., Kubiak, K., Spiralski, M., and Kotlarz, J. (2020). Fire Blight Disease Detection for Apple Trees: Hyperspectral Analysis of Healthy, Infected and Dry Leaves. Remote Sens., 12.","DOI":"10.3390\/rs12132101"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/22797254.2017.1391054","article-title":"Detection of Fire Blight disease in pear trees by hyperspectral data","volume":"51","author":"Bagheri","year":"2018","journal-title":"Eur. J. Remote Sens"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Morellos, A., Tziotzios, G., Orfanidou, C., Pantazi, X.E., Sarantaris, C., Maliogka, V., Alexandridis, T.K., and Moshou, D. (2020). Non-Destructive Early Detection and Quantitative Severity Stage Classification of Tomato Chlorosis Virus (ToCV) Infection in Young Tomato Plants Using Vis\u2013NIR Spectroscopy. Remote Sens., 12.","DOI":"10.3390\/rs12121920"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Gold, K.M., Townsend, P.A., Chlus, A., Herrmann, I., Couture, J.J., Larson, E.R., and Gevens, A.J. (2020). Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato. Remote Sens., 12.","DOI":"10.3390\/rs12020286"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1109\/JSTARS.2014.2298752","article-title":"Toward a semiautomatic machine learning retrieval of biophysical parameters","volume":"7","author":"Caicedo","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4927","DOI":"10.3390\/rs6064927","article-title":"On the semi-automatic retrieval of biophysical parameters based on spectral index optimization","volume":"6","author":"Rivera","year":"2014","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Meng, R., Lv, Z., Yan, J., Chen, G., Zhao, F., Zeng, L., and Xu, B. (2020). Development of spectral disease indices for southern corn rust detection and severity classification. Remote Sens., 12.","DOI":"10.3390\/rs12193233"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"110316","DOI":"10.1016\/j.plantsci.2019.110316","article-title":"Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning","volume":"295","author":"Gold","year":"2020","journal-title":"Plant Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.isprsjprs.2015.05.005","article-title":"Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties\u2014A review","volume":"108","author":"Verrelst","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","first-page":"607","article-title":"Evaluation of narrowband and broadband vegetation indices for determining optimal hyperspectral wavebands for agricultural crop characterization","volume":"68","author":"Thenkabail","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","first-page":"37","article-title":"Remote Sensing of Vegetation Biophysical Parameters for Detecting Stress Condition and Land Cover Changes","volume":"8","year":"2007","journal-title":"Estud. Zona No Saturada Suelo"},{"key":"ref_21","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_22","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":"Hunt","year":"2011","journal-title":"Agron. J."},{"key":"ref_23","unstructured":"Gitelson, A.A., Merzlyak, M., Zur, Y., Stark, R., and Gritz, U. (2023, July 15). Non-destructive and remote sensing techniques for estimation of vegetation status. Available online: https:\/\/digitalcommons.unl.edu\/cgi\/viewcontent.cgi?article=1275&context=natrespapers."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1023\/A:1025608728405","article-title":"Application of reflectance spectroscopy for analysis of higher plant pigments","volume":"50","author":"Merzlyak","year":"2003","journal-title":"Russ. J. Plant Physiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"L11402","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_26","unstructured":"Escadafal, R., Belghith, A., and Ben Moussa, H. (1994, January 17\u201324). Indices spectraux pour la t\u00e9l\u00e9d\u00e9tection de la d\u00e9gradation des milieux naturels en Tunisie aride. Proceedings of the Actes du 6eme Symposium International sur les Mesures Physiques et Signatures en T\u00e9l\u00e9d\u00e9tection, Val d\u2019Is\u00e8re."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1007\/s10712-018-9478-y","article-title":"Quantifying vegetation biophysical variables from imaging spectroscopy data: A review on retrieval methods","volume":"40","author":"Verrelst","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Reis-Pereira, M., Tosin, R., Martins, R., Neves dos Santos, F., Tavares, F., and Cunha, M. (2022). Kiwi Plant Canker Diagnosis Using Hyperspectral Signal Processing and Machine Learning: Detecting Symptoms Caused by Pseudomonas syringae pv. actinidiae. Plants, 11.","DOI":"10.3390\/plants11162154"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"103937","DOI":"10.1016\/j.chemolab.2020.103937","article-title":"mdatools\u2013R package for chemometrics","volume":"198","author":"Kucheryavskiy","year":"2020","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"106710","DOI":"10.1016\/j.compag.2022.106710","article-title":"Unscrambling spectral interference and matrix effects in Vitis vinifera Vis-NIR spectroscopy: Towards analytical grade \u2018in vivo\u2019 sugars and acids quantification","volume":"194","author":"Martins","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2793","DOI":"10.1038\/s41598-018-21191-6","article-title":"Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor","volume":"8","author":"Lu","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.rse.2012.09.019","article-title":"Development of spectral indices for detecting and identifying plant diseases","volume":"128","author":"Mahlein","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.isprsjprs.2015.04.013","article-title":"Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods\u2014A comparison","volume":"108","author":"Verrelst","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Morcillo-Pallar\u00e9s, P., Rivera-Caicedo, J.P., Belda, S., De Grave, C., Burriel, H., Moreno, J., and Verrelst, J. (2019). Quantifying the robustness of vegetation indices through global sensitivity analysis of homogeneous and forest leaf-canopy radiative transfer models. Remote Sens., 11.","DOI":"10.3390\/rs11202418"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Thenkabail, P.S., Lyon, J.G., and Huete, A. (2018). Hyperspectral Indices and Image Classifications for Agriculture and Vegetation, CRC Press.","DOI":"10.1201\/9781315159331"},{"key":"ref_36","unstructured":"Ashburn, P. The vegetative index number and crop identification. In Proceedings of Technical Sessions of the LACIE Symposium, Houston, DX, USA, 23\u201326 October 1978."},{"key":"ref_37","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_38","doi-asserted-by":"crossref","first-page":"2455","DOI":"10.1016\/j.biombioe.2011.02.028","article-title":"A review of remote sensing methods for biomass feedstock production","volume":"35","author":"Ahamed","year":"2011","journal-title":"Biomass Bioenergy"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1029\/2002GL016450","article-title":"Remote estimation of leaf area index and green leaf biomass in maize canopies","volume":"30","author":"Gitelson","year":"2003","journal-title":"Geophys. Res. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1109\/TGRS.2003.813206","article-title":"Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes","volume":"41","author":"Datt","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","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":"Dufrene","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_42","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_43","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_44","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S1672-6308(07)60027-4","article-title":"New vegetation index and its application in estimating leaf area index of rice","volume":"14","author":"Wang","year":"2007","journal-title":"Rice Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/BF00031911","article-title":"GEMI: A non-linear index to monitor global vegetation from satellites","volume":"101","author":"Pinty","year":"1992","journal-title":"Vegetatio"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.1109\/36.934080","article-title":"Scaling-up and model inversion methods with narrow-band 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_47","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.compag.2010.08.005","article-title":"Sensing technologies for precision specialty crop production","volume":"74","author":"Lee","year":"2010","journal-title":"Comput. Electron. Agric."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.rse.2004.12.016","article-title":"Remote sensing of forest biophysical variables using HyMap imaging spectrometer data","volume":"95","author":"Schlerf","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/0034-4257(90)90085-Z","article-title":"Calculating the vegetation index faster","volume":"1","author":"Crippen","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_50","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_51","first-page":"23","article-title":"Kauth-Thomas brigthness and greenness axes","volume":"9-14350","author":"Misra","year":"1977","journal-title":"Contract NASA"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices over a global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1080\/07038992.1996.10855178","article-title":"Evaluation of vegetation indices and a modified simple ratio for boreal applications","volume":"22","author":"Chen","year":"1996","journal-title":"Can. J. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"968","DOI":"10.2134\/agronj2005.0200","article-title":"Aerial color infrared photography for determining early in-season nitrogen requirements in corn","volume":"98","author":"Sripada","year":"2006","journal-title":"Agron. J."},{"key":"ref_55","unstructured":"Apan, A., Held, A., Phinn, S., and Markley, J. (2003, January 17\u201323). Formulation and assessment of narrow-band vegetation indices from EO-1 hyperion imagery for discriminating sugarcane disease. Proceedings of the 2003 Spatial Sciences Institute Conference: Spatial Knowledge Without Boundaries (SSC2003), Canberra, Australia."},{"key":"ref_56","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_57","doi-asserted-by":"crossref","first-page":"3169","DOI":"10.1080\/01431160110104647","article-title":"Derivation of the red edge index using the MERIS standard band setting","volume":"23","author":"Clevers","year":"2002","journal-title":"Int. J. Remote Sens."}],"event":{"name":"CSAC 2023","acronym":"CSAC 2023"},"container-title":["CSAC 2023"],"original-title":[],"link":[{"URL":"https:\/\/www.mdpi.com\/2673-4591\/48\/1\/22\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:10:01Z","timestamp":1760130601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2673-4591\/48\/1\/22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,5]]},"references-count":57,"alternative-id":["CSAC2023-14920"],"URL":"https:\/\/doi.org\/10.3390\/csac2023-14920","relation":{},"subject":[],"published":{"date-parts":[[2023,10,5]]}}}