Large-scale Production Systems Research Articles

Exploration of the configuration and operation rule of the multi-electrolyzers hybrid system of large-scale alkaline water hydrogen production system

This study presents a multi-electrolyzers hybrid system for wind-hydrogen system, and two control strategies are proposed. And two different configurations that could achieve the target value of the lower load limit are compared and analyzed. Different switch strategies between multi-electrolyzer are also proposed and simulated. In terms of the configuration of the electrolyzer, the results show that four 0.5 MW electrolyzer could achieve the 99% energy absorptivity and the absorption is 96.54% when the 0.5 MW electrolyzer and 1.5 MW electrolyzer are configured, however, the hydrogen production of the latter is higher. Then the switching strategies between four electrolyzers are proposed. The first strategy (“Equal force strategy”) will lead to a disbalance in the working time of electrolyzers, it’s dangerous for the ALK system. The improved strategy (“Doctor triage strategy”) is proposed and simulated, the results show that the disbalance between electrolyzers is slight compared with the first strategy. And the disbalance will be enlarged when the cycle period becomes longer in the improved strategy. If the period is extended to 6017 h, the value even reaches 75 times of 6.42 h. In a word, the developed general procedure is well feasible for the improvement of energy efficiency and scale of the industry’s commercial alkaline water electrolyzers.

Smallholder vegetable farming produces more soil microplastics pollution than large-scale farming

Microplastics (MPs) accumulation in farmland has attracted global concern. Smallholder farming is the dominant type in China's agriculture. Compared with large-scale farming, smallholder farming is not constrained by restrictive environmental policies and public awareness about pollution. Consequently, the degree to which smallholder farming is associated with MP pollution in soils is largely unknown. Here, we collected soil samples from both smallholder and large-scale vegetable production systems to determine the distribution and characteristics of MPs. MP abundance in vegetable soils was 147.2–2040.4 MP kg−1 (averaged with 500.8 MP kg−1). Soil MP abundance under smallholder cultivation (730.9 MP kg−1) was twice that found under large-scale cultivation (370.7 MP kg−1). MP particle sizes in smallholder and large-scale farming were similar, and were mainly <1 mm. There were also differences in MP characteristics between the two types of vegetable soils: fragments (60%) and fibers (34%) were dominant under smallholder cultivation, while fragments (42%), fibers (42%), and films (11%) were dominant under large-scale cultivation. We observed a significant difference in the abundance of fragments and films under smallholder versus large-scale cultivation; the main components of MPs under smallholder cultivation were PP (34%), PE (28%), and PE-PP (10%), while these were PE (29%), PP (16%), PET (16%), and PE-PP (13%) under large-scale cultivation. By identifying the shape and composition of microplastics, it can be inferred that agricultural films were not the main MP pollution source in vegetable soil. We show that smallholder farming produces more microplastics pollution than large-scale farming in vegetable soil.

Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems

AbstractThe past 50 yr of advances in weed recognition technologies have poised site-specific weed control (SSWC) on the cusp of requisite performance for large-scale production systems. The technology offers improved management of diverse weed morphology over highly variable background environments. SSWC enables the use of nonselective weed control options, such as lasers and electrical weeding, as feasible in-crop selective alternatives to herbicides by targeting individual weeds. This review looks at the progress made over this half-century of research and its implications for future weed recognition and control efforts; summarizing advances in computer vision techniques and the most recent deep convolutional neural network (CNN) approaches to weed recognition. The first use of CNNs for plant identification in 2015 began an era of rapid improvement in algorithm performance on larger and more diverse datasets. These performance gains and subsequent research have shown that the variability of large-scale cropping systems is best managed by deep learning for in-crop weed recognition. The benefits of deep learning and improved accessibility to open-source software and hardware tools has been evident in the adoption of these tools by weed researchers and the increased popularity of CNN-based weed recognition research. The field of machine learning holds substantial promise for weed control, especially the implementation of truly integrated weed management strategies. Whereas previous approaches sought to reduce environmental variability or manage it with advanced algorithms, research in deep learning architectures suggests that large-scale, multi-modal approaches are the future for weed recognition.

Modeling the growth of diverse microorganisms during feast‐famine enrichment

Polyhydroxyalkanoates (PHAs) are biodegradable polymers that can decrease the severe environmental pollution of petroleum plastics. PHA production by mixed microbial communities has been extensively studied to lower the high PHA prices. However, the competition between distinct microbial communities during the enrichment of PHA accumulators in mixed cultures has not been widely investigated. Thus, in this work, we developed a mathematical model for the competition between PHA accumulators and non-PHA accumulators in the feast-famine enrichment strategy. The developed model successfully simulated published lab-scale experimental data for Plasticicumulans acidivorans, a well-studied PHA accumulator that can store PHA up to 90% of the cell weight. The growth kinetics for both PHA and non-PHA accumulators were estimated and compared to the values in the literature. The uncertainties in the model kinetics were studied by expanding the model to include additional sub-biomass components for each heterotrophic group. As a result, the microbial diversity of microbial communities was observed to influence the enrichment of PHA accumulators in mixed cultures. Additionally, the calibrated model was applied to investigate the cultivation conditions, such as cycle lengths, carbon-to-nitrogen ratio, and solids retention time for successful P. acidivorans enrichment in mixed cultures. The developed model can be applied to control the cultivation and enrichment of PHA accumulators in large-scale PHA production systems. PRACTITIONER POINTS: A new model for the enrichment of PHA accumulators was developed. The model can simulate PHA accumulation by enriched cultures. The model was calibrated and validated for Plasticicumulans acidivorans. The impact of microbial diversity on enriching PHA accumulators was investigated. Short cycles (<12 h) and SRT (<10 d) are suggested for successful enrichment.

Study on performance of a green hydrogen production system integrated with the thermally activated cooling

The energy transition is at the centre of research and development activities with the aim to fight against the effects of global warming. Today, renewable energies play a significant role in the electricity supply to the World and their use increases day after day. Because of the intermittency of a large-scale production system generates the need to develop clean energy storage systems. Hence, energy storage systems play is one of key elements in the energy transition. In this perspective, a green hydrogen is defined as an energy carrier thanks to its high energy density in relation to its negligible mass, not to mention its abundance in our environment, and its extraction, which does not contribute to any greenhouse gases. However, the production cost is not negligible. Hence, this work shows a numerical modelling of the heat balance from a green hydrogen production system using a thermal storage in a Metal Hydride (MH) tank for an electrification by Proton Exchange Membrane (PEM) fuel cell integrated into the production of heating, cooling and sanitary hot water (SHW) through the recovery of the heat released by the whole system combined with the technology of thermally activated cooling of an adsorber. This allows demonstrating that the green hydrogen can be an interesting solution according in the hydrogen production chain and in particular in the tertiary sectors.

The Vinca minor genome highlights conserved evolutionary traits in monoterpene indole alkaloid synthesis.

Vinca minor, also known as the lesser periwinkle, is a well-known species from the Apocynaceae, native to central and southern Europe. This plant synthesizes monoterpene indole alkaloids, which are a class of specialized metabolites displaying a wide range of bioactive- and pharmacologically important properties. Within the almost 50 monoterpene indole alkaloids it produces, V. minor mainly accumulates vincamine, which is commercially used as a nootropic. Using a combination of Oxford Nanopore Technologies long read- and Illumina short-read sequencing, a 679,098 Mb V. minor genome was assembled into 296 scaffolds with an N50 scaffold length of 6 Mb, and encoding 29,624 genes. These genes were functionally annotated and used in a comparative genomic analysis to establish gene families and to investigate gene family expansion and contraction across the phylogenetic tree. Furthermore, homology-based monoterpene indole alkaloid gene predictions together with a metabolic analysis across 4 different V. minor tissue types guided the identification of candidate monoterpene indole alkaloid genes. These candidates were finally used to identify monoterpene indole alkaloid gene clusters, which combined with synteny analysis allowed for the discovery of a functionally validated vincadifformine-16-hydroxylase, reinforcing the potential of this dataset for monoterpene indole alkaloids gene discovery. It is expected that access to these resources will facilitate the elucidation of unknown monoterpene indole alkaloid biosynthetic routes with the potential of transferring these pathways to heterologous expression systems for large-scale monoterpene indole alkaloid production.

Green hydrogen production: Analysis for different single or combined large-scale photovoltaic and wind renewable systems

Hydrogen is a promising energy carrier to provide sustainable energy use throughout the world. Researchers and policy-makers have focused on investigations in three areas of hydrogen-related technologies in the energy market: (1) alternative fuel production based on hydrogen and carbon dioxide; (2) hydrogen injection to the natural gas pipeline networks; (3) usage of hydrogen in transportation applications. One of the most important challenges facing hydrogen technology development is the production of green hydrogen, which can be achieved through water electrolysis coupled with renewable power generation. Although many studies have been conducted, there is still a need for further development, which requires open-source big data and models and standardization of the processes to compare different renewable-based hydrogen production systems. To fill this research gap, the performance of a grid-connected hybrid wind turbine and solar photovoltaic-based water electrolysis systems for large-scale green hydrogen production were investigated. The objective is to propose an accurate methodology to compare wind and solar systems, or hybrid ones, for green hydrogen production worldwide. A large dataset describing the hybrid wind turbine-photovoltaic hydrogen production in various locations was created by performing dynamic simulations using TRNSYS and analyzed using MATLAB and Excel. Several dimensionless indicators were employed and assessed for standardizing the performance evaluation procedure of renewable-based hydrogen production systems, including the electrolyser load portion satisfied by the wind turbine and photovoltaic, the generated wind turbine and photovoltaic energy portion supplied to the electrolyser load and the quantity of energy exported to and imported from the grid. The annual and monthly values of these indicators together with the total amount of green hydrogen production were estimated for 28 global locations. The procedure applied can be easily used to test small-scale applications like residential users or large-scale applications like industrial users, as well as for any hydrogen demand and climatic conditions.

Uses of electro-coagulation-flocculation (ECF) for the pre-concentration of microalgae biomass

The separation of microalgae biomass from diluted cultures found in large-scale production systems is a major challenge for microalgae-related processes. Conventional methods use centrifugation but it requires too much energy (1 kWh/m3), the combination with previous pre-concentration operations such as settling or flotation is needed to reduce this energy consumption. However, both settling and flotation of microalgae biomass require the addition of chemical coagulants/flocculants, thus contaminating the biomass. This work explores the potential use of Electro-Coagulation-Flocculation (ECF) as a method for the pre-concentration of microalgae biomass. Thus, the recovery of freshwater microalgae Scenedesmus almeriensis was studied, both in batch and continuous mode, using this technique to optimize the operating conditions. Data from batch experiments show as a minimum conductivity of 5 mS∙cm−1 is required, the electrical potential of 12 V and current density of 18 mA∙cm−2 allowing for the recovery of 90 % of the biomass, while the biomass recovery increases up to 99 % when increasing the current density to 23 mA∙cm−2. The efficiency of the process increases when increasing the biomass concentration, thus energy consumption reduces by half from 1.0 to 0.5 kWh∙Kg−1 when the biomass concentration increases from 2.8 to 5.0 g∙L−1. To optimize the performance of the system experiments were performed in continuous mode maintaining the voltage and current density at 12 V and 47 mA∙cm−2 respectively, but modifying the flow rate and biomass concentration provided to the electrocoagulation chamber. Data shows as the optimal residence time is 15 s whereas the energy consumption reduces from 3.2 to 0.58 kWh∙Kg−1 when increasing the biomass concentration from 0.75 to 4.20 g∙L−1. Results confirm the reliability of this method for the pre-concentration of microalgae biomass, it being a fast process consuming reasonable energy. Further optimization of the electrocoagulation chamber and electrical conditions will improve the efficiency of this system for further commercial processes while keeping its major advantages of non-contaminating the biomass and allowing to achieve high biomass recovery values in short times.

Synthetic-Gas Production through Chemical Looping Process with Concentrating Solar Dish: Temperature-Distribution Evaluation

The energy crisis and the adaptation of the global energy structure promote the development of renewable energies, in particular solar energy, also for syngas production. In this work, attention was focused on solar devices, necessary to provide high-temperature heat for the reduction reaction of metal oxides involved in the chemical looping driven by solar energy. Thermochemical processes for synthetic-gas production and CO2 sequestration were investigated using a concentrating solar thermal system. This paper proposes a useful forecasting model of the receiver temperature to make a realistic estimate of the system’s producibility for the different periods of the year. The model proposed was validated in the winter season, and the predicted temperature varied below 5% considering the real experimental data (442–472 °C). The validated model was used to evaluate the temperature receiver in spring and in summer, when the thermal level is reliable for thermochemical processes. From the spring season until the completion of the summer season, optimum conditions inside the receiver were reached (above 1000 °C). These preliminary findings could be used for the development of large-scale production systems.

Exploration of the Mechanisms of Differential Indole Alkaloid Biosynthesis in Dedifferentiated and Cambial Meristematic Cells of Catharanthus roseus Using Transcriptome Sequencing.

Catharanthus roseus produces terpenoid indole alkaloids (TIAs) of high medicinal importance. The current research focuses on finding an efficient production system such as cell suspension cultures for high TIA concentrations. Catharanthus roseus cambial meristematic cells (CMCs) offer multiple advantages over dedifferentiated cells (DDCs) regarding growth, homogeneity, and shear resistance. Our lab has established a CMC culture system induced by C. roseus cambium. We determined the concentrations of TIAs in CMCs and DDCs. CMCs produced significantly higher concentrations of total alkaloids, vindoline, vinblastine, catharanthine, and ajmalicine as compared to DDCs. We then performed Illumina HiSeq transcriptome sequencing of CMCs and DDCs and explored the differential transcriptomic signatures. Of the 96,004 unigenes, 9,564 were differentially expressed between the 2 cell suspension types. These differentially expressed genes (DEGs) were enriched in 137 KEGG pathways. Most importantly, genes from the indole alkaloid biosynthesis and the upstream pathways i.e., tryptophan metabolism, monoterpenoid biosynthesis, tropane, piperidine, and pyridine alkaloid biosynthesis, and terpenoid backbone biosynthesis showed differential transcriptomic signatures. Remarkably, the expression of genes associated with plant hormone biosynthesis, signaling, and MAPK signaling pathways was relatable to the different TIA concentrations in CMCs and DDCs. These results put forward multiple target genes, transcription factors, and regulators to develop a large-scale TIA production system using C. roseus CMCs.

Metabolomics for Agricultural Waste Valorization: Shifting Toward a Sustainable Bioeconomy.

Agriculture has been considered as a fundamental industry for human survival since ancient times. Local and traditional agriculture are based on circular sustainability models, which produce practically no waste. However, owing to population growth and current market demands, modern agriculture is based on linear and large-scale production systems, generating tons of organic agricultural waste (OAW), such as rejected or inedible plant tissues (shells, peels, stalks, etc.). Generally, this waste accumulates in landfills and creates negative environmental impacts. The plant kingdom is rich in metabolic diversity, harboring over 200,000 structurally distinct metabolites that are naturally present in plants. Hence, OAW is considered to be a rich source of bioactive compounds, including phenolic compounds and secondary metabolites that exert a wide range of health benefits. Accordingly, OAW can be used as extraction material for the discovery and recovery of novel functional compounds that can be reinserted into the production system. This approach would alleviate the undesired environmental impacts of OAW accumulation in landfills, while providing added value to food, pharmaceutical, cosmetic, and nutraceutical products and introducing a circular economic model in the modern agricultural industry. In this regard, metabolomics-based approaches have gained increasing interest in the agri-food sector for a variety of applications, including the rediscovery of bioactive compounds, owing to advances in analytical instrumentation and data analytics platforms. This mini review summarizes the major aspects regarding the identification of novel bioactive compounds from agricultural waste, focusing on metabolomics as the main tool.

The effects of soil properties, cropping systems and geographic location on soil prokaryotic communities in four maize production regions across China

The diversity of prokaryotic communities in soil is shaped by both biotic and abiotic factors. However, little is known about the major factors shaping soil prokaryotic communities at a large scale in agroecosystems. To this end, we undertook a study to investigate the impact of maize production cropping systems, soil properties and geographic location (latitude and longitude) on soil prokaryotic communities using metagenomic techniques, across four distinct maize production regions in China. Across all study sites, the dominant prokaryotes in soil were Alphaproteobacteria, Gammaproteobacteria, Betaproteobacteria, Gemmatimonadetes, Acidobacteria, and Actinobacteria. Non-metric multidimensional scaling revealed that prokaryotic communities clustered into the respective maize cropping systems in which they resided. Redundancy analysis (RDA) showed that soil properties especially pH, geographic location and cropping system jointly determined the diversity of the prokaryotic communities. The functional genes of soil prokaryotes from these samples were chiefly influenced by latitude, soil pH and cropping system, as revealed by RDA analysis. The abundance of genes in some metabolic pathways, such as genes involved in microbe–microbe interactions, degradation of aromatic compounds, carbon fixation pathways in prokaryotes and microbial metabolism were markedly different across the four maize production regions. Our study indicated that the combination of soil pH, cropping system and geographic location significantly influenced the prokaryotic community and the functional genes of these microbes. This work contributes to a deeper understanding of the composition and function of the soil prokaryotic community across large-scale production systems such as maize.

Strain Construction and Process Development for Efficient Recombinant Production of Mannuronan C-5 Epimerases in Hansenula polymorpha.

Alginates are linear polysaccharides produced by brown algae and some bacteria and are composed of β-D-mannuronic acid (M) and α-L-guluronic acid (G). Alginate has numerous present and potential future applications within industrial, medical and pharmaceutical areas and G rich alginates are traditionally most valuable and frequently used due to their gelling and viscosifying properties. Mannuronan C-5 epimerases are enzymes converting M to G at the polymer level during the biosynthesis of alginate. The Azotobacter vinelandii epimerases AlgE1-AlgE7 share a common structure, containing one or two catalytic A-modules (A), and one to seven regulatory R-modules (R). Despite the structural similarity of the epimerases, they create different M-G patterns in the alginate; AlgE4 (AR) creates strictly alternating MG structures whereas AlgE1 (ARRRAR) and AlgE6 (ARRR) create predominantly G-blocks. These enzymes are therefore promising tools for producing in vitro tailor-made alginates. Efficient in vitro epimerization of alginates requires availability of recombinantly produced alginate epimerases, and for this purpose the methylotrophic yeast Hansenula polymorpha is an attractive host organism. The present study investigates whether H. polymorpha is a suitable expression system for future large-scale production of AlgE1, AlgE4, and AlgE6. H. polymorpha expression strains were constructed using synthetic genes with reduced repetitive sequences as well as optimized codon usage. High cell density cultivations revealed that the largest epimerases AlgE1 (147 kDa) and AlgE6 (90 kDa) are subject to proteolytic degradation by proteases secreted by the yeast cells. However, degradation could be controlled to a large extent either by co-expression of chaperones or by adjusting cultivation conditions. The smaller AlgE4 (58 kDa) was stable under all tested conditions. The results obtained thus point toward a future potential for using H. polymorpha in industrial production of mannuronan C-5 epimerases for in vitro tailoring of alginates.

South–South Cooperation in Agriculture: Impacts of Brazil’s More Food International Program on Post-Land Reform Social Organizations in Zimbabwe

South–South Cooperation has received significant attention. This article assesses the implications of Brazil’s More Food International on farm-level social organizations in Goromonzi and Mvurwi districts in Zimbabwe. Data was collected using mainly focus group discussions, key-informant interviews, and the application of a questionnaire among 410 farming households. Differentiated implications and outcomes were observed between the two districts. Overall, the Brazilian programs improved access to tractor and irrigation implements. Still, the implements were more suited to the large-scale production systems rather than to those of the small-scale A1 farmers. Furthermore, a top-down approach utilized by the state has adverse consequences. The prerequisite of forming cooperatives before accessing the tractors and irrigation implements disrupted local political and socio-economic organizations already in existence within the two districts. The study concludes that, while farm mechanization is crucial for agricultural production, the exclusion of the farmers during policy conceptualization undermines the success of these programs.

Cellular Automata Machine Modeling to obtain optimal conditions and productivity of microalgae biomass

Microalgae is a promising source of superior biomass for sustainable food sources, high value products, and 3rd generation biofuel. The main factors affecting growth, carbon fixation and biomass production of microalgae are species type, CO2 supply, nutrients, light, temperature, pH and mixing. This paper discusses the precision farming approach in microalgae biomass production using the Cellular Automata Machine modeling, i.e., Probabilistic Cellular Automata. Cellular Automata is a decentralized computing model that provides a useful platform to model the complex dynamic systems such as growth of cells. The application of this method on a large-scale microalgae production system can simulate and model the characteristics of microalgae growth and biomass. In conclusion, the Biological Lattice Gas Cellular Automaton (BIO-LGCA) has been proposed as modeling tools to obtain the optimal conditions and maximum productivity in microalgae biomass production.

Cost-effective Purification of Membrane Proteins using a Dual-detergent Strategy.

Understanding the mechanisms of membrane protein function is critical for biomedical research and drug discovery as membrane proteins constitute ∼30% of the proteins encoded by the genomes of both lower and higher organisms and are targets for two-thirds of approved drugs worldwide. Significant progress has been made in engineering host expression systems for large-scale production of membrane proteins and in determining their three-dimensional high-resolution structures. Despite these efforts, the study of membrane proteins at the atomic level is challenging due to poor expression and extraction, low yields of functional protein, and the complexity and heterogeneity of source membranes. Structural and spectroscopic studies of any membrane protein require that the protein be extracted from its native membranes into a membrane-mimetic stable environment, which is often achieved by the use of detergents. Unfortunately, there is no magic detergent that can extract all membrane proteins and successful extraction often requires a thorough screen of detergents. Furthermore, membrane protein purification in general and the detergents used are very expensive, which puts a financial constraint on sophisticated membrane protein studies. To overcome this hurdle, a dual-detergent strategy has recently been developed and successfully applied to purify various classes of pure, stable, and functionally relevant membrane proteins in a cost-effective manner. This strategy uses an inexpensive detergent for solubilization of the desired protein from membranes and a second detergent during protein purification. In the Basic Protocol, we describe the dual-detergent strategy to significantly reduce the overall purification cost of a bacterial membrane protein using the magnesium ion channel MgtE as an example. Support Protocols are also provided for selecting a suitable E. coli strain for protein expression and the optimal detergent(s) for membrane protein solubilization. © 2022 Wiley Periodicals LLC. Basic Protocol: Expression, membrane solubilization, and cost-effective purification of MgtE Support Protocol 1: Selecting a suitable E. coli strain for optimal protein expression Support Protocol 2: Identification of suitable detergents for membrane protein solubilization.

Dextran sulfate prevents excess aggregation of human pluripotent stem cells in 3D culture by inhibiting ICAM1 expression coupled with down-regulating E-cadherin through activating the Wnt signaling pathway

BackgroundHuman pluripotent stem cells (hPSCs) have great potential in applications for regenerative medicine and drug development. However, 3D suspension culture systems for clinical-grade hPSC large-scale production have been a major challenge. Accumulating evidence has demonstrated that the addition of dextran sulfate (DS) could prevent excessive adhesion of hPSCs from forming larger aggregates in 3D suspension culture. However, the signaling and molecular mechanisms underlying this phenomenon remain elusive.MethodsBy using a cell aggregate culture assay and separating big and small aggregates in suspension culture systems, the potential mechanism and downstream target genes of DS were investigated by mRNA sequence analysis, qRT-PCR validation, colony formation assay, and interference assay.ResultsSince cellular adhesion molecules (CAMs) play important roles in hPSC adhesion and aggregation, we assumed that DS might prevent excess adhesion through affecting the expression of CAMs in hPSCs. As expected, after DS treatment, we found that the expression of CAMs was significantly down-regulated, especially E-cadherin (E-cad) and intercellular adhesion molecule 1 (ICAM1), two highly expressed CAMs in hPSCs. The role of E-cad in the adhesion of hPSCs has been widely investigated, but the function of ICAM1 in hPSCs is hardly understood. In the present study, we demonstrated that ICAM1 exhibited the capacity to promote the adhesion in hPSCs, and this adhesion was suppressed by the treatment with DS. Furthermore, transcriptomic analysis of RNA-seq revealed that DS treatment up-regulated genes related to Wnt signaling resulting in the activation of Wnt signaling in which SLUG, TWIST, and MMP3/7 were highly expressed, and further inhibited the expression of E-cad.ConclusionOur results demonstrated that DS played an important role in controlling the size of hPSC aggregates in 3D suspension culture by inhibiting the expression of ICAM1 coupled with the down-regulation of E-cad through the activation of the Wnt signaling pathway. These results represent a significant step toward developing the expansion of hPSCs under 3D suspension condition in large-scale cultures.

Fertilizer type and humic acid improve the growth responses, nutrient uptake, and essential oil content on Coriandrum sativum L.

In recent decades, the over-use of chemical fertilizers has imposed many environmental challenges worldwide. Nowadays, organic fertilizers such as vermicompost and livestock manure have gained a huge interest in sustainable agricultural systems. A 2-year field research was conducted as factorial based on a randomized complete block design to assay the fertilizer and humic acid (HA) efficiency on the growth responses and essential oil composition of Coriandrum sativum. The treatments were different fertilizer sources (livestock manure, vermicompost, and chemical fertilizers) and humic acid fertigation before and at the beginning of the flowering stage. The highest protein content was observed under vermicompost × HA application before flowering (0.118 μmol L−1 and 0.128 μmol L−1, respectively). Moreover, the co-application of organic fertilizers × HA at the beginning of flowering resulted in a significant increase in the photosynthetic pigments and N, P, K, Fe, Zn, and Mn content. According to the GC-FID and GC–MS analysis, linalool (55.91–63.19%), γ-terpinene (4.65–6.13%), α-pinene (2.64–5.74%), geranyl acetate (3.49–5.51%), 2-dodecanal (2.92–4.46%), menthol (1.33–3.90%), p-cymene (1.73–2.24%), and geraniol (1.25–2.15%) were the main essential oil constituents. The top linalool content was obtained by using chemical fertilizers and vermicompost × HA at the flowering onset stage. In general, the results revealed that chemical fertilizers could be replaced with vermicompost × HA and their co-application positively influenced the growth responses and the essential oil composition of coriander. Furthermore, the results obtained would be advisable to the extension section and the pioneer farmers to amend the large-scale production systems in favor of environmental health.

Biomass-derived carbons physically activated in one or two steps for CH4/CO2 separation

The present study aims at evaluating the suitability of producing activated carbons (ACs) derived from wheat straw by a one-step synthesis approach, as an alternative to more conventional two steps production processes (i.e., pyrolysis and subsequent activation). The performance of the produced ACs, in one or two steps, as sustainable and selective CO2 adsorbents for CH4/CO2 separation is compared. In addition, the influence of pyrolysis conditions on the properties of the resulting two-step ACs is carefully analyzed. We show that the biochar-based precursors of ACs presenting the best textural properties were obtained under mild conditions of maximum temperature and absolute pressure during pyrolysis. The one-step ACs were fully comparable —in terms of textural properties as well as CO2 uptake and selectivity— to those produced by the more conventional two-step synthesis process. In addition, results obtained from breakthrough curve simulations highlight that the best AC in terms of CH4 recovery under dynamic conditions was produced by a one-step activation. Therefore, the one-step process appears to be as an attractive route for the production of engineered carbon materials, which can lead to significant cost savings in large-scale production systems.

Potential Use of Quartzipisamment under Agroforestry and Silvopastoral System for Large-Scale Production in Brazil

The need to put into practice sustainable agricultural production systems has been supported by agroecology science that seeks to optimize land use to food production with the lowest impact on soil. This study evaluated soil quality, based on physical and chemical attributes, in agroforestry (AGF) and silvopastoral (SILVP) systems developed for large-scale food production. The study was carried out in the municipality of Itirapina, state of São Paulo, in two areas with AGF and SILVP system, compared to an area with a forest fragment and another with pasture in a Quartzipisamment Sand Neosol. The soil collections were carried out in the layers of 0.00–0.05, 0.05–0.10, 0.10–0.20, and 0.20–0.40 m, where physical soil attributes were evaluated (total porosity, microporosity, and microporosity, density, mean diameter of aggregates) as well as chemical attributes (macro- and micronutrients), in addition to carbon and nitrogen storage. To interpret the data, Tukey’s test was applied to compare means, and principal component analysis was used to better characterize the study environments. The results showed that agroforestry and silvopastoral systems developed for large-scale production are efficient in improving chemical and physical attributes that reflect on soil quality, especially in the superficial layers of the soil, overcoming pasture and the natural regeneration process. Carbon and nitrogen storage were the main variables that differentiated the production systems, highlighting the importance of the AGF and SILVP systems as more sustainable agricultural intensification strategies, even in soils of low agricultural suitability.