Hitachi F7000 Instruction Manual
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Page 311
9.2 Use of AS-3000 Intelligent Autosampler 9 - 10 9.2 Use of AS-3000 Intelligent Autosampler Set the rack parameters, injection volume and other items with the AS-3000 Intelligent Autosampler. For details, refer to the instruction manual attached to the AS-3000. Fig. 9-14 Cord Connection Parameter setting: Set all parameters in the AS-3000. NOTE: When using a sample table, match the number of samples set in the AS-3000 with that set in the sample...
Page 312
9.2 9 - 11 (1) Select the Measure command from the Spectrophotometer menu of the FL Solutions program or click the (measurement) button on the toolbar. A window as in Fig. 9-15 will open. Fig. 9-15 For Start from Creation of Calibration curve (2) Press the START key on the AS-3000. (3) Measurement will start.
Page 313
9.3 Analog Output 9 - 12 9.3 Analog Output For connection, use the analog output terminal. Select the Analog Output command from the Utility menu. (The analog output I/F (option) is required.) Fig. 9-16 This is a setting of data value corresponding to analog output of 1 V. Analog output value (V) becomes as follows. Low : (data value)/1000 High : (data value)/10000
Page 314
A - 1 APPENDIX A DETAILS OF QUANTIFICATION A.1 Foreword In the Photometry mode of the F-7000 spectrophotometer, the following four calibration curve types are available. Linear working curve Quadratic working curve Cubic working curve Multiple segment working curve These are explained in detail below. A.2 Linear Working Curve (1st order) A regression line is determined via the least squares method from a maximum of 20 data. The calculation formula is as...
Page 315
A - 2 A.3 Quadratic Working Curve (2nd order) A quadratic curve is determined via the least squares method from a maximum of 20 data. The calculation formula is as follows: x = A2 y 2 + A1 y + A0 ()()()() ()()(){} ASy xSyy SyxSyy SyySy y Syy 2 22 22 22 = ()()Syy yy nii=∑ ∑22 ()()()() ()()(){} ASyxSy y Sy xSyy SyySy y Syy 1 22 2 2 22 22 = ()Syx y xyx niiii=−⋅∑ ∑ ∑ AAAx nx ny nii i012 2 = ∑∑ ∑ ()Syy yyy niii 232=−⋅∑ ∑ ∑ ()Sy x y xyx ni iii 222=−⋅∑ ∑ ∑ () ()Sy y yy nii 22...
Page 316
A - 3 A.5 Multiple Segment Working Curve (Segmented) The calibration curve is apt to bend when measuring turbid samples or the like. Use of a quantification program allows correcting the calibration curve by using up to 20 standards. Figure A-1 shows an example of curve correction. For the part which exceeds the measuring range of the standards, simply extend the line as it is. Fig. A-1 Correction of Curve Bending Data Conc
Page 317
A - 4 <Notes on Preparation of Multiple Segment Working Curve> (1) A correct calibration curve can be created only when the measured value increases or decreases monotonically versus the concentration value. Especially when the inclination is negative- going, be sure to measure a blank having a data value larger than the other standards. A curve not showing a monotonic increase will appear as in Fig. A-2. And when the data value of the blank is small, regardless of a negative-going...
Page 318
A - 5 (2) Remeasurement of Standards The standards can be remeasured after once preparing a calibration curve. The curve prepared in such a case will appear as in Fig. A-4. Fig. A-4 Calibration Curve when Standards are Remeasured Data Conc Redrawn calibration curve Remeasured STD1 Initially measured STD1
Page 319
A - 6 APPENDIX B DETAILS OF RATE ANALYSIS FUNCTION B.1 Foreword Rate analysis is used in the analysis of enzyme reactions. It is utilized for clinical and biochemical tests by reagent manufacturers, hospitals and so on. A computer is used to calculate the concentration from the variation in data per unit time, and the result is displayed and printed out. B.2 Calculation Method A timing chart for rate analysis is shown in Fig. B-1. Data is acquired when the initial delay...
Page 320
A - 7 Prepare a regression line via the least squares method from the measured data, and obtain a determination coefficient. y = ax + b where, () axyxy n xx niiii ii= ∑ ∑ ∑ ∑ ∑ 22 ()byax nii=−∗∑ ∑ x i : Time (s) of each data y i : Value of each data n : Number of samples The determination coefficient CD becomes as follows: () () () CDnxy x y nx x ny yii i i ii ii=− − ⎛ ⎝ ⎜⎞ ⎠ ⎟− ⎛ ⎝ ⎜⎞ ⎠ ⎟∑ ∑ ∑ ∑ ∑∑∑ 2 22 22 Gradient (variation per minute) min) (/ a 60 Tka Di= = ...
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