The amino acid composition and the physicochemical and functional properties of quinoa protein isolates were evaluated. Protein isolates were prepared from quinoa seed by alkaline solubilization (at pH 9, called Q9, and at pH 11, called Q11) followed by isoelectric precipitation and spray drying. Q9 and Q11 had high levels of essential amino acids, with high levels of lysine. Both isolates showed similar patterns in native/SDS-PAGE and SEM. The pH effect on fluorescence measurements showed decreasing fluorescence intensity and a shift in the maximum of emission of both isolates. Q9 showed an endotherm with a denaturation temperature of 98.1 degrees C and a denaturation enthalpy of 12.7 J/g, while Q11 showed no endotherm. The protein solubility of Q11 was lower than that of Q9 at pH above 5.0 but similar at the pH range 3.0-4.0. The water holding capacity (WHC) was similar in both isolates and was not affected by pH. The water imbibing capacity (WIC) was double for Q11 (3.5 mL of water/g isolate). Analysis of DSC, fluorescence, and solubility data suggests that there is apparently denaturation due to pH. Some differences were found that could be attributed to the extreme pH treatments in protein isolates and the nature of quinoa proteins. Q9 and Q11 can be used as a valuable source of nutrition for infants and children. Q9 may be used as an ingredient in nutritive beverages, and Q11 may be used as an ingredient in sauces, sausages, and soups.
In this paper we explore the maximum precision attainable in the location of a point source imaged by a pixel array detector in the presence of a background, as a function of the detector properties. For this we use a well-known result from parametric estimation theory, the so-called Cramér-Rao lower bound. We develop the expressions in the 1-dimensional case of a linear array detector in which the only unknown parameter is the source position. If the object is oversampled by the detector, analytical expressions can be obtained for the Cramér-Rao limit that can be readily used to estimate the limiting precision of an imaging system, and which are very useful for experimental (detector) design, observational planning, or performance estimation of data analysis software: In particular, we demonstrate that for background-dominated sources, the maximum astrometric precision goes as B/F 2 , where B is the background in one pixel, and F is the total flux of the source, while when the background is negligible, this precision goes as F −1 . We also explore the dependency of the astrometric precision on: (1) the size of the source (as imaged by the detector), (2) the pixel detector size, and (3) the effect of source de-centering. Putting these results into context, the theoretical Cramér-Rao lower bound is compared to both groundas well as spaced-based astrometric results, indicating that current techniques approach this limit very closely. It is furthermore demonstrated that practical astrometric estimators like maximum likelihood or least-squares techniques can not formally reach the Cramér-Rao bound, but that they approach this limit in the 1-dimensional case very tightly, for a wide range of S/N of the source. Our results indicate that we have found in the Cramér-Rao lower variance bound a very powerful astrometric "benchmark" estimator concerning the maximum expected positional precision for a point source, given a prescription for the source, the background, the detector characteristics, and the detection process.
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