Browsing by Subject "quantification"

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    Development Of Fourier Transform Near Infrared Spectroscopy Methods For The Rapid Quantification Of Starch And Cellulose In Mozzarella And Other Italian-Type Cheeses
    (2019-09) Vazquez, Leilany
    Flow-aids consisting of starch and cellulose are added to prevent caking and sticking in grated and shredded cheese and are used as carriers for added antimycotics to prevent mold growth. The accurate quantification of these flow-aids involves difficult wet-chemistry methods. When too little antimycotic is added, quality issues can occur. Conversely, when too much flow-aid is added in order to dilute the cheese for economic gain, the reputation of the dairy industry is damaged. As a way to prevent the over or underuse of these ingredients, Fourier Transform Near-Infrared Spectroscopy (NIR) could be useful. The goal of this research was to investigate whether calibrations could be made to quantify starch and cellulose in Asiago, Parmesan, and Romano cheeses, alone and separately. Samples of Asiago, Parmesan, and Romano loafs were shredded, and 0 – 5.66% of a starch/cellulose flow-aid was added. Treatments were ground, weighed, formed into a ball and pressed in the middle of the glass petri dish to create a homogenous scanning surface. Samples were scanned using a BUCHI NIRFlex N-500 FT-NIR spectrometer (BUCHI Labortechnik AG, CH). NIRCal 5.2 Chemometric Software (BUCHI Labortechnik) was used to analyze the spectra after first dividing the spectra of the 2,367 samples into 1,578 calibration and 789 validation samples. The spectra were treated with standard normal variate to minimize variations and optimize the calibration. The calibrations obtained had an r2 greater than 0.94 and worked better when they were specific to one specific cheese (ie. Asiago) instead of one kind of cheese (ie. Hard-grated cheese). Future research will determine if cellulose and starch can be identified and quantified separately in the same sample, and the effect of different starch and cellulose types on quantification.
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    Journalism in an Era of Big Data: Cases, Concepts, and Critiques
    (Digital Journalism, 2015) Lewis, Seth C.
    “Journalism in an era of big data” is thus a way of seeing journalism as interpolated through the conceptual and methodological approaches of computation and quantification. It is about both the ideation and implementation of computational and mathematical mindsets and skill sets in newswork—as well as the necessary deconstruction and critique of such approaches. Taking such a wide-angle view of this phenomenon, including both practice and philosophy within this conversation, means attending to the social/cultural dynamics of computation and quantification—such as the grassroots groups that are seeking to bring pro-social “hacking” into journalism (Lewis and Usher 2013, 2014)—as well as the material/technological characteristics of these developments. It means recognizing that algorithms and related computational tools and techniques “are neither entirely material, nor are they entirely human—they are hybrid, composed of both human intentionality and material obduracy” (Anderson 2013, 1016). As such, we need a set of perspectives that highlight the distinct and interrelated roles of social actors and technological actants at this emerging intersection of journalism (Lewis and Westlund 2014a). To trace the broad outline of journalism in an era of big data, we need (1) empirical cases that describe and explain such developments, whether at the micro (local) or macro (institutional) levels of analysis; (2) conceptual frameworks for organizing, interpreting, and ultimately theorizing about such developments; and (3) critical perspectives that call into question taken-for-granted norms and assumptions. This special issue takes up this three-part emphasis on cases, concepts, and critiques.