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The South American tomato moth, Phthorimaea absoluta (Meyrick), is one of the key pests of tomato in India. Since its report in 2014, chemical control has been the main means of tackling this pest, both in the open field and protected cultivation. Despite regular insecticidal sprays, many outbreaks were reported from major tomato-growing regions of South India during 2019-2020. A study was conducted to investigate the effect of insecticide resistance on biology, biochemical enzymes, and gene expression in various P. absoluta field populations viz ., Bangalore, Kolar, Madurai, Salem, and Anantapur to commonly used insecticides such as flubendiamide, cyantraniliprole, and indoxacarb. Increased levels of insecticide resistance ratios (RR) were recorded in P. absoluta populations of different locations. A significant increase in cytochrome P450 monooxygenase (CYP/MFO) and esterase levels was noticed in the resistant population compared to susceptible one. Through molecular studies, we identified four new CYP genes viz ., CYP248f (flubendiamide), CYP272c, CYP724c (cyantraniliprole), and CYP648i (indoxacarb). The expression levels of these genes significantly increased as the folds of resistance increased from G1 to G20 (generation), indicating involvement of the identified genes in insecticide resistance development in P. absoluta . In addition, the resistant populations showed decreased fecundity, increased larval development period, and adult longevity, resulting in more crop damage. The information generated in the present study thus helps in understanding the development of insecticide resistance by P. absoluta and suggests the farmers and researchers to use insecticides wisely by adopting insecticide resistance management as a strategy under integrated pest management.

This paper proposes a blend of three techniques to select COVID-19 testing centers. The objective of the paper is to identify a suitable location to establish new COVID-19 testing centers. Establishment of the testing center in the needy locations will be beneficial to both public and government officials. Selection of the wrong location may lead to lose both health and wealth. In this paper, location selection is modelled as a decision-making problem. The paper uses fuzzy analytic hierarchy process (AHP) technique to generate the criteria weights, monkey search algorithm to optimize the weights, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the different locations. To illustrate the applicability of the proposed technique, a state named Tamil Nadu, located in India, is taken for a case study. The proposed structured algorithmic steps were applied for the input data obtained from the government of India website, and the results were analyzed and validated using the government of India website. The ranks assigned by the proposed technique to different locations are in aligning with the number of patients and death rate., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this article., (Copyright © 2022 S. Saroja et al.)