Modelling response patterns of physico-chemical indicators during high-rate composting of green waste for suppression ofPythium ultimum

Abstract

High-rate composting studies on green waste, i.e. banana leaves (BL) and lawn clippings (LC), were conducted in 0.25-m3 rotary barrel composters to evaluate and model changes in key physico-chemical parameters during composting. Time to compost maturity and antagonistic effects and relationships of composts against Pythium ultimum were also investigated. Higher temperatures were achieved in LC compost (LCC), which did not translate to higher total organic carbon (TOC) loss but resulted in lower carbon to nitrogen ratio (C:N) and a more mature compost. With the exception of electrical conductivity (EC), net decreases were observed in pH, TOC and C:N across compost types. Total Kjeldahl nitrogen (TKN) showed a net increase in LCC and a net decrease in BLC. With the exception of TOC and pH, the results showed that compost type and time had a significant effect on the respective TKN, EC and C:N models. Compost temperature and TOC were best described by the critical exponential and rectangular hyperbola functions, respectively. Whereas TKN, C:N and pH were described using double Fourier functions and EC using Fourier functions. Composts achieved maturity within 19 days and significantly inhibited the growth of P. ultimum. Bacterial population was positively related to growth inhibition (GI) across compost types, whereas total microbial population had a positive relationship with GI in LCC. Evidence suggests that multiple groups of microorganisms contributed to GI through antibiosis and competition for resources. Composts were determined to be suitable for use as components of plant growth substrates based on compost maturity indices.

A Review of Composting Process Models of Organic Solid Waste with a Focus on the Fates of C, N, P, and K

“…The composting process can be modeled based on one variable (single regression) model or multiple variables (multiple linear regression (MLR)) model. St Martin et al used different function models to simulate different parameters of the composting process, leading to the recognition that the composting temperature and OC are best described by the critical exponential function and the rectangular hyperbolic function, respectively [53]. ON, C/N, and pH are best described by double Fourier functions, while electrical conductivity (EC) is best described via Fourier functions.…”

“…For the data-driven model, in addition to the conventional sensitivity analysis (n = 7), there is the adopting analysis of variance (ANOVA), which can also be used to achieve the purpose of sensitivity analysis (n = 3) in terms of selected input variables. For instance, the ANOVA of St Martin et al indicated that composting formula, time and composting formula interacting through time had a significant impact on the variables such as temperature, total organic carbon (TOC), total Kjeldahl nitrogen (TKN), C/N, pH, and EC [53]. Li et al showed that the effect of addition ratio and addition time on nitrogen loss was statically significant at the 95% confidential level through ANOVA [54].…”

“…Others, such as Nash-Sutcliffe efficiency (NSE), a normalized statistic used to determine the relative size of the residual variance compared to the variation of the measured data, is also used to evaluate a model's quality [51,52,70]. St Martin et al adopted a parallel curve analysis to carry out variance accumulation analysis of the effect of compost type and time on physical and chemical parameter models [53].…”

“…data, is also used to evaluate a model's quality [51,52,70]. St Martin et al adopted a pa curve analysis to carry out variance accumulation analysis of the effect of compost and time on physical and chemical parameter models [53].…”