Este estudo é apoiado por um programa de NSF (Investigação Experiências para alunos de graduação) na Universidade de Washington em St. Louis.

1. O cultivo de algas e Scale-up <ol><li> Preparar o meio de cultura usando água desionizada contendo 0,55 g / L -1 ureia, 0,1185 g / L -1 KH 2 PO 4, 0,102 g / L -1 MgSO4 · 7H 2 O 0,015 g / L de FeSO4 · -1 7H 2 O e 22,5 microelementos ul (18,5 g / L -1 H 3 BO 3, 21,0 g / L -1 CuSO4 · 5H 2 O, 73,2 g / L -1 MnCl2 · 4H 2 O, 13,7 g / L -1 CoSO 4 · 7H 2 O, 59,5 g / L -1 ZnSO4 · 5H 2 O, 3,8 g / L -1 (NH 4) 6 Mo 7 O 24 · 4H 2 O, 0,31 g / L -1 NH 4 VO 3 ). Ajustar pH do meio para 7-8. Esterilizar o meio de cultura através de filtro de seringa de 0,22 um. </li><li> Inocular Chlorella sp. a partir de uma única colônia em uma placa de ágar fresco em uma agitação flask contendo 50 ml de meio com uma ansa de inoculação estéril. Algas Cultura sob 150 rpm e 30 ° C durante seis dias (condição de luz contínua, de fluxo de fótons = 40-50 mol m -2 s -1). Monitorar a densidade celular por um espectrofotómetro (OD 730). </li><li> Transferir 50 ml de cultura de algas (fase de crescimento meio-log, OD 730&gt; 1) em um balão de vidro de 2-L (com ~ 1 L esterilizado meio de cultura). Bomba de ar filtrado (ou CO 2) para a cultura durante a incubação (durante 5 dias). </li><li> Transferência de 1 L de cultura de algas num garrafão de 20 L contendo 15 L de vidro médio não-esterilizado a cultura (nesta fase, o risco de contaminação microbiana é pequeno), então a cultura de algas sob a mesma condição como indicado no passo 1.3. </li><li> Coloque 15 L de cultura fresco algal (OD 730 = 2) e 85 L meio não esterilizado em uma placa plana photobioreactor (equipado com diodos emissores de luz, controlador do computador, mistura de gás, analisadores de densidade óptica celular, pH, dissolvido oxigen, temperatura e dissolveu-se CO 2). Bomba de gás de mistura ar / combustão no bioreactor. </li><li> Completamente seco limpa o photobioreactor utilizando etanol 70% após a colheita da biomassa (OD 730&gt; 20). </li></ol> 2. Demonstração Laboratório de Tratamento de Gás de combustão usando pequenos fotobioreatores <ol><li> Inocular culturas de algas em garrafas de vidro (200 ml / min médio / garrafa, OD inicial 730 ~ 0,3). </li><li> Queimar gás natural e bombear o gás de combustão (~ 250 cm 3 min -1) através de um funil, um tubo de condensador, e um frasco de 0,5 L de lavagem (contendo lama de água / calcário). </li><li> Os controladores de fluxo de massa de controlar o fluxo do gás de combustão para a cultura de algas (Figura 1). Pulsos de gases de combustão incluem dois modos: gás-em combustão e combustão de gás-off (bombear ar em seu lugar). </li></ol> 3. Modelo de Desenvolvimento Kinetic O modelo cinético assume: (1) as culturas são o sistema homogêneos. (2) concentração de CO 2 e de intensidade de luz nas culturas são fatores limitantes para o crescimento de algas. (3) CO 2 pressão parcial e o seu equilíbrio de fase líquida com H 2 CO 3, HCO 3 -, e CO 3 2 - é simplificada com a Lei de Henry). As equações do modelo são: <img alt="Equações 1 e 2" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq1and2.jpg" width="500px" /> X é a biomassa (kg m-3). S é o CO 2 dissolvido (mol · m -3). P é a pressão parcial de CO2 na fase gasosa (Pa). p é a pressão parcial do i th composto tóxico nos gases (tais como NOx e SOx). P max.i é a pressão parcial de um gás tóxico para uma inibição completa do crescimento de biomassa. η i é o coeficiente empírico. K s é a constante de Michaelis-Mentende CO 2 (mol · m -3). K I é a constante de inibição de CO 2 (mol · m -3). K é a constante de Michaelis-Menten da intensidade da luz (umol · · m -2 s -1). H é constante o de Henry para o CO 2 (Pa · m 3 · mol -1). La K é a taxa de transferência de massa de CO 2 (-1 h). I é a intensidade média da luz, umol · · m -2 s -1, a qual pode ser calculada como se segue (Equação (3)) 9. <img alt="Equação 3" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq3.jpg" width="500px" /> A definição dos parâmetros do modelo, é apresentada no Quadro 1. As condições iniciais para assumir que a biomassa e CO 2 dissolvido concentrações são de 100 mg / L e 13 mmol / L, respectivamente. O coeficiente de transferência de massa volumétrica pode ser estimada pela correlação empíricação ao biorreactor parâmetros 10: <img alt="Equação 4" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq4.jpg" width="500px" /> P g / V é o consumo de energia do sistema arejada no bioreactor (W / m 3). u gs é a velocidade superficial do fluxo de gás através do bioreactor (m / seg). α, β e γ são constantes relacionadas com condições de mistura. <ol><li> Construir um arquivo Simulink para a simulação do modelo (capturas de tela são apresentados no material de apoio I). <ol><li> Escolha Arquivo / Novo / Modelo na interface MATLAB para criar um modelo Simulink, e aberto &quot;Browser Library&quot; (tela 1). </li><li> Escolha bloco &#39;Subsystem&#39; no navegador da biblioteca para criar os subsistemas para Equação 1 e 2. Arraste um bloco de subsistema para o arquivo de modelo Simulink, mudar seu nome para &quot;Equação 1&quot;, e, em seguida, repita os mesmos passos para a Equação 2. </li><li&gt; Criar blocos e parâmetros adequados em cada subsistema (tela 3). Clique bloco a &quot;Equação 1&quot;, escolha blocos apropriados a partir do navegador da biblioteca e conectá-los com setas que indicam a seqüência de cálculo, clique duas vezes os blocos para configurar os parâmetros, e repita essas etapas para o outro subsistema duplo. Nota: 1) A sequência deve começar com blocos de entrada e concluir com blocos de saída, 2) Os blocos de operador para adição, subtração, multiplicação, divisão e integração podem ser todos encontrados no navegador da biblioteca, e sugerimos aos usuários explorar os arquivos de ajuda do o Simulink para entender como usá-los, 3) O solucionador de otimização pode ser definido através de parâmetros via Simulação / Configuração na barra de ferramentas. </li><li> Ligar os dois subsistemas para representar equações do modelo (1 e 2). Ligue a saída de um subsistema para a entrada do outro subsistema pela seta, se necessário. Por exemplo, a concentração de CO 2 dissolvido é ooutput na Equação 2 subsistema, e também a entrada do subsistema Equação 1. </li><li> Use &#39;Pulse Generator&#39; bloco como as entradas para &quot;Equação 2 &#39;para simular os pulsos de CO 2 on-off, use block&#39; constante &#39;, como o valor de entrada de luz de superfície. Clique duas vezes os blocos para alterar os parâmetros, tais como o período de tempo e amplitude. </li><li> Escolha bloco &#39;Mux &quot;no navegador da biblioteca. Ligue todas as saídas para &quot;Mux&quot; e, em seguida, conectá-lo ao &#39;Para Workspace&#39; bloco que armazena os resultados simulados. </li><li> Defina o &quot;tempo de parada de simulação&quot; na barra de ferramentas superior, clique no botão &quot; <img src="/files/ftp_upload/50718/playarrow.jpg" alt="Seta" width="10px" fo:content-width="0.1in" fo:src="/files/ftp_upload/50718/playarrow.jpg" /> &quot;Para iniciar a simulação e os resultados serão mostrados na área de trabalho do MATLAB (tela 4). </li></ol></li><li> Aplicar abordagem de otimização dinâmica para o perfil ideal de CO 2 condições. </li&gt; </ol> Para encontrar as mudanças de entrada de fluxo de CO 2 perfil (P opt) que maximizam a produção de biomassa 11, a função MATLAB &#39;fmincon&#39; e CVP (controle de vetores parametrização) 12 são usados. Figura 2 ilustra o algoritmo de otimização (ver códigos de programação MATLAB no Coadjuvante Material III).

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Neste estudo, demonstramos o protocolo experimental para a ampliação cultivos de algas em fotobiorreatores. Também examinamos vários métodos para entradas de gases de combustão para promover o crescimento de algas. Usando um modelo de transferência de massa e de bio-reacção, que demonstram que o coeficiente de transferência de massa de CO 2 K La (determinado por biorreactor mistura condição e CO 2 velocidade superficial) influencia fortemente o crescimento de algas. A simulaç...

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	<tbody>
		<tr height="21"> 
			<td height="21" style="height:21px;width:212px;">Spectrophotometer</td>
			<td style="width:212px;">Thermal Scientific, Texas USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">CO2 gas analyzer</td>
			<td style="width:212px;">LI-COR, Biosciences, Nebraska USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">Mass flow controllers</td>
			<td style="width:212px;">OMEGA Engineering INC, Connecticut USA</td>
			<td style="width:212px;">FMA5416</td>
		</tr>
		<tr height="58">
			<td height="58" style="height:58px;width:212px;">Data acquisition card</td>
			<td style="width:212px;">Measurement Computing Corporation, Massachusetts USA</td>
			<td style="width:212px;">USB-1208FS</td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">Filters</td>
			<td style="width:212px;">Aerocolloid LLC, Minnesota USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">MATLAB/Simulink</td>
			<td style="width:212px;">Mathworks, Massachusetts USA</td>
			<td style="width:212px;">R2010a</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:212px;">Glass bottles</td>
			<td style="width:212px;">Fisher USA</td>
			<td style="width:212px;"> </td>
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optimize flue gas settings to promote microalgae growth in photobioreactors via computer simulations

De gases de combustão das usinas pode promover o cultivo de algas e reduzir as emissões de gases de efeito de estufa 1. As microalgas não só captar a energia solar de forma mais eficiente do que as plantas 3, mas também sintetizam biocombustíveis avançados 2-4. Geralmente, CO 2 atmosférico não é uma fonte suficiente para suportar o crescimento de algas máxima 5. Por outro lado, as elevadas concentrações de CO 2 nos gases de escape industriais têm efeitos adversos sobre a fisiologia das algas. Consequentemente, ambas as condições de cultura (tais como nutrientes e luz) e o controlo do fluxo dos gases de combustão para os foto-biorreatores são importantes para o desenvolvimento de um &quot;gás de combustão para as algas&quot; eficiente do sistema. Os pesquisadores propuseram diferentes configurações photobioreactor 4,6 e estratégias de cultivo 7,8 com gás de combustão. Aqui, apresentamos um protocolo que demonstra como usar modelos para prever o crescimento de microalgas em resposta a tarrafa configurações de gás. Nós perfORM ambos ilustração e modelo simulações experimentais para determinar as condições favoráveis ​​para o crescimento de algas, com gás de combustão. Desenvolvemos um modelo baseado em Monod, juntamente com a transferência de massa e as equações de intensidade de luz para simular o crescimento de microalgas em uma foto-biorreator homogênea. A simulação do modelo de crescimento e compara combustão algas consumos de gás sob diferentes configurações de combustão a gás. O modelo ilustra: 1) como o crescimento de algas é influenciada por diferentes coeficientes de transferência de massa volumétrica de CO 2, 2) como podemos encontrar ótima concentração de CO 2 para o crescimento de algas, através da abordagem de otimização dinâmica (DOA), 3) como podemos projetar um rectangular on-off de impulsos de gás de combustão para promover o crescimento da biomassa das algas e para reduzir o uso de gás de combustão. No lado experimental, apresentamos um protocolo para o cultivo de Chlorella sob o gás de combustão (gerada pela combustão do gás natural). Os resultados experimentais qualitativamente validar as previsões do modelo que o gás de combustão de alta freqüência puLSEs pode melhorar significativamente o cultivo de algas.

Nossa análise experimental anterior indica que a exposição de gases de combustão contínua afeta negativamente o crescimento Chlorella, ao diminuir o tempo de exposição CO 2 é capaz de aliviar esta inibição 13. Para entender melhor o fluxo dos gases de combustão e relacionamento crescimento de algas, desenvolvemos um modelo empírico para simular o crescimento da biomassa na presença de gases de combustão. Assumimos que o gás de combustão contém 15% de CO 2 (nota:...

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Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

De gases de combustão das usinas é um barato CO 2 fonte para o crescimento de algas. Nós construímos &quot;gás de combustão para cultivo de algas&quot; protótipo sistemas e descreveu como para ampliar o processo de cultivo de algas. Demonstrámos a utilização de um modelo bio-reacção de transferência de massa para simular e conceber o funcionamento óptimo do gás de combustão para o crescimento de Chlorella sp. em algas foto-biorreatores.

Otimizar Configurações de gases de combustão para promover o crescimento de microalgas em fotobiorreatores via simulações de computador

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently ...

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14.2K visualizações.  Washington University in St. Louis, St. Louis.  De gases de combustão das usinas é um barato CO 2 fonte para o crescimento de algas. Nós construímos "gás de combustão para cultivo de algas" protótipo sistemas e descreveu como para ampliar o processo de cultivo de algas. Demonstrámos a utilização de um modelo bio-reacção de transferência de massa para simular e conceber o funcionamento óptimo do gás de combustão para o crescimento de Chlorella sp. em algas foto-biorreatores...

Vídeo: Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Analysis of Fatty Acid Content and Composition in Microalgae

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of microalgal biomass. These fatty acids can be present in different acyl-lipid classes. Especially the fatty acids present in triacylglycerol (TAG) are of commercial interest, because they can be used for production of transportation fuels, bulk chemicals, nutraceuticals (&omega;-3 fatty acids), and food commodities. To develop commercial applications, reliable analytical methods for quantification of fatty acid content and composition are needed. Microalgae are single cells surrounded by a rigid cell wall. A fatty acid analysis method should provide sufficient cell disruption to liberate all acyl lipids and the extraction procedure used should be able to extract all acyl lipid classes.
With the method presented here all fatty acids present in microalgae can be accurately and reproducibly identified and quantified using small amounts of sample (5 mg) independent of their chain length, degree of unsaturation, or the lipid class they are part of.
This method does not provide information about the relative abundance of different lipid classes, but can be extended to separate lipid classes from each other.
The method is based on a sequence of mechanical cell disruption, solvent based lipid extraction, transesterification of fatty acids to fatty acid methyl esters (FAMEs), and quantification and identification of FAMEs using gas chromatography (GC-FID). A TAG internal standard (tripentadecanoin) is added prior to the analytical procedure to correct for losses during extraction and incomplete transesterification.

A method for the determination of fatty acid content and composition in microalgae based on mechanical cell disruption, solvent based lipid extraction, transesterification, and quantification and identification of fatty acids using gas chromatography is described. A tripentadecanoin internal standard is used to compensate for the possible losses during extraction and incomplete transesterification.

Análise do conteúdo de ácidos graxos e composição em Microalgas

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of ...

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Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.

This article showcases the static chamber-based method for measurement of greenhouse gas flux from soil systems. With relatively modest infrastructure investments, measurements may be obtained from multiple treatments/locations and over timeframes ranging from hours to years.

Medição do fluxo de gases com efeito de Solos Agrícolas Usando Chambers estáticos

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the ...

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages include high potential yield, use of non-arable land and integration with waste streams. The nutrient requirements of a large-scale microalgae production system will require the coupling of cultivation systems with industrial waste resources, such as carbon dioxide from flue gas and nutrients from wastewater. Inorganic contaminants present in these wastes can potentially lead to bioaccumulation in microalgal biomass negatively impact productivity and limiting end use. This study focuses on the experimental evaluation of the impact and the fate of 14 inorganic contaminants (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn) on Nannochloropsis salina growth. Microalgae were cultivated in photobioreactors illuminated at 984 &#181;mol m-2 sec-1 and maintained at pH 7 in a growth media polluted with inorganic contaminants at levels expected based on the composition found in commercial coal flue gas systems. Contaminants present in the biomass and the medium at the end of a 7 day growth period were analytically quantified through cold vapor atomic absorption spectrometry for Hg and through inductively coupled plasma mass spectrometry for As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Se, Sn, V and Zn. Results show N. salina is a sensitive strain to the multi-metal environment with a statistical decrease in biomass yieldwith the introduction of these contaminants. The techniques presented here are adequate for quantifying algal growth and determining the fate of inorganic contaminants.

Integration of microalgal cultivation with industrial flue gas will ultimately introduce heavy metals and other inorganic compounds into the growth media. This study presents a procedure used to determine the end fate and impact of heavy metals and inorganic contaminants on the growth of Nannochloropsis salina grown in photobioreactors.

Quantificação de Metais Pesados ​​e outros contaminantes inorgânicos sobre a produtividade de Microalgas

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages ...

Laboratory Simulation of an Iron(II)-rich Precambrian Marine Upwelling System to Explore the Growth of Photosynthetic Bacteria

A conventional concept for the deposition of some Precambrian Banded Iron Formations (BIF) proceeds on the assumption that ferrous iron [Fe(II)] upwelling from hydrothermal sources in the Precambrian ocean was oxidized by molecular oxygen [O2] produced by cyanobacteria. The oldest BIFs, deposited prior to the Great Oxidation Event (GOE) at about 2.4 billion years (Gy) ago, could have formed by direct oxidation of Fe(II) by anoxygenic photoferrotrophs under anoxic conditions. As a method for testing the geochemical and mineralogical patterns that develop under different biological scenarios, we designed a 40 cm long vertical flow-through column to simulate an anoxic Fe(II)-rich marine upwelling system representative of an ancient ocean on a lab scale. The cylinder was packed with a porous glass bead matrix to stabilize the geochemical gradients, and liquid samples for iron quantification could be taken throughout the water column. Dissolved oxygen was detected non-invasively via optodes from the outside. Results from biotic experiments that involved upwelling fluxes of Fe(II) from the bottom, a distinct light gradient from top, and cyanobacteria present in the water column, show clear evidence for the formation of Fe(III) mineral precipitates and development of a chemocline between Fe(II) and O2. This column allows us to test hypotheses for the formation of the BIFs by culturing cyanobacteria (and in the future photoferrotrophs) under simulated marine Precambrian conditions. Furthermore we hypothesize that our column concept allows for the simulation of various chemical and physical environments &#8212; including shallow marine or lacustrine sediments.

Laboratory Simulation of an IronII-rich Precambrian Marine Upwelling System to Explore the Growth of Photosynthetic Bacteria

We simulated a Precambrian ferruginous marine upwelling system in a lab-scale vertical flow-through column. The goal was to understand how geochemical profiles of O2 and Fe(II) evolve as cyanobacteria produce O2. The results show the establishment of a chemocline due to Fe(II) oxidation by photosynthetically produced O2.

Laboratório de Simulação de um ferro (II) rico em Precambrian Marinha Ressurgência do sistema para explorar o crescimento de bactérias fotossintéticas

A conventional concept for the deposition of some Precambrian Banded Iron Formations (BIF) proceeds on the assumption that ferrous iron [Fe(II)] upwelling ...

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

A Tabela Gusseted Thermogradient para controlar a temperatura do solo para avaliar o crescimento da planta e monitoramento de processos do solo

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Procedures of Laboratory Fumigation for Pest Control with Nitric Oxide Gas

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on fresh products and procedures for residue analysis and product quality evaluation. An airtight fumigation chamber containing fresh fruit and vegetables is first flushed with nitrogen (N2) to establish an ultralow oxygen (ULO) environment followed by injection of NO. The fumigation chamber is then kept at a low temperature of 2 - 5 &#176;C for a specified time period necessary to kill a target pest to complete a fumigation treatment. At the end of a fumigation treatment, the fumigation chamber is flushed with N2 to dilute NO prior to opening the chamber to ambient air to prevent the reaction between NO and O2, which produces NO2 and may damage delicate fresh products. At different times after NO fumigation, NO2 in headspace and nitrate and nitrite in liquid samples were measured as residues. Product quality was evaluated after 2 weeks of post-treatment cold storage to determine effects of NO fumigation on product quality. Keeping&#160;O2 from reacting with NO is critical to NO fumigation and is an important part of the protocols. Measuring NO levels is challenging and a practical solution is provided. Possible protocol modifications are also suggested for measuring NO levels in the fumigation chambers as well as residues. NO fumigation has the potential to be a practical alternative to methyl bromide fumigation for postharvest pest control on fresh and stored products. This publication is intended to assist other researchers in conducting NO fumigation research for postharvest pest control and accelerating the development of NO fumigation for practical applications.

This paper describes nitric oxide (NO) fumigation protocols for postharvest pest control. Fumigation chambers are flushed with nitrogen (N2) to establish ultralow oxygen conditions before NO is injected. At the end, chambers are flushed with N2 to dilute NO before exposing products to ambient air to prevent exposure to NO2.

Procedimentos de laboratório de fumigação para controle de pragas com gás de óxido nítrico

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on ...

Lab-Scale Model to Evaluate Odor and Gas Concentrations Emitted by Deep Bedded Pack Manure

A lab-scaled simulated bedded pack model was developed to study air quality and nutrient composition of deep-bedded packs used in cattle mono-slope facilities. This protocol has been used to effectively evaluate many different bedding materials, environmental variables (temperature, humidity), and potential mitigation treatments that can improve air quality in commercial deep-bedded mono-slope facilities. The model is dynamic and allows researchers to easily collect many chemical and physical measurements from the bedded pack. Weekly measurements, collected over the course of six to seven weeks, allows sufficient time to see changes in air quality measurements over time as the bedded pack matures. The data collected from the simulated bedded packs is within the range of concentrations previously measured in commercial deep-bedded mono-slope facilities. Past studies have demonstrated that 8 - 10 experimental units per treatment are sufficient to detect statistical differences among the simulated bedded packs. The bedded packs are easy to maintain, requiring less than 10 minutes of labor per bedded packs per week to add urine, feces, and bedding. Sample collection using the gas sampling system requires 20 - 30 minutes per bedded pack, depending on the measurements that are being collected. The use of lab-scaled bedded packs allows the researcher to control variables such as temperature, humidity, and bedding source that are difficult or impossible to control in a research or commercial facility. While not a perfect simulation of &#34;real-world&#34; conditions, the simulated bedded packs serve as a good model for researchers to use to examine treatment differences among bedded packs. Several lab-scale studies can be conducted to eliminate possible treatments before trying them in a research or commercial-sized facility.

A protocol has been developed to measure gases, odors, and nutrient composition in lab-scaled bedded manure packs, which can be used to study ways to improve air quality in commercial cattle facilities using deep-bedded manure packs.

Laboratório-escala modelo para avaliar o Odor e as concentrações de gases emitidas pelo profundo com camas Pack estrume

A lab-scaled simulated bedded pack model was developed to study air quality and nutrient composition of deep-bedded packs used in cattle mono-slope ...

Experimental Study of the Relationship Between Particle Size and Methane Sorption Capacity in Shale

The amount of adsorbed shale gas is a key parameter used in shale gas resource evaluation and target area selection, and it is also an important standard for evaluating the mining value of shale gas. Currently, studies on the correlation between particle size and methane adsorption are controversial. In this study, an isothermal adsorption apparatus, the gravimetric sorption analyzer, is used to test the adsorption capacity of different particle sizes in shale to determine the relationship between the particle size and the adsorption capacity of shale. Thegravimetric method requires fewer parameters and produces better results in terms of accuracy and consistency than methods like the volumetric method. Gravimetric measurements are performed in four steps: a blank measurement, preprocessing, a buoyancy measurement, and adsorption and desorption measurements. Gravimetric measurement is presently considered to be a more scientific and accurate method of measuring the amount of adsorption; however, it is time-consuming and requires a strict measuring technique. A Magnetic Suspension Balance (MSB) is the key to verify the accuracy and consistency of this method. Our results show that adsorption capacity and particle size are correlated, but not a linear correlation, and the adsorptions in particles sieved into 40 - 60 and 60 - 80 meshes tend to be larger. We propose that the maximum adsorption corresponding to the particle size is approximately 250 &#181;m (60 mesh) in the shale gas fracturing.

We use an isothermal adsorption apparatus, the gravimetric sorption analyzer, to test the adsorption capacity of different particle sizes of shale, in order to find out the relationship between particle size and the adsorption capacity of shale.

Estudo experimental da relação entre o tamanho de partícula e capacidade de adsorção de metano em xisto

The amount of adsorbed shale gas is a key parameter used in shale gas resource evaluation and target area selection, and it is also an important standard ...

An Optimized Rhizobox Protocol to Visualize Root Growth and Responsiveness to Localized Nutrients

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive harvest or expensive equipment. We present a customizable and affordable rhizobox method that allows the non-destructive visualization of root growth over time and is particularly well-suited to studying root plasticity in response to localized resource patches. The method was validated by assessing maize genotypic variation in plasticity responses to patches containing 15N-labeled legume residue. Methods are described to obtain representative developmental measurements over time, measure root length density in resource-containing and control patches, calculate root growth rates, and determine 15N recovery by plant roots and shoots. Advantages, caveats, and potential future applications of the method are also discussed. Although care must be taken to ensure that experimental conditions do not bias root growth data, the rhizobox protocol presented here yields reliable results if carried out with sufficient attention to detail.

Visualizing and measuring root growth in situ is extremely challenging. We present a customizable rhizobox method to track root development and proliferation over time in response to nutrient enrichment. This method is used to analyze maize genotypic differences in root plasticity in response to an organic nitrogen source.

Um protocolo otimizado de Rhizobox para visualizar o crescimento da raiz e receptividade aos nutrientes localizadas

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive ...

Cultivation of Green Microalgae in Bubble Column Photobioreactors and an Assay for Neutral Lipids

There is significant interest in the study of microalgae for engineering applications such as the production of biofuels, high value products, and for the treatment of wastes. As most new research efforts begin at laboratory scale, there is a need for cost-effective methods for culturing microalgae in a reproducible manner. Here, we communicate an effective approach to culture microalgae in laboratory-scale photobioreactors, and to measure the growth and neutral lipid content of that algae. Instructions are also included on how to set up the photobioreactor system. Although the example organisms are species of Chlorella and Auxenochlorella, this system can be adapted to cultivate a wide range of microalgae, including co-cultures of algae with non-algae species. Stock cultures are first grown in bottles to produce inoculum for the photobioreactor system. Algae inoculum is concentrated and transferred to photobioreactors for cultivation in batch mode. Samples are collected daily for the optical density readings. At the end of the batch culture, cells are harvested by centrifuge, washed, and freeze dried to obtain a final dry weight concentration. The final dry weight concentration is used to create a correlation between the optical density and the dry weight concentration. A modified Folch method is subsequently used to extract total lipids from the freeze-dried biomass and the extract is assayed for its neutral lipid content using a microplate assay. This assay has been published previously but protocol steps were included here to highlight critical steps in the procedure where errors frequently occur. The bioreactor system described here fills a niche between simple flask cultivation and fully-controlled commercial bioreactors. Even with only 3-4 biological replicates per treatment, our approach to culturing algae leads to tight standard deviations in the growth and lipid assays.

Here, we present a protocol to construct lab-scale bubble column photobioreactors and use them to culture microalgae. It also provides a method for the determination of the culture growth rate and neutral lipid content.

Cultivo de microalgas verdes em fotobiorreatores coluna de bolha e um ensaio para lípidos neutros

There is significant interest in the study of microalgae for engineering applications such as the production of biofuels, high value products, and for the ...