Amir Heydari

Iranian Foeniculum vulgare Essential Oil and Alcoholic Extracts: Chemical Composition, Antimicrobial, Antioxidant and Application in Olive Oil Preservation

Abstract The aim of this research was to investigate chemical compositions, antibacterial properties and in vitro and in vivo antioxidant properties of essential oil and methanol and ethanol extracts of Feoniculum vulgare. Antimicrobial properties of Feoniculum vulgare essential oil and extracts against pathogenic bacteria, fungi, and yeast were determined by agar disk diffusion and minimum inhibitory of concentration. The chemical composition of essential oil was characterized using gas chromatography/mass spectrometry (GC-MS). The results of EOs analysis indicated that there are different compounds in EO giving it different characteristics. According to the results, EO and each extracts has a different potential to inhibit the growth of microorganism. Protective effects of essential oil and methanol and ethanol extract of fennel in stabilizing olive oil were tested, compared to synthetic antioxidants, by measuring their peroxide values (PV) and p-anisidine value during accelerated storage. Results indicated that essential oil of fennel exhibited stronger antioxidant activity in olive oil than butylated hydroxyanisole (BHA), while its antioxidant activity was less than that of butylated hydroxytoluene (BHT). In summary Iranian Foeniculum vulgare extract has potential application as antioxidant, antimicrobial agent in food applications.

The effects of Sucrose/NaCl/Time interactions on the osmotic dehydration of banana slices

The objective of this work was to study the mass transfer kinetics during the osmotic dehydration of banana slices in an osmotic solution prepared by combining sugar with salt. Two levels of sucrose concentration (50 and 60 °Bx), three levels of NaCl content (0, 5% and 10% w/v) and four time levels (90, 180, 270 and 360 min) were applied according to the full factorial technique. The experiments were carried out with three replications and the means analyzed using response surface methodology (RSM). The experimental data revealed that the water loss increased with increase in time, sucrose and salt contents. According to the data obtained the minimum and maximum water losses observed were 9.0% (at 50 °Bx, 0% salt and 90 min) and 46.5% (at 60 °Bx, 10% salt and 360 min), respectively. Furthermore, a small portion of salt was found to reduce the solids gain while the sugar content and time increased it. The effects of all the parameters were significant for water loss, while only those of sucrose content, time and the interaction of salt with sucrose were significant for solids gain. Based on Fick’s second law, the effective diffusivity of water in banana slices was evaluated in the range from 5.67×10-9 to 9.11×10-9 m2/s for the solutions studied.

A Computer Model for Simulating Sunflower Growth and Yield

Sunflower (Helianthus annus L.) is one of the most important oil seed crops in Iran. In spite of very progressing in production mechanization and varieties breeding, weather is still one of the most important determining factors for growth and production crops. Under optimal water and nutrient supply, radiation and temperature are two important factors for determining of production and dry matter accumulation. Quantification of the effect of radiation and effect of temperature on growth and yield of sunflower is important in selecting this crop for different agro-climatic situation. Environmental limitations in production at each regional can be evaluated using a crop simulation model and prolong weather data. The model operates simulation daily and it has four segments include simulation of leaf area index, light interception, dry matter production and seed yield. For testing model, the capability of the model was determined to predicting of leaf area index and accumulated dry matter production. Paired data of observed and simulated for both leaf area index and accumulated dry matter were tested by t test. Between paired data were not significant (α =0.05). Also linear regression between observed and simulated values for leaf area index and accumulated dry matter explained more than 95% of variability.