A Simulation Analysis of a Microalgal-Production Plant for the Transformation of Inland-Fisheries Wastewater in Sustainable Feed

The present research evaluates the simulation of a system for transforming inland-fisheries wastewater into sustainable fish feed using Designer® software. The data required were obtained from the experimental cultivation of Chlorella sp. in wastewater supplemented with N and P. According to the results, it is possible to produce up to 11,875 kg/year (31.3 kg/d) with a production cost of up to 18 (USD/kg) for dry biomass and 0.19 (USD/bottle) for concentrated biomass. Similarly, it was possible to establish the kinetics of growth of substrate-dependent biomass with a maximum production of 1.25 g/L after 15 days and 98% removal of available N coupled with 20% of P. It is essential to note the final production efficiency may vary depending on uncontrollable variables such as climate and quality of wastewater, among others.

A Modeling and Analysis Framework for Integrated Energy Systems Exposed to Climate Change-Induced NaTech Accidental Scenarios

This paper proposes a novel framework for the analysis of integrated energy systems (IESs) exposed to both stochastic failures and “shock” climate-induced failures, such as those characterizing NaTech accidental scenarios. With such a framework, standard centralized systems (CS), IES with distributed generation (IES-DG) and IES with bidirectional energy conversion (IES+P2G) enabled by power-to-gas (P2G) facilities can be analyzed. The framework embeds the model of each single production plant in an integrated power-flow model and then couples it with a stochastic failures model and a climate-induced failure model, which simulates the occurrence of extreme weather events (e.g., flooding) driven by climate change. To illustrate how to operationalize the analysis in practice, a case study of a realistic IES has been considered that comprises two combined cycle gas turbine plants (CCGT), a nuclear power plant (NPP), two wind farms (WF), a solar photovoltaicS (PV) field and a power-to-gas station (P2G). Results suggest that the IESs are resilient to climate-induced failures.

Application of Extremophiles in Sustainable Agriculture

With the increasing demands for foods and other agriculture-based products, sustainable agricultural practices are the cornerstone for improving low-input agricultural production. In contrast to crop production, plant-microorganism interaction (PMI) plays a crucial role. PMI significantly raises productivity as well as maintaining the overall health of the crop. During harsh and extreme physiological conditions, plant-associated extremophilic microbes (PAEM) are known to contribute to crop production, survivability, and fitness. Thus, the application of extremophiles either in the form of biofertilizer or biopesticides is highly beneficial. Extremophiles have been adapted to withstand diverse harsh environmental conditions. They possess unique mechanisms at the molecular level to produce enormous potential extremozymes and bioactive compounds. Consequently, extremophiles represent the foundation of efficient and sustainable agriculture. This chapter introduces the significance and application of plant-associated extremophilic microbes in sustainable agriculture.

Detection and Classification of Leaf Disease Using Deep Neural Network

Modern technologies have improved their application in field of agriculture in order to improve production. Plant diseases are harmful to plant growth, which leads to reduced quality and quantity of crop. Early identification of plant disease will reduce the loss of the crop productivity. So, it is necessary to identify and diagnose the disease at an early stage before it spreads to the entire field. In this chapter, the proposed model uses VGG16 with attention mechanism for leaf disease classification. This model makes use of convolution neural network which consist of convolution block, max pool layer, and fully connected layer with softmax as an activation function. The proposed approach integrates CNN with attention mechanism to focus more on the diseased part of leaf and increase the classification accuracy. The proposed model design is a novel deep learning model to perform the fine tuning in the classification of nine different type of tomato plant disease.

IDENTIFICATION OF SOME ROOTSTOCKS FOR WATERMELON CULTURES FROM ROMANIA

Among the grafting aims are (1) to enhance plant growth, fruit yield and quality; (2) to control wilt caused by pathogens; (3) to reduce viral, fungal and bacterial infection; (4) to strengthen tolerance to thermal or saline stress; (5) to increase nutrient and mineral uptake to the shoot. The cultivars used to obtain of grafted seedlings were from the Baronesa F1 (Citrullus lanatus) hybrid scion and the Pelops F1 (Lagenaria siceraria), Kiwano (Cucumis metuliferus) and Zefir (Benicasa hispida) rootstocks. The rootstock has influenced the number of fruits per plant, weight/fruit and production/plant; the Pelops rootstock has had a positive influence and the Kiwano and Zefir rootstocks have had a negative influence compared to the non-grafted variant. The Pelops rootstock (105.84 t/ha) has had a positive influence and the Kiwano rootstock (53.45 t/ha) and Zefir rootstock (51.38 t/ha) have had have a negative influence compared to the non-grafted variant (95.5 t/ha). The biometric measurements on watermelon fruit yield were made in 2020 year. The experience aimed the identification of some rootstocks for the watermelon cultures from Romania. The research shows that the rootstocks has influenced fruit yield and some grafting combinations researched may be recommended for cropping in Romania.

Process Simulation Integrated Life Cycle Net Energy Analysis and GHG Assessment of Fuel-Grade Bioethanol Production from Unutilized Rice Straw

The life cycle stage of paddy rice cultivation can be excluded with a zero-inventory allocation rule for the life cycle scenario of bioethanol production from unutilized rice straw, i.e., rice straw with no applied valorization in current practice. Accordingly, this study evaluates the life cycle net energy analysis and greenhouse gas (GHG) assessment for a scaled-up bioethanol production plant using unutilized rice straw as the feedstock. The process simulation technique is integrated to model a scaled-up production plant to produce bioethanol at 99.7 vol% purity from unutilized rice straw, and the simulation results are retrieved to calculate inventory data for life cycle assessment (LCA). The simulated mass flow and energy flow results are comparable with that of real plants, reported in the published literature, which validates the process simulations in this study. Inclusive of energy generation using the waste flows in the process (i.e., wastewater and solid residues), the life cycle net energy analysis results show a net energy gain of 7,804.0 MJ/m3 of bioethanol with a net renewable energy gain of 38,230.9 MJ/m3 of bioethanol that corresponds to a net energy ratio of 1.20 and renewability factor of 5.49. The life cycle GHG assessment exhibits a net global warming potential of 584.8 kg CO2 eq./m3 of bioethanol. The effect of system boundary expansion up to the end-of-life stage as gasohol (E10), the sensitivity of the key process parameters, and the economic benefit via valorization of unutilized rice straw are further analyzed and discussed.

Experiences in long-term operation of a green hydrogen production plant using wind power in Germany - a possible model for Vietnam

Hydrogen is considered as "the green fuel of the 21st century" and forecasted to play a leading role in the energy transition. The article introduces the processes of green hydrogen production in Energiepark Mainz, the first wind power hydrogen production plant with a capacity of 6 MW in Germany. The article describes the production, storage, transportation, and consumption (gas, fuel for bus and industries) of green hydrogen through the continuous operation of the plant. Based on that, the author analyses opportunities and challenges when applying Energiepark Mainz's model to the green hydrogen production strategy in Vietnam.

A Simulation Analysis of an Influenza Vaccine Production Plant in Areas of High Humanitarian Flow. A Preliminary Study for the Region of Norte de Santander (Colombia)

The production of vaccines of biological origin presents a tremendous challenge for researchers. In this context, animal cell cultures are an excellent alternative for the isolation and production of biologicals against several viruses, since they have an affinity with viruses and a great capacity for their replicability. Different variables have been studied to know the system’s ideal parameters, allowing it to obtain profitable and competitive products. Consequently, this work focuses its efforts on evaluating an alternative for producing an anti-influenza biological from MDCK cells using SuperPro Designer v8.0 software. The process uses the DMEN culture medium supplemented with nutrients as raw material for cell development; the MDCK cells were obtained from a potential scale-up with a final working volume of 500 L, four days of residence time, inoculum volume of 10%, and continuous working mode with up to a total of 7400 h/Yr of work. The scheme has the necessary equipment for the vaccine’s production, infection, and manufacture with yields of up to 416,698 units/h. In addition, it was estimated to be economically viable to produce recombinant vaccines with competitive prices of up to 0.31 USD/unit.