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This version is not peer-reviewed
Submitted:
14 September 2023
Posted:
18 September 2023
Read the latest preprint version here
Matrix type | neferine in lotus and daidzein and genistein in soybean matrices | ||||
---|---|---|---|---|---|
LOD (μg/kg)1) |
LOQ (μg/kg)2) |
Linearity3) | Calibration equation | ||
Lotus matrix (n = 3) |
Neferine | 0.12 | 0.36 | R2=0.9967 |
y=0.0021x+0.007 |
Soybean matrix (n = 3) |
Daidzein | 0.08 | 0.24 | R2=0.9958 | y=0.0012x-0.008 |
Genistein | 0.09 | 0.27 | R2=0.9942 | y=0.0015x-0.005 |
Matrix type | Conc. | 3 (μg/kg) | 10 (μg/kg) | 40 (μg/kg) |
---|---|---|---|---|
Lotus matrix (n = 3) |
Neferine | 82.95±0.67 | 102.75±0.56 | 99.54±0.32 |
Soybean matrix (n = 3) |
Daidzein | 93.02±2.45 | 111.46±5.67 | 86.72±0.11 |
Genistein | 96.75±3.64 | 107.65±8.65 | 104.77±0.96 |
Matrix type | Conc. | Intraday (n=3) | Interday (n=3) |
---|---|---|---|
Precision (%)1) | Precision (%) | ||
Lotus matrix (n = 3) |
Neferine | 0.24 | 0.65 |
Soybean matrix (n = 3) |
Daidzein | 1.26 | 3.42 |
Genistein | 6.82 | 4.67 |
Sample name |
Concentrations (μg/kg)1) | |||
---|---|---|---|---|
Neferine | Daidzein | Genistein | Total | |
Sample 1 | 1.02±0.25 | 1.67±0.86 | 1.11±0.05 | 3.80±1.16 |
Sample 2 | 0.78±0.11 | 2.45±0.06 | 1.43±0.09 | 4.66±0.26 |
Sample 3 | 0.66±0.05 | 2.31±0.09 | 1.67±0.08 | 4.64±0.22 |
Sample 4 | 2.21±0.05 | 0.49±0.07 | 1.90±0.76 | 4.60±0.88 |
Sample 5 | 0.56±0.23 | 0.41±0.07 | 2.03±0.87 | 3.00±1.17 |
Sample 6 | 0.47±0.01 | 0.56±0.09 | 2.11±0.78 | 3.14±0.88 |
Sample 7 | 0.45±0.15 | 1.25±0.99 | 2.78±0.93 | 4.48±2.07 |
Sample 8 | 1.43±0.17 | 1.56±0.32 | 3.11±0.45 | 6.10±0.94 |
Sample 9 | 0.87±0.14 | 2.78±0.54 | 0.78±0.32 | 4.52±1.00 |
Sample 10 | 0.98±0.05 | 3.04±0.11 | 0.54±0.02 | 4.56±0.18 |
Sample 11 | 0.76±0.34 | 2.93±0.54 | 0.32±0.01 | 4.01±0.89 |
Sample 12 | 0.88±0.07 | 0.67±0.32 | 0.88±0.75 | 2.43±1.14 |
Sample 13 | 1.05±0.78 | 0.44±0.11 | 1.02±0.99 | 2.51±1.88 |
Sample 14 | 1.34±0.54 | 0.78±0.05 | 1.11±0.45 | 3.23±1.04 |
Sample 15 | 1.97±0.08 | 1.56±0.99 | 1.75±0.03 | 5.28±1.10 |
Sample 16 | 2.06±0.04 | 0.86±0.54 | 1.32±0.41 | 4.24±0.99 |
Sample 17 | 2.21±0.03 | 0.54±0.07 | 1.05±0.55 | 3.80±0.65 |
Sample 18 | <LOQ | 0.32±0.05 | 2.97±0.66 | 3.29±0.71 |
Sample 19 | <LOQ | 0.27±0.08 | 3.23±0.77 | 3.50±0.85 |
Sample 20 | <LOQ | 0.67±0.09 | 0.99±0.66 | 1.66±0.75 |
Sample 21 | <LOQ | 0.99±0.06 | 1.92±0.43 | 2.91±0.49 |
Sample 22 | <LOQ | 1.76±0.11 | 1.54±0.78 | 3.30±0.89 |
Sample 23 | <LOQ | 2.01±0.07 | 2.03±0.97 | 4.04±1.04 |
Sample 24 | <LOQ | 2.26±1.02 | 2.11±0.45 | 4.37±1.47 |
Sample 25 | <LOQ | 3.02±0.96 | 3.02±0.86 | 6.04±1.82 |
Sample 26 | <LOQ | 2.05±0.87 | 0.87±0.05 | 2.92±0.92 |
Sample 27 | 0.55±0.08 | <LOQ | 0.45±0.03 | 1.00±0.11 |
Sample 28 | 1.54±0.07 | <LOQ | 0.54±0.08 | 2.08±0.15 |
Sample 29 | 1.23±0.56 | <LOQ | 1.25±0.07 | 2.48±0.63 |
Sample 30 | 1.86±0.59 | <LOQ | 1.11±0.09 | 2.97±0.68 |
Sample 31 | <LOQ | 3.01±0.67 | 1.56±0.06 | 4.57±0.73 |
Sample 32 | <LOQ | 3.33±0.09 | 0.88±0.54 | 4.21±0.63 |
Sample 33 | <LOQ | 2.06±0.08 | 0.55±0.09 | 2.61±0.17 |
Sample 34 | <LOQ | 2.54±0.10 | 1.23±0.04 | 3.77±0.14 |
Sample 35 | 0.56±0.03 | 1.45±0.67 | <LOQ | 2.01±0.70 |
Sample 36 | 0.32±0.21 | 1.67±0.54 | <LOQ | 1.99±0.75 |
Sample 37 | 0.45±0.09 | 2.55±0.43 | <LOQ | 3.00±0.52 |
Sample 38 | 0.78±0.06 | 2.11±0.07 | <LOQ | 2.89±0.13 |
Sample 39 | <LOQ | 0.99±0.06 | 1.78±0.32 | 2.77±0.38 |
Sample 40 | <LOQ | 1.54±0.09 | 1.02±0.89 | 2.56±0.98 |
Sample 41 | <LOQ | 1.23±0.41 | 1.65±0.32 | 2.88±0.73 |
Sample 42 | 1.87±0.09 | 0.67±0.04 | <LOQ | 2.54±0.13 |
Sample 43 | 1.56±0.76 | 0.78±0.09 | <LOQ | 2.34±0.85 |
Sample 44 | 1.32±0.04 | 0.45±0.04 | <LOQ | 1.77±0.08 |
Sample 45 | 1.13±0.75 | 0.67±0.08 | <LOQ | 1.80±0.83 |
Sample 46 | 0.97±0.66 | 1.54±0.07 | <LOQ | 2.51±0.73 |
Sample 47 | 0.45±0.08 | 2.02±0.78 | <LOQ | 2.47±0.86 |
Sample 48 | 0.76±0.32 | 2.11±0.54 | <LOQ | 2.87±0.86 |
Sample 49 | 1.05±0.33 | 2.34±0.65 | <LOQ | 3.39±0.98 |
Sample 50 | 1.15±0.64 | 2.11±0.08 | <LOQ | 3.26±0.72 |
Sample 51 | 1.78±0.56 | 2.34±0.54 | <LOQ | 4.12±1.10 |
Sample 52 | 1.43±0.07 | 0.54±0.02 | <LOQ | 1.97±0.09 |
Sample 53 | 1.32±0.56 | 0.87±0.06 | <LOQ | 2.19±0.62 |
Sample 54 | 1.88±0.97 | 0.45±0.02 | <LOQ | 2.33±0.99 |
Sample 55 | 1.32±0.54 | 0.34±0.08 | <LOQ | 1.68±0.62 |
Sample 56 | 1.42±0.68 | 0.92±0.09 | <LOQ | 2.34±0.77 |
Sample 57 | <LOQ | 1.05±0.45 | 1.24±0.07 | 2.29±0.52 |
Sample 58 | <LOQ | 1.52±0.88 | 1.43±0.05 | 2.95±0.93 |
Sample 59 | <LOQ | 2.11±0.32 | 1.25±0.68 | 3.36±1.00 |
Sample 60 | <LOQ | 1.76±0.54 | 1.67±0.07 | 3.43±0.61 |
Sample 61 | <LOQ | 2.01±0.66 | 1.54±0.16 | 3.55±0.82 |
Sample 62 | <LOQ | 3.42±0.09 | 2.02±0.47 | 5.44±0.56 |
Sample 63 | <LOQ | 2.11±0.78 | 2.33±0.87 | 4.44±1.65 |
Sample 64 | <LOQ | 0.75±0.07 | 1.98±0.07 | 2.73±0.14 |
Sample 65 | <LOQ | 0.41±0.08 | 1.67±0.54 | 2.08±0.62 |
Sample 66 | 1.65±0.08 | 0.76±0.43 | <LOQ | 2.41±0.51 |
Sample 67 | 1.23±0.05 | 0.88±0.02 | <LOQ | 2.11±0.07 |
Sample 68 | 1.01±0.43 | 0.99±0.05 | <LOQ | 2.00±0.48 |
Sample 69 | 2.45±0.09 | 1.05±0.23 | <LOQ | 3.50±0.32 |
Sample 70 | 2.11±0.04 | 1.23±0.08 | <LOQ | 3.34±0.12 |
Overall average | 0.78±0.20 | 1.40±0.29 | 1.01±0.27 | 3.19±0.76 |
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