Effect of Tomato Leaf Constituents on Survival of Thrips palmi KARNY(Thysanoptera: Thripidae).

Abstract Background In this study, commercial bioinsecticides including entomopathogenic fungi, Beauveria bassiana, Metarhizium anisopliae, and Verticillium lecanii, and Spinetoram active ingredient insecticide were evaluated against the tomato leaf miner, Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae) larvae. Main body The active ingredients were prepared at the recommended concentrations under laboratory conditions and applied to the 2nd instar larvae of T. absoluta by spraying with a hand sprayer. On the 1st, 3rd, 5th, and 7th days of the application, evaluations were made by counting survived individuals. The findings showed that the highest mortality rates were detected in the case of Spinetoram with 56, 60, 88, and 100% on all counting days of the experiments, respectively. The highest mortality rate among bioinsecticides was recorded for M. anisopliae, with 87% mortality on the 7th day of application. Short conclusion As a result, Spinetoram was found the most effective insecticide when applied to T. absoluta, followed by M. anisopliae.

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Screening Luffa germplasm and advanced breeding lines for resistance to Tomato leaf curl New Delhi virus

Journal of General Plant Pathology ◽

10.1007/s10327-021-01010-z ◽

2021 ◽

Author(s):

Manpreet Kaur ◽

B. Varalakshmi ◽

M. Pitchaimuthu ◽

B. Mahesha

Keyword(s):

Tomato Leaf ◽

New Delhi ◽

Breeding Lines ◽

Tomato Leaf Curl ◽

Leaf Curl

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

Journal of Plant Diseases and Protection ◽

10.1007/s41348-021-00463-w ◽

2021 ◽

Author(s):

Ravinder Kumar ◽

Rahul Kumar Tiwari ◽

Arjunan Jeevalatha ◽

Sundaresha Siddappa ◽

Mohd. Abas Shah ◽

...

Keyword(s):

Tomato Leaf ◽

Current Status ◽

New Delhi ◽

Apical Leaf ◽

Tomato Leaf Curl ◽

Leaf Curl Disease ◽

Leaf Curl

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Tomato Leaf Disease Diagnosis Based on Improved Convolution Neural Network by Attention Module

Agriculture ◽

10.3390/agriculture11070651 ◽

2021 ◽

Vol 11 (7) ◽

pp. 651

Author(s):

Shengyi Zhao ◽

Yun Peng ◽

Jizhan Liu ◽

Shuo Wu

Keyword(s):

Neural Network ◽

High Performance ◽

Model Comparison ◽

Research Direction ◽

Disease Diagnosis ◽

Tomato Leaf ◽

Identification Accuracy ◽

Main Research ◽

Proposed Model ◽

Complex Features

Crop disease diagnosis is of great significance to crop yield and agricultural production. Deep learning methods have become the main research direction to solve the diagnosis of crop diseases. This paper proposed a deep convolutional neural network that integrates an attention mechanism, which can better adapt to the diagnosis of a variety of tomato leaf diseases. The network structure mainly includes residual blocks and attention extraction modules. The model can accurately extract complex features of various diseases. Extensive comparative experiment results show that the proposed model achieves the average identification accuracy of 96.81% on the tomato leaf diseases dataset. It proves that the model has significant advantages in terms of network complexity and real-time performance compared with other models. Moreover, through the model comparison experiment on the grape leaf diseases public dataset, the proposed model also achieves better results, and the average identification accuracy of 99.24%. It is certified that add the attention module can more accurately extract the complex features of a variety of diseases and has fewer parameters. The proposed model provides a high-performance solution for crop diagnosis under the real agricultural environment.

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Progression of Watermelon Bud Necrosis Virus Infection in Its Vector, Thrips palmi

Cells ◽

10.3390/cells10020392 ◽

2021 ◽

Vol 10 (2) ◽

pp. 392

Author(s):

Amalendu Ghosh ◽

Priti ◽

Bikash Mandal ◽

Ralf G. Dietzgen

Keyword(s):

Virus Infection ◽

Salivary Glands ◽

Frankliniella Occidentalis ◽

Western Flower Thrips ◽

Malpighian Tubules ◽

Necrosis Virus ◽

Posterior Portion ◽

Thrips Palmi ◽

Thrips Species ◽

Anterior Midgut

Thrips are important pests of agricultural, horticultural, and forest crops worldwide. In addition to direct damages caused by feeding, several thrips species can transmit diverse tospoviruses. The present understanding of thrips–tospovirus relationships is largely based on studies of tomato spotted wilt virus (TSWV) and Western flower thrips (Frankliniella occidentalis). Little is known about other predominant tospoviruses and their thrips vectors. In this study, we report the progression of watermelon bud necrosis virus (WBNV) infection in its vector, melon thrips (Thrips palmi). Virus infection was visualized in different life stages of thrips using WBNV-nucleocapsid protein antibodies detected with FITC-conjugated secondary antibodies. The anterior midgut was the first to be infected with WBNV in the first instar larvae. The midgut of T. palmi was connected to the principal salivary glands (PSG) via ligaments and the tubular salivary glands (TSG). The infection progressed to the PSG primarily through the connecting ligaments during early larval instars. The TSG may also have an ancillary role in disseminating WBNV from the midgut to PSG in older instars of T. palmi. Infection of WBNV was also spread to the Malpighian tubules, hindgut, and posterior portion of the foregut during the adult stage. Maximum virus-specific fluorescence in the anterior midgut and PSG indicated the primary sites for WBNV replication. These findings will help to better understand the thrips–tospovirus molecular relationships and identify novel potential targets for their management. To our knowledge, this is the first report of the WBNV dissemination path in its vector, T. palmi.

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Metagenomic analyses and genetic diversity of Tomato leaf curl Arusha virus affecting tomato plants in Kenya

Virology Journal ◽

10.1186/s12985-020-01466-z ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Edith Khamonya Avedi ◽

Adedapo Olutola Adediji ◽

Dora Chao Kilalo ◽

Florence Mmogi Olubayo ◽

Isaac Macharia ◽

...

Keyword(s):

Genetic Diversity ◽

Selection Pressure ◽

Management Strategies ◽

Purifying Selection ◽

Tomato Leaf ◽

Amino Acid Sequences ◽

Virus Population ◽

Tomato Production ◽

Tomato Leaf Curl ◽

Leaf Curl

Abstract Background Tomato production is threatened worldwide by the occurrence of begomoviruses which are associated with tomato leaf curl diseases. There is little information on the molecular properties of tomato begomoviruses in Kenya, hence we investigated the population and genetic diversity of begomoviruses associated with tomato leaf curl in Kenya. Methods Tomato leaf samples with virus-like symptoms were obtained from farmers’ field across the country in 2018 and Illumina sequencing undertaken to determine the genetic diversity of associated begomoviruses. Additionally, the occurrence of selection pressure and recombinant isolates within the population were also evaluated. Results Twelve complete begomovirus genomes were obtained from our samples with an average coverage of 99.9%. The sequences showed 95.7–99.7% identity among each other and 95.9–98.9% similarities with a Tomato leaf curl virus Arusha virus (ToLCArV) isolate from Tanzania. Analysis of amino acid sequences showed the highest identities in the regions coding for the coat protein gene (98.5–100%) within the isolates, and 97.1–100% identity with the C4 gene of ToLCArV. Phylogenetic algorithms clustered all Kenyan isolates in the same clades with ToLCArV, thus confirming the isolates to be a variant of the virus. There was no evidence of recombination within our isolates. Estimation of selection pressure within the virus population revealed the occurrence of negative or purifying selection in five out of the six coding regions of the sequences. Conclusions The begomovirus associated with tomato leaf curl diseases of tomato in Kenya is a variant of ToLCArV, possibly originating from Tanzania. There is low genetic diversity within the virus population and this information is useful in the development of appropriate management strategies for the disease in the country.

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