Temporary immersion systems (TISs): A comprehensive review.

The temporary immersion systems (TISs) have been widely used in plant biotechnology. TISs have different advantages from the point of micropropagation and production of secondary metabolites over other continuous liquid-phase bioreactors. The current work presents the structure, operation mode, configuration type, and micropropagation or secondary metabolite production in TISs. This review deals with the advantages and disadvantages of TISs and the factors affecting their performance. Future research could focus on new designs based on CFD simulation, facilitating sterilization, and combining TISs with other bioreactors (e.g., mist bioreactors) to make a hybrid bioreactor.

Design of nutrient gas-phase bioreactors: a critical comprehensive review.

To reach an efficient and economical gas-phase bioreactor is still one of the most critical challenges in biotechnology engineering. The numerous advantages of gas-phase bioreactors (GPBs) as well as disadvantages of these bioreactors should be exactly recognized, and efforts should be made to eliminate these defects. The first step in upgrading these bioreactors is to identify their types and the results of previous research. In the present work, a summary of the studies carried out in the field of cultivation in these bioreactors, their classification, their components, their principles and relations governing elements, modeling them, and some of their inherent engineering aspects are presented. Literature review showed that inoculation of shoots, roots, adventurous roots, callus, nodal explants, anther, nodal segment, somatic embryo, hairy roots, and fungus is reported in 15, 2, 2, 2, 3, 2, 1, 1, 37, and 5 cases, respectively.

Going beyond conventional wastewater treatment plants within circular bioeconomy concept - a sustainability assessment study.

Wastewater treatment plants (WWTP) have extensive energy processes that undermine their economic and environmental performance. In this context, the integration of wastewater treatment with other biochemical processes such as co-digestion of sludge with organic wastes, and production of value-added products at their downstream processes will shift conventional WWTPs into biorefinery platforms with better sustainability performance. The sustainability of such a biorefinery platform has been investigated herein using an economic and life cycle assessment approach. This WWTP-based biorefinery treats wastewater from Copenhagen municipality, co-digests the source-sorted organic fraction of municipal solid waste and sludge, and upgrades biogas into biomethane using a hydrogen-assisted upgrading method. Apart from bioenergy, this biorefinery also produces microbial protein (MP) using recovered nutrients from WWTP's reject water. The net environmental savings achieved in two damage categories, i.e., -1.07 × 10-2 species.yr/FU in ecosystem quality and -1.68 × 106 USD/FU in resource scarcity damage categories along with high potential windows for the further environmental profile improvements make this biorefinery platform so encouraging. Despite being promising in terms of environmental performance, the high capital expenditure and low gross profit have undermined the economic performance of the proposed biorefinery. Technological improvements, process optimization, and encouraging incentives/subsidies are still needed to make this platform economically feasible.

Joint analytical hierarchy and metaheuristic optimization as a framework to mitigate fertilizer-based pollution.

The emission of nitrogenous pollution from agricultural lands in form of ammonia volatilization, leaching, runoff, N2O emissions, etc. is still a serious challenge to which agricultural sector faces. In this context, a vast number of decision support systems have been developed and tested to find the best nitrogen application rate. These models are highly dependent on crop simulation models, mathematical and regression models, evolutionary algorithms and artificial intelligent, GIS-based models, etc., while in most cases have ignored to be interfered with regional and national regulations established by experts in the field. In this study, a new framework combining analytical hierarchy (AHP)/modified AHP methods (MAHP) plus metaheuristic optimization techniques has been suggested to find the best nitrogen application rate considering regional capacities and requirements. To reach the objectives of the present study a three yield field experiment was conducted upon which crop yield, nitrogen use efficiency, nitrogen uptake, soil nitrate, ammonia volatilization, N2O emissions, and N leaching were monitored or measured. Using the results from the field experiments and a survey from local experts, the models were developed. AHP-assisted optimization model could cause some biases in the final results due to its intrinsic nature which avoids direct pairwise comparison among indicators (so called sub-criteria) under two different main-criteria. On the contrary, MAHP-assisted model could well reflect the concerns of experts and notably decrease hotspot pollution. Such decision support system can satisfy both farmers and environmentalists' need because of the created high profit and low environmental pollution, while saving resources and ensuring a sustainable production system.

Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg-1 and 66,112.94MJkg-1, respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy.

Sustainability evaluation of pasteurized milk production with a life cycle assessment approach: An Iranian case study.

Agro-food systems play a significant role in the economies of all nations due to energy use and the resulting environmental consequences. The sustainability of these systems is determined by a multitude of interacting economic, social and environmental factors. Dairy production presents a relevant example of the sustainability trade-offs that occur within such systems. On the one hand, dairy production constitutes an important part of the human diet, but it is also responsible for significant emissions of potent greenhouse gases and other pollutants. In this study, the environmental aspects of pasteurized milk production in Iran were investigated using a life-cycle approach. Three sub-systems, namely feed production, dairy farm and dairy factory, were taken into account to determine how and where Iranian pasteurized milk production might be made more environmentally friendly and energy efficient. The results clearly demonstrate that the feed production stage was the hot spot in pasteurized milk production in terms of energy consumption, environmental burdens and economic costs. The largest share of the total production costs belonged to animal feeds (43%), which were part of the feed production stage. The largest consumers of energy in the production of raw milk were alfalfa (30.3%), concentrate (24%), straw (17.8%) and maize (10.9%) for cows, followed by diesel fuel (6.6%) and electricity (5.6%). The global warming potential for the production of 1000kg of raw milk at the dairy-farm gate was estimated at 457kg CO2,eq. Thus, more than 69% of the total impact at the milk-processing gate resulted from the previous two sub-systems (feed production and dairy farm), with the feed-production stage accounting for the largest fractions of the environmental burdens.

Real-time color change monitoring of apple slices using image processing during intermittent microwave convective drying.

An intermittent microwave convective drying method combined with a real-time computer vision technique was employed to detect the effect of drying parameters on color properties of apple slices. The experiments were performed at air temperature of 40 to 80℃, air velocities of 1-2 m/s, microwave powers of 200-600 W, and pulse ratios (PRs) of 2-6. Drying rate and drying time varied from 0.014 to 0.000001 min-1 and 27 to 244 min, respectively. The normalized lightness values had ascending and descending parabolic trends with decrease in product moisture content. With descending dimensionless moisture content, redness, yellowness, color change, hue angle, and chroma were enlarged. The normalized redness values changed from -4 to 3. Models relating drying parameters with drying time, drying rate, and lightness were obtained and found to be significant (P < 0.01). Results indicated that microwave power and PRs had more influence on lightness and color change than other parameters.

Optimization of intermittent microwave-convective drying using response surface methodology.

In this study, response surface methodology was used for optimization of intermittent microwave-convective air drying (IMWC) parameters with employing desirability function. Optimization factors were air temperature (40-80°C), air velocity (1-2 m/sec), pulse ratio) PR ((2-6), and microwave power (200-600 W) while responses were rehydration ratio, bulk density, total phenol content (TPC), color change, and energy consumption. Minimum color change, bulk density, energy consumption, maximum rehydration ratio, and TPC were assumed as criteria for optimizing drying conditions of apple slices in IMWC. The optimum values of process variables were 1.78 m/sec air velocity, 40°C air temperature, PR 4.48, and 600 W microwave power that characterized by maximum desirability function (0.792) using Design expert 8.0. The air temperature and microwave power had significant effect on total responses, but the role of air velocity can be ignored. Generally, the results indicated that it was possible to obtain a higher desirability value if the microwave power and temperature, respectively, increase and decrease.

A comparative study of dried apple using hot air, intermittent and continuous microwave: evaluation of kinetic parameters and physicochemical quality attributes.

In the study, the effectiveness of intermittent (IMWD) and continuous (CMWD) microwave drying and hot air drying (HAD) treatments on apple slices were compared in terms of drying kinetics (moisture diffusivity and activation energy) and critical physicochemical quality attributes (color change, rehydration ratio, bulk density, and total phenol content (TPC) of the final dried product. The temperature, microwave power, air velocity, and pulse ratio (PR) applied in the experiments were 40-80°C, 200-600 W, 0.5-2 m/s, and 2-6, respectively. Results showed that IMWD and CMWD more effective than HAD in kinetic parameters and physicochemical quality attributes. Also, results indicated CMWD had the lowest and highest drying time and effective diffusivity. The exponential model for estimating IMWD activation energy, considering absolute power (1/P) and pulse ratio were also represented. The color change in apple slices dried by HAD showed the highest change.

Optimization on drying conditions of a solar electrohydrodynamic drying system based on desirability concept.

The purpose of this article was to present a new drying method for agricultural products. Electrohydrodynamic (EHD) has been applied for drying of agricultural materials due to several advantages such as energy saving, low cost equipment, low drying temperatures, and superior material quality. To evaluate this method, an EHD dryer based on solar (photovoltaic) energy was designed and fabricated. Moreover, the optimum condition for the EHD drying of kiwi fruit was studied by applying the Box-Behnken design of response surface methodology. The desirability function was applied for optimization in case of single objective and multiobjective functions. By using the multiobjective optimization method, maximum desirability value of 0.865 was obtained based on the following: applied voltage of 15 kV, field strength of 5.2 kV cm(-1), without forced air stream, and finally a combination of 17 discharge electrodes (needles). The results indicated that increasing the applied voltage from 6 to 15 kV, moisture ratio (MR) decreased, though energy efficiency and energy consumption were increasing. On the other hand, field strength of 5.2 kV cm(-1) was the optimal point in terms of MR.

Modeling of electrohydrodynamic drying process using response surface methodology.

Energy consumption index is one of the most important criteria for judging about new, and emerging drying technologies. One of such novel and promising alternative of drying process is called electrohydrodynamic (EHD) drying. In this work, a solar energy was used to maintain required energy of EHD drying process. Moreover, response surface methodology (RSM) was used to build a predictive model in order to investigate the combined effects of independent variables such as applied voltage, field strength, number of discharge electrode (needle), and air velocity on moisture ratio, energy efficiency, and energy consumption as responses of EHD drying process. Three-levels and four-factor Box-Behnken design was employed to evaluate the effects of independent variables on system responses. A stepwise approach was followed to build up a model that can map the entire response surface. The interior relationships between parameters were well defined by RSM.

Image analysis and green tea color change kinetics during thin-layer drying.

This study was conducted to investigate the effect of air temperature and air flow velocity on kinetics of color parameter changes during hot-air drying of green tea, to obtain the best model for hot-air drying of green tea, to apply a computer vision system and to study the color changes during drying. In the proposed computer vision system system, at first RGB values of the images were converted into XYZ values and then to Commission International d'Eclairage L*a*b* color coordinates. The obtained color parameters of L*, a* and b* were calibrated with Hunter-Lab colorimeter. These values were also used for calculation of the color difference, chroma, hue angle and browning index. The values of L* and b* decreased, while the values of a* and color difference (ΔE*ab ) increased during hot-air drying. Drying data were fitted to three kinetic models. Zero, first-order and fractional conversion models were utilized to describe the color changes of green tea. The suitability of fitness was determined using the coefficient of determination (R (2)) and root-mean-square error. Results showed that the fraction conversion model had more acceptable fitness than the other two models in most of color parameters.

Integrated optimization of fish oil microencapsulation process by spray drying.

An integrated approach through coupling response surface method (RSM) and genetic algorithm (GA) was applied to optimize the spray dryer operational condition for production of fish oil microcapsules. The inlet drying air temperature, aspirator rate, and peristaltic pump rate were independent and encapsulation efficiency (EE) and exergy efficiency were dependent variables. RSM was applied to establish the relationship between the independent and dependent variables followed by integrating the developed models using three mathematical approaches and measure the fitness value of GA. Consequently, the optimal drying condition for microencapsulation of fish oil was: inlet drying air temperature = 177.23°C, aspirator rate = 63.93%, and peristaltic pump rate = 14.04% yielding exergy efficiency of 8.10% and EE of 79.14%. The results of confirmation experiments for selected drying condition proved the capability of utilized approach for determination of sustainable and qualified process in fish oil microencapsulation by spray drying.

Improving energy productivity of sunflower production using data envelopment analysis (DEA) approach.

BACKGROUND: Efficient use of energy in agriculture is one of the conditions for sustainable agricultural production. This study applies the data envelopment analysis (DEA) approach to the data of 95 randomly selected farms to investigate the technical and scale efficiencies of farmers with respect to energy use for sunflower production in Golestan province, Iran. The study also helps to identify the wasteful usage and the optimum level of energy from different inputs. RESULTS: According to the results of DEA models, about 36% of farmers were found to be technically efficient and the mean efficiency of sunflower producers was found to be 0.87 and 0.96 under the constant and variable returns to scale assumptions respectively. The optimum energy requirement was calculated as 8448.3 MJ ha⁻¹; accordingly, a potential reduction of 10.8% (1020.3 MJ ha⁻¹) in total energy input could be achieved by raising the performance of farmers to the highest level. CONCLUSION: Applying a better machinery management technique and conservation tillage methods, application of fertilisers by performance monitoring and utilisation of alternative sources of energy such as compost and chopped residues may be the pathways for improving energy productivity and reducing the environmental footprint.