RESUMO
Flooding stress nowadays is one of the major stressors for plants under climate change. This kind of stress may cause severe depression of the plant's growth through inhibition of photosynthesis and oxidative cell damage as well as changes in cell respiration. The present work aimed to study the effect of flooding stress on oxidative and antioxidative parameters in leaves of two maize hybrids (ZP 555 and ZP 606). Leaves of maize plants at the stage of three fully developed leaves were harvested after 6, 24, 72, and 144 h of applied flooding stress. Leaves were used for determination of physiological (the content of photosynthetic pigments and soluble proteins), oxidative stress parameters (the content of malondialdehyde (MDA) and H2O2) as well as antioxidants (the total polyphenols content, and activity of antioxidative enzymes [catalase (CAT, EC 1.11.1.6), superoxide dismutase (SOD, EC 1.15.1.1), and Class III peroxidases (POX, EC, 1.11.1.7)]). Results indicated that flooding stress-induced time-dependent changes of measured parameters and those hybrids differ in response to stress. The noticeable difference between hybrids was detected in the H2O2 and MDA content. An increase in the activity of SOD, POX and polyphenols content, with the most pronounced changes in POX activity and polyphenols concentration, could minimize the cellular damage caused by flooding. The results of the present study suggest that a more robust antioxidative metabolism is essential under flooding stress and could be a protective strategy against oxidative damage induced by flooding in ZP 606 maize plants compared to ZP 555 plants.
Assuntos
Antioxidantes , Zea mays , Ascorbato Peroxidases/metabolismo , Catalase/metabolismo , Peróxido de Hidrogênio , Peroxidação de Lipídeos , Estresse Oxidativo , Folhas de Planta/metabolismo , Superóxido Dismutase/metabolismo , Zea mays/metabolismoRESUMO
This paper presents an analysis of the fouling of a ceramic membrane by a mixture containing high concentrations of humic acid and colloidal silica during cross-flow ultrafiltration under various operating conditions. Two types of feed water were tested: feed water containing humic acid and feed water containing a mixture of humic acid and colloidal silica. The colloidal silica exacerbated the fouling, yielding lower fluxes (109-394 L m-2 h-1) compared to the humic acid feed water (205-850 L m-2 h-1), while the retentions were higher except for the highest cross-flow rate. For the humic acid feed water, the irreversible resistance prevails under the cross-flow rate of 5 L min-1. During the filtration of an organic-inorganic mixture, the reversible resistance due to the formation of a colloidal cake layer prevails under all operating conditions with an exception. The exception is the filtration of the organic-inorganic mixture of a 50 mg L-1 humic acid concentration which resulted in a lower flux than the one of a 150 mg L-1 humic acid concentration under 150 kPa and a cross-flow rate of 5 L min-1. Here, the irreversible fouling is unexpectedly overcome. This is unusual and occurs due to the low agglomeration at low concentrations of humic acid under a high cross-flow rate. Under lower transmembrane pressure and a moderate cross-flow rate, fouling can be mitigated, and relatively high fluxes are yielded with high retentions even in the presence of nanoparticles. In this way, colloidal silica influences the minimization of membrane fouling by organic humic acid contributing to the control of in-pore organic fouling.
RESUMO
Degradation of environment is a challenge to crop production around the world. Biological control of various plant diseases using antagonistic bacteria is an encouraging alternative to traditionally used chemical control strategies. Chitosan as a well-known natural flocculation agent also exhibits antimicrobial activity. The goal of this study was to investigate a dual nature of chitosan in flocculation of Bacillus sp. BioSol021 cultivation broth intended for biocontrol applications. Experiments were performed based on L18 standard Taguchi orthogonal array design with five input parameters (chitosan type and dosage, pH value, rapid and slow mixing rates). In this study, the grey relational analysis was used to perform multi-objective optimization of the chosen responses, i.e., flocculation efficiency and four inhibition zone diameters against the selected phytopathogens. The results have indicated a great potential of a highly efficient method for removal of the Bacillus bacteria from the cultivation broth using chitosan. The good flocculation efficiency and high precipitate antimicrobial activity against the selected phytopathogens were achieved. It has been shown that multiple flocculation performance parameters were improved, resulting in slightly improved response values.
RESUMO
The use of membrane filtration as a downstream process for microbial biomass harvesting is hampered due to the low permeate flux values achieved during the microfiltration of fermentation broths. Several hydrodynamic methods for increasing permeate flux by creating turbulent flow patterns inside the membrane module are used to overcome this problem. The main goal of this study was to investigate the combined use of a Kenics static mixer and gas sparging during cross-flow microfiltration of Bacillus velezensis IP22 cultivation broth. Optimization of the microfiltration process was performed by using the response surface methodology. It was found that the combined use of a static mixer and gas sparging leads to a considerable increase in the permeate flux, up to the optimum steady-state permeate flux value of 183.42 L·m-2·h-1 and specific energy consumption of 0.844 kW·h·m-3. The optimum steady-state permeate flux is almost four times higher, whilst, at the same time, the specific energy consumption is almost three times lower compared to the optimum results achieved using gas sparging alone. The combination of Kenics static mixer and gas sparging during cross-flow microfiltration is a promising technique for the enhancement of steady-state permeate flux with simultaneously decreasing specific energy consumption.
RESUMO
Hydrology is a major environmental factor determining plant fitness, and hydrological niche segregation (HNS) has been widely used to explain species coexistence. Nevertheless, the distribution of plant species along hydrological gradients does not only depend on their hydrological niches but also depend on their seed dispersal, with dispersal either weakening or reinforcing the effects of HNS on coexistence. However, it is poorly understood how seed dispersal responds to hydrological conditions. To close this gap, we conducted a common-garden experiment exposing five wind-dispersed plant species (Bellis perennis, Chenopodium album, Crepis sancta, Hypochaeris glabra, and Hypochaeris radicata) to different hydrological conditions. We quantified the effects of hydrological conditions on seed production and dispersal traits, and simulated seed dispersal distances with a mechanistic dispersal model. We found species-specific responses of seed production, seed dispersal traits, and predicted dispersal distances to hydrological conditions. Despite these species-specific responses, there was a general positive relationship between seed production and dispersal distance: Plants growing in favorable hydrological conditions not only produce more seeds but also disperse them over longer distances. This arises mostly because plants growing in favorable environments grow taller and thus disperse their seeds over longer distances. We postulate that the positive relationship between seed production and dispersal may reduce the concentration of each species to the environments favorable for it, thus counteracting species coexistence. Moreover, the resulting asymmetrical gene flow from favorable to stressful habitats may slow down the microevolution of hydrological niches, causing evolutionary niche conservatism. Accounting for context-dependent seed dispersal should thus improve ecological and evolutionary models for the spatial dynamics of plant populations and communities.
RESUMO
Production of highly efficient biomass-based microbial biopesticides significantly depends on downstream processing in terms of obtaining as high concentration of viable cells as possible. Microfiltration is one of the recommended operations for microbial biomass separation, but its main limitation is permeate flux decrease due to the membrane fouling. The effect of air sparging as a hydrodynamic technique for improvement of permeate flux during microfiltration of Bacillus velezensis cultivation broth was investigated. Modeling of the microfiltration was performed using the response surface methodology, while desirability function approach and genetic algorithm were applied for optimization, i.e., maximization of permeate flux and minimization of specific energy consumption. The results have revealed antagonistic relationship between the investigated dependent variables. The optimized values of superficial feed velocity and transmembrane pressure were close to the mean values of the investigated value ranges (0.68 bar and 0.96 m/s, respectively), while the optimized value of superficial air velocity had a more narrow distribution around 0.25 m/s. The results of this study have revealed a significant improvement of microfiltration performance by applying air sparging, thus this flux improvement method should be further investigated in downstream processing of different bacterial cultivation broths.
RESUMO
Cross-flow microfiltration is a broadly accepted technique for separation of microbial biomass after the cultivation process. However, membrane fouling emerges as the main problem affecting permeate flux decline and separation process efficiency. Hydrodynamic methods, such as turbulence promoters and air sparging, were tested to improve permeate flux during microfiltration. In this study, a non-recurrent feed-forward artificial neural network (ANN) with one hidden layer was examined as a tool for microfiltration modeling using Bacillus velezensis cultivation broth as the feed mixture, while the Kenics static mixer and two-phase flow, as well as their combination, were used to improve permeate flux in microfiltration experiments. The results of this study have confirmed successful application of the ANN model for prediction of permeate flux during microfiltration of Bacillus velezensis cultivation broth with a coefficient of determination of 99.23% and absolute relative error less than 20% for over 95% of the predicted data. The optimal ANN topology was 5-13-1, trained by the Levenberg-Marquardt training algorithm and with hyperbolic sigmoid transfer function between the input and the hidden layer.