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Heirloom tomato varieties are in demand by consumers due to high antioxidant levels. However, these varieties are difficult to produce and are prone to disease and low yield. To overcome these problems, heirloom tomatoes may be grafted onto disease-resistant rootstocks and cultivated in hydroponic systems. However, it is unknown if the lycopene content of hydroponically grown tomatoes is affected by grafting. Heirloom (Black Krim and Green Zebra) and standard (Big Beef) varieties were grafted onto wild type (WT) or productive rootstocks (Arnold and Supernatural). Tomatoes were harvested at maturity, freeze-dried, ground into a powder, and stored at -20ºC until further analysis. Phenolic content of methanol extracts was determined using the Folin-Ciocalteu assay. In brief, 20 uL tomato extract was incubated with 10 uL 2 N Folin-Ciocalteu reagent, 100 uL ddH2O, and 120 uL 12.5% sodium carbonate, and incubated for 30 min. Phenolic content was then measured spectrophotometrically at 750 nm (Spectra Max 250 Microplate Reader, Molecular Devices, San Jose, CA). Gallic acid was used as a phenolic standard for calculations of gallic acid equivalents (GAE; μmol/g tomato dry weight). The phenolic content of Big Beef, Black Krim, and Green Zebra grafted onto WT, Arnold, and Supernatural was 13.57±3.14, 14.34±2.40, 15.80±2.77 (Big Beef), 14.40±2.72, 15.29±2.93, 13.59±2.58 (Black Krim), and 16.97±4.03, 10.95±4.22, 15.84±2.81 (Green Zebra; GAE; mean±std), respectively. Green Zebra grafted onto Arnold exhibited significantly lower (p<0.01) phenolic levels compared to self-grafted Green Zebra.
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Data set for distractor beads task and PDI.
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Heirloom tomato varieties are in demand by consumers due to high antioxidant levels. However, these varieties are difficult to produce and are prone to disease and low yield. To overcome these problems, heirloom tomatoes may be grafted onto disease-resistant rootstocks and cultivated in hydroponic systems. However, it is unknown if the antioxidant capacity of hydroponically grown tomatoes is affected by grafting. Heirloom (Black Krim and Green Zebra) and standard (Big Beef) varieties were grafted onto wild type (WT) or productive rootstocks (Arnold and Supernatural). Tomatoes were harvested at maturity, freeze-dried, ground into a powder, and stored at -20ºC until further analysis. Antioxidant capacity of methanol extracts was evaluated by the 2,2’-azino-di[3-ethylbenzthiazoline sulfonsyr]sulphonic acid (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. For the ABTS assay, the antioxidant capacity was measured by incubating 10 uL tomato extract was with 95 uL 3.5 mM ABTS• for 30 s at room temperature, and the absorbance at 734 nm was measured spectrophotometrically (Spectra Max 250 Microplate Reader, Molecular Devices, San Jose, CA). Trolox was used as an antioxidant standard for calculations of trolox equivalents (TE; μmol/g tomato dry weight). The antioxidant capacity of Big Beef, Black Krim, and Green Zebra grafted onto WT, Arnold, and Supernatural was 12.18±0.82, 12.34±0.65, 12.26±0.79 (Big Beef), 12.35±0.83, 11.99±1.31, 11.60±1.54 (Black Krim), and 11.42±1.12, 11.76±1.93, 11.71±0.83 (Green Zebra; TE; mean±std), respectively. For the DPPH assay, 10 μM DPPH in 90% aqueous methanol was measured spectrophotometrically at 517 nm (Spectra Max 250 Microplate Reader, Molecular Devices, San Jose, CA) to ensure that the absorbance was between 0.510-0.540. To determine the antioxidant capacity, 10 uL tomato extract was mixed with 195 uL 10 μM DPPH in 90% aqueous methanol and incubated in the dark for 15 min. The decrease in absorbance at 517 nm was then measured. Trolox was used as an antioxidant standard for calculations of TE. The antioxidant capacity of Big Beef, Black Krim, and Green Zebra grafted onto WT, Arnold, and Supernatural was 7.88±0.72, 7.62±0.87, 7.99±0.68, (Big Beef), 7.59±0.78, 8.11±0.54, 7.70±0.88 (Black Krim), and 8.00±0.53, 7.66±0.78, 8.19±0.64 (Green Zebra; TE; mean±std). The results further showed that none of the tomato varieties exhibited statistically significantly different antioxidant capacity.
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Retention data used in publications in or submitted to Journal of Chromatography A with A. R. Horner as first author. Retention data for ~ 100 compounds on a Waters BEH C-18 column in acidic acetonitrile/water mobile phases at phase ratio and temperatures giving a range of k for each compound about 1 - 100. These are in the CSV file "RetentionData". The compounds/solutes are identified by number. The correspondence between the number and the compound name is in "Compound List and Conditions". Enthalpies for the compounds and functional group counts are in FGEnthalpyData.xlsx
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The data is about some emerging markets firms fundamentals for the period 2010-2018. The data are gathered from Compustat Global. It includes the variables total assets, cash and equivalents, capital expenditures, leverage, R&D, Cash flow, intangibles, net working capital, yearly sales growth, cash flow volatility...
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These 10 attached datasets are what underly the data in the paper "Lin C., Cohen J.B., Wang S., and Lan R. (2020) "Application of a Combined Standard Deviation and Mean Based Approach to MOPITT CO Column Data, and Resulting Improved Representation of Biomass Burning and Urban Air Pollution Sources." Submitted to Remote Sensing of Environment. In specific the data represent: dataset1.mat: Map of classifications (2000-2016) dataset2.mat: Map of classifications (2000-2009) dataset3.mat: Map of classifications (2010-2016) dataset4.mat: Weekly averaged CO Total Column dataset5.mat: Climatological Mean of #4 dataset6.mat: Climatological Normalized Standard Deviation of #4 dataset7.mat: Weekly averaged AERONET AOD at 12 stations dataset8.mat: MOPITT CO mean time series over the Yangtze River Delta region dataset9.mat: MOPITT CO mean time series over the Upper, Lower, and Downwind Biomass Burning regions dataset10.mat: MOPITT CO mean and standard deviation over the Chengdu Basin fig_16.mat: EOF1 and the linear combination of EOF2 and EOF3 finn_year_2000_2018.mat: FINN CO emissions year by year
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statistical data
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The current database is the backbone of the research by Angouria-Tsorochidou and Thomsen (2020) “The effect of the collection system on biowaste quality and a modelling framework to evaluate organic waste-derived fertilizers” Elisavet Angouria-Tsorochidou1, 2 and Marianne Thomsen1, 2*. The database consists of two data sets, i) quality data of source-separated organic fraction of municipal solid waste (SS-OFMSW) [column C:CN] and ii) quality data of mechanically separated organic fraction of municipal solid waste (MS-OFMSW) from mixed collected residual waste [column CP:DY.] The goal of this database is to present aggregated data on biowaste quality for the ease of future research on circular bio-economy. The database is given on the “Data” tab. It includes 111 cases (row 1) and consists of 55 registered parameters (column A). The references for each case is given in row 58 for all 111 cases while the bibliographic form is given in the “Bibliography” tab in detail. The authors suggest that before the utilization of each case, the users should refer to the original data paper for further information, as well as, citing the original reference. The data included in the database are transformed into uniform units to allow for comparison. The “Memorandum” tab includes further information for the inserted data. 1 Research Group on Eco-Industrial System Analysis, Department of Environmental Science, Aarhus University, Frederiksborgvej 399, Postboks 358, DK-4000, Roskilde, Denmark 2 Aarhus University Centre for Circular Bioeconomy *Corresponding Author email: mth@envs.au.dk The research was performed as part of the Horizon 2020 project DECISIVE (Decentralised valorisation of biowaste) under grant agreement N° 689229. The Graduate School of Science and Technology at Aarhus University further supported this work.
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The R data file (supp.RData) contains a list object that has observed covariance matrixes, residual correlation matrixes, approximate fit indices, and weighted least squares diagonal weight matrixes (models 2-3 only) for the three primary models. The .R file (supp.R) demonstrates how to access the data in the supp.RData file.
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Different daily distribution of proteins does not influence the variations in body composition in a sample of subjects undergoing a low-calorie Mediterranean-type diet.
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