{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T02:43:03Z","timestamp":1768099383359,"version":"3.49.0"},"reference-count":11,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T00:00:00Z","timestamp":1621209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed to understand citrus pest dynamics and management. This article presents a dataset that contains 665 healthy and unhealthy lemon leaf images. The latter are leaves with the presence of aphids, and visible white spots characterize them. Moreover, each image includes a set of annotations that identify the leaf, its health state, and the infestation severity according to the percentage of the affected area on it. Images were collected manually in real-world conditions in a lemon plant field in Jun\u00edn, Manab\u00ed, Ecuador, during the winter, by using a smartphone camera. The dataset is called LeLePhid: lemon (Le) leaf (Le) image dataset for aphid (Phid) detection and infestation severity. The data can facilitate evaluating models for image segmentation, detection, and classification problems related to plant disease recognition.<\/jats:p>","DOI":"10.3390\/data6050051","type":"journal-article","created":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T02:31:34Z","timestamp":1621218694000},"page":"51","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["LeLePhid: An Image Dataset for Aphid Detection and Infestation Severity on Lemon Leaves"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8558-9122","authenticated-orcid":false,"given":"Jorge","family":"Parraga-Alava","sequence":"first","affiliation":[{"name":"Facultad de Ciencias Inform\u00e1ticas, Universidad T\u00e9cnica de Manab\u00ed, Avenida Jose Mar\u00eda Urbina, Portoviejo 130104, Ecuador"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6282-8493","authenticated-orcid":false,"given":"Roberth","family":"Alcivar-Cevallos","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Inform\u00e1ticas, Universidad T\u00e9cnica de Manab\u00ed, Avenida Jose Mar\u00eda Urbina, Portoviejo 130104, Ecuador"}]},{"given":"J\u00e9ssica","family":"Morales Carrillo","sequence":"additional","affiliation":[{"name":"Carrera de Computaci\u00f3n, Escuela Superior Polit\u00e9cnica Agropecuaria de Manab\u00ed, Sitio El Lim\u00f3n, Calceta 130250, Ecuador"}]},{"given":"Magdalena","family":"Castro","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Inform\u00e1ticas, Universidad T\u00e9cnica de Manab\u00ed, Avenida Jose Mar\u00eda Urbina, Portoviejo 130104, Ecuador"}]},{"given":"Shabely","family":"Avell\u00e1n","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Inform\u00e1ticas, Universidad T\u00e9cnica de Manab\u00ed, Avenida Jose Mar\u00eda Urbina, Portoviejo 130104, Ecuador"}]},{"given":"Aaron","family":"Loor","sequence":"additional","affiliation":[{"name":"Carrera de Computaci\u00f3n, Escuela Superior Polit\u00e9cnica Agropecuaria de Manab\u00ed, Sitio El Lim\u00f3n, Calceta 130250, Ecuador"}]},{"given":"Fernando","family":"Mendoza","sequence":"additional","affiliation":[{"name":"Carrera de Computaci\u00f3n, Escuela Superior Polit\u00e9cnica Agropecuaria de Manab\u00ed, Sitio El Lim\u00f3n, Calceta 130250, Ecuador"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chen, T., Zeng, R., Guo, W., Hou, X., Lan, Y., and Zhang, L. (2018). Detection of Stress in Cotton (Gossypium hirsutum L.) Caused by Aphids Using Leaf Level Hyperspectral Measurements. Sensors, 18.","DOI":"10.3390\/s18092798"},{"key":"ref_2","unstructured":"Virginio-Filho, E., and Astorga, C. (2015). Prevenci\u00f3n y Control de la Roya del Caf\u00e9. Manual de Buenas Pr\u00e1cticas para T\u00e9cnicos y Facilitadores, Centro Agron\u00f3mico Tropical de Investigaci\u00f3n y Ense\u00f1anza (CATIE)."},{"key":"ref_3","first-page":"3964376:1","article-title":"Aphid Identification and Counting Based on Smartphone and Machine Vision","volume":"2017","author":"Suo","year":"2017","journal-title":"J. Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"104414","DOI":"10.1016\/j.dib.2019.104414","article-title":"RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition","volume":"25","author":"Cusme","year":"2019","journal-title":"Data Brief"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"276","DOI":"10.11613\/BM.2012.031","article-title":"Interrater reliability: The kappa statistic","volume":"22","author":"McHugh","year":"2012","journal-title":"Biochem. Medica"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Botto-Tobar, M., Zamora, W., Larrea Pl\u00faa, J., Bazurto Roldan, J., and Santamar\u00eda Philco, A. (2021). Aphids Detection on Lemons Leaf Image Using Convolutional Neural Networks. Systems and Information Sciences, Springer International Publishing.","DOI":"10.1007\/978-3-030-59194-6"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Chen, J., Fan, Y., Wang, T., Zhang, C., Qiu, Z., and He, Y. (2018). Automatic Segmentation and Counting of Aphid Nymphs on Leaves Using Convolutional Neural Networks. Agronomy, 8.","DOI":"10.3390\/agronomy8080129"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Bah, M.D., Hafiane, A., and Canals, R. (2018). Deep Learning with Unsupervised Data Labeling for Weed Detection in Line Crops in UAV Images. Remote Sens., 10.","DOI":"10.20944\/preprints201809.0088.v1"},{"key":"ref_9","first-page":"273","article-title":"Use of drones in cadastral works and precision works in silviculture and agriculture","volume":"37","author":"Croitoru","year":"2020","journal-title":"Rom. Agric. Res."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kitano, B.T., Mendes, C.C.T., Geus, A.R., Oliveira, H.C., and Souza, J.R. 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