Bacterial Count Case Study

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Total Bacterial Count Table 1 presents the total bacterial count of treatments at different time intervals. There are no significant differences between treatments before EM application, one day, two weeks and three weeks after EM application when analysis of variance (ANOVA) was tested on each time interval. (Appendix C Table C.1; Table C.2; Table C.3; Table C.4) Table 1. Total Bacterial Count of water from DMMMSU-SLUC Wells at different time intervals. Treatment Before EM Application 1 Day After EM Application 2 Weeks After EM Application 3 Weeks After EM Application T1 12,866,667 28,000,000 650,000 10,636,667 T2 11,566,667 25,866,667 14,050,000 866,667 T3 4,966,667 30,000,000 4,000,000 1,903,333 It shows in table 1 that before EM application,…show more content…
However, differences were not significant to each other. The increased of bacterial count may be attributed to the application of EM. EM contains different types of bacteria and these bacteria were added to the bacteria that were already in the water samples before the application of EM. Two weeks after EM application, treatment 2 becomes the highest in bacterial count followed by treatment 3 and lastly treatment 1. But after three weeks after EM application, treatment 1 contains the highest bacterial count followed by treatment 3 and treatment 2, respectively. In addition, it can be seen in the table 1 that treatment 1 increases in its bacterial count one day after EM application due to the addition of bacteria from the EM, however, bacterial count of treatment 1 decreases two weeks after EM application. The bacterial count increases again three weeks after EM application. The effectiveness of EM to decrease bacterial count can be noted up to two weeks after EM application. Increase of bacterial count were registered one day after EM application in treatment 2 but the bacterial count decreases until three weeks after EM application. The EM capability to decrease bacterial count is until three

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