Recently, bioassay has been getting much attention as it can comprehensively evaluate water toxicity without identifying the individual chemical component. In this technique, a microscope observation is required to know the critical features of the targeted microorganisms. However, as the size of the microorganism becomes smaller, observation becomes more difficult due to the narrower focal depth of the imaging system. Here, to overcome these difficulties, a novel biospeckle technique is used for the microbioassay utilizing the biospeckle in the diffraction field generated from the microorganisms. Paramecium caudatum (200-300µm) and Euglena gracilis(50-60µm) were used as a microorganism. Dynamic biospeckle patterns were captured using a CCD camera to evaluate the swimming activity of microorganisms under varying water toxicity levels induced by heavy metal pollutants (Zn(NO₃)₂·6H₂O and FeSO₄·7H₂O). To quantitatively evaluate the swimming activity of microorganisms, the crosscorrelation function between the initial frame as a reference frame and the subsequent frames was measured, and the correlation time was evaluated as a measure of their swimming ability. Results show a concentration dependent effect of Zn on both species, leading to decreased swimming ability. Conversely, Fe exhibited varying effects on Paramecia and Euglena, with the latter displaying tolerance at lower concentrations but a notable response at higher concentrations. The advantage of the method is that owing to the non-imaging system, an enormous number of planktons can be processed. This allows for an immediate and statistically significant estimation of their swimming ability in response to environmental pollution.
Nanoparticles (NPs) have become more prevalent in the agricultural, industrial, and medicinal fields. There is rising interest in how nanomaterials interact with plants since they influence plants and seeds differently depending on their size, shape, and dose. The techniques to monitor the response of plants to NPs are crucial since the effects of nanomaterials on seed germination and plant growth are uncertain. In this study, a highly sensitive, real-time, non-invasive novel technique called Biospeckle optical coherence tomography (bOCT) is used to examine the size-dependent impact of metal oxides NPs and microparticles (MPs) like Zinc Oxide (ZnO) with a size less than 50 nm, and 45μm and Titanium dioxide (TiO2) with a size 21 nm and <5μm at concentrations of 25mg/L and 100mg/L on the internal activity of lentil seeds before germination. The results showed that ZnO NPs had an adverse effect at both higher and lower concentrations on the internal activity of lentil seeds, while MPs of 45μm had significantly positive effects even with higher concentrations. However, TiO2 MPs and NPs showed a significant positive effect on Lentil seed’s internal activity at both concentrations in comparison to control. The proposed method was able to detect the response of Lentil seed’s internal activities to different concentrations and sizes of metal oxides NPs and MPs at an early stage just after 5 hours of exposure before the germination. On the other hand, the conventional physiological methods required a week for the effects to be detected, and the results from bOCT after 5 hours were consistent with those obtained by conventional measures. Because of the non-invasive nature of bOCT, requiring only tens of seconds of measurement with an intact. Furthermore, the technique is capable of monitoring internal biological activities while the conventional OCT monitors just structural images. It has not only the potential to screen but could also constantly monitor long-term changes, thus contributing to the study of the effects of nanomaterials on plants.
KEYWORDS: Light emitting diodes, Signal to noise ratio, Photoacoustic spectroscopy, Photoacoustic imaging, Pulse signals, Signal processing, Laser systems engineering, Autocorrelation
Photoacoustic imaging is a new imaging technique that can measure optical absorbers with high resolution. Lasers are commonly used as light sources for photoacoustic imaging, but there are many safety restrictions. Therefore, devices in which the light source is replaced by LEDs, which have fewer safety restrictions, are attracting attention. However, LED light sources have very low energy, and the photoacoustic signal generated is correspondingly small. Therefore, the photoacoustic signal is buried in noise, resulting in a low signal-to-noise ratio (SNR). Averaging can also improve SNR, but it is difficult to maintain a high frame rate. M-sequence signal processing can improve SNR while maintaining a high repetition rate, and its effectiveness has been demonstrated in photoacoustic measurements of laser light sources. However, LED power supplies have time delays in emission and circuit jitter, which affect decoding. Therefore, we propose a new decoding algorithm that compensates for LED jitter. We then experimentally verified the SNR improvement using this signal processing in practice.
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