Studies on Ground Corn Flowability as Affected by Particle Size and Moisture Content

Corn is the primary feed grain in the U.S., and it accounts for more than 90 percent of total feed grain production and use. Besides this, corn is the primary input for the U.S. ethanol industry. This results in tremendous infrastructure for handling and storage of corn and byproducts throughout the year. The flow properties of ground corn, which is a principal ingredient of animal feed, are very complex in nature. Many physical and chemical properties viz. angle of repose, bulk density, moisture of the product, protein content in the surface layer, etc. affects the flow properties of corn and its products. Flow through a hopper is a typical example of complex flow. Bridging or caking of feed material in feed hoppers are common problems, and many times blocks the flow completely leaving animals without feed. Daily changes in temperature and relative humidity affect the equilibrium moisture content of feed. Size of corn particles affect angle of repose, bulk density and cohesive forces between particles, and thus flow characteristics of the feed. In this study, flow characteristics of ground corn were examined as functions of particle size and moisture content. Feed utilization was historically maximum (i.e. minimum ratio of feed consumption to weight gain), when mean particle size diameter is about 822 microns for roller milled corn flour. In recent times, livestock producers have found that feed efficiency can increase as particle size decreases. Furthermore, excess moisture makes flour sticky and hampers free sliding of particles over each other during flow. Keeping this in view, different combinations of particle sizes and product moisture content were studied with the objectives of understanding and enhancing corn flour flowability

Quero et al 2013 Ecosystems

Quero et al 2013 Ecosystem

Data from "Warming reduces the cover and diversity of biocrust-forming mosses and lichens, and increases the physiological stress of soil microbial communities in a semi-arid Pinus halepensis plantation"

<p>Data from "F. T. Maestre, Escolar, C., R. Bardgett, J. A. D. Dungait, B. Gozalo & V. Ochoa. Warming reduces the cover and diversity of biocrust-forming mosses and lichens, and increases the physiological stress of soil microbial communities in a semi-arid Pinus halepensis plantation. Frontiers in Microbiology 6:865. doi: 10.3389/fmicb.2015.00865"</p> <p>There are three spreadsheets with data. The spreadsheet "PLFA_data" contains the raw PLFA data at the different sampling times. The spreadsheet "Cover_data" contains the cover data for mosses, lichens and the sum of both at the different sampling times. The third spreadshet contains the associated metadata, where a description of all the variables and units can be found.</p

Soil microbial communities drive the resistance of ecosystem multifunctionality to global change in drylands across the globe

<p>Data from "Manuel Delgado-Baquerizo, David J. Eldridge, Victoria Ochoa, Beatriz Gozalo, Brajesh K. Singh & Fernando T. Maestre. Soil microbial communities drive the resistance of ecosystem multifunctionality to global change in drylands across the globe ” There are four spreadsheets with data. The spreadsheets " Multiresistance" and “Multifunctionality” contain the raw data used in this paper. The spreadsheets "Dataset_metadata" contain the associated metadata, where a description of all the variables and units can be found.</p

Pathways regulating decreased soil respiration with warming in a biocrust-dominated dryland

This dataset corresponds to a long-term warming study performed in a biocrust-dominated dryland ecosystem in southeastern Spain, where we assessed the different autotrophic and heterotrophic pathways determining the effects of warming on soil respiration, and the consequences for soil organic carbon accumulation

Data from "Increasing aridity reduces soil microbial diversity and abundance in global drylands"

<p>Data from "Maestre, F. T., M. Delgado-Baquerizo, M., T. C. Jeffries, V. Ochoa, B. Gozalo, D. J. Eldridge, J. L. Quero, M. García-Gómez, A. Gallardo, W. Ulrich, M. A. Bowker, T. Arredondo, C. Barraza, D. Bran, A. Florentino, J. Gaitán, J. R. Gutiérrez, E. Huber-Sannwald, M. Jankju, R. L. Mau, M. Miriti, K. Naseri, A. Ospina, I. Stavi, D. Wang, N. N. Woods, X. Yuan, E. Zaady & B. K. Singh. Increasing aridity reduces soil microbial diversity and abundance in global drylands. Proceedings of the National Academy of Sciences USA, doi: 10.1073/pnas.1516684112"</p> <p>There are two spreadsheets with data. The spreadsheet "Data" contains the data used in the different analyses presented in the article. The spreadsheet "Metadata" contains the associated metadata, where a description of all the variables and units can be found.</p> <p> </p> <p> </p

N availability in soils from Stipa tenacissima grasslands along an aridity gradient in the Mediterranean

Data on N availability in soils from Stipa tenacissima grasslands along a Mediterranean aridity gradient (from Spain to Tunisia). The database also includes information about other soil, plant and abiotic variables of the sites surveyed. All the units and information about the variables are included in the "Metadata" spreadsheet

Top eight best-fitting regression models, ranked according to their AICc value, are presented.

<p>AICc measures the relative goodness of fit of a given model; the lower its value, the more likely the model to be correct. Aridity, pH, plant-ax1 and organic C were included in these models. Bare = data from bare ground soils only, and Stipa = data from <i>Stipa tenacissima</i> soils only.</p

Relationships between total nitrogen (N) availability and aridity, pH, plant-ax1 (first component of a PCA including the cover of bare and plant microsites, average plant patch interdistance, area of plant patches and number of plant patches per 10 m of transect) and organic carbon for both <i>Stipa tenassicima</i> (STIPA) and Bare ground (BS) microsites.

<p>Every data point is the average of five replicated soil samples. Significance levels are as follows: *p<0.05, **p<0.01 and ***p<0.001.</p

Relative importance of aridity, pH, organic C, and plant-ax1 (first component of a PCA including the cover of bare and plant microsites, average plant patch interdistance, area of plant patches and number of plant patches per 10 m of transect) variables as drivers of variations in N availability.

<p>Results are shown for: i) bare ground microsites, and ii) <i>Stipa tenacissima</i> microsites. The height of each bar is the sum of the Akaike weights of all models that included the predictor of interest, taking into account the number of models in which each predictor appears.</p