Appraisal of the Impact of Three Insecticides on the Principal Rice Pests and Their Predators in China

Chen, Yong; Xue, Zhenyi; Liu, Jie; Wei, Hui; Chen, Yongdui; Su, Xiaoxia; Zhang, Jie

doi:10.1653/024.099.0209

Cited by 7 publications

(6 citation statements)

References 16 publications

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“…The current results are consistent with the previous findings by Muralibaskaran et al (2013) and Chen et al (2016). An insecticides mixture having two different mode of action may be more effective in controlling insect pests than the usage of single insecticide effective specific to particular insect family.…”

Section: Resultssupporting

confidence: 93%

“…ha (31.2 tha ), Thiamethoxam 75% SG (30.2 -1 -1 tha ) and Dimethoate 35% EC (28.1 tha ). Chen et al (2016) reported that Virtako at a higher rate showed long-lasting effect, produced 65.8% plant hopper control 28 days after application, and rice leaf folder control was 1.75 fold more than chlorantraniliprole treatment after 28 days. Muralibaskaran et al (2013) reported that Virtako 1.5 G was effective in controlling rice pests such as brown planthopper, leaf folder and stem borer while also produced significantly higher yields than the control.…”

Section: Resultsmentioning

confidence: 98%

“…Andorno et al (2019) studied the susceptibility of O. insidiosus to some common pesticides including diamide insecticides such as Flubendiamide and Cyantraniliprole in the laboratory and categorized that Flubendiamide as harmless, while Cyantraniliprole was slightly harmful to O. insidiosus and it had an impact on the fecundity of predatory bug. Chen et al (2016)…”

Section: Acknowledgmentmentioning

confidence: 99%

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Bioefficacy, phytotoxicity and safety of Virtako 1.5 Gr a premixed commercial insecticide against thrips, black cutworm and natural enemies in onion

Karuppaiah¹,

Soumia²,

Singh³

2023

JEB

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Aim: This study aimed to evaluate the relative field-efficacy, natural enemies safety and phytotoxicity of premixed soil insecticide formulation Virtako 1.5 Gr (Chlorantraniliprole 0.5% + Thiamethoxam 1%) against onion thrips (Thrips tabaci) and black cutworm (Agrotis ipsilon) infesting onion. Methodology: Two field experiments were conducted in successive years (2017-18 & 2018-19) to evaluate the bio-efficacy of Virtako 1.5® Gr against thrips, cutworms and natural enemies in onion. The desired dosage of Virtako 1.5® Gr was applied as soil broadcasting after 10 days of transplanting. Thrips population, cutworm damage, natural enemies and phytotoxicity observation were made using standard procedures. Results: The results revealed that Virtako® 1.5 Gr applied @ 105 and 90 g a.i ha-1 recorded the lowest mean thrips population, 18.03 and 19.50 thrips per plant, respectively. Similarly, Virtako 1.5 Gr at 105 a.i. ha-1 reduced cutworm damage by 88.5%, followed by Virtako 1.5 Gr at 90 g a.i. ha-1 (85.5%). Although no natural enemies’ activity (Coccinellids, Orius spp, and Spiders) was found in the early phase of onion growth, they were recorded in all treatments at later crop growth stages. All doses of Virtako 1.5 Gr had no noticeable phytotoxicity effects on onion plants. Interpretation: Application of Virtako 1.5 Gr effectively minimized thrips population and cutworm damage in onions. Further, it did not show any significant harmful impact on the activity to above-ground natural enemies. Therefore, Virtako 1.5 Gr at a lower effective dose 90 g a.i ha-1 can be recommended for onion against thrips and black cutworm. Key words: Cutworm, Onion thrips, Premixed insecticide, Phytotoxicty, Virtako 1.5 Gr

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 98%

Section: Acknowledgmentmentioning

confidence: 99%

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Bioefficacy, phytotoxicity and safety of Virtako 1.5 Gr a premixed commercial insecticide against thrips, black cutworm and natural enemies in onion

Karuppaiah¹,

Soumia²,

Singh³

2023

JEB

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“…alginolyticus foi identificado pela primeira vez como um patógeno de humanos em 1973 (LONGO et al, 2011). É reconhecido principalmente como um patógeno para peixes, mas também pode ser encontrado em caranguejos, ostras e camarões (BARROS, 2004); Ele é frequentemente relacionado a surtos de vibriose, doença bacteriana na aquicultura de camarão na qual sofre grandes perdas econômicas SABIR et al, 2013;CHEN et al, 2016), sendo facilmente isolada e identificada.…”

Section: Vibrio Alginolyticusunclassified

“…Tendo em vista a ação dos jasmonatos para reduzir as injúrias causadas por estresses, observa-se que esse grupo de hormônios atua ativando enzimas e compostos metabólicos relacionados ao catabolismo da arginina contribuindo para redução dos danos causados pelo estresse a baixas temperaturas (ZHANG et al, 2012 (CHEN et al, 2016).…”

Section: Efeitos Fisiológicos Dos Jasmonatosunclassified

Perfil Dos Casos De Coqueluche No Estado De Goiás

Borges¹,

Dietz²,

Oliveira³

et al. 2019

Análise Crítica Das Ciências Biológicas E Da Natureza

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Monitoring the leaf damage by the rice leafroller with deep learning and ultra‐light UAV

Xia,

Zhang,

Chen

et al. 2024

Pest Management Science

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BACKGROUNDRice leafroller is a serious threat to the production of rice. Monitoring the damage caused by rice leafroller is essential for effective pest management. Owing to limitations in collecting decent quality images and high‐performing identification methods to recognize the damage, studies recommending fast and accurate identification of rice leafroller damage are rare. In this study, we employed an ultra‐lightweight unmanned aerial vehicle (UAV) to eliminate the influence of the downwash flow field and obtain very high‐resolution images of the damaged areas of the rice leafroller. We used deep learning technology and the segmentation model, Attention U‐Net, to recognize the damaged area by the rice leafroller. Further, a method is presented to count the damaged patches from the segmented area.RESULTSThe result shows that Attention U‐Net achieves high performance, with an F1 score of 0.908. Further analysis indicates that the deep learning model performs better than the traditional image classification method, Random Forest (RF). The traditional method of RF causes a lot of false alarms around the edge of leaves, and is sensitive to the changes in brightness. Validation based on the ground survey indicates that the UAV and deep learning‐based method achieve a reasonable accuracy in identifying damage patches, with a coefficient of determination of 0.879. The spatial distribution of the damage is uneven, and the UAV‐based image collecting method provides a dense and accurate method to recognize the damaged area.CONCLUSIONOverall, this study presents a vision to monitor the damage caused by the rice leafroller with ultra‐light UAV efficiently. It would also contribute to effectively controlling and managing the hazardous rice leafroller. © 2024 Society of Chemical Industry.

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Appraisal of the Impact of Three Insecticides on the Principal Rice Pests and Their Predators in China

Cited by 7 publications

References 16 publications

Bioefficacy, phytotoxicity and safety of Virtako 1.5 Gr a premixed commercial insecticide against thrips, black cutworm and natural enemies in onion

Bioefficacy, phytotoxicity and safety of Virtako 1.5 Gr a premixed commercial insecticide against thrips, black cutworm and natural enemies in onion

Perfil Dos Casos De Coqueluche No Estado De Goiás

Monitoring the leaf damage by the rice leafroller with deep learning and ultra‐light UAV

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