Temporal changes in the abundance of Musca domestica Linn (Diptera: Muscidae) in poultry farms in Penang, Malaysia.

Trop Biomed

Vector Control Research Unit, School of Biological Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.

Published: August 2009

Changes in the abundance of the house fly, Musca domestica, was studied for a period of one year in two poultry farms in Penang, Malaysia: one in Balik Pulau, located in Penang island, and the other in Juru, located on mainland Penang. The sampling of house flies were carried out from March 2007 to April 2008 using the Scudder grill, and the correlation with meteorological conditions particularly rainfall, relative humidity and temperature were observed. In Balik Pulau, the fly abundance showed an inverse relationship to relative humidity and total rainfall. However, no significant correlations were found between the abundance of flies and the above mentioned climatic factors. In contrast, the occurrence of flies in Juru showed strong correlation indices with relative humidity (r=0.803, p<0.05) and total rainfall (r=0.731, p<0.05). Temperature had no significant effect on the abundance of flies in both poultry farms due to imperceptible changes in monthly temperature.

Download full-text PDF

Source

Publication Analysis

Top Keywords

relative humidity
12
changes abundance
8
musca domestica
8
poultry farms
8
farms penang
8
penang malaysia
8
balik pulau
8
temporal changes
4
abundance
4
abundance musca
4

Similar Publications

Background: Japanese encephalitis (JE) is a zoonotic parasitic disease caused by the Japanese encephalitis virus (JEV), and may cause fever, nausea, headache, or meningitis. It is currently unclear whether the epidemiological characteristics of the JEV have been affected by the extreme climatic conditions that have been observed in recent years.

Objective: This study aimed to examine the epidemiological characteristics, trends, and potential risk factors of JE in Taiwan from 2008 to 2020.

View Article and Find Full Text PDF

Background: While previous reports characterised global and regional variations in RSV seasonality, less is known about local variations in RSV seasonal characteristics. This study aimed to understand the local-level variations in RSV seasonality and to explore the role of geographical, meteorological, and socio-demographic factors in explaining these variations.

Methods: We conducted a systematic literature review to identify published studies reporting data on local-level RSV season onset, offset, or duration for at least two local sites.

View Article and Find Full Text PDF

Precession modulates the poleward expansion of atmospheric circulation to the Arctic Ocean.

Nat Commun

January 2025

Centre for Marine Magnetism (CM2, Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China.

Under sustained global warming, Arctic climate is projected to become more responsive to changes in North Pacific meridional heat transport as a result of teleconnections between low and high latitudes, but the underlying mechanisms remain poorly understood. Here, we reconstruct subarctic humidity changes over the past 400 kyr to investigate the role of low-to-high latitude interactions in regulating Arctic hydroclimate. Our reconstruction is based on precipitation-driven sediment input variations in the Subarctic North Pacific (SANP), which reveal a strong precessional cycle in subarctic humidity under the relatively low eccentricity variations that dominated the past four glacial-interglacial cycles.

View Article and Find Full Text PDF

Pathogen contamination and harborage in low-moisture food (LMF) processing environments have resulted in outbreaks and recalls, but researchers are limited in their abilities to investigate solutions. Methods used in most laboratory studies do not accurately reflect the route of contamination or harborage of pathogens in LMF environments, which complicates studying of sanitation methods. Inoculation methods were compared to establish low-moisture food persistent bacterial populations (LMF PBPs) that realistically reflect populations found in LMF environments.

View Article and Find Full Text PDF

Groundwater plays a key role in the water cycle and is used to meet industrial, agricultural, and domestic water demands. High-resolution modeling of groundwater storage is often challenging due to the limitations of observation techniques and mathematical methods. In this study, two machine learning (ML) algorithms, namely random forest (RF) and artificial neural networks (ANNs), were employed to estimate groundwater level anomaly (GWLA) and groundwater storage anomaly (GWSA) with a 0.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!