Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food.

中文翻译：

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基于快速可视化方法的无背景上转换编码微球用于霉菌毒素检测。

由于霉菌毒素对健康的危害很大，因此检测霉菌毒素的方法非常重要。但是，实时感测中背景本底高，信噪比低，因此难以满足食品质量控制的快速，准确，方便的要求。在这里，我们构建了基于多色上转换纳米晶体（UCN）编码的微球的定量荧光图像分析，用于检测曲霉毒素A和玉米赤霉烯酮。掺有UCN的微球的无背景编码图像信号通过荧光显微镜在近红外激发下捕获，而藻红蛋白标记的与微球结合的二抗的检测图像信号在蓝光激发下捕获。我们定制编写了一种算法，可以在10 s内分析同一样本的两个图像，只有次级探针红色通道中的灰度值可以确认数量。结果表明，该新型检测平台通过该方法进行了可行且可靠的荧光图像测量。此外，曲霉毒素A的检出限为0.34721 ng / mL，玉米赤霉烯酮的检出限为0.41162 ng / mL。我们预想，这种UCN编码策略将可有效地应用于多种食品污染物的快速，准确和便捷的测试，以确保食品的安全性。曲霉毒素A的检出限为0.34721 ng / mL，玉米赤霉烯酮的检出限为0.41162 ng / mL。我们预想，这种UCN编码策略将可有效地应用于多种食品污染物的快速，准确和便捷的测试，以确保食品的安全性。曲霉毒素A的检出限为0.34721 ng / mL，玉米赤霉烯酮的检出限为0.41162 ng / mL。我们预想，这种UCN编码策略将可有效地应用于多种食品污染物的快速，准确和便捷的测试，以确保食品的安全性。