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1.
Article in English | MEDLINE | ID: mdl-24124879

ABSTRACT

A large national investigation into the extent of gluten cross-contamination of naturally gluten-free ingredients (flours and starches) sold in Canada was performed. Samples (n = 640) were purchased from eight Canadian cities and via the internet during the period 2010-2012 and analysed for gluten contamination. The results showed that 61 of the 640 (9.5%) samples were contaminated above the Codex-recommended maximum level for gluten-free products (20 mg kg⁻¹) with a range of 5-7995 mg kg⁻¹. For the ingredients that were labelled gluten-free the contamination range (5-141 mg kg⁻¹) and number of samples were lower (3 of 268). This picture was consistent over time, with approximately the same percentage of samples above 20 mg kg⁻¹ in both the initial set and the subsequent lot. Looking at the total mean (composite) contamination for specific ingredients the largest and most consistent contaminations come from higher fibre ingredients such as soy (902 mg kg⁻¹), millet (272 mg kg⁻¹) and buckwheat (153 mg kg⁻¹). Of the naturally gluten-free flours and starches tested that do not contain a gluten-free label, the higher fibre ingredients would constitute the greatest probability of being contaminated with gluten above 20 mg kg⁻¹.


Subject(s)
Celiac Disease/diet therapy , Diet, Gluten-Free/adverse effects , Edible Grain/chemistry , Flour/analysis , Food Contamination , Glutens/analysis , Starch/chemistry , Canada , Diet Surveys , Dietary Fiber/analysis , Edible Grain/adverse effects , Edible Grain/economics , Enzyme-Linked Immunosorbent Assay , Fagopyrum/adverse effects , Fagopyrum/chemistry , Fagopyrum/economics , Flour/adverse effects , Flour/economics , Food Handling , Food Labeling , Glutens/adverse effects , Humans , Internet , Nuts/adverse effects , Nuts/chemistry , Nuts/economics , Panicum/adverse effects , Panicum/chemistry , Panicum/economics , Seeds/adverse effects , Seeds/chemistry , Soy Foods/adverse effects , Soy Foods/analysis , Soy Foods/economics , Starch/adverse effects , Starch/economics
2.
Environ Sci Technol ; 43(21): 8016-20, 2009 Nov 01.
Article in English | MEDLINE | ID: mdl-19924916

ABSTRACT

Food price fluctuations, which will be exacerbated by climate change, make West African food security even more tenuous.


Subject(s)
Climate Change/economics , Food/economics , Marketing , Africa, Western , Agriculture/economics , Panicum/economics , Panicum/growth & development , United Nations , Zea mays/economics , Zea mays/genetics
3.
Environ Sci Technol ; 41(19): 6657-62, 2007 Oct 01.
Article in English | MEDLINE | ID: mdl-17969677

ABSTRACT

This paper presents a linear programming (LP) methodology for estimating the cost of reducing a state's coal-fired power plant carbon dioxide emissions by cofiring switchgrass and coal. LP modeling allows interplay between regionally specific switchgrass production forecasts, coal plant locations, and individual coal plant historic performance data to determine an allocation of switchgrass minimizing cost or maximizing carbon reduction. The LP methodology is applied to two states, Pennsylvania (PA) and Iowa (IA), and results are presented with a discussion of modeling assumptions, techniques, and carbon mitigation policy implications. The LP methodology estimates that, in PA, 4.9 million tons of CO2/year could be mitigated at an average cost of less than $34/ton of CO2 and that, in IA, 7 million tons of CO2/year could be mitigated at an average Cost of Mitigation of $27/ton of CO2. Because the factors determining the cofiring costs vary so much between the two states, results suggest that cofiring costs will also vary considerably between different U.S. regions. A national level analysis could suggest a lowest-cost cofiring region. This paper presents techniques and assumptions that can simplify biomass energy policy analysis with little effect on analysis conclusions.


Subject(s)
Air Pollution/prevention & control , Carbon Dioxide/economics , Coal/economics , Energy-Generating Resources , Panicum/economics , Power Plants/economics , Air Pollutants/economics , Air Pollution/economics , Costs and Cost Analysis , Iowa , Models, Economic , Pennsylvania
4.
Bioresour Technol ; 98(5): 1033-44, 2007 Mar.
Article in English | MEDLINE | ID: mdl-16797978

ABSTRACT

This study develops cost, energy input and carbon emissions for a number of switchgrass supply options. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model developed at Oak Ridge National Laboratory is used to evaluate the delivery systems. Three biomass collection systems: baling, loafing and ensiling are evaluated. The number and operational performance of equipment are specified to complete collection operations within 120 days of harvest after August 1. Bales are stacked and tarped on the farm side. The transport of biomass from the farm side to a biorefinery takes place over a full year cycle, i.e. 365 days. Supply quantities range from 454 to 4540 dry tonnes/day (500-5000 dry tons/day). Delivered costs to a biorefinery with capacity of 1814 dry tonnes/day (2000 dry tons/day) are: 44-47 dollars/dry tonne for delivered bales (round and square); 37 dollars/dry tonne for delivered loafs (size 2.4 m x 3.6 m x 6 m); 40 dollars/dry tonne for chopped biomass; and 48 dollars/dry tonne for ensiled chops. These costs do not include any payment to the farmers or switchgrass farming cost. Based on the data from literature, the switchgrass farming cost can range from 30 to 36 dollars/dry tonne. These costs would be additional to the switchgrass collection and transportation cost. Switchgrass collection is generally less expensive than collection of straw or corn stover because of the assumed high yield of 11 dry tonnes/ha and a denser biomass. Energy consumption for delivery systems at this capacity ranges from 4.8% to 6.3% of the energy content of switchgrass. Additional 1% of the energy content of switchgrass is consumed in its farming. At 1814 dry tonnes/day (2000 dry tons/day) capacity, greenhouse gas emissions ranges from 75 to 100 kg of CO2/dry tonne of switchgrass delivered.


Subject(s)
Biomass , Energy-Generating Resources/economics , Logistic Models , Panicum/economics , Panicum/supply & distribution , Transportation/economics , Air Pollution/analysis , Computer Simulation , Cost-Benefit Analysis/methods , Energy-Generating Resources/statistics & numerical data
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