Isolation and screening of strains producing high amounts of rutin degrading enzymes from Fagopyrum tataricum seeds.

The rutin degrading enzyme (RDE) was isolated and purified from tartary buckwheat seeds. The RDE was purified about 11.34-fold and its final yield was 3.5%, which was very low, due to our purification strategy of giving priority to purity over yield. The RDE molecular weight was estimated to be about 60 kDa. When rutin was used as substrate, an optimal enzyme activity was seen at around pH 5.0 and 40 °C. Strains isolation strategy characterized by the use of rutin as sole carbon source in enrichment cultures was used to isolate RDE-producing strains. Then the active strains were identified by morphology characterization and 18s rDNA-ITS (Internal Transcribed Spacer) gene sequencing. Three isolates coded as B3, W2, Y2 were successfully isolated from fusty Fagopyrum tataricum flour cultures. Strain B3 possessed the highest unit activity among these three strains, and its total activity reached up to 171.0 Unit. The active isolate (B3) could be assigned to Penicillium farinosum. When the Penicillium farinosum strains were added to tartary buckwheat flour cultures at pH 5.0, 30 °C after 5 days fermentation, the quercetin production raised up to 1.78 mg/l, almost 5.1 times higher than the fermentation without the above active strains. Hence, a new approach was available to utilize microorganism-aided fermentation for effective quercetin extraction from Fagopyrum tataricum seeds.

Note: anti-strong-disturbance signal processing method of vortex flowmeter with two sensors.

Some digital signal processing methods have been used to deal with the output signal of vortex flowmeter for extracting the flow rate frequency from the noisy output of vortex flow rate sensor and achieving the measurement of small flow rate. In applications, however, the power of noise is larger than that of flow rate sometimes. These strong disturbances are caused by pipe vibration mostly. Under this condition the previous digital signal processing methods will be unavailable. Therefore, an anti-strong-disturbance solution is studied for the vortex flowmeter with two sensors in this Note. In this solution, two piezoelectric sensors are installed in the vortex probe. One is called the flow rate sensor for measuring both the flow rate and vibration noise, and the other is called the vibration sensor for detecting the vibration noise and sensing the flow rate signal weakly at the same time. An anti-strong-disturbance signal processing method combining the frequency-domain substation algorithm with the frequency-variance calculation algorithm is proposed to identify the flow rate frequency. When the peak number of amplitude spectrum of the flow rate sensor is different from that of the vibration sensor, the frequency-domain subtraction algorithm will be adopted; when the peak number of amplitude spectrum of the flow rate sensor is the same as that of the vibration sensor, the frequency-variance calculation algorithm will be employed. The whole algorithm is implemented in real time by an ultralow power micro control unit (MCU) to meet requirements of process instrumentation. The experimental results show that this method can obtain the flow rate frequency correctly even if the power of the pipe vibration noise is larger than that of the vortex flow rate signal.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.