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Intelligent diagnosis of northern corn leaf blight with deep learning model

Journal of Integrative Agriculture 2022年第4期21卷 1094-1105页

作者： PAN Shuai-qun QIAO Jing-fen WANG Rui YU Hui-lin WANG Cheng Kerry TAYLOR PAN Hong-yu School of Computing Australian National UniversityCanberra 2601Australia College of Plant Sciences Jilin UniversityChangchun 130062P.R.China

Maize(Zea mays L.), also known as corn, is the third most cultivated crop in the world. northern corn leaf blight(NCLB) is a globally devastating maize foliar disease caused by Setosphaeria turcica(Luttrell) Leonard and Suggs. Early intelligent diagnosis and warning is an effective and economical strategy to control this disease. Today, deep learning is beginning to play an essential role in agriculture. Notably, deep convolutional neural networks(DCNN) are amongst the most successful machine learning techniques in plant disease detection and diagnosis. Our study aims to identify NCLB in the maize-producing area in Jilin Province based on several DCNN models. We established a database of 985 leaf images of healthy and infected maize and applied data augmentation techniques including image segmentation, image resizing, image cropping, and image transformation, to expand to 30 655 images. Several proven convolutional neural networks, such as AlexNet, Google Net, VGG16, and VGG19, were then used to identify diseases. Based on the best performance of the DCNN pre-trained model Google Net, some of the recent loss functions developed for deep facial recognition tasks such as Arc Face, Cos Face, and A-Softmax were applied to detect NCLB. We found that a pre-trained Google Net architecture with the Softmax loss function can achieve an excellent accuracy of 99.94% on NCLB diagnosis. The analysis was implemented in Python with two deep learning frameworks, Pytorch and Keras. The techniques, training, validation, and test results are presented in this paper. Overall, our study explores intelligent identification technology for NCLB and effectively diagnoses NCLB from images of maize.

关键词： maize northern corn leaf blight Setosphaeria turcica intelligent diagnosis deep learning convolutional neural network

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Distribution,Etiology,Molecular Genetics and Management Perspectives of northern corn leaf blight of Maize(Zea mays L.)

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Phyton-International Journal of Experimental Botany 2022年第10期91卷 2111-2133页

作者： M.Ashraf Ahangar Shabir Hussain Wani Zahoor A.Dar Jan Roohi Fayaz Mohiddin Monika Bansal Mukesh Choudhary Sumit K.Aggarwal S.A.Waza Khursheed Ahmad Dar Ayman El Sabagh Celaleddin Barutcular Omer Konuşkan Mohammad Anwar Hossain Mountain Research Centre for Field Crops Sher-e-Kashmir University of Agricultural Sciences and Technology of KashmirJammu&Kashmir192124India Dry Land Agriculture Research Station Rangreth Sher-e-Kashmir University of Agricultural Sciences and Technology of KashmirJammu&Kashmir191132India School of Agricultural Biotechnology Punjab Agricultural UniversityLudhiana141001India Indian Institute of Maize Research PAU CampusLudhiana141001India College of Temperate Sericulture Sher-e-Kashmir University of Agricultural Sciences and Technology of KashmirJammu&Kashmir191132India Department of Agronomy Faculty of AgricultureKafrelsheikh UniversityKafr El-Sheikh33516Egypt Department of Field Crops Faculty of AgricultureSiirt UniversitySiirt56100Turkey Department of Field Crops Faculty of AgricultureUniversity ofÇukurovaAdana01330Turkey Department of Field Crops Faculty of AgricultureHatay Mustafa Kemal UniversityHatay31060Turkey Department of Genetics and Plant Breeding Bangladesh Agricultural UniversityMymensingh2202Bangladesh

Maize is cultivated extensively throughout the world and has the highest production among ***,northern corn leaf blight(NCLB)disease caused by Exherohilum turcicum,is the most devastating limiting factor of maize *** disease causes immense losses to corn yield if it develops prior or during the tasseling and silking stages of crop *** has a worldwide distribution and its development is favoured by cool to moderate temperatures with high relative *** prevalence of the disease has increased in recent years and new races of the pathogen have been reported *** fungus *** is highly variable in *** different management strategies have proved effective to reduce economic losses from NCLB,the development of varieties with resistance to *** is the most efficient and inexpensive way for disease manage*** resistance for NCLB governed by Ht genes is a race-specific resistance which leads to a higher level of ***,some Ht genes can easily become ineffective under the high pressure of virulent strains of the ***,it is imperative to understand and examine the consistency of the genomic locations of quantitative trait loci for resistance to NCLB in diverse maize *** breeding approaches for pyramiding resistant genes against *** in maize can impart NCLB resistance under high disease pressure ***,the genome editing approaches like CRISPR-cas9 and RNAi can also prove vital for developing NCLB resistant maize *** such this review delivers emphasis on the importance and current status of the disease,racial spectrum of the pathogen,genetic nature and breeding approaches for resistance and management strategies of the disease in a sustainable manner.

关键词： northern corn leaf blight etiology Exherohilum turcicum pathogenic variability disease resistance management strategies

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