A fundamental aspect of predictive microbiology is the shape of the microbial growth curve and many models are used to fit microbial count data, the modified Gompertz and Baranyi equation being two of the most widely used. Rapid, automated methods such as turbidimetry have been widely used to obtain growth parameters, but do not directly give the microbial growth curve. Optical density (OD) data can be used to obtain the specific growth rate and if used in conjunction with the known initial inocula, the maximum population data and knowledge of the microbial number at a predefined OD at a known time then all the information required for the reconstruction of a standard growth curve can be obtained. Using multiple initial inocula the times to detection (TTD) at a given standard OD were obtained from which the specific growth rate was calculated. The modified logistic, modified Gompertz, 3-phase linear, Baranyi and the classical logistic model (with or without lag) were fitted to the TTD data. In all cases the modified logistic and modified Gompertz failed to reproduce the observed linear plots of the log initial inocula against TTD using the known parameters (initial inoculum, MPD and growth rate). The 3 phase linear model (3PLM), Baranyi and classical logistic models fitted the observed data and were able to reproduce elements of the OD incubation-time curves. Using a calibration curve relating OD and microbial numbers, the Baranyi equation was able to reproduce OD data obtained for Listeria monocytogenes at 37 and 30°C as well as data on the effect of pH (range 7.05 to 3.46) at 30°C. The Baranyi model was found to be the most capable primary model of those examined (in the absence of lag it defaults to the classic logistic model). The results suggested that the modified logistic and the modified Gompertz models should not be used as Primary models for TTD data as they cannot reproduce the observed data.
Nitrogen (N) losses are prevalent under South East Asia’s due to high N fertilizer inputs, but low N fertilizer use efficiency. This leaves a large quantity of reactive N at risk of loss to the environment. Biochar has been found to reduce N losses across a variety of soil types, however, there is limited data available for semi-arid climates, particularly at a field-scale. Herein we present an exploration of the biological and chemical enhancement effects observed of a cotton stalk-based biochar on wheat growth and yield under arid field conditions. The biochar was treated with urea-N and biofertilizer (bio-power) in different treatment setups. The six experimental treatments included; (i) a full N dose “recommended for wheat crops in the region” (104 kg N ha−1) as a positive control; (ii) a half N dose (52 kg N ha−1); (iii) a half N dose + biofertilizer (4.94 kg ha−1) as a soil mixture; (iv) a half N dose + biofertilizer as a seed inoculation; (v) a full N dose as broadcast + biochar (5 t ha−1) inoculated with biofertilizer; and (vi) a full N dose loaded on biochar + biofertilizer applied as a soil mixture. The half dose N application or biofertilizer addition as soil mix/seed inoculated/biochar inoculation with biofertilizer caused reduced wheat growth and yield compared to the control (conventional N fertilization). However, co-application of chemically enhanced biochar (loaded with a full N dose) and biofertilizer as soil mixture significantly increased the crop growth rate (CGR) and leaf area index (LAI). A significantly higher crop growth and canopy development led to a higher light interception and radiation use efficiency (RUE) for total dry matter (TDM) and grain yield (11% greater than control) production compared to the control. A greater grain yield, observed for the full N dose loaded on biochar + biofertilizer applied as a soil mixture, is attributed to prolonged N availability as indicated by greater plant and soil N content at harvest and different crop growth stages, respectively. The present study has improved our understanding of how the application of nitrogen loaded biochar and biofertilizer as soil mixtures can synergize to positively affect wheat growth and soil-nitrogen retention under arid environmental conditions.
Artificial soils made from waste materials offer an alternative to imported natural top-soils, notably in large-scale groundworks and reclamation projects. Benefits include diversion of waste from landfill and recycling. Nonetheless, there is limited information on the characteristics needed to support plant growth in the long-term, particularly the existence of a sustainable nitrogen reservoir. Therefore we assessed the efficacy of nitrogen cycling and retention within an artificial soil composed of 25 % sand, 10 % clay, 32.5 % composted bark and 32.5 % composted green waste over 52 weeks. Leachate was analysed for nitrogen species and nitrogen concentrations and two of the soil columns had fertiliser added after 26 and 48 weeks.Results show that nitrate concentrations decreased from 6.73 to 0.36 mg N L -1 after 2 weeks, due to poor retention of this anion in soil, and remained low for 6 months, before increasing up to 5.87 mg N L -1 after week 26, in unfertilised soils. The sharp increase in dissolved nitrate was preceded by a decrease of the ratio of dissolved organic carbon over dissolved organic nitrogen in the soil leachate. This finding indicates that the soil had become carbonlimited, leading to mineralisation of organic nitrogen by soil organisms and excretion of nitrogen.We also found that fertilisation of the soil with nitrogen-rich substrate did not alleviate carbon-limitation and nitrogen-loss was greater in fertilised soils, indicating nitrogensaturation. After the onset of carbon-limitation, the dissolved nitrate concentrations in both the fertilised and unfertilised soils were close to exceeding the European Union threshold of concern for nitrate groundwater and river pollution. Thus while the deployment of artificial soils is a viable option for landscaping projects, loss of nitrogen may be environmentally significant and soil management protocols must take account of both the carbon and nitrogen status of the substrate.
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Time to detection (TTD) measurements using turbidometry allow a straightforward method for the measurement of bacterial growth rates under isothermal conditions. Growth rate measurements were carried out for Listeria monocytogenes at 25, 30 and 37°C and for Pseudomonas aeruginosa over the temperature range 25 to 45°C. The classical three-parameter logistic model was rearranged to provide the theoretical foundation for the observed TTD. A model was subsequently developed for the analysis of TTD data from non-isothermal studies based on the Malthusian approximation of the logistic model. The model was able to predict the TTD for cultures of L. monocytogenes or P. aeruginosa undergoing simple temperature shunts (e.g. 25 to 37°C and vice versa), and for a multiple temperature shunt for L. monocytogenes (25-37-25-37°C and 37-25-37-25°C) over a period of 24h. In no case did a temperature shunt induce a lag.
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