Study on soft sensor modeling method for sign of contaminated fermentation broth in Chlortetracycline fermentation process.

During Chlortetracycline fermentation, contamination of fermentation broth by non-target bacteria is an unavoidable problem. There is no online analytical instrument to determine whether the fermentation broth has been contaminated. Only the results of manual sampling analysis can be used to determine whether the fermentation broth is contaminated. This analysis process usually takes several hours. In order to predict online whether the fermentation broth is contaminated by non-target bacteria, a soft sensor modeling method for the signs of contamination in Chlortetracycline fermentation broth was proposed in this paper. Based on recursive wavelet neural network (RWNN) and Gaussian process regression (GPR) method, the soft sensor model of online measurable parameters and total sugar content of fermentation broth was established. By deeply analyzing the correlation between the total sugar content (it is a parameter that is difficult to measure online) of fermentation broth and the signs of bacterial contamination during fermentation, a soft sensor model was established combining with the correlation between the total sugar content of fermentation broth and the symptoms of bacterial infection, and the symptoms of non-target bacterial infection of fermentation broth were predicted. Based on the field data of the fermentation process, the different signs of Chlortetracycline fermentation were predicted for the fermentation broth uninfected with non-target bacteria, infected with bacilli and infected with phages. The experimental results showed that the proposed soft sensor model could be used to predict the occurrence of contamination during Chlortetracycline fermentation. Based on the field data, the validity of the modeling method is verified. The proposed soft sensor model of signs of bacterial contamination can be used to predict the occurrence of bacterial contamination in Chlortetracycline, Penicillin and related biological fermentation processes. So that the site operators can take effective measures in time to reduce production losses to a minimum.

Effects of Defatting Pretreatment on Polysaccharide Extraction from Rambutan Seeds Using Subcritical Water: Optimization Using the Desirability Approach.

Rambutan seeds are by-products generated from fruit-processing factories; the leftover seeds are buried in landfills, generating methane emissions. This work aimed to extract polysaccharides (POLS) from rambutan seeds by using subcritical water extraction (SWE). The effects of defatting pretreatment and operating parameters in SWE were investigated using a Box-Behnken design. The results show that defatting pretreatment significantly enriched the POLS yield, while it had no significant effect on the total sugar content. Using the desirability approach, the suitable feedstock for SWE was defatted rambutan seeds. The maximum desirability of 0.86 was found at a temperature range of 145-150 °C, an extraction time of 15 min, and a liquid-solid ratio of 10:1. The POLS yield and total sugar content were in the range of 52.33-55.63 g/100 g feedstock and 83.37-87.45 g/100 g POLS, respectively. The extracted POLS had an equivalent molecular weight of 413.70 kDa that could be used as an extender in plant-based products. In conclusion, the defatting pretreatment of rambutan seeds not only improved the POLS yield obtained via SWE but also generated additional lipids that could be utilized as an unconventional source of specialty fat.

Botanical Origin Influence on Some Honey Physicochemical Characteristics and Antioxidant Properties.

Five types of honey (multifloral, sunflower, linden, rapeseed, and acacia), from Southern Romania, were classified using chemometrics methods coupled with IR spectroscopy. The botanical origin's effect on the physicochemical characteristics of honey was studied to highlight the most valuable plant source of honey. Except for antioxidant activity, the moisture, ash, electrical conductivity (EC), pH, free acidity (FA), total sugar content (TSC), hydroxymethylfurfural (HMF), total phenolic (TPC), tannin (TTC), and flavonoid content (TFC) were significantly influenced by the botanical origin of the honey. The results showed that sunflower honey had the highest moisture (15.53%), free acidity (16.67 mEq kg-1), electrical conductivity (483.92 µS cm-1), phenolics (167.59 mg GAE 100 g-1), and flavonoids (19.00 mg CE 100 g-1), whereas multifloral honey presented the highest total sugar content (69.64 g Glu 100 g-1). The highest HMF content was found in linden honey (33.94 mg kg-1). The HMF contents of all tested honey were within the standard recommended limit, and they confirmed that the tested honey was free of any heat treatment. All five types of tested honey presented a safe moisture content for storage and consumption (12.21-18.74%). The honey's free acidity was in the range of 4.00 to 25.00 mEq kg-1; this indicated the freshness of the samples and the absence of any fermentation processes in the tested honey. Honey with a total sugar content over 60% (except for linden honey, with 58.05 g glucose 100 g-1) showed the characteristic of nectar-derived honey. The elevated antioxidant activity of honey was correlated with its high moisture, flavonoids, and HMF, whereas the tannins and HMF were positively correlated with ash and electrical conductivity. The higher content of phenolics, flavonoids, and tannins was correlated with higher free acidity. The chemometric method, coupled with ATR-FTIR spectra, revealed a clear separation between linden honey from acacia, multifloral, and sunflower honey.

Effects of monosaccharide composition on quantitative analysis of total sugar content by phenol-sulfuric acid method.

Phenol-sulfuric acid method is one of the most common methods applied to the analysis of total sugar content during polysaccharides study. However, it was found that the results obtained from the phenol-sulfuric acid method was generally lower than the real total sugar content, especially when acidic monosaccharides were contained in the polysaccharides samples. Therefore, the present study focused to unveil the proposed problem. Based on the optimization of colorimetric conditions, such as optimal wave length of absorption, linearity range, color reaction time and temperature, it indicated that the phenol-sulfuric acid method was a convenient and accurate way for the total sugar content analysis. In addition, the color-rendering capabilities of 10 common monosaccharides were systematically analyzed to obtain a relative correction factor for each monosaccharide relative to glucose, which was proved to be the main reason for the deviation in the detection of total sugar content. Moreover, the key points during the application of phenol-sulfuric acid method were suggested. This study provides a scientific theoretical basis and a reliable experimental research method for the accurate determination of total sugar content by the phenol-sulfuric acid method, and which will also promote the application of this convenient method in the polysaccharides study.

Online prediction of total sugar content and optimal control of glucose feed rate during chlortetracycline fermentation based on soft sensor modeling.

In the process of chlortetracycline (CTC) fermentation, no instrument can be used to measure the total sugar content of the fermentation broth online due to its high viscosity and large amount of impurities, so it is difficult to realize the optimal control of glucose feed rate in the fermentation process. In order to solve this intractable problem, the relationship between on-line measurable parameters and total sugar content (One of the parameters that are difficult to measure online) in fermentation tank is deeply analyzed, and a new soft sensor model of total sugar content in fermentation tank and a new optimal control method of glucose feed rate are proposed in this paper. By selecting measurable variables of fermentation tank, determining different fermentation stages, constructing recursive fuzzy neural network (RFNN) and applying network rolling training method, an online soft sensor model of total sugar content is established. Based on the field multi-batch data, the change trend of the amount of glucose feed required at each fermentation stage is divided, and the online prediction of total sugar content and the optimal control strategy of glucose feed rate are realized by using the inference algorithm of expert experience regulation rules and soft sensor model of total sugar content. The experiment results in the real field demonstrate that the proposed scheme can effectively predict the total sugar content of fermentation broth online, optimize the control of glucose feed rate during fermentation process, reduce production cost and meet the requirements of production technology.

Quality assessment of 178 cultivars of plum regarding phenolic, anthocyanin and sugar content.

In this study assessment of total phenolic, individual anthocyanin and total sugar content (TSC) of wide range of plum cultivars was done in order to select cultivars with high health benefiting compounds for potential breeding purposes. Total phenolics varied between 38.45 and 841.50mg GAE 100g(-1) FW. Cyaniding-3-rutinoside, cyaniding-3- glucoside and its equivalents were identified in anthocyanin measurement by HPLC with different ranges. TSC differed between 9.63 and 29.47%. Besides, evaluation of the effect of cultivar and year on phenolic content of 23 randomly selected cultivars over two following years (2013 & 2014) showed significant effect of both factors on phenolic content of plum cultivars. Overall, cultivars "Cacaks Spaete" which had high amount of total phenolics with stability over time, as well as "Hohenheim breed 4894" as a cultivar which contained high amounts of total phenolics, anthocyanins and TSC were selected for further breeding purposes to provide high nutritional quality plum to consumers.