本研究では、セントルイスのワシントン大学でNSFのプログラム（学部生のための研究体験）によってサポートされています。

1。藻類培養およびスケールアップ<ol><li> 0.55グラム/ Lを含有する脱イオン水を用いて培地を調製-1尿素、0.1185グラム/ L -1 KH 2 PO 4、0.102グラム/ L -1 の MgSO 4·7H 2 O、0.015グラム/ L -1のFeSO 4·7H 2 Oおよび22.5μlの微量元素（18.5グラム/ L -1のH 3 BO 3、21.0グラム/ L -1のCuSO 4·5H 2 Oを、73.2グラム/ L -1のMnCl 2·4H 2 O、13.7グラム/ L -1のCoSO 4·7H 2 O、59.5グラム/ L -1のZnSO 4·5H 2 O、3.8グラム/ L -1（NH 4）6 Moを7 O 24·4H 2 O、0.31グラム/ L -1 NH 4 VO 3 ）。 7-8に培地のpHを調整します。 0.22μmのシリンジフィルターを介して培地を滅菌する。 </li><li> クロレラ属に接種。新鮮な寒天プレート上の単一コロニーからの手ぶれFLAへ無菌接種ループを有する50mLの培地を含むskは。 6日間、150 rpmで30℃で培養藻類（連続光条件、光子束= 40から50マイクロモルのM -2秒-1）。分光光度計（OD 730）によって細胞密度をモニターする。 </li><li>転写50mLの藻類（1〜L滅菌培地を含む）2リットルのガラスフラスコに培養物（&gt; 1中間対数増殖期、OD 730）。ポンプ（5日間）インキュベーション中の文化の中に空気（またはCO 2）を濾過した。 </li><li>段階1.3で述べたと同様の条件で、次に（この段階では、微生物汚染の危険性が小さい）非滅菌培地、培養藻類を15 Lを含む20-Lガラス製カーボイに移す1 L藻類培養物。 </li><li>平坦な発光ダイオードを備えたプレートフォトバイオリアクター（コンピュータ制御装置、ガス混合物は、細胞の光学密度分析器、pH、溶存酸素中に15 Lの新鮮な藻類培養物（OD 730 = 2）、85 Lの非滅菌媒体を配置世代、温度、溶存CO 2）。バイオリアクターに、煙道ガス/空気混合物をポンプ。 </li><li> （OD 730&gt; 20）バイオマス収穫後、70％エタノールを使用して徹底的にドライクリーニングのフォトバイオリアクター。 </li></ol> 2。小型フォトバイオリアクターを使用した排煙処理の実験室で実証<ol><li>ガラスボトル（200ミリリットル/分中/ボトル、初期OD 730〜0.3）での藻類の培養液に接種する。 </li><li>天然ガスを燃焼し、ロート、冷却管、及び（水/石灰石スラリを含む）、0.5L洗浄瓶を通して煙道ガス（〜250cm 3の分-1）をポンプ。 </li><li>マスフローコントローラは、藻類の培養への煙道ガス流（ 図1）を制御する。 排ガスオンや排ガスオフ（代わりに空気をポンプ）：排ガスパルスは2つのモードがあります。 </li></ol> 3。動力学モデルの開発動力学モデルを前提としています（1）文化が均一系であるS。 （2）培養中のCO 2濃度および光強度は藻類の成長のための制限要因である。 （3）CO 2分圧およびH 2 CO 3との液相平衡を、HCO 3 - 、およびCO 3 2 -は 、ヘンリーの法則に簡略化される）。モデル方程式は、次のとおりです。 <img alt="式（1）及び（2）" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq1and2.jpg" width="500px" /> Xは、バイオマス（キロ·メートル-3）である。 Sは、溶解したCO 2（モル·M -3）である。 Pは、気相（Pa）の中のCO 2分圧である。 P 私は （そのようなNO XおよびSO Xなどの）ガス中の有害化合物を番目の分圧である。のP max.iは、バイオマスの成長に完全な阻害を持っている有毒ガスの分圧である。 η 私は経験的な係数である。 K Sはミカエリス·メンテン定数であるCO 2の量（モル·M -3）。 K Iは、CO 2（モル·mで-3）の阻害定数である。 Kは、光強度のミカエリス·メンテン定数（μモル·メートル-2·秒-1）である。 Hはヘンリー定数のCO 2（PA·M 3·モル-1）のためである。 K Laは CO 2の物質移動速度（時間-1）である。私は平均光強度であり、μモル·メートル-2·秒-1、次のように計算することができます（式（3））9。 <img alt="式3" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq3.jpg" width="500px" />モデルパラメータの定義は、表1にある。初期条件は、バイオマスを想定し、CO 2の濃度に溶解し、それぞれを100mg / Lおよび13モル/ Lである。物質移動容量係数は、経験的相関によって推定することができるバイオリアクターへのTiONは10パラメータ： <img alt="式4" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq4.jpg" width="500px" /> P gは / Vは、バイオリアクター内の曝気システムの消費電力（W / m 3）である。 uは、バイオリアクター（10m /秒）を通るガス流の表面速度でgsを 。 α、β、γは、混合条件に関連する定数である。 <ol><li>モデルシミュレーション（スクリーンショットは、支持材料、私に与えられている）のためのSimulinkのファイルを作成します。 <ol><li> Simulinkモデルを作成するためのMATLABインターフェイスでファイル/新規作成/モデルを選択し、[開く]「ライブラリブラウザー」（スクリーンショット1）。 </li><li>式1および2のためのサブシステムを作成するために、ライブラリ·ブラウザの「サブシステム」のブロックを選択してください。 、Simulinkモデルファイルに1 Subsystemブロックをドラッグして、「式1」に社名を変更してから、式（2）に同じ手順を繰り返します。 </li><l私は&gt;各サブシステム内の適切なブロックおよびパラメータを作成します（スクリーンショット3）。ダブルダブルのパラメータを設定するためのブロックをクリックして、他のサブシステムのためにこれらのステップを繰り返して、ライブラリブラウザから適切なブロックを選択し、計算順序を表す矢印、それらを接続し、「式1」のブロックをクリックします。 注：1）シーケンスが入力ブロックで開始し、出力ブロックを締結すべきである、2）、加算、減算、乗算、除算、および統合のためのオペレータ·ブロックは、すべてのライブラリのブラウザで見つけることができ、我々は、ユーザーがヘルプファイルのを探る示唆Simulinkは、それらを使用する方法を理解するために、3）最適化ソルバーは、ツールバー上の経路シミュレーション/設定パラメータを使用して設定することができます。 </li><li>モデル方程式（1および2）を表現するために2サブシステムをリンクします。必要に応じて矢印で他のサブシステムの入力に1サブシステムの出力を接続します。例えば、溶存CO 2濃度はoです式2サブシステム内utputなど、また式（1）サブシステムの入力。 </li><li>面発光入力値として&#39;定数&#39;ブロックを使用し、オン·オフのCO 2パルスをシミュレートするために、「式2」の入力としてブロック「ジェネレータパルス」を使用してください。重な周期時間と振幅などのパラメータを変更するには、ブロックをクリックします。 </li><li>ライブラリ·ブラウザの「マルチプレクサ」のブロックを選択してください。 「マルチプレクサ」に、すべての出力を接続して、シミュレートされた結果を格納するブロック「ワークスペースへ」に接続します。 </li><li> 「上部のツールバーにある「シミュレーション停止時間 &#39;を定義、ボタンをクリックしてください<img src="/files/ftp_upload/50718/playarrow.jpg" alt="矢印" width="10px" fo:content-width="0.1in" fo:src="/files/ftp_upload/50718/playarrow.jpg" /> 「シミュレーションを開始するには、その結果が（スクリーンショット4）MATLABワークスペースに表示されます。 </li></ol></li><li>最適なCO 2の条件をプロファイルする動的最適化手法を適用します。 </李&gt; </ol> 12が使用されているバイオマス生産11を最大入口流入CO 2のプロファイル（のP OPT）、MATLABの「fminconを&#39;機能とCVP（制御ベクトルパラメータ）の変更を検索します。 図2は、最適化アルゴリズムは、（支援するMATLABプログラミングのコードを参照してください。説明材料II）。

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これらの著者は、開示することは何もありません。

本研究では、フォトバイオリアクターで藻類の栽​​培を拡大するための実験プロトコルを示しています。我々はまた、藻類の成長を促進するための排煙入力するためのいくつかの方法を検討する。物質移動およびバイオ反応モデルを用いて、CO 2物質移動係数（バイオリアクター混合条件及びCO 2空塔速度によって決定される）K Laが強く藻類の成長に影響を与えるこ?...

<table border="0" cellpadding="0" cellspacing="0" width="636">
	<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>
		</tr>
	</tbody>
</table>

optimize flue gas settings to promote microalgae growth in photobioreactors via computer simulations

発電所からの煙道ガスは、藻類の培養を促進し、温室効果ガスの排出量を低減することができる1。微細藻類は、より効率的に植物3よりも太陽エネルギーを取り込むだけでなく、高度なバイオ燃料2-4を合成するだけでなく。一般的には、大気中のCO 2は、最大の藻類の成長5をサポートするための十分なソースではありません。一方、工業排気ガス中のCO 2の高濃度の藻類生理学に悪影響を与える。従って、（例えば、栄養素および光など）の両方の培養条件および光バイオリアクターへの煙道ガス流の制御は、システムを「藻類する煙道ガス「効率を開発することが重要である。研究者は、煙道ガスと異なるフォトバイオリアクタ構成4,6と7,8培養戦略を提案している。ここでは、排ガスの設定に応じて、微細藻類の成長を予測するためにモデルを使用する方法を示したプロトコルを提示する。私たちは、PERF煙道ガスとの藻類の成長のための有利な条件を決定するために、両方の実験的例証とモデルシミュレーションをORM。我々は、均一な光バイオリアクターでの微細藻類の成長をシミュレートするために、物質移動および光強度の方程式と相まってモノーベースのモデルを開発する。モデルシミュレーションは、さまざまな排煙設定で藻類の成長と煙道ガス消費量を比較します。モデルは示しています。1）どのように藻 ​​類の成長をCO 2の異なる物質移動容量係数に影響されます。2）どのように我々は、動的な最適化アプローチ（DOA）を介して藻類の成長のための最適なCO 2濃度を見つけることができます。3）どのようにして設計することができます藻類バイオマスの成長を促進し、煙道ガスの使用量を減らすためにオンオフ排ガスパルス矩形。実験面では、（天然ガスの燃焼によって生成される）、煙道ガスの下でクロレラを成長させるためのプロトコルを提示する。実験結果は、定性的にモデル予測を検証し、その高周波排ガスのPU小売り供給が大幅に藻類の栽培を向上させることができます。

我々の以前の実験的分析は、この阻害が13を軽減することができるCO 2露光時間を減少させながら、連続される煙道ガス暴露悪影響、 クロレラの成長に影響を与えることを示している。良好な煙道ガスの流入、藻類の成長の関係を理解するために、我々は、煙道ガスの存在下でのバイオマス成長をシミュレートするための経験的モデルを開発する。私たちは、煙道ガス15...

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

発電所からの煙道ガスは、藻類の成長のための安価なCO 2源である。私たちは、システム「栽培藻類する煙道ガス」のプロトタイプを構築し、藻類培養工程をスケールアップする方法を説明してきました。我々は、Chlorella種の成長のための煙道ガスの最適な動作をシミュレートし、設計するために、物質移動のバイオ反応モデルの使用を実証した。藻類のフォトバイオリアクター中。

計算機シミュレーションを通してフォトバイオリアクターで藻類の成長を促進するために排煙設定を最適化

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

optimize-flue-gas-settings-to-promote-microalgae-growth

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JoVE Journal

Environment

14.2K ビュー.  Washington University in St. Louis, St. Louis. 発電所からの煙道ガスは、藻類の成長のための安価なCO 2源である。私たちは、システム「栽培藻類する煙道ガス」のプロトタイプを構築し、藻類培養工程をスケールアップする方法を説明してきました。我々は、Chlorella種の成長のための煙道ガスの最適な動作をシミュレートし、設計するために、物質移動のバイオ反応モデルの使用を実?...

ビデオ: 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.

微細藻類中の脂肪酸含量および組成の分析

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

環境学

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.

静的チャンバを用いて農用地の土壌からの温室効果ガスフラックスの測定

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.

重金属や微細藻類の生産性に関するその他の無機汚染物質の定量

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.

光合成細菌の増殖を探検する鉄（II）リッチ先カンブリア時代マリン湧昇システムの実験室でのシミュレーション

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.

マチ付きThermogradient表は、植物の成長を評価し、土壌プロセスの監視のための土壌の温度を制御します

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.

窒素酸化物ガスで害虫駆除のため研究所くん蒸処理の手順

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.

臭気と深いから放出されるガスの濃度を評価する実験室スケール モデル層状パック肥料

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.

粒子径と頁岩中のメタン吸着容量との関係に関する実験的研究

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.

根の生長およびローカライズされた栄養素に対する反応性を可視化する最適化された Rhizobox プロトコル

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.

中性脂質のバブル列フォトバイオリアクターとアッセイで緑の微細藻類の栽培

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