Potato apical leaf curl disease: current status and perspectives on a disease caused by tomato leaf curl New Delhi virus

Kumar, Ravinder; Tiwari, Rahul Kumar; Jeevalatha, A.; Siddappa, Sundaresha; Shah, Mohd Abas; Sharma, Sanjeev; Sagar, Vinay; Kumar, Manoj; Chakrabarti, S. K.

doi:10.1007/s41348-021-00463-w

Cited by 37 publications

(9 citation statements)

References 68 publications

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“…In host–pathogen interactions, phenols are considered to be the most important components in the defense response and play a key role in imparting resistance to plant diseases ( Kumar et al., 2021 ). Our study found that resistant cultivars had a higher phenol content compared to susceptible cultivars.…”

Section: Discussionmentioning

confidence: 99%

“…It is transmitted by whitefly ( Bemisiatabaci Gem.) through circulative persistent transmission in plants ( Sharma and Rishi, 2003 ; Kumar et al., 2021 ). CLCuV poses a significant threat to cotton production around the world, causing substantial yield loss and economic harm.…”

Section: Introductionmentioning

confidence: 99%

“…Biochemical compounds play a crucial role in the survival and reproduction of plants under biotic stress ( Wilson and Smith, 1976 ; Hedin and McCarty, 1990 ; Borkar and Verma, 1991 ; Bhat, 1997 ; Chakrabarty et al., 2002 ; Singh and Agarwal, 2004 ; Beniwal et al., 2006 ; Acharya and Singh, 2008 ; Govindappa et al., 2008 ; Ajmal et al., 2011 ; Anuradha, 2014 ). Although their association with plant response to biotic stresses has been extensively studied, little research has been conducted on the response of plants to virus-induced diseases ( Kumar et al., 2020 ; Kumar et al., 2021 ; Kumar et al., 2022 ). To address this gap, we investigated the biochemical response of cotton plants to CLCuD by examining the production of various primary and secondary metabolites.…”

Section: Introductionmentioning

confidence: 99%

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Utilization of primary and secondary biochemical compounds in cotton as diagnostic markers for measuring resistance to cotton leaf curl virus

et al. 2023

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IntroductionCotton (Gossypium hirsutum L.) is one of the most important staple fibrous crops cultivated in India and globally. However, its production and quality are greatly hampered by cotton leaf curl disease (CLCuD) caused by cotton leaf curl virus (CLCuV). Therefore, the aim of the present study was to investigate the biochemical mechanisms associated with CLCuD resistance in contrasting cotton genotypes.MethodsFour commercial cotton varieties with susceptible (HS 6 and RCH-134 BG-II) and resistant (HS 1236 and Bunty) responses were used to analyze the role of primary (sugar, protein, and chlorophyll) and secondary (gossypol, phenol, and tannin) biochemical compounds produced by the plants against infection by CLCuV. The resistant cultivars with increased activity of protein, phenol, and tannin exhibited biochemical barriers against CLCuV infection, imparting resistance in cotton cultivars.ResultsReducing sugar in the healthy plants of the susceptible Bt cultivar RCH 134 BG-II exhibited the highest value of 1.67 mg/g at 90 days. In contrast, the lowest value of 0.07 mg g-1 was observed at 60 DAS in the highly diseased plants of the susceptible hybrid HS 6. Higher phenol content (0.70 mg g-1) was observed at 90 DAS in resistant cultivars, whereas highly susceptible plants exhibited the least phenol (0.25 mg g-1) at 90 DAS. The lowest protein activity was observed at 120 DAS in susceptible cultivars HS 6 (9.4 mg g-1) followed by RCH 134 BG-II (10.5 mg g-1). However, other biochemical compounds, including chlorophyll, sugar, and gossypol, did not show a significant role in resistance against CLCuV. The disease progression analysis in susceptible cultivars revealed non-significant differences between the two susceptible varieties.DiscussionNevertheless, these compounds are virtually associated with the basic physiological and metabolic mechanisms of cotton plants. Among the primary biochemical compounds, only protein activity was proposed as the first line of defense in cotton against CLCuV. The secondary level of defense line in resistance showed the activity of secondary biochemical compounds phenol and tannins, which displayed a significant increase in their levels while imparting resistance against CLCuV in cotton.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Utilization of primary and secondary biochemical compounds in cotton as diagnostic markers for measuring resistance to cotton leaf curl virus

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“…These factors can significantly affect plant growth, yield, and quality. Similarly, biotic stresses, such as viruses, fungi, bacteria, insects, vectors, and nematodes, can severely damage the vigour and productivity of horticultural crops ( Kumar et al., 2021 ; Lal et al., 2021 ; El-Sappah et al. ; Sun et al.…”

Section: Introductionmentioning

confidence: 99%

Editorial: Abiotic and biotic stress in horticultural crops: insight into recent advances in the underlying tolerance mechanism

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“…Even though agriculture is India's backbone, no technological advances have been researched in developing automation in agriculture. Due to various diseases and parasites, there are signi cant challenges in terms of productivity and quality [3]. Plant disorder has been considered one of the most signi cant hazards to food security [4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Classification of Real-Time Diseased Cotton Leaves and Plants Using a Deep-Convolutional Neural Network

Kumar

2022

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The automated detection and classification of plant diseases based on images of leaves is a significant milestone in agriculture. In this paper, the concept of deep learning was used to identify and predict cotton plant disease status using real-time images of leaves and plants. The models were trained using a database of 2293 images of cotton leaves and plants. The data included four distinct classes of leaves, plants disease combinations, and their respective categories. Python version 3.6.9 is used to implement the developed model. The model includes a deep learning package such as Keras, TensorFlow, and a Googlecolab cloud-based jupyter notebook as the development environment. For classifying leaves and plant diseases in cotton plants, our model attained an accuracy of 97.98%. The proposed technique outperformed the recent approaches indicated in earlier literature for relevant parameters. As a result, the technique is intended to reduce the time spent identifying cotton leaf disease in significant production regions and human error and time spent determining its severity.

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Potato apical leaf curl disease: current status and perspectives on a disease caused by tomato leaf curl New Delhi virus

Cited by 37 publications

References 68 publications

Utilization of primary and secondary biochemical compounds in cotton as diagnostic markers for measuring resistance to cotton leaf curl virus

Utilization of primary and secondary biochemical compounds in cotton as diagnostic markers for measuring resistance to cotton leaf curl virus

Editorial: Abiotic and biotic stress in horticultural crops: insight into recent advances in the underlying tolerance mechanism

Automatic Classification of Real-Time Diseased Cotton Leaves and Plants Using a Deep-Convolutional Neural Network

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