Quantification of 3,4-Dimethyl-1H-Pyrazole Using Ion-Pair LC-MS/MS on a Reversed-Phase Column.

BACKGROUND: Few methods exist for the analysis of the soil nitrification inhibitor 3,4-dimethyl-1H-pyrazole (3,4-DMP), which is a pesticide with the ability to reduce the production of nitrogenous greenhouse gases in soils as a result of fertilizer application. Due to its small size and polar nature, 3,4-DMP can be difficult to retain on an LC column, which makes diversion of a co-extracted soil matrix away from the MS/MS impossible. OBJECTIVE: The current study aims to better control the retention time (RT) of 3,4-DMP. Additionally, 3,4-DMP-15N2 was synthesized and used as an internal standard for the soil extraction of 3,4-DMP. METHODS: Perfluoroalkanoic acids were used as ion-pair reagents and were compared for their abilities to improve peak shape and RT, to better separate 3,4-DMP from the soil matrix without the need for cleanup during soil extraction. RESULTS: RTs increased with both the carbon number and the concentration of the perfluoroalkanoic acid, and this improved peak shape and height. Perfluorooctanoic acid performed best, and improved peak height (PH) and shape were obtained by increasing the flow rate, resulting in a better S/N than from formic acid. The method provided a 10-fold improvement limit of quantitation on the most sensitive existing method and the use of 3,4-DMP-15N2 as an internal standard resulted in recoveries of 101-107%. CONCLUSION: Ion-pair reagents drastically increased the retention of 3,4-DMP and allowed the re-use of old LC columns that may otherwise be discarded. Improved separation of 3,4-DMP from the soil matrix allowed much of the matrix to be diverted from the MS/MS spray chamber. HIGHLIGHTS: Greater control of 3,4-DMP retention by the LC column resulting in the ability to separate 3,4-DMP from the soil matrix. The inclusion of ion-pair reagents only in the aqueous phase reduced ionization suppression of the analytes in the MS source.

A Bayesian belief data mining approach applied to rice and shrimp aquaculture.

In many parts of the world, conditions for small scale agriculture are worsening, creating challenges in achieving consistent yields. The use of automated decision support tools, such as Bayesian Belief Networks (BBNs), can assist producers to respond to these factors. This paper describes a decision support system developed to assist farmers on the Mekong Delta, Vietnam, who grow both rice and shrimp crops in the same pond, based on an existing BBN. The BBN was previously developed in collaboration with local farmers and extension officers to represent their collective perceptions and understanding of their farming system and the risks to production that they face. This BBN can be used to provide insight into the probable consequences of farming decisions, given prevailing environmental conditions, however, it does not provide direct guidance on the optimal decision given those decisions. In this paper, the BBN is analysed using a novel, temporally-inspired data mining approach to systematically determine the agricultural decisions that farmers perceive as optimal at distinct periods in the growing and harvesting cycle, given the prevailing agricultural conditions. Using a novel form of data mining that combines with visual analytics, the results of this analysis allow the farmer to input the environmental conditions in a given growing period. They then receive recommendations that represent the collective view of the expert knowledge encoded in the BBN allowing them to maximise the probability of successful crops. Encoding the results of the data mining/inspection approach into the mobile Decision Support System helps farmers access explicit recommendations from the collective local farming community as to the optimal farming decisions, given the prevailing environmental conditions.

Cross-continental importance of CH4 emissions from dry inland-waters.

Despite substantial advances in quantifying greenhouse gas (GHG) emissions from dry inland waters, existing estimates mainly consist of carbon dioxide (CO2) emissions. However, methane (CH4) may also be relevant due to its higher Global Warming Potential (GWP). We report CH4 emissions from dry inland water sediments to i) provide a cross-continental estimate of such emissions for different types of aquatic systems (i.e., lakes, ponds, reservoirs, and streams) and climate zones (i.e., tropical, continental, and temperate); and ii) determine the environmental factors that control these emissions. CH4 emissions from dry inland waters were consistently higher than emissions observed in adjacent uphill soils, across climate zones and in all aquatic systems except for streams. However, the CH4 contribution (normalized to CO2 equivalents; CO2-eq) to the total GHG emissions of dry inland waters was similar for all types of aquatic systems and varied from 10 to 21%. Although we discuss multiple controlling factors, dry inland water CH4 emissions were most strongly related to sediment organic matter content and moisture. Summing CO2 and CH4 emissions revealed a cross-continental average emission of 9.6 ± 17.4 g CO2-eq m-2 d-1 from dry inland waters. We argue that increasing droughts likely expand the worldwide surface area of atmosphere-exposed aquatic sediments, thereby increasing global dry inland water CH4 emissions. Hence, CH4 cannot be ignored if we want to fully understand the carbon (C) cycle of dry sediments.

Understanding and modeling alternating tangential flow filtration for perfusion cell culture.

Alternating tangential flow (ATF) filtration has been used with success in the Biopharmaceutical industry as a lower shear technology for cell retention with perfusion cultures. The ATF system is different than tangential flow filtration; however, in that reverse flow is used once per cycle as a means to minimize fouling. Few studies have been reported in the literature that evaluates ATF and how key system variables affect the rate at which ATF filters foul. In this study, an experimental setup was devised that allowed for determination of the time it took for fouling to occur for given mammalian (PER.C6) cell culture cell densities and viabilities as permeate flow rate and antifoam concentration was varied. The experimental results indicate, in accordance with D'Arcy's law, that the average resistance to permeate flow (across a cycle of operation) increases as biological material deposits on the membrane. Scanning electron microscope images of the post-run filtration surface indicated that both cells and antifoam micelles deposit on the membrane. A unique mathematical model, based on the assumption that fouling was due to pore blockage from the cells and micelles in combination, was devised that allowed for estimation of sticking factors for the cells and the micelles on the membrane. This model was then used to accurately predict the increase in transmembane pressure during constant flux operation for an ATF cartridge used for perfusion cell culture.