محمود محمودی اشکفتکی

In this research, wheat, rice, and corn residue were used as a substrate for biogas production. Due to the high amount of lignin in all three substrates (> 9.9) and in order to increase the degradability of these substrates, an ultrasonic pretreatment with a power of 150 w at 15 min was used prior to initiating enzymatic digestion process. Some physical and chemical properties including solid and volatile particles and contents of lignin, cellulose and hemicellulose were measured before and after digesting the substances; and in addition, the biogas compounds including hydrogen, methane, hydrogen sulfide and carbon monoxide was measured during digestion. The metabolic pathways of converting glucose as the main constituent of all three waste types into biogas were studied to determine the factors affecting biogas compounds. The results showed that use of ultrasonic pretreatment in all three wastes increased the breakdown of lignin structures, which decreased the content of these structures in the feedstock compared to the substrate. The amount of solid and volatile particles of the feedstock obtained from the substrate of wheat residue was 35.1% and 95.3%, respectively, which was more than that of the other substrates. The highest amounts of reduction of solid particles (19.6%), volatile particles (18%), cellulose (12.6%), hemicellulose (4.4%) and lignin (3.6%) were related to the feedstock obtained from wheat residue. Analyses of biogas compounds showed that the highest biohydrogen production obtained for wheat substrate (ppm 18000), but its biomethane production was lower than the other substrates. The highest amounts of biohydrogen production of all the substrates occurred after seven days, which was related to the butyrate acidification stage. With increasing digestion time, hydrogen production decreased while the other biogas compounds increased. One of the probable reasons was the consumption of hydrogen produced in the stages of hydrolysis, acidification and acetate formation in the stages of alcoholization and methanation. The highest amount of hydrogen production was related to the stage of butyrate formation and then acetate formation. The higher production of biohydrogen by wheat residue is most likely due to its high volume of volatile, hydrocarbon and hemicellulose compounds. While the low production of hydrogen by corn residue was due to driving the reactions towards the production of ethanol and consuming hydrogen.

Among agricultural activities, working and driving with farm tractors in open weather is very hard and lead to fatigue and especial burnout. The objective of this study was to evaluate the job satisfaction and mental health of farm tractor drivers besides their hope in different weather conditions of Fars province. From tractor drivers in the central region of Fars, 115tractor drivers were selected as the statistical sample. The required information was gathered via different questionnaires related to job satisfaction, mental health, and hope. To analyze the data, we used SPSS/18 and Mann-Whitney U test (α= 0.05). The results showed that the indicators of hope, mental health and job satisfaction of medium age people were higher than those of in young and older people. One of the reasons for this result is that medium age people had a higher range of income. The regression analysis showed a positive and significant relationship between income and job satisfaction for young people. There were significant differences in the hope and job satisfaction between different ages and working experiences (P<0.05), but there was no difference in the mental health of a different group of drivers (P>0.05). Considering the drivers' suitable level of hope and mental health, their job satisfaction should be improved by increasing income levels.

With the increase of population and the level of welfare of the society, the amount of food resources (plant and animal) has increased, and thus, their wastes increase; therefore, the production of renewable fuels like biogas has increased. Biogas production and its quality are influenced by different slurry characteristics and biogas compounds, and their management is done using a computer with the help of complex algorithms, which are costly and require specialized training. For this purpose, a BioOptim application under the Android platform using Java programming language and 64-bit IDE was implemented with a high accuracy. For this purpose, some slurry characteristics and biogas compounds produced with co-digestion of different mixtures of citrous wastes and cow manure (0‒100%) pretreated with different amounts of NaOH and H2O2 (0‒3%) were studied. The measured parameters were modeled using multivariable regression models and used to imply in the BioOptim application. The evaluation results of the application showed that NRMSE of the parameters of C, N, C/N, Ca, TS, VS, K2O, P2O5, pH, CH4, CO2, and CO was lower than 0.45. For these parameters, the statistical quantities of ENS, d, R2, and IR2 were higher than 0.85, 0.95, 0.34, and 0.87, respectively. As found, the BioOptim application was only weak in determining parameter of H2S and BOD.

The quail egg is a without cholesterol food and riches of different vitamins. This food expunges the radioactive particle and the carcinogen of human’s body. For mechanizing its preparation process, the quality parameters should be modeled with computer techniques. Therefore in this research, the image processing technique was used to determine the physical properties of quail egg, then egg volume was calculated by slicing each egg and rotating the slices around its main axis. Furthermore to determine the egg weight, a regression multi-variable model and a neural network model were developed. The results of suggested methods and models in this research were compared with real values and previous methods (Hoyt model). Finally, the influence of nutrition, ventilation and female quail age on quality parameters of eggs was determined. By comparing the real volume of eggs with the Hoyt model, accuracy was 97% and with the slices-rotation method, accuracy was 100% which well shows the importance of slices-rotation method. By comparing the real weight of eggs with the Hoyt model, accuracy was 83%, with the regression multi-variable model, accuracy was 90%, and with the neural network model, accuracy was 95%. The neural network model not only presented the egg weight with high accuracy but also considered the effect of laying time which is very important for the egg weight estimation. After comparing the results, it was shown that the nutrition, ventilation and female quail age influence egg quality. The eggs of younger females were limited to spherical geometry that may be due to the mother's womb not being expanded. Furthermore, the female quails in topper cages which had better nutrition and ventilation showed more weighting and sizing. These results show that coupled the image processing and artificial neural network techniques can help very well to mechanize the preparation process of quail egg.

Farm tractors are an unavoidable part of agricultural activity and it is desired that when failures accoured, the tractors get prepared at a minimum time and back to the farms. With an effective maintenance program, the costs of maintenance and machine downtime reduce at an acceptable value. In the current study, the life and maintenance distribution functions of a mechanized system including two MF285, two MF399 and two NewHolland 155 tractors were assessed. The maintainability of tractors and system reliability were analyzed in the next steps. Finally, a suitable maintenance system was proposed based on the queuing theory. Indeed, in the current study by combination of life and maintenance distribution functions and queuing theory, the capacity of a suitable maintenance system was estimated such that tractors with minimum downtime work continuously. The results showed Poisson function suitable for life and Exponential function suitable for maintenance. The two NewHolland 155 tractors consume around 180 hour more time for emergency maintenances compared to two MF285 tractors in around 6700 hour life duration. The reliability of the system was 80% during 30 working hours with three available tractors. The suitable maintenance capacity was proposed around 0.4 maintenance per working shift.

As reported by Sabetghadam (2005), 53.4, 36.3, 1.1, 8.9, and 0.2% of total energy consumption in Iran consisted of oil products, natural gas, coal, electricity energy, and modern energy sources, respectively. The modern energies included solar, biomass, wind and nuclear. The energy mix has been evolving towards clean energies. From 1966–2005, the contribution of natural gas increased from 1.3% to 36.3% and the contribution of electricity was doubled from 4.1% to 8.9%. The share of oil products in domestic consumption has dropped from 84.3% to 53.4%.
Iran has abundant renewable energy resources, including solar energy, wind power, geothermal energy, and biomass, as well as the ability to manufacture the relatively labor-intensive systems that harness these. By developing such energy sources developing countries can reduce their dependence on oil and natural gas, creating energy portfolios that are less vulnerable to price rises. In many circumstances, these investments can be less expensive than fossil fuel energy systems. Over the past ten years some researches on solar and biomass energy have resulted in development and the establishment of a few small- and medium-scale electricity generation plants, powered via solar and biomass energy. There has also been the development of digesters to increase biogas production. Renewable energy is new to Iran and there is a long way to go. Except for the few afore mentioned projects, small-scale technologies to bring power to remote villages have a better chance of being adopted than those implemented at the national level.
In this research the amount of generated methane (methane content of biogas %) from co-digestion of municipal sewage, kitchen waste, and cow dung was measured in 7 different combinations (treatment). Two important parameters affecting methane production such as volatile solid (VS) and total solid (TS) were measured according to Method 1684 and CEN/TS 15148. Furthermore some environmental conditions such as temperature, pH, EC and some of the most important elements of desired substrate such as amount of C, N, P, K, and SO42- were determined. pH using pH-meter and EC using EC-meter, C using titration method according to Rongping et al. (2010) and N using Kjeldahl apparatus, P using Spectrophotometer, K using Flame photometer, and SO42- using weighting were determined according to Standard Method for the Examination of Water and Wastewater.
Methane (CH4) was determined using a multi-function gas detector brand GMI Ltd model GT-42. Its detection ranges were 0–10000 ppm (parts per million), 0–100 % LEL (lower explosive limit), and 0–100 % VOL (volume) in temperature limit -20–50 °C and 0–95% R.H (relative humidity).
The mean amount of methane contents of biogas during the co-digestion of the substrates for all 7 treatments reported in table 1 were 4363.25, 875.13, 169.13, 3424.38, 2911.88, 2714.38, and 193.5 ppm, respectively. Methane contents obtained from municipal waste was the highest among the substrates and after that the combination of 1:1:1 of the substrates was more than the others. The methane content was low in the first seven days of digestion, and thereafter rapidly increased over 85% within 22 days. Totally the highest methane contents of treatments were during 30–35 days of digestion which was agreed with other researches. This can be shown in Fig. 5 that the highest methane content was 10000 ppm and appertain to treatment 1.
The results showed that TS and VS of kitchen waste were lower than the other substrates. These findings agreed with Chen et al. (2010) researches in which had been reported the commercial kitchen waste has lower TS and VS contents, possibly because the commercial kitchen waste stream contains food with higher moisture contents such as fruits. Furthermore it can be shown that after digestion, the amount of TS of municipal waste, cow manure, and kitchen waste decreased 46, 57, and 46% respectively, while amount of VS of these substrates decreased 82, 92, and 85%, respectively. The results were similar to Chen et al. (2010) results. They reported that between 58 and 99% of the VS were degraded to methane and carbon dioxide under most feed concentrations. The obtained methane significantly correlated with VS, TS at level of 5 %. The pH of the substrate nearly was constant during the digestion. The results showed that the treatments with more municipal waste had more VS and TS while the treatments with more cow dung had more C/N.
Some mathematical models were made between the properties and generated methane. The best empirical model which can estimate amount of generated methane using the properties was a polynomial function. The function coefficients were determined for each parameter by normalizing them. Finally the results show that the model made using difference of VS and TS before and after of digestion had the most accuracy among the models (R2=0.897, RMSE=630, SSE=4.76e).
The results of conducted methane fermentation study on physico-chemical properties of substrates including municipal waste, kitchen waste and cow dung reviled that VS, TS, C/N, P, K, and SO42- affect biogas and methane production. However the correlation between methane contents with VS and TS was more than the other properties and the methane estimation models made using the VS and TS was more accurate than the other models.

The goal of the present study was to study the effect of mixer speed on biogas compounds produced from semi-industrial biogas plant. The biogas was produced with slurry made by combination of 41% cow manure, 56% municipal waste and 3% kitchen waste with adding 2.38% NaOH and 3.75% H2O2 as the chemical pretreatment. Then, the effect of mixer rotation speed on mixing quality of the slurry was linked to the anaerobic microbial communities and some of physical and chemical parameters of the slurry. The results showed that by increasing the rotation speed from 60rpm to 100rpm, the amounts of CH4 and CO within the biogas compound increased by 6.6% and 71.7%, and the amounts of H2S and O2 decreased by 4% and 5.5%, respectively. This was due to decrease in the chemical oxygen demand (COD) and total volatile solids (TVS) of the slurry by 3.6% and 3.9%, respectively because of an increase in the anaerobic microbial communities by 3.7%. Furthermore, the same trend existed between the CH4 and anaerobic microbial communities of the slurry that was similar to the COD and TVS decreasing trends.