Real-time automatic detection and classification of groundnut leaf disease using hybrid machine learning techniques

Alok N, Krishan K, Chauhan P (2021) Deep learning-based image classifier for malaria cell detection. Machine Learning for Healthcare Applications, pp 187-197

Anil K, Podile AR (2012) HarpinPss-mediated enhancement in growth and biological control of late leaf spot in groundnut by a chlorothalonil-tolerant bacillus thuringiensis SFC24. Microbiol Res 167(4):194–198

Ansari H, Vijayvergia A, Kumar K, (2018) DCR-HMM: depression detection based on content rating using hidden Markov model. In: 2018 Conference on Information and Communication Technology (CICT). IEEE, pp 1–6

Appiah AS, Sossah FL, Tegg RS, Offei SK, Wilson CR (2017) Assessing sequence diversity of groundnut rosette disease agents and the distribution of groundnut rosette assistor virus in major groundnut-producing regions of Ghana. Tropic Plant Pathol 42(2):109–120

Ashourloo D, Matkan AA, Huete A, Aghighi H, Mobasheri MR (2016) Developing an index for detection and identification of disease stages. IEEE Geosci Remote Sens Lett 13(6):851–855

Ashourloo D, Aghighi H, Matkan AA, Mobasheri MR, Rad AM (2016) An investigation into machine learning regression techniques for the leaf rust disease detection using hyperspectral measurement. IEEE J Select Topics Appl Earth Observ Remote Sens 9(9):4344–4351

Atila Ü, Uçar M, Akyol K, Uçar E (2021) Plant leaf disease classification using EfficientNet deep learning model. Eco Inform 61:101182

Chen J, Yin H, Zhang D (2020) A self-adaptive classification method for plant disease detection using GMDH-logistic model. Sustain Computing: Inf Sys 28:100415

Dabral I, Singh M, Kumar K (2019) Cancer detection using convolutional Neural network. In: International Conference on Deep Learning, Artificial Intelligence and Robotics. Springer, Cham, pp 290-298. https://doi.org/10.1007/978-3-030-67187-7_30

Dai Q, Cheng X, Qiao Y, Zhang Y (2020) Crop leaf disease image super-resolution and identification with dual attention and topology fusion generative adversarial network. IEEE Access 8:55724–55735

Darbari A, Kumar K, Darbari S, Patil PL (2021) Requirement of artificial intelligence technology awareness for thoracic surgeons. The Cardiothoracic Surgeon 29(1):1–10

Devi KS, Srinivasan P, Bandhopadhyay S (2020) H2K–A robust and optimum approach for detection and classification of groundnut leaf diseases. Comput Electron Agric 178:105749

Jadon KS, Thirumalaisamy PP, Kumar V, Koradia VG, Padavi RD (2015) Management of soil borne diseases of groundnut through seed dressing fungicides. Crop Prot 78:198–203

Jiang P, Chen Y, Liu B, He D, Liang C (2019) Real-time detection of apple leaf diseases using deep learning approach based on improved convolutional neural networks. IEEE Access 7:59069–59080

Kaur S, Pandey S, Goel S (2018) Semi-automatic leaf disease detection and classification system for soybean culture. IET Image Process 12(6):1038–1048

Khattab A, Habib SE, Ismail H, Zayan S, Fahmy Y, Khairy MM (2019) An IoT-based cognitive monitoring system for early plant disease forecast. Comput Electron Agric 166:105028

Kiruba Raji I, Thyagharajan KK, Vignesh T, Kalaiarasi G (2021) Classifying Indian Medicinal Leaf Species Using LCFN-BRNN Model. KSII Trans Internet Inf Syst (TIIS) 15(10). https://doi.org/10.3837/tiis.2021.10.013

Kumar A, Singh N, Kumar P, Vijayvergia A, Kumar K (2017) A novel superpixel based color spatial feature for salient object detection. In: 2017 Conference on Information and Communication Technology (CICT). IEEE, pp 1–5

Kumar PL, Goud KVK, Kumar GV, Kumar PS (2020) Enhanced weighted sum back propagation neural network for leaf disease classification. Materials Today: Proceedings

Kumari V, Gowda MVC, Tasiwal V, Pandey MK, Bhat RS, Mallikarjuna N, Upadhyaya HD, Varshney RK (2014) Diversification of primary gene pool through introgression of resistance to foliar diseases from synthetic amphidiploids to cultivated groundnut (Arachishypogaea L.). Crop J 2(2–3):110–119

Kumari S, Singh M, Kumar K (2021) Prediction of liver disease using grouping of machine learning classifiers. In: International Conference on Deep Learning, Artificial Intelligence and Robotics. Springer, Cham, pp 339–349. https://doi.org/10.1007/978-3-030-67187-7_35

Mishra M, Choudhury P, Pati B (2021) Modified ride-NN optimizer for the IoT based plant disease detection. J Ambient Intelli Humaniz Comput 12(1):691–703

Mugisa IO, Karungi J, Akello B, Ochwo-Ssemakula MKN, Biruma M, Okello DK, Otim G (2016) Determinants of groundnut rosette virus disease occurrence in Uganda. Crop Prot 79:117–123

Negi A, Kumar K, Chauhan P (2021) Deep neural network-based multi-class image classification for plant diseases. Agricultural Informatics: Automation Using the IoT and Machine Learning, pp 117–129

Nie X, Wang L, Ding H, Xu M (2019) Strawberry Verticillium wilt detection network based on multi-task learning and attention. IEEE Access 7:170003–170011

Pantazi XE, Moshou D, Tamouridou AA (2019) Automated leaf disease detection in different crop species through image features analysis and one class classifiers. Comput Electron Agric 156:96–104

Ramesh S, Vydeki D (2020) Recognition and classification of paddy leaf diseases using optimized deep neural network with Jaya algorithm. Inf Process Agriculture 7(2):249–260

Senthilraja G, Anand T, Kennedy JS, Raguchander T, Samiyappan R (2013) Plant growth promoting rhizobacteria (PGPR) and entomopathogenic fungus bioformulation enhance the expression of defense enzymes and pathogenesis-related proteins in groundnut plants against leafminer insect and collar rot pathogen. Physiol Mol Plant Pathol 82:10–19

Shoba D, Manivannan N, Vindhiyavarman P, Nigam SN (2012) SSR markers associated for late leaf spot disease resistance by bulked segregant analysis in groundnut (Arachishypogaea L.). Euphytica 188(2):265–272

Singh UP, Chouhan SS, Jain S, Jain S (2019) Multilayer convolution neural network for the classification of mango leaves infected by anthracnose disease. IEEE Access 7:43721–43729

Sinha A, Shekhawat RS (2020) Olive spot disease detection and classification using analysis of leaf image textures. Procedia Comput Sci 167:2328–2336

Sun J, Yang Y, He X, Wu X (2020) Northern maize leaf blight detection under complex field environment based on deep learning. IEEE Access 8:33679–33688

Thyagharajan KK, Kiruba Raji I (2021) Diagnosis of Neem Leaf Disease Using Fuzzy-HOBINM and ANFIS Algorithms. CMC-Comput Mater Continua 69(2):2061–2076. https://doi.org/10.32604/cmc.2021.017591

Thyagharajan KK, Kiruba Raji I (2019) A review of visual descriptors and classification techniques used in leaf species identification. Archives Computational Methods Eng 26(4):933–960. https://doi.org/10.1007/s11831-018-9266-3

Tripathy AK, Adinarayana J, Vijayalakshmi K, Merchant SN, Desai UB, Ninomiya S, Hirafuji M, Kiura T (2014) Knowledge discovery and leaf spot dynamics of groundnut crop through wireless sensor network and data mining techniques. Comput Electron Agric 107:104–114

Vaishnnave MP, Devi KS, Srinivasan P, ArutPerumJothi G (2019) Detection and classification of groundnut leaf diseases using KNN classifier. In: 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN). IEEE, pp 1–5

Zeng Q, Ma X, Cheng B, Zhou E, Pang W (2020) GANs-based data augmentation for Citrus disease severity detection using deep learning. IEEE Access 8:172882–172891

Zhang X, Qiao Y, Meng F, Fan C, Zhang M (2018) Identification of maize leaf diseases using improved deep convolutional neural networks. IEEE Access 6:30370–30377

Zhang Y, Song C, Zhang D (2020) Deep learning-based object detection improvement for tomato disease. IEEE Access 8:56607–56614

Zongo A, Khera P, Sawadogo M, Shasidhar Y, Sriswathi M, Vishwakarma MK, Sankara P, Ntare BR, Varshney RK, Pandey MK, Desmae H (2017) SSR markers associated to early leaf spot disease resistance through selective genotyping and single marker analysis in groundnut (Arachishypogaea L.). Biotechnol Reps 15:132–137