Ankush Rai

Bio: Ankush Rai is an academic researcher from VIT University. The author has contributed to research in topics: Population & Cyber-physical system. The author has an hindex of 7, co-authored 81 publications receiving 167 citations. Previous affiliations of Ankush Rai include Nalsar University of Law & Indian Institute of Technology Guwahati.

Potentiality of Chinese cabbage (Brassica rapa subsp. pekinensis) as a trap crop for diamondback moth (Plutella xylostella) management in cabbage.

Abstract: Laboratory, net house and field experiments were conducted at Varanasi during 2003–07 to study a few biological parameters and ovipositional preference of diamondback moth (Plutella xylostella L.) among 6 crucifers for searching an effective and alternative host other than mustard (Brassica juncea) with potential of being used as trap crop for management of diamondback moth in cabbage (Brassica oleracea var. capitata). Although the larval weight was significantly more in Chinese cabbage, the larval period of diamondback moth was significantly more prolonged on Chinese cabbage (10.44 days) than other cruciferous hosts. In laboratory experiments, both no-choice and free-choice tests consistently showed almost two-fold preference by diamondback moth for oviposition on Chinese cabbage over cabbage. In the net house, under free-choice situation also the egg laying preference on Chinese cabbage was significantly higher (377 eggs/plant) than mustard (148.50 eggs/plant) and cabbage (114.50 eggs/plant). The larval population at two intervals after release (10 and 15 days) of adults among the test crucifers inside the field screen cage also confirmed maximum attractiveness of Chinese cabbage over mustard and cabbage for egg laying and larval survival. Considering these facts and better agronomic feasibility of Chinese cabbage as an ideal alternative to mustard for use as a trap crop in the management of diamondback moth of cabbage.

Attribute Based Level Adaptive Thresholding Algorithm (ablata) For Image Compression And Transmission

Abstract: Image processing plays a vital role in the computer vision because most of the scenarios require object extraction & recognition. But there lies a self-concatenated issue with it because such an algorithm is also supposed to simultaneously solves the problem of image restoration and transmission. In order to achieve this objective we furthered the effective ABLATA algorithm for the same Once the image is denoised and features are extracted then it can be resized to the half of the actual image, compressing it in a mathematical equation that shall help it restore with the half of the data and thus can readily be restored with the half of the actual imagery data to reproduce it, while maintaining the high image quality. The advantage of such a process is the low storage cost and image transmission requires less time than that required by the original one.

Yellow Mite (Polyphagotarsonemus Latus Banks) Menace in Chilli Crop

Abstract: The yellow mite, Polyphagotarsonemus latus Banks is one of the very important arthropod pests causing leaf curl in chilli through out the globe. In chilli, the mite and thrips complex causes on an average yield loss to the tune of 34.14 per cent. However, in extreme cases, the complete failure of the crop is not uncommon. Many conventional insecticides including monocrotophos, thiometon, phosphomidon, methyl-o-demeton, formothion, ethion, cypermethrin, deltarnethrin, clocythrin and more recently imidacloprid have induced resurgence against mite, besides causing residue problems in green chilli. Sources of resistance against mite are less. Promising control by an antibiotic preparation, liuyangmycin derived from Streptomyccs griseolus, entomopathogenic fungi (Hirsutella thonipsonil, Paecilornyces furnosoroseus, Beauveria bassiana), phytoseiid predators (Neoseilus barkeri, Amblyseius ovalis, Neoselulus cucumeris, Amblyseius longispinosus, A. californicus, Amblyseius peregrinus), botanicals like Annona squamosa and vegetable oils as synergist arid chitin inhibitor, buprofezin have shown new hope for ecofriendly management of this pest. Bioecology and management of P. latus, are reviewed with special reference to chilli crop. Areas for future research include the possible emergence of sibling species or feeding strains, better understanding of the reproductive biology, role of info-chemicals, vital antibiosis effect of host plants, mechanism of resistance and quick diagnostic tool for pesticide resistance, and exploration for additional effective bioagents.

An overview of insecticides and acaricides with new chemistries for the management of sucking pests in vegetable crops

Abstract: Vegetable production is facing enormous challenge to meet the future demands of growing population in India. Sucking pests are one of the major threats and cause considerable economic damage to vegetable cultivation. Many of the sucking pests like whitefly, thrips, aphids, mealybugs and mites not only cause damage by direct feeding, most of them act as vector for several plant pathogenic viruses. Coventional insecticides or acaricides are extensively used to control the sucking pests but most of them have failed due to lower efficacy, development of high folds of resistance and resurgence of the pests. Modern insecticides or acaricides with green chemistries having novel biochemical target sites are available to combat the menace of sucking pests in vegetable crops. The new products have more favourable mammalian vs insect selectivity and can be a suitable component of integrated pest management (IPM) and resistance management programmes in vegetable crops. This paper gives an overview of the innovotaive products launched over past one decade and their propsects in future vegetable pest control.

Environment polluting conventional chemical control compared to an environmentally friendly IPM approach for control of diamondback moth, Plutella xylostella (L.), in China: a review

Abstract: The diamondback moth, Plutella xylostella, is recognized as a widely distributed destructive insect pest of Brassica worldwide. The management of this pest is a serious issue, and an estimated annual cost of its management has reached approximately US$4 billion. Despite the fact that chemicals are a serious threat to the environment, lots of chemicals are applied for controlling various insect pests especially P. xylostella. An overreliance on chemical control has not only led to the evolution of resistance to insecticides and to a reduction of natural enemies but also has polluted various components of water, air, and soil ecosystem. In the present scenario, there is a need to implement an environmentally friendly integrated pest management (IPM) approach with new management tactics (microbial control, biological control, cultural control, mating disruption, insecticide rotation strategies, and plant resistance) for an alternative to chemical control. The IPM approach is not only economically beneficial but also reduces the environmental and health risks. The present review synthesizes published information on the insecticide resistance against P. xylostella and emphasizes on adopting an alternative environmentally friendly IPM approach for controlling P. xylostella in China.

Energy consumption prediction using machine learning: A review

Abstract: Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.