Due to its effect on weather and its propensity to cause catastrophic incidents, climate change has garnered considerable global attention. Depending on the area, the effects of climate change may vary. Rainfall is among the most significant meteorological factors associated with climate change. In Malaysia, changes in rainfall distribution pattern have led to many floods and droughts events which lead to La Nina and El Nino where Johor is one of the states in southern part that usually affected. Thus, rainfall trend analysis is important to identify changes in rainfall pattern as it gives an initial overview for future analysis. This research aims to evaluate historical rainfall data of Johor between 1991 and 2020. Normality and homogeneity tests were used to ensure the quality of data followed by Mann-Kendall and Sen's slope analysis to determine rainfall trend as the rainfall data is not normally distributed (p > 0.05). Standardized precipitation anomaly, coefficient of variation, precipitation concentration index and rainfall anomaly index were used to identify rainfall variability and intensity while standard precipitation index was used to evaluate drought severity. The lowest annual rainfall recorded was 1725.07 mm in 2016 and the highest was 2993.19 mm in 2007. Annual rainfall and seasonal rainfall showed a declining trend although it is not statistically significant (p > 0.05). Results reveal that Johor experienced extreme wet and dry years, leading to drought and flood incidents. Major floods arose in 2006, 2007, 2008, 2010 and 2011 while driest years occurred in 1997, 1998 and 2016 which led to El Nino phenomenon. March and April were identified as the driest months among all. Thus, the findings from this study would assist researchers and decision-makers in the development of applicable adaptation and mitigation strategies to reduce climate change impact. It is recommended that more data analysis from more stations should be done in the future research study to obtain a clearer view and more comprehensive results.
The aim of the present study was to examine the prevalence of thermophilic Campylobacter spp. (Campylobacter jejuni and Campylobacter coli) in soil, poultry manure, irrigation water, and freshly harvested vegetables from vegetable farms in Malaysia. C. jejuni was detected in 30.4% and 2.7% of the soil samples, 57.1% and 0% of the manure samples, and 18.8% and 3% of the vegetable samples from farm A and farm B, respectively, when using the MPNPCR method. Campylobacter spp. was not found in any of the irrigation water samples tested. Therefore, the present results indicate that the aged manure used by farm A was more contaminated than the composted manure used by farm B. Mostly, the leafy and root vegetables were contaminated. C. coli was not detected in any of the samples tested in the current study. Both farms tested in this study were found to be contaminated by campylobacters, thereby posing a potential risk for raw vegetable consumption in Malaysia. The present results also provide baseline data on Campylobacter contamination at the farm level.
Accurate identification and separation of non-classical Bordetella species is very difficult. These species have been implicated in animal infections. B. hinzii, a non-classical Bordetella, has been isolated from mice in experimental facilities recently. We isolated and characterized one non-classical Bordetella isolate from the trachea and lung of an ICR mouse. Isolate BH370 was initially identified as B. hinzii by 16S ribosomal DNA and ompA sequencing. Additionally, isolate BH370 also displayed antimicrobial sensitivity profiles similar to B. hinzii. However, analyses of nrdA sequences determined its identity as Bordetella genogroup 16. The isolation of BH370 from a healthy mouse suggests the possibility of it being a commensal. The nrdA gene was demonstrated to possess greater phylogenetic resolution as compared with 16S ribosomal DNA and ompA for the discrimination of non-classical Bordetella species.