{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T20:52:38Z","timestamp":1784667158742,"version":"3.55.0"},"reference-count":74,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,19]],"date-time":"2018-05-19T00:00:00Z","timestamp":1526688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The rapid development of image-based phenotyping methods based on ground-operating devices or unmanned aerial vehicles (UAV) has increased our ability to evaluate traits of interest for crop breeding in the field. A field site infested with beet cyst nematode (BCN) and planted with four nematode susceptible cultivars and five tolerant cultivars was investigated at different times during the growing season. We compared the ability of spectral, hyperspectral, canopy height- and temperature information derived from handheld and UAV-borne sensors to discriminate susceptible and tolerant cultivars and to predict the final sugar beet yield. Spectral indices (SIs) related to chlorophyll, nitrogen or water allowed differentiating nematode susceptible and tolerant cultivars (cultivar type) from the same genetic background (breeder). Discrimination between the cultivar types was easier at advanced stages when the nematode pressure was stronger and the plants and canopies further developed. The canopy height (CH) allowed differentiating cultivar type as well but was much more efficient from the UAV compared to manual field assessment. Canopy temperatures also allowed ranking cultivars according to their nematode tolerance level. Combinations of SIs in multivariate analysis and decision trees improved differentiation of cultivar type and classification of genetic background. Thereby, SIs and canopy temperature proved to be suitable proxies for sugar yield prediction. The spectral information derived from handheld and the UAV-borne sensor did not match perfectly, but both analysis procedures allowed for discrimination between susceptible and tolerant cultivars. This was possible due to successful detection of traits related to BCN tolerance like chlorophyll, nitrogen and water content, which were reduced in cultivars with a low tolerance to BCN. The high correlation between SIs and final sugar beet yield makes the UAV hyperspectral imaging approach very suitable to improve farming practice via maps of yield potential or diseases. Moreover, the study shows the high potential of multi- sensor and parameter combinations for plant phenotyping purposes, in particular for data from UAV-borne sensors that allow for standardized and automated high-throughput data extraction procedures.<\/jats:p>","DOI":"10.3390\/rs10050787","type":"journal-article","created":{"date-parts":[[2018,5,21]],"date-time":"2018-05-21T04:07:30Z","timestamp":1526875650000},"page":"787","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Aerial and Ground Based Sensing of Tolerance to Beet Cyst Nematode in Sugar Beet"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3009-1869","authenticated-orcid":false,"given":"Samuel","family":"Joalland","sequence":"first","affiliation":[{"name":"Syngenta Crop Protection M\u00fcnchwillen AG, Schaffhauserstrasse, 4332 Stein, Switzerland"},{"name":"Institute of Agricultural Sciences, ETH Z\u00fcrich, Universit\u00e4tstrasse 2, 8092 Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Screpanti","sequence":"additional","affiliation":[{"name":"Syngenta Crop Protection M\u00fcnchwillen AG, Schaffhauserstrasse, 4332 Stein, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hubert Vincent","family":"Varella","sequence":"additional","affiliation":[{"name":"Syngenta Crop Protection M\u00fcnchwillen AG, Schaffhauserstrasse, 4332 Stein, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie","family":"Reuther","sequence":"additional","affiliation":[{"name":"Verband der Hessisch-Pf\u00e4lzischen Zuckerr\u00fcbenanbauer e.V., Rathenaustra\u00dfe 10, 67547 Worms, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mareike","family":"Schwind","sequence":"additional","affiliation":[{"name":"Verband der Hessisch-Pf\u00e4lzischen Zuckerr\u00fcbenanbauer e.V., Rathenaustra\u00dfe 10, 67547 Worms, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Lang","sequence":"additional","affiliation":[{"name":"Verband der Hessisch-Pf\u00e4lzischen Zuckerr\u00fcbenanbauer e.V., Rathenaustra\u00dfe 10, 67547 Worms, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Achim","family":"Walter","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Sciences, ETH Z\u00fcrich, Universit\u00e4tstrasse 2, 8092 Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0000-7491","authenticated-orcid":false,"given":"Frank","family":"Liebisch","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Sciences, ETH Z\u00fcrich, Universit\u00e4tstrasse 2, 8092 Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,19]]},"reference":[{"key":"ref_1","unstructured":"Food and Agriculture Organization (FAO) (2009). Global Agriculture towards 2050, Food and Agriculture Organization (FAO)."},{"key":"ref_2","first-page":"205","article-title":"The economic importance of Heterodera schachtii in Europe","volume":"36","year":"1999","journal-title":"Helminthologia"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Biancardi, E., McGrath, J.M., Panella, L.W., Lewellen, R.T., and Stevanato, P. (2010). Sugar beet. Root and Tuber Crops, Springer.","DOI":"10.1007\/978-0-387-92765-7_6"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"573","DOI":"10.5274\/jsbr.13.7.573","article-title":"The host range of the sugar beet nematode; Heterodera schachtii Schmidt","volume":"13","author":"Steele","year":"1965","journal-title":"J. Am. Soc. Sugar Beet Technol."},{"key":"ref_5","unstructured":"Harveson, R.M., and Jackson, T.M. (2008). Sugar Beet Cyst Nematode, University of Nebraska\u2013Lincoln Extension."},{"key":"ref_6","first-page":"135","article-title":"Beet cyst nematode (Heterodera schachtii Schmidt) and its control on sugar beet","volume":"2","author":"Cooke","year":"1987","journal-title":"Agric. Zool. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1163\/156854106777998755","article-title":"Detection of Heterodera schachtii infestation in sugar beet by means of laser-induced and pulse amplitude modulated chlorophyll fluorescence","volume":"8","author":"Schmitz","year":"2006","journal-title":"Nematology"},{"key":"ref_8","first-page":"185","article-title":"The potential use of spectral reflectance from the potato crop for remote sensing of infection by potato cyst nematodes","volume":"60","author":"Heath","year":"2000","journal-title":"Asp. Appl. Biol."},{"key":"ref_9","first-page":"222","article-title":"Use of remote sensing to detect soybean cyst nematode-induced plant stress","volume":"34","author":"Nutter","year":"2002","journal-title":"J. Nematol."},{"key":"ref_10","unstructured":"Laudien, R. (2005). Entwicklung Eines GIS-Gest\u00fctzten Schlagbezogenen F\u00fchrungsinformationssystems f\u00fcr die Zuckerwirtschaft. (Development of a Field- and GIS-Based Management Information System for the Sugar Beet Industry). [Ph.D. Thesis, University of Hohenheim]."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s11119-011-9237-2","article-title":"Use of imaging spectroscopy to discriminate symptoms caused by Heterodera schachtii and Rhizoctonia solani on sugar beet","volume":"13","author":"Mahlein","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s11104-015-2660-9","article-title":"Belowground biomass accumulation assessed by digital image based leaf area detection","volume":"398","author":"Joalland","year":"2016","journal-title":"Plant Soil."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/s13007-017-0223-1","article-title":"Comparison of visible imaging; thermography and spectrometry methods to evaluate the effect of Heterodera schachtii inoculation on sugar beets","volume":"13","author":"Joalland","year":"2017","journal-title":"Plant Methods"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/0304-3770(95)00460-H","article-title":"Relationship between biomass and surface area of six submerged aquatic plant species","volume":"51","author":"Oertli","year":"1995","journal-title":"Aquat. Bot."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0304-3770(99)00085-6","article-title":"Evaluation of digital photography for estimating live and dead aboveground biomass in monospecific macrophyte stands","volume":"67","author":"Smith","year":"2000","journal-title":"Aquat. Bot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/S0378-1127(02)00281-5","article-title":"Image analysis measure of crown condition; foliage biomass and stem growth relationships of Chamaecyparis obtusa","volume":"172","author":"Mizoue","year":"2003","journal-title":"For. Ecol. Manag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1093\/aob\/mcm009","article-title":"A new method for non-destructive measurement of biomass; growth rates; vertical biomass distribution and dry matter content based on digital image analysis","volume":"99","author":"Tackenberg","year":"2007","journal-title":"Ann. Bot. Lond."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/0034-4257(91)90009-U","article-title":"Potentials and limits of vegetation indices for LAI and APAR assessment","volume":"35","author":"Baret","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.fcr.2011.02.007","article-title":"Remote sensing to detect plant stress induced by Heterodera schachtii and Rhizoctonia solani in sugar beet fields","volume":"122","author":"Mahlein","year":"2011","journal-title":"Field Crop Res."},{"key":"ref_20","first-page":"359","article-title":"Use of high resolution digital thermography to detect Heterodera schachtii infestation in sugar beets","volume":"69","author":"Schmitz","year":"2004","journal-title":"Commun. Agric. Appl. Biol. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.tplants.2013.09.008","article-title":"Field high-throughput phenotyping\u2014The new crop breeding frontier","volume":"19","author":"Araus","year":"2014","journal-title":"Trends Plant Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s13007-015-0056-8","article-title":"Plant phenotyping: From bean weighing to image analysis","volume":"11","author":"Walter","year":"2015","journal-title":"Plant Methods"},{"key":"ref_24","unstructured":"Bendig, J., Bolten, A., and Bareth, G. (September, January 25). Introducing a low-cost mini-UAV for thermal- and multispectral-imaging. Proceedings of the XXII ISPRS Congress, Melbourne, Australia."},{"key":"ref_25","unstructured":"Guo, T., Kujirai, T., and Watanabe, T. (September, January 25). Mapping crop status from an unmanned aerial vehicle for precision agriculture applications. Proceedings of the XXII ISPRS Congress, Melbourne, Australia."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s11119-012-9257-6","article-title":"Flexible unmanned aerial vehicle for precision agriculture","volume":"13","author":"Primicerio","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.3389\/fpls.2016.01131","article-title":"A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding","volume":"7","author":"Tattaris","year":"2016","journal-title":"Front. Plant Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"117","DOI":"10.24057\/2071-9388-2017-10-4-117-128","article-title":"Application of hyperspectral images and ground data for precision farming","volume":"10","author":"Akhtman","year":"2017","journal-title":"Geogr. Environ. Sustain."},{"key":"ref_29","unstructured":"Constantin, D., Rehak, M., Akhtman, Y., and Liebisch, F. (2015). Detection of crop properties by means of hyperspectral remote sensing from a micro UAV. Bornimer Agrartechnische Berichte, Leibniz-Institut f\u00fcr Agrartechnik Potsdam-Bornim eV."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Khanna, R., M\u00f6ller, M., Pfeifer, J., Liebisch, F., Walter, A., and Siegwart, R. (2015, January 8\u201311). Beyond point clouds-3d mapping and field parameter measurements using UAVs. Proceedings of the IEEE 20th Conference on Emerging Technologies and Factory Automation (ETFA), Luxembourg.","DOI":"10.1109\/ETFA.2015.7301583"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s13007-015-0048-8","article-title":"Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach","volume":"11","author":"Liebisch","year":"2015","journal-title":"Plant Methods"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1007\/s11119-017-9504-y","article-title":"Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution","volume":"19","author":"Burkart","year":"2018","journal-title":"Precis. Agric."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Jimenez-Bello, M.A., Royuela, A., Manzano, J., Zarco-Tejada, P.J., and Intrigliolo, D. (2013). Assessment of drip irrigation sub-units using airborne thermal imagery acquired with an Unmanned Aerial Vehicle (UAV). Precision Agriculture 13, Wageningen Academic Publishers.","DOI":"10.3920\/9789086867783_089"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.3390\/rs70404213","article-title":"High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: Application in breeding trials","volume":"7","author":"Leon","year":"2015","journal-title":"Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Roth, L., and Streit, B. (2017). Predicting cover crop biomass by lightweight UAS-based RGB and NIR photography: An applied photogrammetric approach. Precis. Agric., 1\u201322.","DOI":"10.31220\/osf.io\/wd39z"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.eja.2015.07.004","article-title":"Low-altitude; high-resolution aerial imaging systems for row and field crop phenotyping: A review","volume":"70","author":"Sankaran","year":"2015","journal-title":"Eur. J. Agron."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.3389\/fpls.2017.01111","article-title":"Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives","volume":"8","author":"Yang","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.isprsjprs.2014.08.005","article-title":"Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects","volume":"97","author":"Yu","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1109\/LRA.2017.2774979","article-title":"weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming","volume":"3","author":"Sa","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"277","DOI":"10.36961\/si18397","article-title":"Nematode-tolerant sugar beet varieties\u2014Resistant or susceptible to the Beet Cyst Nematode Heterodera schachtii?","volume":"142","author":"Reuther","year":"2017","journal-title":"Sugar Ind."},{"key":"ref_41","first-page":"111","article-title":"Neuer Labortest zum Nachweis des R\u00fcbennematoden (Heterodera schachtii)","volume":"39","author":"Grosse","year":"1985","journal-title":"Nachr.-Bl. Pflanzenschutz DDR"},{"key":"ref_42","first-page":"227","article-title":"Untersuchungen zur Eignung von Biotest und Schlupftest f\u00fcr den quantitativen Nachweis des R\u00fcbenzysten\u00e4lchen (Heterodera schachtii) in Bodenproben","volume":"43","author":"Grosse","year":"1989","journal-title":"Nachr.-Bl. Pflanzenschutz DDR"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Oerke, E.C., Gerhards, R., Menz, G., and Sikora, R.A. (2010). Potential of digital thermography for disease control. Precision Crop Protection\u2014The Challenge and Use of Heterogeneity, Springer.","DOI":"10.1007\/978-90-481-9277-9"},{"key":"ref_44","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W. (1974). Monitoring Vegetation Systems in the Great Plains with ERTS, NASA."},{"key":"ref_45","unstructured":"Mistele, B., Gutser, R., Schmidhalter, U., and Mulla, D.J. (2004, January 25\u201328). Validation of field-scaled spectral measurements of the nitrogen status in winter wheat. Proceedings of the 7th International Conference on Precision Agriculture and Other Precision Resources Management, Hyatt Regency, Minneapolis, MN, USA."},{"key":"ref_46","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_47","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_48","doi-asserted-by":"crossref","unstructured":"Gitelson, A.A., Keydan, G.P., and Merzlyak, M.N. (2006). Three-band model for noninvasive estimation of chlorophyll; carotenoids; and anthocyanin contents in higher plant leaves. Geophys. Res. Lett., 33.","DOI":"10.1029\/2006GL026457"},{"key":"ref_49","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_50","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"579","DOI":"10.2134\/agronj2005.0204","article-title":"Characterizing water and nitrogen stress in corn using remote sensing","volume":"98","author":"Clay","year":"2006","journal-title":"Agron. J."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2869","DOI":"10.1080\/014311697217396","article-title":"Estimation of plant water concentration by the reflectance water index WI (R900\/R970)","volume":"18","author":"Penuelas","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_53","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_54","unstructured":"R Development Core Team (2017, July 01). Available online: http:\/\/www.R-project.org."},{"key":"ref_55","unstructured":"Witten, I.H., Frank, E., Hall, M.A., and Pal, C.J. (2016). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann."},{"key":"ref_56","unstructured":"Weiss, S.M., and Kulikowski, C.A. (1991). Computer Systems that Learn, Kaufmann Publishers."},{"key":"ref_57","unstructured":"Breiman, L., Friedman, J., Olshen, R., and Stone, C. (1984). Classification and Regression Trees, Wadsworth International Group."},{"key":"ref_58","unstructured":"Oostenbrink, M. (1966, January 8\u201314). Major characteristics of the relations between nematodes and plants. Proceedings of the 8th International Symposium of nematology, Antibes, France."},{"key":"ref_59","unstructured":"Sherrod, P.H. (2018, February 01). DTREG Predictive Modeling Software. Users Manual. Available online: www.dtreg. com\/DTREG.pdf."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1163\/187529265X00582","article-title":"The relation between nematode density and damage to plants","volume":"11","author":"Seinhorst","year":"1965","journal-title":"Nematologica"},{"key":"ref_62","first-page":"124","article-title":"The relationship between population density of Heterodera schachtii; soil temperature; and sugarbeet yields","volume":"11","author":"Cooke","year":"1979","journal-title":"J. Nematol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1016\/j.fcr.2015.07.003","article-title":"Water use efficiency of sugar beet cultivars (Beta vulgaris L.) susceptible; tolerant or resistant to Heterodera schachtii (Schmidt) in environments with contrasting infestation levels","volume":"183","author":"Hauer","year":"2015","journal-title":"Field Crops Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1146\/annurev.py.29.090191.001123","article-title":"Resistance to and tolerance of plant parasitic nematodes in plants","volume":"29","author":"Trudgill","year":"1991","journal-title":"Annu. Rev. Phytopathol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/0168-1923(90)90039-9","article-title":"Remote estimation of leaf transpiration rate and stomatal resistance based on infrared thermometry","volume":"51","author":"Inoue","year":"1990","journal-title":"Agric. For. Meteorol."},{"key":"ref_66","first-page":"19","article-title":"Thermal and other remote sensing of plant stress","volume":"34","author":"Jones","year":"2008","journal-title":"Gen. Appl. Plant Physiol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1163\/187529280X00134","article-title":"Effects of Globodera rostochiensis and fertilisers on the mineral nutrient content and yield of potato plants","volume":"26","author":"Trudgill","year":"1980","journal-title":"Nematologica"},{"key":"ref_68","first-page":"162","article-title":"The influence of cyst nematodes and drought on potato growth. 2. Effects on plant water relations under semi-controlled conditions","volume":"97","author":"Haverkort","year":"1991","journal-title":"Eur. J. Plant Pathol."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/S0065-2296(04)41003-9","article-title":"Application of thermal imaging and infrared sensing in plant physiology and ecophysiology","volume":"41","author":"Jones","year":"2004","journal-title":"Adv. Bot. Res."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1163\/187529279X00172","article-title":"Tolerance to cyst-nematode attack in commercial potato cultivars and some possible mechanisms for its operation","volume":"25","author":"Evans","year":"1979","journal-title":"Nematologica"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Trudgill, D.L. (1986). Concepts of resistance; tolerance and susceptibility in relation to cyst nematodes. Cyst Nematodes, Springer.","DOI":"10.1007\/978-1-4613-2251-1_10"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"855","DOI":"10.2134\/agronj1990.00021962008200050001x","article-title":"Cyst nematode vs. tolerant and intolerant soybean cultivars","volume":"82","author":"Radcliffe","year":"1990","journal-title":"Agron. J."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.rse.2017.10.043","article-title":"Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers\u2013From theory to application","volume":"205","author":"Aasen","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.pbi.2017.05.006","article-title":"High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field","volume":"38","author":"Shakoor","year":"2017","journal-title":"Curr. Opin. Plant Biol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/787\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:05:02Z","timestamp":1760195102000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,19]]},"references-count":74,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2018,5]]}},"alternative-id":["rs10050787"],"URL":"https:\/\/doi.org\/10.3390\/rs10050787","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,19]]}}}