Population Dynamics of Sucking Pests in Dual Season Cotton Ecosystem and Its Correlation with Weather Factors

Kiruthika, A.; Murugan, M.; Jeyarani, S.; Sathyamoorthy, N. K.; Senguttuvan, K.

doi:10.9734/ijecc/2022/v12i1131010

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Present results are corroborate with the findings of Sohrab et al [7] who observed two peaks during the crop growth period, 1 st peak at 30 DAS and 2 nd at 150 DAS with 11.65 and 26.83 aphids/leaf. Whereas Kiruthika et al [8] the highest aphid population was observed at 50DAS itself, during flowering stage of the crop with 18.7 adults / 3 leaves.…”

Section: Resultsmentioning

confidence: 81%

Study on the Incidence of Sucking Pests and Pink Bollworm in Cotton

Rajasekhar

Subbaiah

Prasad

et al. 2023

JEAI

View full text Add to dashboard Cite

Sucking pests and pink bollworm are serious pest of cotton one after the other in India by causing serious yield losess. The present investigation was carried out in three major cotton growing mandals of NTR district to understand the level of pest incidence in Bt cotton during Kharif, 2022-23 on regular interval. Among the sucking pests only thrips population recorded 32.26 no/3 leaves and crossed the ETL at 45 DAS. Remaining sucking pests such as Leafhopper, whitefly and aphid did not crossed ETL during crop growth period and highest incidence of 5.92, 4.04 and 27.14 no/3 leaves was recorded respectively at 45, 60 and 120 DAS. Whereas pink bollworm recorded 23.10% rosette flowers, 44.04% boll damage in Bheemavaram village of Vastavai mandal and 40.83% locule damage in Konakanchi village of Penuganchiprolu mandal.

show abstract

Section: Resultsmentioning

confidence: 81%

Study on the Incidence of Sucking Pests and Pink Bollworm in Cotton

Rajasekhar

Subbaiah

Prasad

et al. 2023

JEAI

View full text Add to dashboard Cite

show abstract

Residual swin transformer for classifying the types of cotton pests in complex background

Zhang,

Zhu,

Zhang

et al. 2024

Front. Plant Sci.

View full text Add to dashboard Cite

BackgroundCotton pests have a major impact on cotton quality and yield during cotton production and cultivation. With the rapid development of agricultural intelligence, the accurate classification of cotton pests is a key factor in realizing the precise application of medicines by utilize unmanned aerial vehicles (UAVs), large application devices and other equipment.MethodsIn this study, a cotton insect pest classification model based on improved Swin Transformer is proposed. The model introduces the residual module, skip connection, into Swin Transformer to improve the problem that pest features are easily confused in complex backgrounds leading to poor classification accuracy, and to enhance the recognition of cotton pests. In this study, 2705 leaf images of cotton insect pests (including three insect pests, cotton aphids, cotton mirids and cotton leaf mites) were collected in the field, and after image preprocessing and data augmentation operations, model training was performed.ResultsThe test results proved that the accuracy of the improved model compared to the original model increased from 94.6% to 97.4%, and the prediction time for a single image was 0.00434s. The improved Swin Transformer model was compared with seven kinds of classification models (VGG11, VGG11-bn, Resnet18, MobilenetV2, VIT, Swin Transformer small, and Swin Transformer base), and the model accuracy was increased respectively by 0.5%, 4.7%, 2.2%, 2.5%, 6.3%, 7.9%, 8.0%.DiscussionTherefore, this study demonstrates that the improved Swin Transformer model significantly improves the accuracy and efficiency of cotton pest detection compared with other classification models, and can be deployed on edge devices such as utilize unmanned aerial vehicles (UAVs), thus providing an important technological support and theoretical basis for cotton pest control and precision drug application.

show abstract

Population Dynamics of Sucking Pests in Dual Season Cotton Ecosystem and Its Correlation with Weather Factors

Cited by 2 publications

References 4 publications

Study on the Incidence of Sucking Pests and Pink Bollworm in Cotton

Study on the Incidence of Sucking Pests and Pink Bollworm in Cotton

Residual swin transformer for classifying the types of cotton pests in complex background

Contact Info

Product

Resources

About