Bu çalışma, St Louis Washington Üniversitesi&#39;nde bir NSF programı (Lisans Öğrencileri için Deneyimleri Araştırma) tarafından desteklenmektedir.

1.. Alg Yetiştiriciliği ve Ölçek-up <ol><li> 7H 2 O, 0.015 g / L -1 FeSO 4 · · 7H 0.55 g / L -1 üre, 0,1185 g / L -1 KH 2 PO 4, 0.102 g / L MgSO -1 4 ihtiva eden iyonu giderilmiş su kullanılarak kültür ortamı hazırlayın 2 O ve 22.5 ul mikro elementler (18.5 g / L -1 H 3 BO 3, 21.0 g / L -1 CuSO 4 · 5H 2 O, 73.2 g / L -1 MnCI2 · 4H 2 O, 13,7 g / L -1 COSO 4 · 7H 2 O, 59,5 g / L -1 ZnSO 4 · 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 .) 7-8 orta pH ayarlayın. 0.22 um şırınga filtresi ile kültür ortamı sterilize edin. </li><li> Chlorella sp aşılamak. Bir sarsıntı fla içine taze agar plaka üzerinde bir tek kolonidensk steril bir aşılama döngü ile 50 mL medyum ihtiva eden. Altı gün boyunca 150 rpm ve 30 ° C&#39;nin altında Kültür algler (sürekli ışık durumu, foton akı = 40-50 ľmol m -2 sn -1). Bir spektrofotometre (OD 730) hücre yoğunluğunu izlemek. </li><li> Aktarım 50 mL alg (~ 1 L steril kültür ortamı ile) 2-L bir cam şişe içine kültür (&gt; 1, orta log büyüme fazı, OD 730). Pompa (5 gün) inkübasyon sırasında hava (ya da CO 2) kültür içine süzüldü. </li><li> Adım 1.3 &#39;de belirtildiği gibi aynı koşullar altında zaman (bu aşamada, mikrobiyal kirlenme riski küçük) sterilize kültür ortamı, kültür yosun 15 L ihtiva eden bir 20-L cam damacana içine aktarın 1 L algal kültürü. </li><li> Işık yayan diyotlar, bilgisayar kontrollü, gaz karışımı, hücre optik yoğunluğu için analizörleri ile donatılmış düz bir plaka fotobiyoreaktör (içine 15 L taze alg kültürü (OD 730 = 2) ve 85 L non-steril ortam yerleştirin, pH, çözünmüş oksigen, sıcaklık ve çözünmüş CO 2). Biyoreaktör içine baca gazı / hava karışımı pompa. </li><li> (OD 730&gt; 20) biyokütle hasattan sonra% 70 etanol kullanılarak iyice kuru-temiz foto-biyo. </li></ol> 2. Küçük fotobiyoreaktörler kullanma Baca Gazı Arıtma Laboratuar Gösteri <ol><li> Cam şişelerde alg kültürleri (200 ml / dakika orta / şişe, ilk OD 730 ~ 0.3) inoküle. </li><li> Doğal gazı yakmak ve bir huni, bir kondansatör tüpünün ve (su / kireçtaşı çamuru ihtiva eden) bir 0.5 L yıkama şişesi yoluyla baca gazı (~ 250 cm3 dk-1) pompa. </li><li> Kütle akış kontrol alg kültürüne baca gazı akımı (Şekil 1) kontrol eder. Baca gaz ve baca gazı-off (yerine hava pompası): Baca gazı bakliyat iki modları içerir. </li></ol> 3. Kinetik Model Geliştirme Kinetik model varsaymaktadır: (1) homojen kültürler sistemidirs. (2) kültürde CO2 konsantrasyonu ve ışık yoğunluğu yosun büyümesi için sınırlayıcı faktörler bulunmaktadır. , Ve CO 3 - 2 -) Henry Kanunu ile basitleştirilmiş H 2 CO 3, HCO 3 ile (3) CO 2 parsiyel basıncı ve sıvı faz dengesi. Model denklemleri: <img alt="Denklem 1 ve 2" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq1and2.jpg" width="500px" /> X biyokütle (kg · m -3) &#39;dir. S çözünmüş CO2 (mol · m -3) &#39;dir. P, gaz fazında (Pa) &#39;de CO2 kısmi basıncıdır. p i i (örneğin, NO ve SO x x gibi) gaz toksik bir bileşim inci kısmi basıncıdır. P max.i biyokütle büyümesi tam inhibisyonu için zehirli gaz kısmi basıncıdır. η i ampirik katsayısıdır. K s, Michaelis-Menten sabitidirCO 2 (mol · m -3). K I CO 2 inhibisyon sabiti (mol · m -3) &#39;dir. K ışık yoğunluğu Michaelis-Menten sabiti (ľmol · m -2 · sn -1). H (m 3 · mol -1 · Pa) CO 2 için Henry&#39;nin sabittir. K La CO 2 (saat -1) kütle aktarım hızıdır. I · aşağıdaki gibi 9 ((3) Denklem) hesaplanabilir m-2 sec · -1, ortalama ışık şiddeti, umol olduğunu. <img alt="Denklem 3" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq3.jpg" width="500px" /> Model parametrelerinin tanımı Tablo 1&#39;de görülmektedir. Başlangıç ​​koşulları biyokütle ve çözünmüş CO2 konsantrasyonları, sırasıyla, 100 mg / L ve 13 umol / L, olduğunu varsayalım. Hacimsel kütle transfer katsayısı ampirik ölçekler içsel tahmin edilebilirbiyoreaktöre tion 10 parametreleri: <img alt="Denklem 4" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq4.jpg" width="500px" /> P g / V biyoreaktörde havalandırılmış sistemin güç tüketimi (W / m 3) &#39;dir. u biyoreaktör (m / saniye) boyunca gaz akışının yüzeysel hızıdır gs. α, β ve γ karıştırma koşulları ile ilişkili sabitlerdir. <ol><li> Modeli simülasyon (Ekran görüntüleri Destekleyici Malzeme I verilmiştir) için bir Simulink dosyası oluşturun. <ol><li> Simulink modeli oluşturmak için MATLAB arabirimde Dosya / Yeni / Model seçin ve açık &quot;Kütüphane Tarayıcısı&quot; (screen shot 1). </li><li> Denklem 1 ve 2 için Subsystems oluşturmak için kütüphane tarayıcı &#39;alt sistemi&#39; bloğu seçin. , Simulink model dosyası için bir alt bloğu sürüklemek &#39;Denklem 1&#39; adını değiştirin ve sonra Denklem 2 için aynı adımları tekrarlayın. </li><li&gt; her bir alt uygun blokları ve parametreleri oluşturma (screen shot 3). Çift çift parametrelerini ayarlamak için blokları tıklayın ve diğer alt sistem için bu adımları yineleyin kütüphane tarayıcıdan uygun blokları seçim ve hesaplama sırasını göstermek oklar, onlara bağlanmak, &#39;Denklem 1&#39; blok tıklatın. Not: 1) dizisi giriş blokları ile başlar ve çıkış blokları ile bitmelidir; 2) toplama, çıkarma, çarpma, bölme ve entegrasyon için operatör blokları tüm kütüphane tarayıcı bulunabilir, ve biz kullanıcıların yardım dosyaları keşfedilecek önermek Simulink bunları kullanmak nasıl anlamak için, 3) optimizasyonu çözücü araç çubuğunda yolu Simülasyonu / Konfigürasyon parametreleri ile ayarlanabilir. </li><li> Model denklemleri (1 ve 2) temsil etmek için iki alt sistemlere bağlantı. Gerekirse, ok ile diğer alt sisteminin girişine bir alt sisteminin çıkışını. Örneğin, çözünmüş CO2 konsantrasyonu, o olduğunuıkış Denklem 2 alt sistemi, ve aynı zamanda Denklem 1 alt sistemi giriş olarak. </li><li> On-off CO 2 darbeleri simüle etmek &#39;Denklem 2&#39; için girdi olarak blok &#39;Jeneratör&#39; Darbe kullanın; yüzey ışık giriş değeri olarak &#39;Constant&#39; bloğunu kullanın. Çift böyle süre süre ve genlik gibi parametreleri değiştirmek için blokları tıklayın. </li><li> Kütüphane tarayıcı &#39;MUX&#39; bloğu seçin. &#39;Mux&#39; tüm çıkışlarını bağlayın ve sonra simüle sonuçları saklar blok &#39;Workspace&#39;in için,&#39; bağlayın. </li><li> Üst araç çubuğunda &#39;Simülasyon durma zamanı&#39; Define, &quot;düğmesini tıklayın <img src="/files/ftp_upload/50718/playarrow.jpg" alt="Ok" width="10px" fo:content-width="0.1in" fo:src="/files/ftp_upload/50718/playarrow.jpg" /> &quot;Simülasyonu başlatmak için, ve sonuçları (ekran görüntüsü 4) MATLAB çalışma alanında gösterilir. </li></ol></li><li> Optimum CO 2 koşulları profile dinamik optimizasyon yaklaşımı uygulayın. </li&gt; </ol> Biyokütle üretimi 11, MATLAB &#39;fmincon&#39; işlevi ve CVP (vektör kontrolü parametrelendirmesini) 12 kullanılır maksimize giriş girişi CO 2 profil (P opt) değişiklikleri bulmak için. 2. optimizasyon algoritması göstermektedir Şekil (Desteklenmesi MATLAB programlama kodlarını görmek Malzeme II).

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Bu yazarlar ifşa hiçbir şey yok.

Bu çalışmada, biz fotobiyoreaktörler alg toprağı ekme ölçekleme için deneysel protokol göstermektedir. Biz de alg büyümesini teşvik etmek için baca gazı girişler için çeşitli yöntemleri inceliyoruz. Bir kütle transferi ve biyo-tepki modeli kullanarak, CO 2 kütle transfer katsayısı (biyoreaktör karıştırma durumuna ve CO 2 yüzeysel hız tarafından belirlenir) K La güçlü alg büyümesini etkilediğini göstermektedir. Modeli simülasyon kısa pulse genişliğ...

<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>
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			<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>
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			<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>
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			<td height="39" style="height:39px;width:212px;">Filters</td>
			<td style="width:212px;">Aerocolloid LLC, Minnesota USA</td>
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			<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>
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</table>

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

Santrallerden kaynaklanan baca gazı alg ekimi teşvik etmek ve sera gazı emisyonlarını 1. azaltabilir. Mikroalg daha verimli bitki 3 daha güneş enerjisini yakalamak, ama aynı zamanda gelişmiş biyoyakıt 2-4 sentez değil sadece. Genellikle, atmosferik CO 2 maksimal alg büyümesini 5 desteklemek için yeterli bir kaynak değildir. Diğer taraftan, endüstriyel egzoz gazlarındaki CO 2&#39;nin yüksek konsantrasyonlarda alg fizyolojisi üzerinde olumsuz etkileri vardır. Sonuç olarak, (örneğin, besin maddeleri ve ışık gibi) hem de yetiştirme koşulları ve foto-biyo-reaktörlere baca gazı akışının kontrol sistemi &quot;Yosunlar için baca gazı&quot; etkili bir geliştirilmesi için önemlidir. Araştırmacılar farklı foto-biyo yapılandırmaları 4,6 ve yetiştirme stratejilerini baca gazı ile 7,8 önerdi. Burada, biz gaz ayarları baca yanıt mikroalgal büyüme tahmin modelleri nasıl kullanılacağını gösteren bir protokol mevcut. Biz perform hem deneysel illüstrasyon ve model simülasyonları baca gazı ile alg büyüme için uygun koşulları belirlemek. Biz homojen bir fotoğraf biyoreaktöründe mikroalgal büyüme simüle etmek için kütle transferi ve ışık yoğunluğu denklemleri ile birleştiğinde bir Monod-temelli bir model geliştirmek. Modeli simülasyon farklı baca gazı ayarları altında alg büyüme ve baca gazı tüketimlerini karşılaştırır. Model göstermektedir: 1) nasıl alg büyüme CO 2 farklı hacimsel kütle transfer katsayıları etkilenir; 2) nasıl dinamik optimizasyon yaklaşımı (DOA) üzerinden alg büyüme için optimal CO 2 konsantrasyonu bulabilirsiniz; 3) nasıl bir tasarlayabilirsiniz alg biyokütle büyümeyi teşvik etmek ve baca gazı kullanımını azaltmak için on-off baca gazı darbe dikdörtgen. Deneysel tarafta, biz (doğal gaz yanma tarafından üretilen) baca gazı altında Chorella yetiştirmek için bir protokol mevcut. Deneysel sonuçlar niteliksel model tahminleri doğrulamak olduğu yüksek frekans baca gazı puLSKÖ önemli ölçüde alg ekimi artırabilir.

Bizim daha önceki deneysel analizi bu önlenmesini 13 hafifletmek mümkün CO 2 pozlama süresini edilir düşürürken, sürekli baca gazı zehirlenmeleri olumsuz, Chlorella büyümeyi etkiler gösterir. Daha iyi baca gazı giriş ve yosun büyümesi ilişkileri anlamak için, baca gazı varlığında biyokütle büyümesi simüle etmek için ampirik bir model geliştirmek. Biz baca gazı% 15 CO 2 (: oksi-yanma santralin baca gazı CO 2&gt;% 15 olurken kömür yakı...

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

Santrallerden kaynaklanan baca gazı alg büyüme için ucuz bir CO 2 kaynağıdır. Biz sistemleri &quot;ekimi alg için baca gazı&quot; prototip inşa ve alg ekimi işlemini büyütmek için nasıl tarif var. Biz, Chlorella sp büyümesi için baca gazının optimum operasyon ve tasarım simülasyonu için kütle transferi bio-tepki modelinin kullanımı göstermiştir. alg fotoğraf biyoreaktörlerde.

Bilgisayar simülasyonları ile fotobiyoreaktörler içinde Mikroalgler Büyüme teşvik için Baca Gazı ayarlarını optimize

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

Research

JoVE Journal

Environment

14.2K Görüntüleme.  Washington University in St. Louis, St. Louis.  Santrallerden kaynaklanan baca gazı alg büyüme için ucuz bir CO 2 kaynağıdır. Biz sistemleri "ekimi alg için baca gazı" prototip inşa ve alg ekimi işlemini büyütmek için nasıl tarif var. Biz, Chlorella sp büyümesi için baca gazının optimum operasyon ve tasarım simülasyonu için kütle transferi bio-tepki modelinin kullanımı göstermiştir. alg fotoğraf biyoreaktörlerde. 

Video: 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.

Mikroalglerden yağlı asit içeriği ve bileşimi analizi

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

Çevre

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.

Statik Chambers kullanma Tarım Topraklarının Sera Gazı Flux Ölçümü

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.

Ağır Metal ve Mikroalglerden Verimlilik Diğer İnorganik Bulaşanlar Kantitasyonu

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.

Prekambriyen Deniz upwelling Sistemi Fotosentetik Bakteri Büyüme Keşfet bakımından zengin bir Demir (II) Laboratuar Simülasyonu

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.

Bir Körüklü Thermogradient Tablo Toprak Süreçleri Bitki Büyüme değerlendirilmesi ve İzleme Toprak Sıcaklıklar Denetim

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.

Laboratuvar İlaçlama haşere kontrolü ile nitrik oksit gaz için prosedürleri

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.

Koku ve derin tarafından yayılan gaz konsantrasyonları değerlendirmek için laboratuvar ölçekli modeli paketi gübre Yataklı

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.

Partikül büyüklüğü ve metan MPA'dan kapasite şeyl arasındaki ilişkinin deneysel çalışma

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.

Kök büyüme ve yerelleştirilmiş besin kavramaları görselleştirmek için en iyi duruma getirilmiş bir Rhizobox Protokolü

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.

Kabarcık sütun Photobioreactors ve bir tahlil yeşil mikroalg ekimi için nötr lipitler

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