Eight insecticidal crystal proteins of Bacillus thuringiensis, CrylAa, CrylAb, CrylAc, CrylB, Cry2Aa, CrylC, CrylDa and Cry 1Ea were assessed for toxicity against 1 st instar larvae of rice leaf folder, Cnaphalocrocis...Eight insecticidal crystal proteins of Bacillus thuringiensis, CrylAa, CrylAb, CrylAc, CrylB, Cry2Aa, CrylC, CrylDa and Cry 1Ea were assessed for toxicity against 1 st instar larvae of rice leaf folder, Cnaphalocrocis medinalis (Guenee) at 48 HAT and 72 HAT. Bioassay results depicted CrylAa was the most toxic (LCso 2.35 ppm) followed by CrylBa (LCso 8,50 ppm) and CrylAb (LCso 8.73 ppm) at 48 HAT, whereas, at 72 HAT CrylAb proved to be highly toxic (LC50 0.50 ppm) followed by CrylAa (LCso 4.07 ppm), CrylAc (LCso 4,84 ppm) and CrylBa (LCso 6.42 ppm). Toxins Cry2Aa, CrylCa, CrylDa and CrylEa did not resulted in any mortality at 48 HAT and 72 HAT, respectively. Baseline estimates for CrylAb against 1st instar larvae of C. medinalis sampled from seven geographical locations revealed variation in LC50's from 0.37 ppm to LC50 16.25 ppm at 48 HAT and LC50 0.50 ppm to LC50 6.49 ppm 72 HAT, respectively with relative resistance ratios of 44-fold and 13-fold at 48 HAT and 72 HAT over the susceptible population.展开更多
In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive ...In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive pests of paddy crops,which are causing severe yield loss.Manual identification of insect pests in the crop is time-consuming,tedious,and ineffective.This paper focuses on a light trap based four-layer deep neural network with search and rescue optimization(DNN-SAR)method to identify leaf folders and yellow stemborers.Light traps are designed to lure the insects in the paddy field and the images of trapped insects are analyzed using the proposed detection method.In the DNN-SAR,images are contrastenhanced using deer hunting algorithm,impulse noise is removed with fast average group filter,and segmented using social ski-driver optimization.The search and rescue optimization algorithm is used for the selection of optimal weights in the deep neural network,which has improved the convergence rate,lowered the complexity of learning,and improved the accuracy of detection.The proposed method outperformed the existing methods and achieved 98.29%pest detection accuracy.展开更多
采用感虫水稻品种TN1,设置3种施硅水平,即高硅(0.32 g Si/kg土壤)、低硅(0.16 g Si/kg土壤)和不施硅对照(0 g Si/kg土壤),研究了施用硅肥对稻纵卷叶螟产卵和取食选择性的影响。结果表明:稻纵卷叶螟幼虫对硅处理水稻叶片的取食选择性和...采用感虫水稻品种TN1,设置3种施硅水平,即高硅(0.32 g Si/kg土壤)、低硅(0.16 g Si/kg土壤)和不施硅对照(0 g Si/kg土壤),研究了施用硅肥对稻纵卷叶螟产卵和取食选择性的影响。结果表明:稻纵卷叶螟幼虫对硅处理水稻叶片的取食选择性和成虫在硅处理水稻上的着卵量、着卵率均显著低于对照水稻。高硅处理水稻叶片中的硅含量、可溶性糖含量和碳氮比高于对照,而氮含量低于对照;低硅处理水稻叶片的碳氮比高于对照、氮含量低于对照。同时,硅处理显著降低水稻的卷叶株率和卷叶率。这些结果表明,施硅能增强稻纵卷叶螟对水稻的不选择性,从而增强水稻对稻纵卷叶螟的抗性。展开更多
文摘Eight insecticidal crystal proteins of Bacillus thuringiensis, CrylAa, CrylAb, CrylAc, CrylB, Cry2Aa, CrylC, CrylDa and Cry 1Ea were assessed for toxicity against 1 st instar larvae of rice leaf folder, Cnaphalocrocis medinalis (Guenee) at 48 HAT and 72 HAT. Bioassay results depicted CrylAa was the most toxic (LCso 2.35 ppm) followed by CrylBa (LCso 8,50 ppm) and CrylAb (LCso 8.73 ppm) at 48 HAT, whereas, at 72 HAT CrylAb proved to be highly toxic (LC50 0.50 ppm) followed by CrylAa (LCso 4.07 ppm), CrylAc (LCso 4,84 ppm) and CrylBa (LCso 6.42 ppm). Toxins Cry2Aa, CrylCa, CrylDa and CrylEa did not resulted in any mortality at 48 HAT and 72 HAT, respectively. Baseline estimates for CrylAb against 1st instar larvae of C. medinalis sampled from seven geographical locations revealed variation in LC50's from 0.37 ppm to LC50 16.25 ppm at 48 HAT and LC50 0.50 ppm to LC50 6.49 ppm 72 HAT, respectively with relative resistance ratios of 44-fold and 13-fold at 48 HAT and 72 HAT over the susceptible population.
文摘In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive pests of paddy crops,which are causing severe yield loss.Manual identification of insect pests in the crop is time-consuming,tedious,and ineffective.This paper focuses on a light trap based four-layer deep neural network with search and rescue optimization(DNN-SAR)method to identify leaf folders and yellow stemborers.Light traps are designed to lure the insects in the paddy field and the images of trapped insects are analyzed using the proposed detection method.In the DNN-SAR,images are contrastenhanced using deer hunting algorithm,impulse noise is removed with fast average group filter,and segmented using social ski-driver optimization.The search and rescue optimization algorithm is used for the selection of optimal weights in the deep neural network,which has improved the convergence rate,lowered the complexity of learning,and improved the accuracy of detection.The proposed method outperformed the existing methods and achieved 98.29%pest detection accuracy.
文摘采用感虫水稻品种TN1,设置3种施硅水平,即高硅(0.32 g Si/kg土壤)、低硅(0.16 g Si/kg土壤)和不施硅对照(0 g Si/kg土壤),研究了施用硅肥对稻纵卷叶螟产卵和取食选择性的影响。结果表明:稻纵卷叶螟幼虫对硅处理水稻叶片的取食选择性和成虫在硅处理水稻上的着卵量、着卵率均显著低于对照水稻。高硅处理水稻叶片中的硅含量、可溶性糖含量和碳氮比高于对照,而氮含量低于对照;低硅处理水稻叶片的碳氮比高于对照、氮含量低于对照。同时,硅处理显著降低水稻的卷叶株率和卷叶率。这些结果表明,施硅能增强稻纵卷叶螟对水稻的不选择性,从而增强水稻对稻纵卷叶螟的抗性。