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SPIN: A Web-Based Application For Exploring Stored-Product Insects

SPIN is a web-based application that collects location-based data on the resistance of stored-product insects to pesticides over time, as well as other environmental factors that influence insect infestations. It uses a machine learning algorithm to generate predictive models for insect infestations based on historical data. The goal is to help reduce pesticide use and encourage more environmentally friendly pest control approaches.

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55 views2 pages

SPIN: A Web-Based Application For Exploring Stored-Product Insects

SPIN is a web-based application that collects location-based data on the resistance of stored-product insects to pesticides over time, as well as other environmental factors that influence insect infestations. It uses a machine learning algorithm to generate predictive models for insect infestations based on historical data. The goal is to help reduce pesticide use and encourage more environmentally friendly pest control approaches.

Uploaded by

The Futura Labs
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOCX, PDF, TXT or read online on Scribd
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SPIN: A Web-Based Application for Exploring Stored-

Product Insects

Abstract
Due to the problems of pests in post-harvest storage, the storage owner usually
copes with this problem by using pesticides. However, those pests can develop
resistance against chemicals in pesticides. As the pests improve resistant level to
pesticide, the storage owner has to use higher dose of chemicals. This might raise
the environmental and consumer safety problems. With these issues, we propose
a web-based application, namely SPIN to collect location-based resistance data of
stored-product insects and other factors (e.g., temperature, relative humidity,
etc.) which might effect to the spread of the insects. Also, we use a machine
learning algorithm, namely, decision tree for classification, to generate a
prediction model for the spread of the insects based on the historical data. With
SPIN, the outputs can be used in making plans to decrease the use of pesticide.
This could also encourage the search for alternative pest control approaches
which are more environmental friendly and much safer for consumers.

Existing system
Currently, the use of insecticide (e.g., Phosphide insecticide) in the stored-product
(e.g., rice, paddy, other whole or cracked grain, etc.) is widespread in order to
prevent the damage in the product caused by pests, especially in the product
storage. In the meanwhile, those insects can build resistance to these insecticides.
Therefore, the storage owner must increase the dosage of these insecticides in
order to get rid of those insects. The authors have shown that the resistance
trend to insecticides of pests is increasing every year. However, the intense use of
insecticide without care can cause serious problems for both environment and
consumers.
Proposed system
SPIN is a web application for exploring stored-product insects. SPIN aims at
providing efficient information to support researchers in improving the research
work about the stored-product insects. SPIN can collect and present geolocation-
based data of existence and resistance level to the insecticides of stored-product
insects and other factors. Also, SPIN provides a prediction function to forecast the
existence of the insects by using a Decision Tree classifier. The results have shown
that the accuracy of the predictive model is relatively high with 81.2808%.

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