The purpose of this paper is to present a detailed account of the precalibration procedures developed and implemented by the USDA Federal Milk Market Administrators (FMMA) for evaluating mid-infrared (MIR) milk analyzers. Mid-infrared analyzers specifically designed for milk testing provide a rapid and cost-effective means for determining milk composition for payment and dairy herd improvement programs. These instruments determine the fat, protein, and lactose content of milk, and enable the calculation of total solids, solids-not-fat, and other solids. All MIR analyzers are secondary testing instruments that require calibration by chemical reference methods. Precalibration is the process of assuring that the instrument is in good working order (mechanically and electrically) and that the readings before calibration are stable and optimized. The main components of precalibration are evaluation of flow system integrity, homogenization efficiency, water repeatability, zero shift, linearity, primary slope, milk repeatability, purging efficiency, and establishment of intercorrection factors. These are described in detail and apply to both filter-based and Fourier transform infrared instruments operating using classical primary and reference wavelengths. Under the USDA FMMA Precalibration Evaluation Program, the precalibration procedures were applied longitudinally over time using a wide variety of instruments and instrument models. Instruments in this program were maintained to pass the criteria for all precalibration procedures. All instruments used similar primary wavelengths to measure fat, protein, and lactose but there were differences in reference wavelength selection. Intercorrection factors were consistent over time within all instruments and similar among groups of instruments using similar primary and reference wavelengths. However, the magnitude and sign of the intercorrection factors were significantly affected by the choice of reference wavelengths.
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http://dx.doi.org/10.3168/jds.S0022-0302(06)72353-0 | DOI Listing |
Data Brief
August 2023
Geodesy Research Group, Faculty of Earth Sciences and Technology, Bandung Institute of Technology, Indonesia.
In this article, we present a dataset of underwater videos captured through manual dives in a complex and unstructured seabed area dominated by harbor structures and coral reefs. The area is shallow (0.5 - 7.
View Article and Find Full Text PDFSensors (Basel)
April 2023
MOE Key Laboratory of Optoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China.
Currently, automatic optical zoom setups are being extensively explored for their applications in search, detection, recognition, and tracking. In visible and infrared fusion imaging systems with continuous zoom, dual-channel multi-sensor field-of-view matching control in the process of synchronous continuous zoom can be achieved by pre-calibration. However, mechanical and transmission errors of the zoom mechanism produce a small mismatch in the field of view after co-zooming, degrading the sharpness of the fusion image.
View Article and Find Full Text PDFFront Physiol
September 2021
Office of Science and Engineering Laboratories, Food and Drug Administration, Silver Spring, MD, United States.
Subject-specific mathematical models for prediction of physiological parameters such as blood volume, cardiac output, and blood pressure in response to hemorrhage have been developed. studies using these models may provide an effective tool to generate pre-clinical safety evidence for medical devices and help reduce the size and scope of animal studies that are performed prior to initiation of human trials. To achieve such a goal, the credibility of the mathematical model must be established for the purpose of pre-clinical testing.
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September 2021
Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy.
Acknowledged guidelines and standards such as those formerly governing project planning in analogue aerial photogrammetry are still missing in UAV photogrammetry. The reasons are many, from a great variety of projects goals to the number of parameters involved: camera features, flight plan design, block control and georeferencing options, Structure from Motion settings, etc. Above all, perhaps, stands camera calibration with the alternative between pre- and on-the-job approaches.
View Article and Find Full Text PDFSci Total Environ
July 2021
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China. Electronic address:
Low-cost air quality sensor networks have been increasingly used for high spatial resolution air quality monitoring in recent years. Ensuring data reliability during continuous operation is critical for these sensor networks. Using particulate matter sensor as an example, this study reports a data quality control method, including sensor selection, pre-calibration, and online inspection.
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