Zeitschriftenartikel zum Thema „Citrus Classification“
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Yang, Taeyang, und Oh-Sang Kwon. „Sequential Effect on Visual Classification: The Citrus Classification Paradigm“. Journal of Vision 16, Nr. 12 (01.09.2016): 548. http://dx.doi.org/10.1167/16.12.548.
WAKATA, Tadayuki, und Miho SAITO. „Psychological classification of the citrus fragrance.“ Proceedings of the Annual Convention of the Japanese Psychological Association 76 (11.09.2012): 1AMA01. http://dx.doi.org/10.4992/pacjpa.76.0_1ama01.
Hiri, A., M. De Luca, G. Ioele, A. Balouki, M. Basbassi, F. Kzaiber, A. Oussama und G. Ragno. „Chemometric classification of citrus juices of Moroccan cultivars by infrared spectroscopy“. Czech Journal of Food Sciences 33, No. 2 (03.06.2016): 137–42. http://dx.doi.org/10.17221/284/2014-cjfs.
Dhiman, Poonam. „Contemporary Study on Citrus Disease Classification System“. ECS Transactions 107, Nr. 1 (24.04.2022): 10035–43. http://dx.doi.org/10.1149/10701.10035ecst.
Schaad, Norman W., Elena Postnikova, George Lacy, Aaron Sechler, Irina Agarkova, Paul E. Stromberg, Verlyn K. Stromberg und Anne K. Vidaver. „Emended classification of xanthomonad pathogens on citrus“. Systematic and Applied Microbiology 29, Nr. 8 (Dezember 2006): 690–95. http://dx.doi.org/10.1016/j.syapm.2006.08.001.
Silva, Alessandra F., Ana Paula Barbosa, Célia R. L. Zimback und Paulo M. B. Landim. „Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus“. Engenharia Agrícola 33, Nr. 6 (Dezember 2013): 1245–56. http://dx.doi.org/10.1590/s0100-69162013000600017.
Dorj, Ulzii-Orshikh, Uranbaigal Dejidbal, Hongseok Chae, Lkhagvadorj Batsambuu, Altanchimeg Badarch und Shinebayar Dalkhaa. „CITRUS FRUIT QUALITY CLASSIFICATION BASED ON SIZE USING DIGITAL IMAGE PROCESSING“. Siberian Herald of Agricultural Science 48, Nr. 5 (09.01.2019): 95–101. http://dx.doi.org/10.26898/0370-8799-2018-5-12.
Elaraby, Ahmed, Walid Hamdy und Saad Alanazi. „Classification of Citrus Diseases Using Optimization Deep Learning Approach“. Computational Intelligence and Neuroscience 2022 (10.02.2022): 1–10. http://dx.doi.org/10.1155/2022/9153207.
Varjão, Jonatha Oliveira Reis, Glenda Michele Botelho, Tiago da Silva Almeida, Glêndara Aparecida de Souza Martins und Warley Gramacho da Silva. „Citrus Fruit Quality Classification using Support Vector Machines“. International Journal of Advanced Engineering Research and Science 6, Nr. 7 (2019): 59–65. http://dx.doi.org/10.22161/ijaers.678.
Lee, Saebom, Gyuho Choi, Hyun-Cheol Park und Chang Choi. „Automatic Classification Service System for Citrus Pest Recognition Based on Deep Learning“. Sensors 22, Nr. 22 (18.11.2022): 8911. http://dx.doi.org/10.3390/s22228911.
Mudholakar, Sunita, Kavitha G, Kanaya Kumari K T und Shubha G V. „Automatic Detection of Citrus Fruit and Leaves Diseases Using Deep Neural Network“. International Journal for Research in Applied Science and Engineering Technology 10, Nr. 7 (31.07.2022): 4043–51. http://dx.doi.org/10.22214/ijraset.2022.45868.
Zia Ur Rehman, Muhammad, Fawad Ahmed, Muhammad Attique Khan, Usman Tariq, Sajjad Shaukat Jamal, Jawad Ahmad und Iqtadar Hussain. „Classification of Citrus Plant Diseases Using Deep Transfer Learning“. Computers, Materials & Continua 70, Nr. 1 (2022): 1401–17. http://dx.doi.org/10.32604/cmc.2022.019046.
Shou Bo, Huang. „A Climatic Classification for Citrus Winter Survival in China“. Journal of Climate 4, Nr. 5 (Mai 1991): 550–55. http://dx.doi.org/10.1175/1520-0442(1991)004<0550:accfcw>2.0.co;2.
Steuer, B., H. Schulz und E. Läger. „Classification and analysis of citrus oils by NIR spectroscopy“. Food Chemistry 72, Nr. 1 (Januar 2001): 113–17. http://dx.doi.org/10.1016/s0308-8146(00)00209-0.
Mittapelli, Suresh Reddy, Shailendar Kumar Maryada, Venkateswara Rao Khareedu und Dashavantha Reddy Vudem. „Structural organization, classification and phylogenetic relationship of cytochrome P450 genes in Citrus clementina and Citrus sinensis“. Tree Genetics & Genomes 10, Nr. 2 (05.01.2014): 399–409. http://dx.doi.org/10.1007/s11295-013-0695-8.
Rauf, Hafiz Tayyab, Basharat Ali Saleem, M. Ikram Ullah Lali, Muhammad Attique Khan, Muhammad Sharif und Syed Ahmad Chan Bukhari. „A citrus fruits and leaves dataset for detection and classification of citrus diseases through machine learning“. Data in Brief 26 (Oktober 2019): 104340. http://dx.doi.org/10.1016/j.dib.2019.104340.
Khanramaki, Morteza, Ezzatollah Askari Asli-Ardeh und Ehsan Kozegar. „Citrus pests classification using an ensemble of deep learning models“. Computers and Electronics in Agriculture 186 (Juli 2021): 106192. http://dx.doi.org/10.1016/j.compag.2021.106192.
Janarthan, Sivasubramaniam, Selvarajah Thuseethan, Sutharshan Rajasegarar, Qiang Lyu, Yongqiang Zheng und John Yearwood. „Deep Metric Learning Based Citrus Disease Classification With Sparse Data“. IEEE Access 8 (2020): 162588–600. http://dx.doi.org/10.1109/access.2020.3021487.
Lopez, Jose J., Maximo Cobos und Emanuel Aguilera. „Computer-based detection and classification of flaws in citrus fruits“. Neural Computing and Applications 20, Nr. 7 (20.06.2010): 975–81. http://dx.doi.org/10.1007/s00521-010-0396-2.
Yanto, Budi, Luth Fimawahib, Asep Supriyanto, B. Herawan Hayadi und Rinanda Rizki Pratama. „Klasifikasi Tekstur Kematangan Buah Jeruk Manis Berdasarkan Tingkat Kecerahan Warna dengan Metode Deep Learning Convolutional Neural Network“. INOVTEK Polbeng - Seri Informatika 6, Nr. 2 (27.11.2021): 259. http://dx.doi.org/10.35314/isi.v6i2.2104.
Horibata, Akira, und Tsuneo Kato. „Phylogenetic relationships among accessions in Citrus and related genera based on the insertion polymorphism of the CIRE1 retrotransposon“. Open Agriculture 5, Nr. 1 (18.06.2020): 243–51. http://dx.doi.org/10.1515/opag-2020-0026.
Wang, Xuefeng, Chunyan Wu und Masayuki Hirafuji. „Visible Light Image-Based Method for Sugar Content Classification of Citrus“. PLOS ONE 11, Nr. 1 (26.01.2016): e0147419. http://dx.doi.org/10.1371/journal.pone.0147419.
Reinhard, Hans, Fritz Sager und Otmar Zoller. „Citrus juice classification by SPME-GC-MS and electronic nose measurements“. LWT - Food Science and Technology 41, Nr. 10 (Dezember 2008): 1906–12. http://dx.doi.org/10.1016/j.lwt.2007.11.012.
Qadri, Salman, Syed Furqan Qadri, Mujtaba Husnain, Malik Muhammad Saad Missen, Dost Muhammad Khan, Muzammil-Ul-Rehman, Abdul Razzaq und Saleem Ullah. „Machine vision approach for classification of citrus leaves using fused features“. International Journal of Food Properties 22, Nr. 1 (01.01.2019): 2072–89. http://dx.doi.org/10.1080/10942912.2019.1703738.
Amorós López, J., E. Izquierdo Verdiguier, L. Gómez Chova, J. Muñoz Marí, J. Z. Rodríguez Barreiro, G. Camps Valls und J. Calpe Maravilla. „Land cover classification of VHR airborne images for citrus grove identification“. ISPRS Journal of Photogrammetry and Remote Sensing 66, Nr. 1 (Januar 2011): 115–23. http://dx.doi.org/10.1016/j.isprsjprs.2010.09.008.
Deng, Xiaoling, Zixiao Huang, Zheng Zheng, Yubin Lan und Fen Dai. „Field detection and classification of citrus Huanglongbing based on hyperspectral reflectance“. Computers and Electronics in Agriculture 167 (Dezember 2019): 105006. http://dx.doi.org/10.1016/j.compag.2019.105006.
Abdulridha, Jaafar, Ozgur Batuman und Yiannis Ampatzidis. „UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning“. Remote Sensing 11, Nr. 11 (08.06.2019): 1373. http://dx.doi.org/10.3390/rs11111373.
Yang, Changcai, Zixuan Teng, Caixia Dong, Yaohai Lin, Riqing Chen und Jian Wang. „In-Field Citrus Disease Classification via Convolutional Neural Network from Smartphone Images“. Agriculture 12, Nr. 9 (16.09.2022): 1487. http://dx.doi.org/10.3390/agriculture12091487.
Petretto, Giacomo Luigi, Maria Enrica Di Pietro, Marzia Piroddi, Giorgio Pintore und Alberto Mannu. „Classification of Pummelo (Citrus grandis) Extracts through UV-VIS-Based Chemical Fingerprint“. Beverages 8, Nr. 2 (13.06.2022): 34. http://dx.doi.org/10.3390/beverages8020034.
Zhang, Haipeng, Huan Wen, Jiajing Chen, Zhaoxin Peng, Meiyan Shi, Mengjun Chen, Ziyu Yuan, Yuan Liu, Hongyan Zhang und Juan Xu. „Volatile Compounds in Fruit Peels as Novel Biomarkers for the Identification of Four Citrus Species“. Molecules 24, Nr. 24 (12.12.2019): 4550. http://dx.doi.org/10.3390/molecules24244550.
Morell-Monzó, Sergio, María-Teresa Sebastiá-Frasquet und Javier Estornell. „Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information“. Remote Sensing 13, Nr. 4 (13.02.2021): 681. http://dx.doi.org/10.3390/rs13040681.
Flamini, Guido, Laura Pistelli, Simona Nardoni, Valentina Ebani, Angela Zinnai, Francesca Mancianti, Roberta Ascrizzi und Luisa Pistelli. „Essential Oil Composition and Biological Activity of “Pompia”, a Sardinian Citrus Ecotype“. Molecules 24, Nr. 5 (05.03.2019): 908. http://dx.doi.org/10.3390/molecules24050908.
Saddoud Debbabi, Olfa, Selma Ben Abdelaali, Rym Bouhlal, Sabrine Zneidi, Nasr Ben Abdelaali und Massaoud Mars. „Genetic Characterization of Tunisian Lime Genotypes Using Pomological Traits“. Journal of Horticultural Research 28, Nr. 1 (30.06.2020): 65–76. http://dx.doi.org/10.2478/johr-2020-0004.
Xiao, Deqin, Ruilin Zeng, Youfu Liu, Yigui Huang, Junbing Liu, Jianzhao Feng und Xinglong Zhang. „Citrus greening disease recognition algorithm based on classification network using TRL-GAN“. Computers and Electronics in Agriculture 200 (September 2022): 107206. http://dx.doi.org/10.1016/j.compag.2022.107206.
X. Zhao, T. F. Burks, J. Qin und M. A. Ritenour. „Digital Microscopic Imaging for Citrus Peel Disease Classification Using Color Texture Features“. Applied Engineering in Agriculture 25, Nr. 5 (2009): 769–76. http://dx.doi.org/10.13031/2013.28845.
Miller, William M. „Comparison of two classification approaches for automatic density separation of Florida citrus“. Computers and Electronics in Agriculture 4, Nr. 3 (Januar 1990): 225–33. http://dx.doi.org/10.1016/0168-1699(90)90021-g.
Shrivastava, Rahul J., und Jennifer L. Gebelein. „Land cover classification and economic assessment of citrus groves using remote sensing“. ISPRS Journal of Photogrammetry and Remote Sensing 61, Nr. 5 (Januar 2007): 341–53. http://dx.doi.org/10.1016/j.isprsjprs.2006.10.003.
Li, Xiuhua, Won Suk Lee, Minzan Li, Reza Ehsani, Ashish Ratn Mishra, Chenghai Yang und Robert L. Mangan. „Spectral difference analysis and airborne imaging classification for citrus greening infected trees“. Computers and Electronics in Agriculture 83 (April 2012): 32–46. http://dx.doi.org/10.1016/j.compag.2012.01.010.
Iqbal, S. Md, A. Gopal, P. E. Sankaranarayanan und Athira B. Nair. „Classification of Selected Citrus Fruits Based on Color Using Machine Vision System“. International Journal of Food Properties 19, Nr. 2 (18.05.2015): 272–88. http://dx.doi.org/10.1080/10942912.2015.1020439.
Wang, Hui, Tie Cai und Wei Cao. „Citrus Huanglongbing Recognition Algorithm Based on CKMOPSO“. International Journal of Cognitive Informatics and Natural Intelligence 15, Nr. 4 (Oktober 2021): 1–11. http://dx.doi.org/10.4018/ijcini.20211001.oa10.
Magalhães, Aida B., Giorgio S. Senesi, Anielle Ranulfi, Thiago Massaiti, Bruno S. Marangoni, Marina Nery da Silva, Paulino R. Villas Boas et al. „Discrimination of Genetically Very Close Accessions of Sweet Orange (Citrus sinensis L. Osbeck) by Laser-Induced Breakdown Spectroscopy (LIBS)“. Molecules 26, Nr. 11 (21.05.2021): 3092. http://dx.doi.org/10.3390/molecules26113092.
Harbi, Ahlem, Khaled Abbes, Beatriz Sabater-Muñoz, Francisco Beitia und Brahim Chermiti. „Residual toxicity of insecticides used in Tunisian citrus orchards on the imported parasitoid Diachasmimorpha longicaudata (Hymenoptera: Braconidae): Implications for IPM program of Ceratitis capitata (Diptera: Tephritidae)“. Spanish Journal of Agricultural Research 15, Nr. 3 (10.07.2017): e1008. http://dx.doi.org/10.5424/sjar/2017153-10734.
Xing, Shuli, und Malrey Lee. „Classification Accuracy Improvement for Small-Size Citrus Pests and Diseases Using Bridge Connections in Deep Neural Networks“. Sensors 20, Nr. 17 (03.09.2020): 4992. http://dx.doi.org/10.3390/s20174992.
Phi Bằng, Cao, und Trần Thị Thanh Huyền. „Identification, classification and chromosome mapping of the dehydrin gene family in clementine oranges (Citrus clementina)“. Journal of Science, Natural Science 61, Nr. 4 (2016): 116–21. http://dx.doi.org/10.18173/2354-1059.2016-0018.
Sun, Xiaopeng, Sai Xu und Huazhong Lu. „Non-Destructive Identification and Estimation of Granulation in Honey Pomelo Using Visible and Near-Infrared Transmittance Spectroscopy Combined with Machine Vision Technology“. Applied Sciences 10, Nr. 16 (05.08.2020): 5399. http://dx.doi.org/10.3390/app10165399.
Franco, Mariane Ferreira, Eduardo Carvalho Marques, Carlos de Sousa Lucci, Bruno Leonardo Mendonça Ribeiro, Lucas Alencar Fernandes Beserra, Jeferson Carvalho da Silva, Gisela Gregoria Choque und Lilian Gregory. „Estudo de diferentes proporções de milho x polpa cítrica x concentrado/volumoso na alimentação de ovinos da raça Suffolk“. Revista Agraria Academica 5, Nr. 5 (01.09.2022): 107–15. http://dx.doi.org/10.32406/v5n5/2022/107-115/agrariacad.
Ge Tu, Wang He Xi, und Bolormaa D. „Size based research on orange quality and classification“. Mongolian Journal of Agricultural Sciences 25, Nr. 03 (28.12.2018): 144–52. http://dx.doi.org/10.5564/mjas.v25i03.1184.
Furuta, Shu, Isao Hayakawa und Yusaku Fujio. „Classification of the Constituents of Citrus Juice Residue by a Wet-Grinding Process“. Journal of the Faculty of Agriculture, Kyushu University 34, Nr. 1/2 (November 1989): 101–6. http://dx.doi.org/10.5109/23892.
FENG, Xinwei, Qinghua ZHANG und Zhongliang ZHU. „Rapid Classification of Citrus Fruits Based on Raman Spectroscopy and Pattern Recognition Techniques“. Food Science and Technology Research 19, Nr. 6 (2013): 1077–84. http://dx.doi.org/10.3136/fstr.19.1077.
Befu, Mayumi, Akira Kitajima und Kojiro Hasegawa. „Classification of the Citrus Chromosomes with Same Types of Chromomycin A Banding Patterns.“ Engei Gakkai zasshi 71, Nr. 3 (2002): 394–400. http://dx.doi.org/10.2503/jjshs.71.394.