Cette étude est soutenue par un programme NSF (recherche expériences pour étudiants de premier cycle) à l&#39;Université de Washington à St. Louis.

Une. Culture d&#39;algues et Scale-up <ol><li> Préparer le milieu de culture en utilisant de l&#39;eau déminéralisée contenant 0,55 g / L -1 urée, 0,1185 g / L -1 KH 2 PO 4, 0,102 g / L -1 MgSO 4 · 7H 2 O, 0,015 g / L -1 FeSO 4 · 7H 2 O et 22,5 ul de micro-éléments (18,5 g / L -1 H 3 BO 3, 21,0 g / L -1 CuSO 4 · 5H 2 O, 73,2 g / L -1 MnCl 2 · 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 ). Ajuster le pH à 7-8 milieu. Stériliser milieu de culture par filtre de 0,22 um seringue. </li><li> Inoculer Chlorella sp. à partir d&#39;une seule colonie sur une plaque de gélose frais dans une secousse de flask milieu contenant 50 mL avec une anse d&#39;inoculation stérile. algues de culture moins de 150 tours par minute et 30 ° C pendant six jours (condition de lumière continue, le flux de photons = 40-50 mol m -2 s -1). Surveiller la densité des cellules par un spectrophotomètre (OD 730). </li><li> ML algues culture transfert 50 (phase de croissance moyen journal, OD 730&gt; 1) dans un flacon de verre de 2 L (avec ~ 1 L milieu de culture stérilisé). Pompe à air filtré (ou CO 2) dans la culture au cours de l&#39;incubation (pendant 5 jours). </li><li> Transfert 1 L algues culture dans une bonbonne de verre de 20 L contenant 15 L milieu non-stérilisé culture (à ce stade, le risque de contamination microbienne est faible), alors la culture des algues sous le même état comme indiqué dans l&#39;étape 1.3. </li><li> Placer 15 L culture fraîche d&#39;algues (DO 730 = 2) et 85 L de milieu non stérilisé dans un photobioréacteur de plaque plate (équipé de diodes émettrices de lumière, le contrôleur d&#39;ordinateur, d&#39;un mélange de gaz, analyseurs de densité optique de la cellule, le pH, oxy dissousgen, la température et le CO 2 dissous). Pomper le mélange air / des gaz de combustion dans le bioréacteur. </li><li> Bien nettoyer à sec photobioréacteur en utilisant 70% d&#39;éthanol après la récolte de la biomasse (OD 730&gt; 20). </li></ol> 2. Laboratoire démonstration de traitement de gaz de combustion utilisant de petits Photobioréacteurs <ol><li> Inoculer des cultures d&#39;algues dans des bouteilles en verre (200 ml / min à moyen / bouteille, DO initial 730 ~ 0,3). </li><li> Brûler du gaz naturel et de pomper les gaz de combustion (~ 250 cm 3 min -1) à travers un entonnoir, un tube de condenseur, et un lave-bouteille de 0,5 L (contenant de l&#39;eau / la suspension de calcaire). </li><li> Les régulateurs de débit massique de contrôler le flux de gaz de combustion dans la culture des algues (figure 1). Impulsions de gaz de combustion comprennent deux modes: cheminée gaz-gaz de combustion et sur-off (pomper l&#39;air à la place). </li></ol> 3. Kinetic modèle de développement Le modèle cinétique suppose: (1) les cultures sont système homogènes. (2) la concentration de CO 2 et de l&#39;intensité de la lumière dans les cultures sont les facteurs limitant pour la croissance des algues. (3) CO 2 pression partielle et son équilibre en phase liquide avec H 2 CO 3, HCO 3 - et CO 3 2 - est simplifiée avec la loi de Henry). Les équations du modèle sont: <img alt="Les équations 1 et 2" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq1and2.jpg" width="500px" /> X est la biomasse (kg · m -3). S est le CO 2 dissous (mol · m -3). P est la pression partielle en CO 2 dans la phase gazeuse (Pa). p i est la pression partielle du ième composé toxique dans le gaz (tels que les NO x et de SO x). Max.i P est la pression partielle de gaz toxique à avoir une inhibition complète de la croissance de la biomasse. η i est le coefficient empirique. K s est la constante de Michaelis-Mentende CO 2 (mol · m -3). K I est la constante d&#39;inhibition de CO 2 (mol · m -3). K est la constante de Michaelis-Menten de l&#39;intensité lumineuse (umol · m -2 · s -1). H est la constante de Henry pour le CO 2 (Pa · m 3 · mol -1). La K est le taux de CO 2 (hr de -1) de transfert de masse. I est l&#39;intensité lumineuse moyenne, umol · m -2 · s -1, qui peut être calculée de la manière suivante (Eq. (3)) 9. <img alt="Equation 3" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq3.jpg" width="500px" /> La définition des paramètres de modèle se trouve dans le tableau 1. Les conditions initiales supposent que la biomasse et de CO 2 dissous concentrations sont de 100 mg / L et 13 mol / L, respectivement. Le coefficient de transfert de masse volumique peut être estimée par corrélation empiriquetion de bioréacteur paramètres 10: <img alt="Equation 4" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq4.jpg" width="500px" /> P g / V est la consommation de puissance du système cellulaire dans le bioréacteur (W / m 3). u GS est la vitesse superficielle de l&#39;écoulement de gaz à travers le bioréacteur (m / sec). α, β, et γ sont des constantes liées à des conditions de mélange. <ol><li> Construire un fichier Simulink pour la simulation du modèle (captures d&#39;écran sont donnés dans le matériel d&#39;appui I). <ol><li> Choisissez File / New / Modèle de l&#39;interface MATLAB pour créer un modèle Simulink, et ouverte &quot;Library Browser&quot; (capture d&#39;écran 1). </li><li> Choisissez bloc «sous-système» dans le navigateur de la bibliothèque pour créer des sous-systèmes pour l&#39;équation 1 et 2. Faites glisser un bloc de sous-système dans le fichier de modèle Simulink, changer son nom pour &quot;l&#39;équation 1 &#39;, puis répéter les mêmes étapes pour l&#39;équation 2. </li><li&gt; Créer des blocs et des paramètres appropriés à chaque sous-système (capture d&#39;écran 3). Double-cliquez sur le bloc &#39;équation 1&#39;, choisir des blocs appropriés à partir du navigateur de la bibliothèque et les relier avec des flèches qui désignent la séquence de calcul, double-cliquez sur les blocs pour définir les paramètres, et répéter ces étapes pour l&#39;autre sous-système. Remarque: 1) La séquence doit commencer par blocs d&#39;entrée et de conclure avec des blocs de sortie; 2) Les blocs de l&#39;opérateur pour l&#39;addition, la soustraction, la multiplication, la division et l&#39;intégration peut être tout trouvé dans le navigateur de la bibliothèque, et nous suggérons aux utilisateurs d&#39;explorer les fichiers d&#39;aide de Simulink pour comprendre comment les utiliser; 3) Le solveur d&#39;optimisation peut être réglé par les paramètres voie Simulation / configuration sur la barre d&#39;outils. </li><li> Relier les deux sous-systèmes pour représenter des équations du modèle (1 et 2). Connecter la sortie de l&#39;un sous-système à l&#39;entrée de l&#39;autre sous-système par la flèche si nécessaire. Par exemple, la concentration en CO 2 dissous est l&#39;output dans l&#39;équation 2 sous-système, et également l&#39;entrée du sous-système de l&#39;équation 1. </li><li> Utilisez &quot;Générateur d&#39;impulsions&quot; bloc que les entrées pour &#39;équation 2&#39; pour simuler les on-off CO 2 impulsions; utiliser le bloc &quot;Constante&quot; que la valeur d&#39;entrée de lumière de surface. Double cliquez sur les blocs de modifier les paramètres tels que le temps de période et d&#39;amplitude. </li><li> Choisissez bloc «Mux &#39;dans le navigateur de la bibliothèque. Connectez toutes les sorties de «multiplexeur» et connectez-le à «Pour l&#39;espace de travail« bloc qui stocke les résultats simulés. </li><li> Définir le «temps d&#39;arrêt de Simulation» sur la barre d&#39;outils, cliquez sur le bouton &quot; <img src="/files/ftp_upload/50718/playarrow.jpg" alt="Flèche" width="10px" fo:content-width="0.1in" fo:src="/files/ftp_upload/50718/playarrow.jpg" /> &quot;Pour commencer la simulation, et les résultats seront affichés dans l&#39;espace de travail MATLAB (capture d&#39;écran 4). </li></ol></li><li> Adopter une approche dynamique de l&#39;optimisation de profil CO 2 conditions optimales. </li&gt; </ol> Pour trouver les changements de l&#39;entrée afflux CO 2 profil (P opt) qui maximisent la production de biomasse 11, la fonction MATLAB »de fmincon &#39;et CVP (vecteur de commande paramétrage) 12 sont utilisés. Figure 2 illustre l&#39;algorithme d&#39;optimisation (voir les codes de programmation MATLAB dans le soutien Matériel II).

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Ces auteurs n&#39;ont rien à révéler.

Dans cette étude, nous démontrons le protocole expérimental pour étendre les cultures d&#39;algues en photobioréacteurs. Nous examinons également plusieurs méthodes pour les entrées de gaz de combustion pour favoriser la croissance des algues. L&#39;utilisation d&#39;un transfert de masse et le modèle bio-réaction, nous démontrons que le coefficient de transfert de masse de CO 2 K La (déterminé par l&#39;état de mélange bioréacteur et CO 2 vitesse superficielle) influence ...

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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

Les gaz de combustion des centrales électriques peut promouvoir la culture d&#39;algues et de réduire les émissions de gaz à effet de serre 1. Les microalgues non seulement capter l&#39;énergie solaire plus efficacement que les plantes 3, mais aussi la synthèse de biocarburants avancés 2-4. Généralement, le CO 2 atmosphérique n&#39;est pas une source suffisante pour soutenir la croissance des algues maximale 5. D&#39;autre part, les fortes concentrations de CO 2 dans les gaz d&#39;échappement industriels ont des effets néfastes sur la physiologie des algues. Par conséquent, les deux conditions de culture (tels que les nutriments et la lumière) et le contrôle de l&#39;écoulement des gaz de combustion dans les photobioréacteurs sont importants pour développer un &quot;gaz de combustion pour les algues&quot; système efficace. Les chercheurs ont proposé différentes configurations de photobioréacteur 4,6 et 7,8 stratégies de culture avec du gaz de carneau. Ici, nous présentons un protocole qui montre comment utiliser des modèles pour prédire la croissance des microalgues en réponse à carneau réglages de gaz. Nous PERForm deux illustrations et modèle simulations expérimentales pour déterminer les conditions favorables à la croissance des algues avec du gaz de combustion. Nous développons un modèle basé Monod couplé avec le transfert de masse et les équations d&#39;intensité de lumière pour simuler la croissance des microalgues dans un photo-bioréacteur homogène. La simulation du modèle compare la croissance d&#39;algues et de combustion des consommations de gaz sous différents réglages des gaz de combustion. Le modèle illustre: 1) comment la croissance des algues est influencée par différents volumétriques coefficients de transfert de masse de CO 2; 2) comment nous pouvons trouver optimale concentration de CO 2 pour la croissance des algues par l&#39;approche d&#39;optimisation dynamique (DOA), 3) la façon dont nous pouvons concevoir un rectangulaire marche-arrêt impulsion de gaz de combustion pour favoriser la croissance de la biomasse d&#39;algues et de réduire l&#39;utilisation de gaz de fumée. Sur le plan expérimental, nous présentons un protocole pour la croissance de la Chlorella sous le gaz de carneau (produit par la combustion de gaz naturel). Les résultats expérimentaux valident qualitativement les prédictions du modèle que le gaz à haute fréquence de combustion puGE peuvent améliorer de manière significative la culture des algues.

Notre analyse expérimentale précédente indique que l&#39;exposition des gaz de combustion en continu affecte négativement la croissance de Chlorella, tout en diminuant le temps de CO 2 de l&#39;exposition est en mesure d&#39;atténuer cette inhibition 13. Pour mieux comprendre l&#39;entrée de gaz de carneau et de la relation de la croissance d&#39;algues, on développe un modèle empirique pour simuler la croissance de la biomasse en présence de gaz de combustion. Nous supposons que ...

Watch this Scientific Journal Video about Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations at JoVE.com

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

Les gaz de combustion des centrales est une source de CO 2 pas cher pour la croissance des algues. Nous avons construit &quot;gaz de combustion à des algues de culture&quot; prototype systèmes et décrit comment redimensionner le processus de culture des algues. Nous avons démontré l&#39;utilisation d&#39;un modèle bio-réaction de transfert de masse afin de simuler et de concevoir le fonctionnement optimal du gaz de fumée pour la croissance de la Chlorella sp. en algues photobioréacteurs.

Optimiser les réglages des gaz de combustion pour la promotion de la croissance des microalgues en photobioréacteurs via des simulations informatiques

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 vues.  Washington University in St. Louis, St. Louis.  Les gaz de combustion des centrales est une source de CO 2 pas cher pour la croissance des algues. Nous avons construit "gaz de combustion à des algues de culture" prototype systèmes et décrit comment redimensionner le processus de culture des algues. Nous avons démontré l'utilisation d'un modèle bio-réaction de transfert de masse afin de simuler et de concevoir le fonctionnement optimal du gaz de fumée pour la croissance de la Ch...

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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.

Analyse de la teneur en acide gras et de la composition en microalgues

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

Recherche

Environnement

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.

Mesure du flux de gaz à effet de serre provenant des sols agricoles utilisant statiques Chambers

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.

Quantification des métaux lourds et d&#39;autres contaminants inorganiques sur la productivité des microalgues

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.

Laboratoire de simulation d&#39;un fer (II) riche système Upwelling précambrien Marine à explorer la croissance des bactéries photosynthétiques

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.

Un tableau Gusseted thermogradient pour contrôler la température du sol pour l&#39;évaluation de la croissance des plantes et de suivi des processus de sol

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.

Procédures de laboratoire Fumigation pour Pest Control avec gaz d’oxyde nitrique

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.

Modèle de laboratoire pour évaluer les odeurs et les Concentrations de gaz émises par Deep lits Pack fumier

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.

Etude expérimentale de la relation entre la taille des particules et capacité de Sorption de méthane en schiste

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.

Un protocole de Rhizobox optimisé pour visualiser la croissance racinaire et la réceptivité aux nutriments localisées

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.

Culture de microalgues vertes en bulle colonne photobioréacteurs et un dosage des lipides neutres

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