scholarly journals Lepidopteron pest control strategy through RNAi Technology using Insect own Enzymes

2017 ◽  
Keyword(s):  
Pest Control ◽  
Control Strategy ◽  
Rnai Technology

scholarly journals Models to Assess the Effects of Nonsmooth Control and Stochastic Perturbation on Pest Control: A Pest-Natural-Enemy Ecosystem

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Xuewen Tan ◽  
Wenjie Qin ◽  
Guangyao Tang ◽  
Changcheng Xiang ◽  
Xinzhi Liu
Keyword(s):  
Numerical Simulations ◽  
Pest Control ◽  
Control Strategy ◽  
Stochastic Perturbation ◽  
Fixed Time ◽  
Control Measures ◽  
Optimal Control Strategy ◽  
Threshold Control ◽  
The Impact ◽  
Ipm Strategy

This paper investigates the impact of the threshold control strategy and environmental randomness on pest control. Firstly, a fixed-time impulsive stochastic ecosystem with IPM strategy is proposed, where the local and global existence of positive solution and the boundedness of expectation are discussed in detail. Moreover a sufficient condition for the extinction of the pest population with probability-1 is given. Then, a state-dependent stochastic ecosystem with IPM strategy is proposed. By employing the numerical simulations, the effects of ambient noise intensity on pest-outbreak are discussed. The result shows that there is a close relationship among the frequency of pest-outbreak, ET, the environmental perturbation intensity, and control measures. This study helps us to understand the impact of random factors on pest-outbreak frequency by theoretical derivations and numerical simulations; the results have directive significance in the design of an optimal control strategy for the department of ecological agriculture.

scholarly journals Targeting an antimicrobial effector function in insect immunity as a pest control strategy

2009 ◽  
Vol 106 (31) ◽  
pp. 12652-12657 ◽  
Author(s):  
M. S. Bulmer ◽  
I. Bachelet ◽  
R. Raman ◽  
R. B. Rosengaus ◽  
R. Sasisekharan
Keyword(s):  
Pest Control ◽  
Control Strategy ◽  
Effector Function ◽  
Insect Immunity

MANAGEMENT OF COMPLEX SYSTEMS: MODELING THE BIOLOGICAL PEST CONTROL

2008 ◽  
Vol 03 (01n02) ◽  
pp. 241-256 ◽  
Author(s):  
MARAT RAFIKOV ◽  
JOSÉ MANOEL BALTHAZAR ◽  
HUBERTUS F. VON BREMEN
Keyword(s):  
Mathematical Modeling ◽  
Complex System ◽  
Mathematical Models ◽  
Pest Control ◽  
Natural Enemies ◽  
Dynamic Systems ◽  
Control Strategy ◽  
Cropping System ◽  
Systems Modeling ◽  
Biological Pest Control

The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction.

scholarly journals GFAT and PFK genes show contrasting regulation of chitin metabolism in Nilaparvata lugens

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cai-Di Xu ◽  
Yong-Kang Liu ◽  
Ling-Yu Qiu ◽  
Sha-Sha Wang ◽  
Bi-Ying Pan ◽  
...  
Keyword(s):  
Rna Interference ◽  
Pest Control ◽  
Mortality Rates ◽  
Nilaparvata Lugens ◽  
Chitin Synthesis ◽  
Chitin Synthesis Inhibitors ◽  
Expression Of Genes ◽  
Rnai Technology ◽  
Wing Bud

AbstractGlutamine:fructose-6-phosphate aminotransferase (GFAT) and phosphofructokinase (PFK) are enzymes related to chitin metabolism. RNA interference (RNAi) technology was used to explore the role of these two enzyme genes in chitin metabolism. In this study, we found that GFAT and PFK were highly expressed in the wing bud of Nilaparvata lugens and were increased significantly during molting. RNAi of GFAT and PFK both caused severe malformation rates and mortality rates in N. lugens. GFAT inhibition also downregulated GFAT, GNPNA, PGM1, PGM2, UAP, CHS1, CHS1a, CHS1b, Cht1-10, and ENGase. PFK inhibition significantly downregulated GFAT; upregulated GNPNA, PGM2, UAP, Cht2-4, Cht6-7 at 48 h and then downregulated them at 72 h; upregulated Cht5, Cht8, Cht10, and ENGase; downregulated Cht9 at 48 h and then upregulated it at 72 h; and upregulated CHS1, CHS1a, and CHS1b. In conclusion, GFAT and PFK regulated chitin degradation and remodeling by regulating the expression of genes related to the chitin metabolism and exert opposite effects on these genes. These results may be beneficial to develop new chitin synthesis inhibitors for pest control.

Dynamics and Bifurcation Analysis of a Filippov Predator–Prey Ecosystem in a Seasonally Fluctuating Environment

2019 ◽  
Vol 29 (02) ◽  
pp. 1950020 ◽  
Author(s):  
Wenjie Qin ◽  
Xuewen Tan ◽  
Xiaotao Shi ◽  
Junhua Chen ◽  
Xinzhi Liu
Keyword(s):  
Pest Control ◽  
Control Strategy ◽  
Sliding Mode ◽  
Dynamical Behavior ◽  
Period Doubling ◽  
Periodic Forcing ◽  
Optimal Control Strategy ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Fluctuating Environment

Mathematical models can assist to design and understand control strategies for limited resources in Integrated Pest Management (IPM). This paper studies the dynamical behavior of a Filippov predator–prey model with periodic forcing. Firstly, bifurcation analyses are carried out to show that the Filippov predator–prey ecosystem may have very complex dynamics, i.e. the system may have periodic, quasi-periodic, chaotic solutions, as well as period doubling bifurcations. Meanwhile, the model is analyzed theoretically and numerically to understand how resource limitation and periodic forcing affect pest population outbreaks, the intersection between the initial densities (pest and natural enemy populations) and pest control has been discussed. Furthermore, the sliding surface, sliding mode dynamics, the existence and stability of sliding periodic solution of the proposed model and its application in IPM strategy are investigated. Our results show that several hidden factors can adversely affect our control strategy in limited resource and fluctuating environment. Thus, choosing a proper threshold value ET may play a decisive role in pest control, which confirms that IPM is the optimal control strategy.

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