| Literature DB >> 29391603 |
Dongmei Wei1,2, Xiaohu Wu2, Jun Xu2, Fengshou Dong2, Xingang Liu2, Yongquan Zheng3, Mingshan Ji4.
Abstract
We developed a sensitive and rapid analytical method to determine the level of Ochratoxin A contamination in grapes, processed grape products and in foods of animal origin (a total of 11 different food matrices). A pretreatment that followed a "quick, easy, cheap, effective, rugged, and safe" protocol was optimized to extract Ochratoxin A from the matrices, and the extracted Ochratoxin A was then detected with the use of a highly sensitive ultra-performance liquid chromatography-tandem mass spectrometry system. Good linearities of Ochratoxin A were obtained in the range of 0.1-500 µg L-1 (correlation coefficient (R2) > 0.9994 in each case). Mean recovery from the 11 matrices ranged from 70.3 to 114.7%, with a relative standard deviation ≤19.2%. The method is easy to use and yields reliable results for routine determination of Ochratoxin A in food products of grape and animal origin. In store-purchased foods and foods obtained from the field and wholesale suppliers, the Ochratoxin A concentration ranged from undetectable to 10.14 µg kg-1, with the more contaminated samples being mainly those of processed grape products. Our results indicate that the necessity for regulation of and supervision during the processing of grape products.Entities:
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Year: 2018 PMID: 29391603 PMCID: PMC5794868 DOI: 10.1038/s41598-018-20534-7
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Calibration equations, R2 values, LOQ values, and matrix effects for Ochratoxin A detection by our optimized UPLC-MS/MS method.
| Matrix | Regression equation | R2 | Slop ratioa | Matrix effectb (%) | LOQ(µg kg−1) |
|---|---|---|---|---|---|
| Acetonitrile | y = 3417.5x − 7266.9 | R² = 0.9999 | 0.1 | ||
| Grape | y = 4558.9x + 800.35 | R² = 1 | 1.33 | 33 | 0.1 |
| Wine | y = 5406.2x + 8354.5 | R² = 0.9997 | 1.58 | 58 | 0.1 |
| Juice | y = 6261.2x + 10692 | R² = 0.9997 | 1.83 | 83 | 0.1 |
| Raisin | y = 6011.2x − 2406.7 | R² = 1 | 1.76 | 76 | 0.1 |
| Pork | y = 4309.4x + 1248.5 | R² = 1 | 1.26 | 26 | 0.1 |
| Porcine liver | y = 3206.1x − 3857.9 | R² = 0.9999 | 0.94 | −6 | 0.1 |
| Porcine Kidney | y = 5251.4x + 4169.7 | R² = 1 | 1.54 | 54 | 0.1 |
| Porcine fat | y = 5673.7x + 8237.3 | R² = 0.9999 | 1.66 | 66 | 0.1 |
| Chicken | y = 4910.9x − 740.04 | R² = 0.9999 | 1.44 | 44 | 0.1 |
| Eggs | y = 4723.7x + 13969 | R² = 0.9994 | 1.38 | 38 | 0.1 |
| Milk | y = 5459.1x + 10234 | R² = 0.9998 | 1.60 | 60 | 0.1 |
Accuracy and precision of the optimized method for the 11 matrices, each of which was spiked with one of four concentrations of Ochratoxin A.
| Matrix | Spiked level | Intra-day (n = 5) | Inter-day(n = 15) | |||||
|---|---|---|---|---|---|---|---|---|
| Day 1 | Day 2 | Day 3 | ||||||
| Average recoveries(%) | RSDr(%) | Average recoveries(%) | RSDr(%) | Average recoveries(%) | RSDr(%) | |||
| Grape | 0.1 | 71.7 | 5.4 | 80.1 | 3.4 | 80.0 | 10.3 | 8.2 |
| 1 | 110.2 | 2.5 | 109.4 | 3.4 | 107.5 | 2.5 | 2.8 | |
| 10 | 110.7 | 1.4 | 110.3 | 1.3 | 103.1 | 4.2 | 4.1 | |
| 500 | 114.7 | 1.1 | 102.6 | 2.6 | 100.1 | 0.8 | 6.4 | |
| Wine | 0.1 | 80.0 | 5.8 | 80.6 | 4.2 | 85.8 | 2.4 | 5.0 |
| 1 | 96.5 | 6.0 | 94.7 | 10.0 | 98.7 | 2.6 | 6.5 | |
| 10 | 93.4 | 3.0 | 91.3 | 4.1 | 98.6 | 1.7 | 4.4 | |
| 500 | 111.2 | 0.8 | 109.9 | 1.5 | 96.0 | 8.7 | 8.0 | |
| Juice | 0.1 | 79.7 | 6.6 | 79.2 | 5.2 | 82.5 | 10.8 | 7.2 |
| 1 | 95.7 | 4.3 | 108.5 | 1.3 | 93.1 | 1.8 | 4.3 | |
| 10 | 93.4 | 3.0 | 111.7 | 1.8 | 101.9 | 3.7 | 6.8 | |
| 500 | 110.6 | 2.1 | 94.7 | 10.0 | 109.0 | 1.3 | 2.0 | |
| Raisin | 0.1 | 80.7 | 3.9 | 85.9 | 8.1 | 74.3 | 6.6 | 8.4 |
| 1 | 106.9 | 3.0 | 100.2 | 5.1 | 82.9 | 7.2 | 11.8 | |
| 10 | 87.0 | 7.4 | 99.5 | 4.4 | 94.6 | 4.6 | 7.6 | |
| 500 | 109.0 | 2.0 | 102.6 | 6.4 | 96.5 | 4.2 | 6.6 | |
| Pork | 0.1 | 90.2 | 3.0 | 79.9 | 8.6 | 83.0 | 9.5 | 8.4 |
| 1 | 97.5 | 7.1 | 102.5 | 3.2 | 89.4 | 2.6 | 7.3 | |
| 10 | 74.9 | 2.3 | 80.4 | 10.8 | 94.6 | 3.6 | 12.0 | |
| 500 | 75.1 | 9.8 | 78.4 | 11.6 | 99.3 | 2.3 | 15.2 | |
| Porcine liver | 0.1 | 76.8 | 3.5 | 73.9 | 5.7 | 77.9 | 12.2 | 7.4 |
| 1 | 84.4 | 4.2 | 103.5 | 4.6 | 100.1 | 6.2 | 10.1 | |
| 10 | 84.3 | 9.8 | 104.6 | 6.3 | 100.4 | 3.8 | 11.3 | |
| 500 | 93.3 | 4.7 | 97.7 | 3.3 | 96.0 | 3.4 | 4.1 | |
| Porcine kidney | 0.1 | 84.4 | 9.4 | 87.5 | 17.2 | 87.7 | 10.4 | 11.3 |
| 1 | 77.4 | 6.7 | 74.4 | 3.9 | 93.4 | 6.8 | 12.0 | |
| 10 | 102.9 | 16.4 | 81.8 | 15.3 | 91.3 | 5.7 | 15.8 | |
| 500 | 87.3 | 6.3 | 91.2 | 9.5 | 98.8 | 5.0 | 8.5 | |
| Porcine fat | 0.1 | 79.9 | 8.3 | 71.6 | 4.1 | 77.8 | 10.4 | 8.6 |
| 1 | 73.0 | 1.7 | 90.5 | 15.1 | 71.4 | 5.4 | 15.0 | |
| 10 | 75.7 | 3.6 | 70.7 | 8.4 | 74.2 | 4.1 | 6.0 | |
| 500 | 70.3 | 3.6 | 103.3 | 7.1 | 92.1 | 5.2 | 16.9 | |
| Chicken | 0.1 | 81.1 | 12.5 | 85.6 | 14.6 | 80.5 | 7.7 | 11.2 |
| 1 | 108.8 | 7.8 | 88.2 | 3.7 | 83.9 | 4.4 | 13.1 | |
| 10 | 73.8 | 9.0 | 83.6 | 19.2 | 72.5 | 2.0 | 13.8 | |
| 500 | 73.7 | 8.5 | 75.6 | 8.9 | 78.8 | 8.9 | 8.6 | |
| Eggs | 0.1 | 75.5 | 12.4 | 80.5 | 4.6 | 81.0 | 5.1 | 7.9 |
| 1 | 97.1 | 4.8 | 101.1 | 7.6 | 99.4 | 4.5 | 5.6 | |
| 10 | 83.2 | 11.5 | 93.8 | 11.9 | 95.8 | 16.7 | 14.2 | |
| 500 | 87.0 | 3.0 | 80.4 | 3.5 | 86.9 | 3.3 | 4.8 | |
| Milk | 0.1 | 84.0 | 5.8 | 90.9 | 4.3 | 96.9 | 3.9 | 7.4 |
| 1 | 94.8 | 13.9 | 90.4 | 12.0 | 84.1 | 7.5 | 12.0 | |
| 10 | 86.1 | 6.4 | 100.6 | 2.0 | 104.1 | 12.6 | 9.0 | |
| 500 | 89.9 | 14.8 | 89.9 | 6.6 | 93.8 | 8.0 | 4.2 | |
Occurrence of Ochratoxin A in samples obtained in the field.
| Sample type | No. of samples analyzed | No. of Positive samples | Incidence of positives (%) | Minimum (µg/kg) | Maximum (µg/kg) |
|---|---|---|---|---|---|
| Grape | 320 | 3 | 0.93 | 0.35 | 1.11 |
| Wine | 21 | 0 | 0 | ND | ND |
| Juice | 41 | 41 | 100 | <LOQ | 0.17 |
| Raisin | 195 | 3 | 1.54 | 0.18 | 10.14 |
| Pork | 20 | 0 | 0 | ND | ND |
| Porcine liver | 20 | 0 | 0 | ND | ND |
| Porcine kidney | 20 | 0 | 0 | ND | ND |
| Porcine fat | 20 | 0 | 0 | ND | ND |
| Chicken | 20 | 0 | 0 | ND | ND |
| Eggs | 20 | 0 | 0 | ND | ND |
| Milk | 20 | 0 | 0 | ND | ND |
Figure 1Typical UPLC-MS/MS multiple reaction-monitoring chromatograms for Ochratoxin A (a) in a standard solution (1 μg L−1), (b) from a grape sample collected at a field in Xinjiang province, (c) from unspiked pork and grape samples, and (d) from pork and grape samples each spiked at 1 μg L−1.
Figure 2Effect of different types of sorbents on the detection of spiked Ochratoxin A (10 µg kg−1) in different processed grape products (n = 3 per matrix).
Figure 3Effect of different extraction solvents and sorbents on the detection of spiked Ochratoxin A (10 µg kg−1) in different foods of animal origin (n = 3 per matrix).
Geographical locations and numbers of the samples acquired in different provinces of China.
| Grape | Wine | Juice | Raisin | Pork | Porcine liver | Porcine Kidney | Porcine fat | Chicken | Eggs | Milk | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Shanxi | 27 | 5 | 10 | 2 | |||||||
| Ningxia | 32 | 1 | 5 | 3 | 7 | ||||||
| Gansu | 35 | 5 | |||||||||
| Xinjiang | 53 | 4 | 129 | 7 | |||||||
| Hebei | 45 | 21 | 20 | 3 | 3 | 3 | 3 | ||||
| Shandong | 35 | 4 | 5 | 3 | 3 | 3 | 3 | ||||
| Beijing | 15 | 4 | 3 | ||||||||
| Yunnan | 2 | 2 | 2 | 2 | |||||||
| Anhui | 1 | 2 | 2 | ||||||||
| Hubei | 2 | 2 | 1 | ||||||||
| Jiangsu | 1 | ||||||||||
| Hainan | 4 | ||||||||||
| Zhejiang | 5 | ||||||||||
| Tianjin | 40 | 2 | 5 | 36 | 7 | 7 | |||||
| Jilin | 38 | ||||||||||
| Henan | 4 | 4 | 4 | 4 | |||||||
| Sichuan | 4 | 4 | 4 | 4 | |||||||
| Guangdong | 3 | 4 | 4 | 4 | |||||||
| Inner Mongolia | 6 | ||||||||||
| total | 320 | 21 | 41 | 195 | 20 | 20 | 20 | 20 | 20 | 20 | 20 |