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A real-time, non-invasive, micro-optrode technique for detecting seed viability by using oxygen influx.

ABSTRACT: Quantifying seed viability is required for seed bank maintenance. The classical methods for detecting seed viability are time consuming and frequently cause seed damage and unwanted germination. We have established a novel micro-optrode technique (MOT) to measure seed viability in a quick and non-invasive manner by measuring the oxygen influxes of intact seeds, approximately 10 seconds to screen one seed. Here, we used soybean, wheat, and oilseed rape as models to test our method. After 3-hour imbibition, oxygen influxes were recorded in real-time with the total measurement taking less than 5 minutes. The results indicated a significantly positive correlation between oxygen influxes and viability in all 3 seed types. We also established a linear equation between oxygen influxes and seed viability for each seed type. For measurements, seeds were kept in the early imbibition stage without germination. Thus, MOT is a reliable, quick, and low-cost seed viability detecting technique.

SUBMITTER: Xin X

PROVIDER: S-EPMC3808820 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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A real-time, non-invasive, micro-optrode technique for detecting seed viability by using oxygen influx.

Xin Xia X Wan Yinglang Y Wang Wenjun W Yin Guangkun G McLamore Eric S ES Lu Xinxiong X

Scientific reports 20131028

Quantifying seed viability is required for seed bank maintenance. The classical methods for detecting seed viability are time consuming and frequently cause seed damage and unwanted germination. We have established a novel micro-optrode technique (MOT) to measure seed viability in a quick and non-invasive manner by measuring the oxygen influxes of intact seeds, approximately 10 seconds to screen one seed. Here, we used soybean, wheat, and oilseed rape as models to test our method. After 3-hour i ...[more]

PMID: 24162185

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Project description:Detecting reactive oxygen species (ROS) that play a critical role as redox modulators and signalling molecules in biological systems currently requires invasive methods such as ROS -specific indicators for imaging and quantification. We developed a non-invasive, real-time, label-free imaging technique for assessing the level of ROS in live cells and thawed cryopreserved tissues that is compatible with in-vivo imaging. The technique is based on autofluorescence multispectral imaging (AFMI) carried out in an adapted fluorescence microscope with an expanded number of spectral channels spanning specific excitation (365 nm-495 nm) and emission (420 nm-700 nm) wavelength ranges. We established a strong quantitative correlation between the spectral information obtained from AFMI and the level of ROS obtained from CellROX staining. The results were obtained in several cell types (HeLa, PANC1 and mesenchymal stem cells) and in live kidney tissue. Additioanly,two spectral regimes were considered: with and without UV excitation (wavelengths > 400 nm); the latter being suitable for UV-sensitive systems such as the eye. Data were analyzed by linear regression combined with an optimization method of swarm intelligence. This allowed the calibration of AFMI signals to the level of ROS with excellent correlation (R = 0.84, p = 0.00) in the entire spectral range and very good correlation (R = 0.78, p = 0.00) in the limited, UV-free spectral range. We also developed a strong classifier which allowed us to distinguish moderate and high levels of ROS in these two regimes (AUC = 0.91 in the entire spectral range and AUC = 0.78 for UV-free imaging). These results indicate that ROS in cells and tissues can be imaged non-invasively, which opens the way to future clinical applications in conditions where reactive oxygen species are known to contribute to progressive disease such as in ophthalmology, diabetes, kidney disease, cancer and neurodegenerative diseases.

Dataset Information

A real-time, non-invasive, micro-optrode technique for detecting seed viability by using oxygen influx.

Publications

A real-time, non-invasive, micro-optrode technique for detecting seed viability by using oxygen influx.

Similar Datasets

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