NMT历史上的今天丨Planta：（专利）NMT评估种子萌发和活力

旭月北京科技有限公司

2020/02/19 16:14

NMT是基因功能的活体检测技术，已被103位诺贝尔奖得主所在单位，及北大、清华、中科院使用。

NMT历史上的今天

2014年02月19日，北京林业大学汪晓峰、李加国用NMT在Planta 上发表了标题为The fluxes of H2O2 and O2 can be used to evaluate seed germination and vigor of Caragana korshinskii的研究成果。

期刊：Planta
主题：H2O2和O2的通量可以评估种子的萌发和活力

标题：The fluxes of H2O2 and O2 can be used to evaluate seed germination and vigor of Caragana korshinskii

影响因子：3.347

检测指标：H2O2、O2流速

作者：北京林业大学汪晓峰、李加国

英文摘要

Seed deterioration is detrimental to plant germplasm conservation, and predicting seed germination and vigor with reliability and sensitivity means is urgently needed for practical problems.

We investigated the link between hydrogen peroxide (H2O2) flux, oxygen influx and seed vigor of Caragana korshinskii by the non-invasive micro-test technique (NMT). Some related physiological and biochemical changes in seeds were also determined to further explain the changes in the molecular fluxes.

The results showed that there was a good linear relationship between germination and H2O2 flux, and that O2 influx was more suitable for assessing seed vigor. H2O2 flux changed relatively little initially, mainly affected by antioxidants (APX, CAT and GSH) and H2O2 content; afterward, the efflux increased more and more rapidly due to high membrane permeability. With the damage of mitochondrial respiration and membrane integrity, O2 influx was gradually reduced.

We propose that monitoring H2O2 and O2 fluxes by NMT may be a reliable and sensitive method to evaluate seed germination and vigor.

中文摘要（谷歌机翻）

种子变质对植物种质的保存有害，因此迫切需要通过可靠性和敏感性手段预测种子的发芽和活力。

我们通过非损伤微测试技术（NMT）研究了过氧化氢（H2O2）通量，氧气流入和柠条锦鸡儿种子活力之间的联系。还确定了种子中一些相关的生理和生化变化，以进一步解释分子通量的变化。

结果表明，发芽率与H2O2通量之间存在良好的线性关系，而O2流入更适合评估种子活力。H2O2通量最初变化相对较小，主要受抗氧化剂（APX，CAT和GSH）和H2O2含量的影响；之后，由于高的膜渗透性，流出量越来越快地增加。随着线粒体呼吸和膜完整性的损害，O2流入量逐渐减少。

我们建议通过NMT监测H2O2和O2通量可能是评估种子发芽和活力的可靠且敏感的方法。

Fig. 3 Effect of arti?cial aging on ?uxes of oxygen and H2O2. The colored lines represent the ?uxes of oxygen and H2O2 over time for one seed (a, b, d, e), and each column gives the mean ± SD from ten different seeds (n = 10) (c, f). Statistical analysis was done using Duncan’s multiple range test. Treatments with different letters are signi?cantly different at the p < 0.05 level

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