{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:58:39Z","timestamp":1776279519963,"version":"3.50.1"},"reference-count":32,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,7,3]],"date-time":"2021-07-03T00:00:00Z","timestamp":1625270400000},"content-version":"vor","delay-in-days":183,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Stomata are the main medium of plants for the trade of water, regulate the gas exchange, and are responsible for the process of photosynthesis and transpiration. The stomata are surrounded by guard cells, which help to control the rate of transpiration by opening and closing the stomata. The stomata states (open and close) play a significant role in describing the plant\u2019s health. Moreover, stomata counting is important for scientists to investigate the numbers of stomata that are open and those that are closed to measure their density and distribution on the surface of leaves through different sampling techniques. Although a few techniques for stomata counting have been proposed, these approaches do not identify and classify the stomata based on their states in leaves. In this research, we have developed an automatic system for stomata state identification and counting in quinoa leaf images through the transformed learning (neural network model Single Shot Detector) approach. In leaf imprint, the state of stomata has been determined by measuring the correlation between the area of stomata and the aperture of each detected stoma in the image. The stomata states have been classified through the Support Vector Machine (SVM) algorithm. The overall identification and classification accuracy of the proposed system are 98.6% and 97%, respectively, helping researchers to obtain accurate stomatal state information for leaves in an efficient and simple way.<\/jats:p>","DOI":"10.1155\/2021\/9938013","type":"journal-article","created":{"date-parts":[[2021,7,3]],"date-time":"2021-07-03T19:50:09Z","timestamp":1625341809000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Stomatal State Identification and Classification in Quinoa Microscopic Imprints through Deep Learning"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4511-387X","authenticated-orcid":false,"given":"Abdul","family":"Razzaq","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sharaiz","family":"Shahid","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad","family":"Akram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad","family":"Ashraf","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2432-1082","authenticated-orcid":false,"given":"Shahid","family":"Iqbal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aamir","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Azam Zia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sulman","family":"Qadri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Najia","family":"Saher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Faisal","family":"Shahzad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7702-7207","authenticated-orcid":false,"given":"Ali Nawaz","family":"Shah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aziz-ur","family":"Rehman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sven-Erik","family":"Jacobsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,7,3]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.9734\/arrb\/2014\/10073"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17691-3_32"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.arplant.57.032905.105434"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-8137.2011.03935.x"},{"key":"e_1_2_9_5_2","article-title":"A review: methods of automatic stomata detection and counting through microscopic images of a leaf","volume":"6","author":"Bhaiswar N.","year":"2007","journal-title":"International Journal of Innovative Research in Science, Engineering and Technology"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.2135\/cropsci1998.0011183X003800060011x"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature01843"},{"key":"e_1_2_9_8_2","article-title":"\u2018A classification of stomatal types","volume":"63","author":"Van Cotthem W. R. J.","year":"1970","journal-title":"Botanical Journal of the Linnean Society"},{"key":"e_1_2_9_9_2","doi-asserted-by":"crossref","unstructured":"LagaH. ShahinniaF. andFleuryD. Image-based plant stornata phenotyping Proceedings of the 13th International Conference on Control Automation Robotics and Vision ICARCV 2014 December 2014 Singapore.","DOI":"10.1109\/ICARCV.2014.7064307"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10343-019-00460-y"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.5772\/24661"},{"key":"e_1_2_9_12_2","unstructured":"OliveiraM. da SilvaN. CasanovaD. PinheiroL. KolbR. andBrunoO. Automatic Counting of Stomata in Epidermis Microscopic Images Proceedings of the X Workshop de Visao Computacional October 2014 Uruguaina Brazil."},{"key":"e_1_2_9_13_2","article-title":"\u2018SSD Object Detection Model Based on Multi-Frequency Feature Theory\u2019","volume":"99","author":"Li J.","year":"2020","journal-title":"IEEE Access"},{"key":"e_1_2_9_14_2","volume-title":"Deepstomata: Facial Recognition Technology for Automated Stomatal Aperture Measurement","author":"Toda Y.","year":"2018"},{"key":"e_1_2_9_15_2","article-title":"Determining leaf stomatal properties in citrus trees utilizing machine vision and artificial intelligence","volume":"21","author":"Costa L.","year":"2020","journal-title":"Precision Agriculture"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.agwat.2014.02.016"},{"key":"e_1_2_9_17_2","doi-asserted-by":"crossref","unstructured":"KuznichovD. AlonZ. HonenY. andKimmelR. Data augmentation for leaf segmentation and counting tasks in rosette plants Proceedings of the 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) June 2019 Long Beach CA USA 2580\u20132589.","DOI":"10.1109\/CVPRW.2019.00314"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1101\/538165"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11024-6_31"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0164576"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.pcp.a076848"},{"key":"e_1_2_9_22_2","unstructured":"KTN De CarvalhoM. A. G.andMartinsP. S. Segmenting high-quality digital images of stomata using the wavelet spot detection and the watershed transform Proceedings of the VISIGRAPP 2017 - Proc. 12th Int. Jt. Conference Compututing Vision Imaging Compututing Graph. Theory Applied August 2017 Porto Portugal."},{"key":"e_1_2_9_23_2","doi-asserted-by":"crossref","unstructured":"SanyalP. BhattacharyaU. andBandyopadhyayS. K. Analysis of SEM images of stomata of different tomato cultivars based on morphological features Proceedings of the 2008 Second Asia International Conference AMS 2008\u2019 May 2008 Kuala Lumpur Malaysia.","DOI":"10.1109\/AMS.2008.81"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13007-017-0244-9"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.1111\/nph.15892"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1093\/icesjms\/fsz171"},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2021.013159"},{"key":"e_1_2_9_28_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10080518"},{"key":"e_1_2_9_29_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13007-021-00727-4"},{"key":"e_1_2_9_30_2","doi-asserted-by":"publisher","DOI":"10.1111\/jac.12290"},{"key":"e_1_2_9_31_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-44127-0"},{"key":"e_1_2_9_32_2","unstructured":"HowardA. G. Mobilenets: efficient convolutional neural networks for mobile vision applications 2017 http:\/\/arxiv.org\/abs\/1704.04861."}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/9938013.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/9938013.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/9938013","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T22:39:22Z","timestamp":1723243162000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/9938013"}},"subtitle":[],"editor":[{"given":"Atif","family":"Khan","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/9938013"],"URL":"https:\/\/doi.org\/10.1155\/2021\/9938013","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"value":"1076-2787","type":"print"},{"value":"1099-0526","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-03-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-04-10","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-07-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"9938013"}}