{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T03:51:17Z","timestamp":1773373877259,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Regional Innovation System &amp; Education (RISE) program through the Gyeongbuk RISE CENTER, which is funded by the Ministry of Education (MOE) and Gyeongsangbuk-do, Republic of Korea","award":["B0080529001944"],"award-info":[{"award-number":["B0080529001944"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Plants"],"abstract":"<jats:p>Hyperspectral imaging (HSI) is a noncontact camera-based technique that enables deep learning models to learn various plant conditions by detecting light reflectance under illumination. In this study, we investigated the effects of four light sources\u2014halogen (HAL), incandescent (INC), fluorescent (FLU), and light-emitting diodes (LED)\u2014on the quality of spectral images and the vase life (VL) of cut roses, which are vulnerable to abiotic stresses. Cut roses \u2018All For Love\u2019 and \u2018White Beauty\u2019 were used to compare cultivar-specific visible reflectance characteristics associated with contrasting petal pigmentation. HSI was performed at four time points, yielding 640 images per light source from 40 cut roses. The results revealed that the light source strongly affected both the image quality (mAP@0.5 60\u201380%) and VL (0\u20133 d) of cut roses. The HAL lamp produced high-quality spectral images across wavelengths (WL) ranging from 480 to 900 nm and yielded the highest object detection performance (ODP), reaching mAP@0.5 of 85% in \u2018All For Love\u2019 and 83% in \u2018White Beauty\u2019 with the YOLOv11x models. However, it increased petal temperature by 2.7\u20133 \u00b0C, thereby stimulating leaf transpiration and consequently shortening the VL of the flowers by 1\u20132.5 d. In contrast, INC produced unclear images with low spectral signals throughout the WL and consequently resulted in lower ODP, with mAP@0.5 of 74% and 69% in \u2018All For Love\u2019 and \u2018White Beauty\u2019, respectively. The INC only slightly increased petal temperature (1.2\u20131.3 \u00b0C) and shortened the VL by 1 d in the both cultivars. Although FLU and LED had only minor effects on petal temperature and VL, these illuminations generated transient spectral peaks in the WL range of 480\u2013620 nm, resulting in decreased ODP (mAP@0.5 60\u201375%). Our results revealed that HAL provided reliable, high-quality spectral image data and high object detection accuracy, but simultaneously had negative effects on flower quality. Our findings suggest an alternative two-phase approach for illumination applications that uses HAL during the initial exploration of spectra corresponding to specific symptoms of interest, followed by LED for routine plant monitoring. Optimizing illumination in HSI will improve the accuracy of deep learning-based prediction and thereby contribute to the development of an automated quality sorting system that is urgently required in the cut flower industry.<\/jats:p>","DOI":"10.3390\/plants15020215","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T16:03:16Z","timestamp":1767974596000},"page":"215","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Light Sources in Hyperspectral Imaging Simultaneously Influence Object Detection Performance and Vase Life of Cut Roses"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7728-5175","authenticated-orcid":false,"given":"Yong-Tae","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Smart Horticultural Science, Gyeongkuk National University, Andong 36729, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2667-9445","authenticated-orcid":false,"given":"Ji Yeong","family":"Ham","sequence":"additional","affiliation":[{"name":"Department of Smart Horticultural Science, Gyeongkuk National University, Andong 36729, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0747-5925","authenticated-orcid":false,"given":"Byung-Chun","family":"In","sequence":"additional","affiliation":[{"name":"Department of Smart Horticultural Science, Gyeongkuk National University, Andong 36729, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"135303","DOI":"10.1016\/j.foodchem.2022.135303","article-title":"Implementation of relevant fourth industrial revolution innovations across the supply chain of fruits and vegetables: A short update on Traceability 4.0","volume":"409","author":"Hassoun","year":"2023","journal-title":"Food Chem."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.biosystemseng.2022.07.013","article-title":"Application of hyperspectral imaging systems and artificial intelligence for quality assessment of fruit, vegetables and mushrooms: A review","volume":"222","author":"Wieme","year":"2022","journal-title":"Biosyst. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"110210","DOI":"10.1016\/j.compag.2025.110210","article-title":"Detection of Botrytis cinerea severity in rose petals using hyperspectral imaging for plant breeding applications","volume":"233","author":"Zerdoner","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"ref_4","first-page":"675","article-title":"Development of a cut rose longevity prediction model using thermography and machine learning","volume":"38","author":"Choi","year":"2020","journal-title":"Hortic. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1186\/s13007-024-01315-y","article-title":"Quality assurance of hyperspectral imaging systems for neural network supported plant phenotyping","volume":"20","author":"Detring","year":"2024","journal-title":"Plant Methods"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Qin, J., Kim, M.S., Chao, K., Chan, D.E., Delwiche, S.R., and Cho, B.-K. (2017). Line-scan hyperspectral imaging techniques for food safety and quality applications. Appl. Sci., 7.","DOI":"10.3390\/app7020125"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"giaa090","DOI":"10.1093\/gigascience\/giaa090","article-title":"Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale","volume":"9","author":"Paulus","year":"2020","journal-title":"Gigascience"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.jfoodeng.2007.06.036","article-title":"Automatic correction of the effects of the light source on spherical objects. An application to the analysis of hyperspectral images of citrus fruits","volume":"85","author":"Aleixos","year":"2008","journal-title":"J. Food Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.biosystemseng.2017.08.022","article-title":"An LED-based spectrally tuneable light source for visible and near-infrared spectroscopy analysis: A case study for sugar content estimation of citrus","volume":"163","author":"Fu","year":"2017","journal-title":"Biosyst. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lee, H., Cho, S., Lim, J., Lee, A., Kim, G., Song, D.-J., Chun, S.-W., Kim, M.-J., and Mo, C. (2023). Performance comparison of tungsten-halogen light and phosphor-converted NIR LED in soluble solid content estimation of apple. Sensors, 23.","DOI":"10.3390\/s23041961"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Qin, J., Monje, O., Nugent, M.R., Finn, J.R., O\u2019Rourke, A.E., Wilson, K.D., Fritsche, R.F., Baek, I., Chan, D.E., and Kim, M.S. (2023). A hyperspectral plant health monitoring system for space crop production. Front. Plant Sci., 14.","DOI":"10.3389\/fpls.2023.1133505"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Appeltans, S., Guerrero, A., Nawar, S., Pieters, J., and Mouazen, A.M. (2020). Practical recommendations for hyperspectral and thermal proximal disease sensing in potato and leek fields. Remote Sens., 12.","DOI":"10.3390\/rs12121939"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"H\u00fcve, K., Bichele, I., Kaldm\u00e4e, H., Rasulov, B., Valladares, F., and Niinemets, \u00dc. (2019). Responses of aspen leaves to heatflecks: Both damaging and non-damaging rapid temperature excursions reduce photosynthesis. Plants, 8.","DOI":"10.3390\/plants8060145"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2822","DOI":"10.1093\/jxb\/erab090","article-title":"The effect of increasing temperature on crop photosynthesis: From enzymes to ecosystems","volume":"72","author":"Moore","year":"2021","journal-title":"J. Exp. Bot."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3961","DOI":"10.3390\/s100403961","article-title":"Spectral identification of lighting type and character","volume":"10","author":"Elvidge","year":"2010","journal-title":"Sensors"},{"key":"ref_16","first-page":"200","article-title":"Comparative analysis of lighting characteristics and ultraviolet emissions from commercial compact fluorescent and incandescent lamps","volume":"16","author":"Azizi","year":"2016","journal-title":"J. Res. Health Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Stergar, J., Hren, R., and Milani\u010d, M. (2022). Design and validation of a custom-made laboratory hyperspectral imaging system for biomedical applications using a broadband LED light source. Sensors, 22.","DOI":"10.3390\/s22166274"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"12834","DOI":"10.3390\/s150612834","article-title":"Supplemental blue LED lighting array to improve the signal quality in hyperspectral imaging of plants","volume":"15","author":"Mahlein","year":"2015","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kim, S., and Lee, A. (2024). Predicting blooming day of cut lily through wavelength reflectance analysis. Horticulturae, 10.","DOI":"10.3390\/horticulturae10080802"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Makraki, T., Tsaniklidis, G., Papadimitriou, D.M., Taheri-Garavand, A., and Fanourakis, D. (2025). Non-Destructive monitoring of postharvest hydration in cucumber fruit using Visible-Light color analysis and Machine-Learning models. Horticulturae, 11.","DOI":"10.3390\/horticulturae11111283"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tsaniklidis, G., Makraki, T., Papadimitriou, D., Nikoloudakis, N., Taheri-Garavand, A., and Fanourakis, D. (2025). Non-destructive estimation of area and greenness in leaf and seedling scales: A case study in cucumber. Agronomy, 15.","DOI":"10.3390\/agronomy15102294"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1007\/s13580-020-00302-1","article-title":"Effects of air-exposure time on water relations, longevity, and aquaporin-related gene expression of cut roses","volume":"62","author":"Ha","year":"2021","journal-title":"Hortic. Environ. Biotechnol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"110984","DOI":"10.1016\/j.postharvbio.2019.110984","article-title":"The impact of light on vase life in (Anthurium andraeanum Hort.) cut flowers","volume":"159","author":"Evelyn","year":"2020","journal-title":"Postharvest Biol. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Ou, Y., Yan, J., Liang, Z., and Zhang, B. (2024). Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease. Agronomy, 14.","DOI":"10.3390\/agronomy14112694"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yan, T., Xu, W., Lin, J., Duan, L., Gao, P., Zhang, C., and Lv, X. (2021). Combining multi-dimensional convolutional neural network (CNN) with visualization method for detection of Aphis gossypii Glover infection in cotton leaves using hyperspectral imaging. Front. Plant Sci., 12.","DOI":"10.3389\/fpls.2021.604510"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Fanourakis, D., Papadakis, V.M., Psyllakis, E., Tzanakakis, V.A., and Nektarios, P.A. (2022). The role of water relations and oxidative stress in the vase life response to prolonged storage: A case study in chrysanthemum. Agriculture, 12.","DOI":"10.3390\/agriculture12020185"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Verdonk, J.C., van Ieperen, W., Carvalho, D.R., van Geest, G., and Schouten, R.E. (2023). Effect of preharvest conditions on cut-flower quality. Front. Plant Sci., 14.","DOI":"10.3389\/fpls.2023.1281456"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Lear, B., Casey, M., Stead, A.D., and Rogers, H.J. (2022). Peduncle necking in Rosa hybrida induces stress-related transcription factors, upregulates galactose metabolism, and downregulates phenylpropanoid biosynthesis genes. Front. Plant Sci., 13.","DOI":"10.3389\/fpls.2022.874590"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.postharvbio.2011.09.016","article-title":"Postharvest water relations in cut rose cultivars with contrasting sensitivity to high relative air humidity during growth","volume":"64","author":"Fanourakis","year":"2012","journal-title":"Postharvest Biol. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2839","DOI":"10.1093\/jxb\/erz068","article-title":"Dynamic leaf energy balance: Deriving stomatal conductance from thermal imaging in a dynamic environment","volume":"70","author":"Lawson","year":"2019","journal-title":"J. Exp. Bot."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Miftahushudur, T., Sahin, H.M., Grieve, B., and Yin, H. (2025). A survey of methods for addressing imbalance data problems in agriculture applications. Remote Sens., 17.","DOI":"10.3390\/rs17030454"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"113282","DOI":"10.1016\/j.postharvbio.2024.113282","article-title":"Enhanced detection of early bruises in apples using near-infrared hyperspectral imaging with geometrical influence correction for universal size adaptation","volume":"219","author":"Li","year":"2025","journal-title":"Postharvest Biol. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"107536","DOI":"10.1016\/j.optlastec.2021.107536","article-title":"Design of active hyperspectral light source based on compact light pipe with LED deflection layout","volume":"145","author":"Song","year":"2022","journal-title":"Opt. Laser Technol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Horibe, T. (2020). Use of light stimuli as a postharvest technology for cut flowers. Front. Plant Sci., 11.","DOI":"10.3389\/fpls.2020.573490"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.postharvbio.2012.10.003","article-title":"Reduction of Botrytis cinerea incidence in cut roses (Rosa hybrida L.) during long term transport in dry conditions","volume":"76","author":"Harkema","year":"2013","journal-title":"Postharvest Biol. Technol."},{"key":"ref_36","unstructured":"VBN (2014). Evaluation Cards for Rosa, FloraHolland."},{"key":"ref_37","first-page":"23","article-title":"Influence of nocturnal supplemental lighting and different irrigation regimes on vase life and vase performance of the hybrid rose \u2018Charming Black\u2019","volume":"39","author":"Shi","year":"2021","journal-title":"Hortic. Sci. Technol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1007\/s13580-016-1119-0","article-title":"Conditions during export affect the potential vase life of cut roses (Rosa hybrida L.)","volume":"57","author":"In","year":"2016","journal-title":"Hortic. Environ. Biotechnol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"790","DOI":"10.21273\/HORTSCI.45.5.790","article-title":"Genotypic variation in the postharvest performance and ethylene sensitivity of cut rose flowers","volume":"45","author":"Macnish","year":"2010","journal-title":"Hortscience"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3064","DOI":"10.1364\/AO.54.003064","article-title":"Establishment and application of the 0\/45 reflectance factor scale over the shortwave infrared","volume":"54","author":"Cooksey","year":"2015","journal-title":"Appl. Opt."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1186\/s13007-018-0352-1","article-title":"Hyperspectral imaging: A novel approach for plant root phenotyping","volume":"14","author":"Bodner","year":"2018","journal-title":"Plant Methods"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"11387","DOI":"10.3390\/s150511387","article-title":"Determining the leaf emissivity of three crops by infrared thermometry","volume":"15","author":"Chen","year":"2015","journal-title":"Sensors"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.scienta.2012.01.022","article-title":"Determining the emissivity of the leaves of nine horticultural crops by means of infrared thermography","volume":"137","author":"Valera","year":"2012","journal-title":"Sci. Hortic."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kang, C., Zhang, Y., Cheng, R., Kaiser, E., Yang, Q., and Li, T. (2021). Acclimating cucumber plants to blue supplemental light promotes growth in full sunlight. Front. Plant Sci., 12.","DOI":"10.3389\/fpls.2021.782465"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.postharvbio.2013.06.017","article-title":"Application of low intensity light pulses to delay postharvest senescence of Ocimum basilicum leaves","volume":"86","author":"Costa","year":"2013","journal-title":"Postharvest Biol. Technol."}],"container-title":["Plants"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2223-7747\/15\/2\/215\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:11:42Z","timestamp":1768281102000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2223-7747\/15\/2\/215"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,9]]},"references-count":45,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["plants15020215"],"URL":"https:\/\/doi.org\/10.3390\/plants15020215","relation":{},"ISSN":["2223-7747"],"issn-type":[{"value":"2223-7747","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,9]]}}}