Oxalic acid was evaluated as a treatment for reducing populations of naturally occurring microorganisms on raw chicken. Raw chicken breasts were dipped in solutions of oxalic acid (0, 0.5, 1.0, 1.5, and 2.0%, wt/vol) for 10, 20, and 30 min, individually packed in oxygen-permeable polyethylene bags, and stored at 4 degrees C. Total plate counts of aerobic bacteria and populations of Pseudomonas spp. and Enterobacteriaceae on breasts were determined before treatment and after storage for 1, 3, 7, 10, and 14 days. The pH and Hunter L, a, and b values of the breast surface were measured. Total plate counts were ca. 1.5 and 4.0 log CFU/g higher on untreated chicken breasts after storage for 7 and 14 days, respectively, than on breasts treated with 0.5% oxalic acid, regardless of dip time. Differences in counts on chicken breasts treated with water and 1.0 to 2.0% of oxalic acid were greater. Populations of Pseudomonas spp. on chicken breasts treated with 0.5 to 2.0% oxalic acid and stored at 4 degrees C for 1 day were less than 2 log CFU/g (detection limit), compared with 5.14 log CFU/g on untreated breasts. Pseudomonas grew on chicken breasts treated with 0.5% oxalic acid to reach counts not exceeding 3.88 log CFU/g after storage for 14 days. Counts on untreated chicken exceeded 8.83 log CFU/g at 14 days. Treatment with oxalic acid caused similar reductions in Enterobacteriaceae counts. Kocuria rhizophila was the predominant bacterium isolated from treated chicken. Other common bacteria included Escherichia coli and Empedobacter brevis. Treatment with oxalic acid caused a slight darkening in color (decreased Hunter L value), retention of redness (increased Hunter a value), and increase in yellowness (increased Hunter b value). Oxalic acid has potential for use as a sanitizer to reduce populations of spoilage microorganisms naturally occurring on raw chicken, thereby extending chicken shelf life.
Matched MeSH terms: Enterobacteriaceae/growth & development
The present study deals with the assessment of Langat River water quality with some chemometrics approaches such as cluster and discriminant analysis coupled with an artificial neural network (ANN). The data used in this study were collected from seven monitoring stations under the river water quality monitoring program by the Department of Environment (DOE) from 1995 to 2002. Twenty three physico-chemical parameters were involved in this analysis. Cluster analysis successfully clustered the Langat River into three major clusters, namely high, moderate and less pollution regions. Discriminant analysis identified seven of the most significant parameters which contribute to the high variation of Langat River water quality, namely dissolved oxygen, biological oxygen demand, pH, ammoniacal nitrogen, chlorine, E. coli, and coliform. Discriminant analysis also plays an important role as an input selection parameter for an ANN of spatial prediction (pollution regions). The ANN showed better prediction performance in discriminating the regional area with an excellent percentage of correct classification compared to discriminant analysis. Multivariate analysis, coupled with ANN, is proposed, which could help in decision making and problem solving in the local environment.
Matched MeSH terms: Enterobacteriaceae/growth & development
The antibiotic, trimethoprim-sulfamethoxazole (TMP-SMX), is generally used for prophylaxis in HIV individuals to protect them from Pneumocystis jiroveci infection. Long-term use of TMP-SMX develops drug resistance among bacteria in HIV patients. The study was aimed to detect the TMP-SMX resistance genes among gram-negative bacteria from HIV patients. TMP-SMX-resistant isolates were detected by the Kirby-Bauer disc diffusion method. While TMP resistance genes such as dfrA1, dfrA5, dfrA7, and dfrA17 and SMX resistance genes such as sul1 and sul2 were detected by multiplex PCR, class 1 and class 2 integrons were detected by standard monoplex PCR. Of the 151 TMP-SMX-resistant bacterial isolates, 3 were positive for sul1 alone, 48 for sul2 alone, 11 for dfrA7 alone, 21 for sul1 and sul2, 1 for sul1 and dfrA7, 23 for sul2 and dfrA7, 2 for sul2 and dfrA5, 41 for sul1, sul2, and dfrA7, and 1 for sul2, dfrA5, and dfrA7. Of 60 TMP-SMX-resistant isolates positive for integrons, 44 had class 1 and 16 had class 2 integrons. It was found that the prevalence of sul genes (n = 202; p
Matched MeSH terms: Enterobacteriaceae/growth & development