Portable Hadamard-Transform Raman Spectrometer: A Powerful Analytical Tool for Point-of-Care Testing.

A portable Hadamard-transform Raman spectrometer with excellent performance was fabricated consisting of a 785 nm laser, an optical filter, an optical system, a control system, and a signal processing system. As the core of the spectrometer, the optical system was composed of a slit, collimator, optical grating, reflector, digital micromirror devices (DMD), lens system, and InGaAs photodetector. Compared with a conventional dispersive Raman spectrometer, the proposed Raman spectrometer adopted the DMD and corresponding controlling device (DLPC350 control chip) to collect the Raman spectrum.

In vivo prediction of abdominal fat and breast muscle in broiler chicken using live body measurements based on machine learning.

The purpose of this study was to predict the carcass characteristics of broilers using support vector regression (SVR) and artificial neural network (ANN) model methods. Data were obtained from 176 yellow feather broilers aged 100-day-old (90 males and 86 females). The input variables were live body measurements, including external measurements and B-ultrasound measurements.

[Discussion of the Application and Influence Factors of Low-Background Gamma Spectrometry in Distinguishing Sedimentary Rock Types].

The contents of radionuclides uranium, thorium and potassium in the sedimentary rocks mainly depend on the contents of clay in the rocks. And the content of clay is the main basis for distinguishing types of sedimentary rock. Therefore, the value of specific activity or content of uranium, thorium and potassium can be as the quantitative index to distinguish sedimentary rock type.

[Visible/NIR analysis of fat, protein and water in chilled pork].

Fat, protein and water were determined by visible and NIR transmittance spectroscopy in chilled pork. After preprocessed by multiplicative scatter correction (MSC), the quantitative analysis models were developed based on the original, first derivative and second derivative spectra by using partial least squares (PLS) at the temperatures of 0-4 degrees C and 20 degrees C, respectively. By comparing the correlation coefficient (r), RMSEC, and SEP, we found that the first derivative model was the best, and the performance for 0-4 degrees C was better than that for 20 degrees C.