## 4 Discussion
Furthermore, within the Phylum _Proteobacteria_, _Campylobacter_ species (class _Epsilon-proteobacteria_; family _Campylobacteriaceae_) had a prolonged survival time as opposed to the other three bacteria (class _Gammaproteobacteria_; family _Enterobacteriaceae_) from the same phylum. This may suggest that _Campylobacter_ species were exposed to a lesser degree of competition regarding nutrients as they utilise amino acids, vitamins, and citric acid cycle intermediates that are not consumed by other bacteria, whereas _E. coli_, _Salmonella_ sp., and _Y. enterocolitica_ faced stiff competition from other nonmethanogenic bacteria (indigenous microflora) for carbohydrates [46]. In addition, _Campylobacter_ species are able to acquire several transition metals necessary for metabolic activities via diverse mechanisms [47]. It is well known that the inactivation of bacteria is temperature-dependent; likewise, the microbial activities conducted by anaerobic microbes during anaerobic digestion are temperature-dependent. This is so because enzymes secreted by the anaerobes are responsible for the degradation process, especially at the hydrolysis stage [25]. Accordingly, [PERSON] et al. [18] reported a higher viable cell reduction caused by anaerobic digestion occurring at thermophilic rather than mesophilic conditions. [PERSON] et al. [46] reported that the temperature may cause a direct impact on the pathogen or enhance the effects of other chemicals such as volatile fatty acids toxicity and ammonia, although not investigatedin this study. Nevertheless, in the present study, the inactivation of the aforementioned bacterial pathogens occurred in the psychrophilic temperature range (lower temperatures), suggesting that factors other than temperature, including pH, volatile fatty acids, and treatment retention time, could play a crucial role added to the progress of the anaerobic digestion process [18; 23]. In a nutshell, the inactivation of pathogens via psychrophilic anaerobic digestion cannot be categorically ascribed to a specific reason but might probably be due to a combination of factors. However, the contribution to pathogen reduction by specific parameters during anaerobic digestion has been deliberated elsewhere [18; 46]. Following the findings of [PERSON] et al. [46] which noted the various factors influencing the inactivation of bacteria during anaerobic digestion, we decided to develop multiple linear regression models with the number of days, average daily temperature, and pH as predictor variables to shed light on the impact of these variables on the response (log bacterial counts). Mathematical modelling is a process whereby real-life situations are simulated with mathematical equations to describe relationships between predictors and responses, as well as to forecast the future behaviour of the parameters involved in the process. From Table 2, A0 denotes the forcing constant, which caters for the contribution from other factors/parameters, though not investigated and incorporated in the development of the mathematical models but would equally have affected the bacterial count. From mathematical induction, a negative scaling constant of the predictor variable indicates an inverse relationship with the response, while a positive scaling constant of the variable demonstrates a direct relationship with the response. By inference to Table 2, overall, the predictor variable, number of days, was inversely related to log bacterial counts for the models built for all the bacterial species except for _L. monocytogenes_, which indicated that an increase in the number of days could cause a decrease in the log bacterial counts. This finding is congruent with the work of [PERSON] et al. [48] who reported the complete inactivation of _E. coli_ in slurry manure stored in tanks operated under lagoon conditions at 14 weeks while _Listeria_ survived until the end of the experiment (29 weeks), although in relatively low levels.