نشریه مهندسی بیوسیستم ایران
سال پنجاه و سوم شماره 1 (بهار 1401)

Vinasse, the effluent of alcohol distilleries, is a highly polluting waste. The high volume of vinasse and its unpleasant odor, along with its acidic properties and high pollution load, has made it one of the most important environmental challenges in Khuzestan. The use of dark fermentation to treat this wastewater is one of the cheapest and most environmentally friendly methods. Hydrogen is a clean fuel and considered as a carrier of renewable energy, if produced biologically. In the present study, the batch production of bio-hydrogen from vinasse by dark fermentation was studied. The effect of inoculum pretreatment (anaerobic digested sludge) and substrate pretreatment (vinasse) on hydrogen production yield were also investigated. The results showed that the use of chloroform as an inoculum pretreatment had increased hydrogen yield very significantly which lead to a yield of 47.8 ± 3.6 Nml/g of initial volatile solids (VS). Also, sodium hydroxide application had a significant effect on vinasse sugars hydrolysis, and the hydrogen production efficiency was increased up to 100 percent by 99.5 ± 0.1 Nml/ g of initial VS. In all treatments, acetic acid and butyric acid were identified as the dominant organic acids in the final fermentation broth. Finally, according to laboratory results and available field information, the production potential of bio-hydrogen, acetic and butyric acid from. vinasse produced in Khouzestan in 2021 was calculated to be 0.003, 0.153 and 0.132 km3, respectively. The results showed that the production of bio-hydrogen from vinasse by dark fermentation is a very efficient method due to the high potential of this gas production.

Determining the best extraction method to obtain high yield of essential oils from medicinal plants has been identified as one of the challenges in scientific research. The sequential ultrasound-microwave method is a new extraction method that in this research has been applied to extraction of essential oil from basil. In order to investigate the effect of this approach on enhancing extraction yield, the microwave method was examined as a base method. To optimize the extraction conditions of the sequential method, ultrasonic power, microwave power, and extraction time were determined as independent variables and essential oil yield as response. Experiments were modeled by central composite design (CCD) of response surface methodology (RSM). The highest yield (2.3% w/w) was obtained at 300 W of ultrasonic power, 600 W of microwave power, and 40 min of extraction time. While the base method yield was 0.74% w/w. The chemical composition analysis of the active compounds showed that the number of compounds in the sequential approach is higher than those in the microwave method. Furthermore, by comparing the antioxidant properties obtained by DPPH and FRAP methods, the sequential method was better in preserving the antioxidant properties of basil essential oil. Scanning electron microscopy images also showed more damage to the glands containing the active ingredients by the sequential process than the base method. Generally, the sequential ultrasound-microwave method can be introduced as an efficient method for the extraction of essential oils from Ocimum basilicum.

Fruit juice is one of the most popular fruit products and is consumed by a wide range of individuals in societies in almost every age group. Some producers, however, perpetrate fraud in the production procedure due to economic and financial purposes. Thus, authenticity as well as quality have always been a major concern of consumers and officials in charge of setting regulations. Being aware of the frequent fraud in terms of fruit juice and being able to detect it are essential to differentiate between the unadulterated and adulterated product with more efficacy, which could be significant with regard to swift and accurate detection process and eventually the health of the consumer. This article aims to review the studies conducted on different common fraud cases in fruit juice production and methods of detecting them. Chromatographic techniques such as high-performance liquid chromatography and gas chromatography are the most common methods for determining the purity of juices. Among novel methods of detecting fruit juice fraud cases are stable isotope analysis, reverse transcription polymerase chain reaction technique, and spectroscopy techniques, namely infrared spectroscopy, visible and ultraviolet spectroscopy, nuclear magnetic resonance spectroscopy, and fluorescence emission spectroscopy. According to a vast majority of the studies, fruit juice production fraud entails cases of adding sugar, organic acids, water, foreign fruit juices, sulfite, and cloudifiers. Also noteworthy were determining fruit content, microbiological damage indicators, and other indicators related to thermal stress, enzyme treatment, and contamination by process water. As a general conclusion, in order to accurately and quickly detect of fraud cases, researchers should always take steps to develop and update fraud detection techniques.

Rapid detection and prevention of disease spread in agricultural products can significantly reduce losses and costs of disease control. In this study, an intelligent system based on image processing method has been presented for detection of grape (Sultana - Vitis vinifera) leaf diseases. For this purpose, different image texture features were extracted from the Gray Level histogram (GLH), Gray Level Co-occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRM) and Local Binary Pattern (LBP) algorithms. Two models of Artificial Neural Network (ANN) and Support Vector Machine (SVM) were used to model the features. The dataset consists of 4062 images including healthy leaves, Black Rot, Esca and Isariopsis leaves. The results showed that the SVM model based on GLRM features with an average accuracy of 89.70% showed the best performance. The results also showed that the use of all extracted features as a single feature vector increases the accuracy of classification. The accuracy of the SVM and ANN models using all of the features for training data were 91.10%, 95.04%, and for the test data were 89.93% and 91.75%, respectively. Finally, using Genetic Bee Colony (GBC) algorithm and reducing the number of features to 34 and 46 for ANN and SVM models, respectively, the average accuracy of 97.20% and 94.10% for training and testing of ANN model and 93.01% and 92.33% for training and testing of SVM model were obtained, which shows the improvement of results by GBC algorithm. The proposed method was evaluated as efficient in diagnosing grape leaf diseases.

Electrical impedance tomography (EIT) is a non-invasive imaging technique that measures properties of multiphase fluids such as particles distribution and volume concentration by injecting a current into a set of electrodes and reading voltages from the electrodes. A strategy of injection and signal measurement has an important role in the image reconstruction quality and measurement accuracy. In large phantoms with high-conductivity, conventional strategies such as adjacent are not able to measure the signal with suitable quality. Therefore, the purpose of this study is to construct and evaluate the EIT system under an innovative strategy for online determination of particles distribution and concentration of solid-liquid fluid in large phantoms. The sensors of this instrument consist of 16 circular electrodes. The liquid phase was water with known conductivity and solid phase was the bottle in different sizes and in three different situations. The results showed that the innovative strategy has the ability to recognize and differentiate the target in different dimensions and different positions. The signal-to-noise rate was 1.05 dB and the dynamic range of boundary potentials was 1600 mV. The sensitivity to the sides and near the electrodes was more than the sensitivity to the middle. In positions close to the electrodes, size error decreases in medium and large target. In the three sizes of the target, ringing has no negative effect on the reconstructed image quality. Therefore, it can be concluded that the innovative strategy has a desirable performance for determining the distribution of materials in the large phantom.

The purpose of this study was to present a strategy for designing and simulating an anaerobic digester for the digestion of raw municipal sewage sludge, based on the flow patterns within the digester, and to investigate the sediment deposition conditions in this anaerobic digester. For this purpose, the simulations were performed based on a step-by-step strategy. First, the inlet gas velocity to the digester was determined, then in the next steps, the draft tube and the conical hanging baffle were added to the digester design, respectively, and simulations were performed with them and determined their characteristics. Simulations were performed for a pilot-scale cylindrical digester. A transparent cylindrical digester was built based on the computational fluid dynamics (CFD) simulations results. Sludge analysis was performed, and determine the sludge sedimentation velocity using the image processing process, so the sludge particle size and each percentage of them based on the total solids (TS) of sludge was performed. According to the results, only in a small area of the floor attached to the digester wall, the velocity of the fluid is less than the sedimentation velocity of the largest particles in the sludge (4.71 × 10-5 m / s) so there was a sedimentation possibility of a small amount of these particles in this area, which confirmed the success of digester design based on step-by-step simulation and flow patterns for mixing in a gas-lift anaerobic digester and showed a step-by-step simulation strategy is suitable and can be used to simulate gas-lift anaerobic digesters successfully.