O'brien N.,Biosystems Engineering |
Cummins E.,Biosystems Engineering
Journal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering | Year: 2010
As nanomaterials find increased application in commercial and industrial products and processes so too the potential for release of these novel materials into the environment increases. The characteristics of these materials also may result in novel toxicological actions related to their nanoscale, which will have implications on their ecotoxicological and toxicological limits of exposure and eventual regulation. A framework for nanomaterial risk assessment on regulatory, ecotoxicological and toxicological bases developed from recent exposure and toxicity studies is presented. The release of nanoscale TiO 2, Ag and CeO2 to the atmosphere and surface waters is assessed against provisional toxicological bench mark doses (BMDs) and critical effect doses (CEDs) developed from best available data. Predicted levels of nanomaterial release to surface waters and the atmosphere resulted in regulatory risk rankings of moderate concern based on worst case provisional regulatory limits. Inhalation and ingestion risk rankings were of very low concern based on the provisional inhalation and ingestion toxicity BMDLs and CEDLs determined for the nanomaterials in question. More toxicological data is needed on nanoscale CeO2 inhalation to develop a true dose response as in vitro cytotoxicity studies yielded an inhalation risk ranking of lower concern. The moderate to high ecotoxicological risk rankings posed by the release of nanoscale TiO2 and Ag to surface waters highlights the need for guidance and restriction on the usage and disposal of commercial products containing nanomaterial. The risk rankings presented in this assessment give a first indication of the relative risks posed by the usage and release of these materials into the environment and indicate what materials require further investigation into their nano-specific toxicological actions. As more nano-relevant toxicity studies are published, end-points and risk levels related to nano-specific toxicity actions may be determined and the provisional BMDLs developed as part of this framework refined, resulting in more confident risk rankings. Copyright © Taylor & Francis Group, LLC.
O'Brien N.,Biosystems Engineering |
Cummins E.,Biosystems Engineering
Human and Ecological Risk Assessment | Year: 2010
Nano-functionalized products such as UV protective paints additives, antimicrobial food packaging, and fuel additives offering reduced CO2 emissions have the potential to secure a significant Irish market share in the near future. This scoping study gives a first estimation of nanomaterial surface water concentrations and population ingestional exposure through drinking water resulting from these products. As nanomaterial behavior in wastewater treatment plants (WWTPs) and water treat-ment plants (WTPs) is currently unclear, bridging data relating to potentially relevant materials (pharmaceuticals and metal removal efficiencies inWWTPs;pathogen removal efficiencies in WTPs) are employed in this study. Mean nanomaterial re-moval efficiencies of 59.8% and 70.2% were predicted for Irish WWTPs, between 96.95% and 0% for Irish WTPs. Predicted nano-scale TiO2 concentrations in surface waters (resulting from exterior paints) were 2 orders of magnitude greater than that of Ag (resulting from food packaging) and CeO2 (resulting from fuel additives), respectively. Predicted surface and drinking water concentrations were unlikely to pose any ecotoxicological or human health risk, although nano-scale TiO2 and Ag may warrant monitoring as part of standard surface water monitoring schemes. Future research should be directed toward characterizing the behavior of different categories of nanomaterials within WWTP processes. © Taylor & Francis Group, LLC.
Harvesting cauliflower is a science unto itself because the white heads are hidden beneath numerous leaves. This means that pickers have to pull back the protective leaves head for head to look at the cauliflower and decide whether it is ripe for harvesting. Pickers comb a field approximately four to five times in intervals of two to three days until the very last head of cauliflower has been harvested. This work is strenuous and backbreaking. Another challenge for farmers is their need for numerous pickers at once for a short time when harvest season is pending. Finding enough hands for this hard work is often difficult, though. Machines on the other hand would harvest the entire field at once and, since cauliflower heads ripen at different rates, thus even heads that are still too small or unripe. In the future, a machine will harvest cauliflower just as selectively as human workers would. This machine is called VitaPanther. It is being developed by researchers at the Fraunhofer Institute for Factory Operation and Automation IFF and and their colleagues at ai-solution GmbH together with five other partners: Gottfried Wilhelm Leibniz University Hannover, Steig GmbH, Beutelmann Gemüseanbau, König Sondermaschinenbau GmbH and Inokon GmbH. A prototype of VitaPanther will be finished and tested in 2017. This machine will benefit farmers in several ways: It will harvest cauliflower heads significantly faster than human pickers and could additionally work at night, too. Another plus is that farmers will be able to dispense with troublesome searches for workers. Martin Steig, farmer and CEO of Steig GmbH and and one of the future potential users of the harvester is convinced it is needed. "Farming is the last profession in which the necessary profits can only be made with a large workforce. Automation is essential for us farmers, because the minimum wage is making vegetable harvesting unfeasible. Harvesting is sustained by two components: the availability of a seasonal workforce and the pay. A shift in one of these components jeopardizes the structure. The demand for technology is thus very great." How can a machine detect the vegetable's ripeness without seeing its "whiteness", without weighing it, without knowing its size? These are the questions on which the researchers at the Fraunhofer IFF are working. They are researching and developing the necessary sensor systems along with the software that analyzes and preprocesses the data obtained so that the machine receives clear information on whether to harvest or to wait. "We are taking advantage of an effect we discovered in preliminary tests: The leaves of ripe cauliflower have a different biochemical composition than those covering unripe heads," explains Prof. Udo Seiffert, Manager of the Biosystems Engineering Expert Group at the Fraunhofer IFF. Hyperspectral cameras mounted on the harvester scan the heads of cauliflower. Whereas a conventional camera only works with visible light and produces a color picture consisting of red, green and blue tones, a hyperspectral camera scans a defined range of wavelengths beyond human vision and also encompassing infrared and ultraviolet light. Applying a mathematical model, the researchers can determine the biochemical composition of the leaves and thus the ripeness of the cauliflower based on the intensity of the light reflected in the different wavelengths scanned. The researchers are not analyzing the exact biochemical composition of the leaves, however, because the machine is only supposed to receive a yes-no command to harvest. The mathematical model that decodes the camera images into exactly this command is based on algorithms that originated with machine learning. The researchers are using examples to teach it. They "show" the camera different heads of cauliflower, which are simultaneously being inspected by a human expert. Following such a teaching phase, the system is able to decide autonomously which cauliflower should be harvested or not, even when the heads of cauliflower are unfamiliar. While the researchers from the Fraunhofer IFF are attending to the sensor systems and data analysis, their colleagues from ai-solution GmbH in Wolfsburg are working on the harvester unit that will be harvesting cauliflower heads in the future. They are building upon their asparagus harvester "Spargelpanther" for this. "We also intend to use this this asparagus harvester for other vegetables – cauliflower and head and leaf lettuce. Then, other harvester modules for other vegetables could be added in the future," says Christian Bornstein, CEO of ai-solution GmbH. "Our goal is to build a module that can be adapted to the existing unit." Farmers will only have to purchase one "vegetable harvester" in the future. Explore further: Hybrid energy harvester generates electricity from vibrations and sunlight
Hossain M.B.,Dublin Institute of Technology |
Hossain M.B.,Teagasc |
Brunton N.P.,Teagasc |
Patras A.,Biosystems Engineering |
And 4 more authors.
Ultrasonics Sonochemistry | Year: 2012
The present study optimized the ultrasound assisted extraction (UAE) conditions to maximize the antioxidant activity [Ferric ion Reducing Antioxidant Power (FRAP)], total phenol content (TP) and content of individual polyphenols of extracts from marjoram. Optimal conditions with regard to amplitude of sonication (24.4-61.0 μm) and extraction temperature (15-35°C) and extraction time (5-15 min) were identified using response surface methodology (RSM). The results showed that the combined treatment conditions of 61 μm, 35°C and 15 min were optimal for maximizing TP, FRAP, rosmarinic acid, luteolin-7-O-glucoside, apigenin-7-O-glucoside, caffeic acid, carnosic acid and carnosol values of the extracts. The predicted values from the developed quadratic polynomial equation were in close agreement with the actual experimental values with low average mean deviations (E%) ranging from 0.45% to 1.55%. The extraction yields of the optimal UAE were significantly (p < 0.05) higher than solid/liquid extracts. Predicted models were highly significant (p < 0.05) for all the parameters studied with high regression coefficients (R 2) ranging from 0.58 to 0.989. © 2011 Elsevier B.V. All rights reserved.
Butler E.,Biosystems Engineering |
Devlin G.,Biosystems Engineering |
Meier D.,Johann Heinrich Von Thunen Institute |
McDonnell K.,Biosystems Engineering
Bioresource Technology | Year: 2013
This research details the characterisation of four Irish-grown lignocellulosic biomasses for pyrolysis by biomass composition analysis, TGA, and Py-GC/MS-FID. Ash content (mf) increased in the order spruce (0.26. wt.%) < salix (1.16. wt.%) < miscanthus (3.43. wt.%) < wheat straw (3.76. wt.%). Analysis of hydrolysis-derived sugar monomers showed that xylose concentrations (4.69-26.76. wt.%) ranged significantly compared to glucose concentrations (40.98-49.82. wt.%). Higher hemicellulose and ash contents probably increased non-volatile matter, and decreased the temperature of maximum degradation by TGA as well as yields of GC-detectable compounds by Py-GC/MS-FID. Differences in composition and degradation were reflected in the pyrolysate composition by lower quantities of sugars (principally levoglucosan), pyrans, and furans for salix, miscanthus, and wheat straw compared to spruce, and increased concentrations of cyclopentenones and acids. © 2012 Elsevier Ltd.