Molecular Characterization and Transmission Study of the Begomovirus on Hollyhock Plant Causing Leaf Curl Disease for the First Time in Province Punjab, Pakistan

I. Background: Hollyhock (Alcea rosea) is an ornamental plant belonging to the Malvaceae family and has a remarkable aesthetic and medicinal value. Previously in Pakistan, the hollyhock plant was not found to be infected by begomovirus and the plant first time showed the symptoms of typical leaf curling, puckering as well as thickened veins. II. Methods and Results: During the year 2018, symptomatic samples of the hollyhock plants were collected that exhibited characteristic typical leaf curling, puckering as well as thickened veins. DNA was extracted from the samples and the PCR technique was optimized for the detection of begomovirus followed by sequencing. The samples were detected to be infected with begomovirus by using Av/Ac core, Begomo 01/02, and CLCV 01/02 primer showed positive results with 579bp, 2.8kb, and 1.1kb nucleotide respectively. The betasatellite was amplified by using beta01/02 and CLCuMuBF11/R33 showed positive results with 1400bp and 481bp respectively. Sequencing results showed that diseased hollyhock plants were associated with Cotton leaf curl Multan virus-Rajasthan strain along with Cotton leaf curl Multan betasatellite. III. Conclusion: Hollyhock plants infected by begomovirus has been reported for the first time as a possible source of virus inoculum from Pakistan.

Efficacy of the entomopathogenic nematode isolate Heterorhabditis taysearae to control the cotton leafworm, Spodoptera littoralis (Boisd.) (Lepidoptera: Noctuidae)

Background Entomopathogenic nematodes (EPNs) are promising alternatives since they have many characteristics as a biological control agent against insect pests. Results Among indigenous EPN isolated, adapted to local environmental conditions by employing the Galleria baiting strategy, only one sample was positive for the presence of EPNs. The new isolate was identified at the species level using DNA sequencing of the internal transcribed spacer region and the Basic Local Alignment Search Tool search of GenBank showed that the isolate had a high similarity (99%) with that sequence available for Heterorhabditis taysearae. The pathogenicity of the EPN isolate was tested against the cotton leaf worm, Spodoptera littoralis (Boisd.) (Lepidoptera: Noctuidae), using different concentrations (60, 90, 120 and 150 IJs/larvae). Data showed that 150 IJs/larvae caused 100% mortality rate, followed by 120 IJs/larvae (90%), while 60 IJs/larvae showed the lowest rate (60%) after 72 h. Conclusions The present study indicated that the native isolate of EPN could be recommended against S. littoralis as an efficient tool in its control programs.

Synthesis and characterization of some new tebufenozide analogues and study their toxicological effect against Spodoptera littoralis (Boisd.)

Many of mimic analogues synthesized before depending on the change in the structure of aromatic rings. In this work, the carbonyl group in the structure of compounds 1-4 converted to thiocarbonyl group, and then studying the toxicological activity due to chemical change in the active center of mimic analogues was performed for compounds N-tert-butyl-2,4-dichloro-N'-(2,4-dichlorobenzoyl)benzohydrazide (2) and N-tert-butyl-2,4-dichloro-N'-[(2,4-dichlorophenyl)carbonothioyl]benzenecarbothiohydrazide (6). The toxicological study was done by using 2nd and 4th instar larvae of the cotton leaf worm, Spodoptera littoralis (Boisd.). Five concentration levels (600, 300, 150, 75 and 37.5 ppm) of compounds (2) and (6) were applied on the fresh plant food to the newly grown (2nd and 4th) instar larvae.

Classification of Cotton Leaf Diseases Using AlexNet and Machine Learning Models

Computer vision has been demonstrated as state-of-the-art technology in precision agriculture in recent years. In this paper, an Alex net model was implemented to identify and classify cotton leaf diseases. Cotton Dataset consists of 2275 images, in which 1952 images were used for training and 324 images were used for validation. Five convolutional layers of the AlexNet deep learning technique is applied for features extraction from raw data. They were remaining three fully connected layers of AlexNet and machine learning classification algorithms such as Ada Boost Classifier (ABC), Decision Tree Classifier (DTC), Gradient Boosting Classifier (GBC). K Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest Classifier (RFC), and Support Vector Classifier (SVC) are used for classification. Three fully connected layers of Alex Net provided the best performance model with a 94.92% F1_score at the training time of about 51min.

Roles of two distinct alphasatellites modulating geminivirus pathogenesis

Background Alphasatellites are small coding DNA satellites frequently associated with a begomovirus/betasatellite complex, where they are known to modulate virulence and symptom development. Two distinct alphasatellites, namely, Cotton leaf curl Multan alphasatellite (CLCuMuA), and Gossypium darwinii symptomless alphasatellite (GDarSLA) associated with Cotton leaf curl Multan virus-India (CLCuMuV-IN) and Ludwigia leaf distortion betasatellite (LuLDB) were found to be associated with yellow mosaic disease of hollyhock (Alcea rosea) plants. In this study, we show that alphasatellites CLCuMuA and GDarSLA attenuate and delay symptom development in Nicotiana benthamiana. The presence of either alphasatellites reduce the accumulation of the helper virus CLCuMuV-IN. However, the levels of the associated betasatellite, LuLDB, remains unchanged. These results suggest that the alphasatellites could contribute to the host defence and understanding their role in disease development is important for developing resistance strategies. Methods Tandem repeat constructs of two distinct alphasatellites, namely, CLCuMuA and GDarSLA associated with CLCuMuV-IN and LuLDB were generated. N. benthamiana plants were co-agroinoculated with CLCuMuV and its associated alphasatellites and betasatellite molecules and samples were collected at 7, 14 and 21 days post inoculation (dpi). The viral DNA molecules were quantified in N. benthamiana plants by qPCR. The sequences were analysed using the MEGA-X tool, and a phylogenetic tree was generated. Genetic diversity among the CLCuMuA and GDarSLA was analysed using the DnaSP tool. Results We observed a reduction in symptom severity and accumulation of helper virus in the presence of two alphasatellites isolated from naturally infected hollyhock plants. However, no reduction in the accumulation of betasatellite was observed. The phylogenetic and genetic variability study revealed the evolutionary dynamics of these distinct alphasatellites , which could explain the role of hollyhock-associated alphasatellites in plants. Conclusions This study provides evidence that alphasatellites have a role in symptom modulation and suppress helper virus replication without any discernible effect on the replication of the associated betasatellite.

Isolation and identification of microbiota from Egyptian common insect pests invading economically important crops

Insects bodies contain multiple distinctive microbial colonies which play key role in the metabolism, development and health of an insect. In the current study bacterial and fungal microbiota were isolated from larval feces and adult wings of two major insect pests in Egypt, the Cotton leaf worm Spodoptera littoralis and the black cutworm Agrotis ipsilon. Isolated pathogens were identified and characterized according to the scientific described methods in such cases. Two different genera of bacteria (Bacillus & Serratia) were isolated from larval feces of both insects while isolated fungus were Paecilomyces variotii and Absidia corymbifera from the feces of A. ipsilon larvae, while Rhozopus stolonifer and Penicillium chrysogenum were isolated from adults wings of the same insect. The fungus Aspergillus flavus, Aspergillus niger and Mucor circinilloides were isolated from feces of S. littoralis larvae. Numerous species of bacteria and fungi had been documented as a bio-agent against many insect pests, and most of them exhibited disruption in life-cycle of different species of Lepidopterous pests. The obtained data sheds light on microbial colonies associated with two major insect pests, however further studies are required to involve the isolated microbiota in the biological control programs of insect pests.