Zhang Zheng, Shi Xinglei, Li Ruhai, Qiang Sheng
Weed Research Laboratory, Nanjing Agricultural University, Nanjing, China.
Institute of Plant Protection and Soil Fertilizer, Hubei Academy of Agricultural Sciences, Wuhan, China.
Front Plant Sci. 2022 Aug 8;13:959046. doi: 10.3389/fpls.2022.959046. eCollection 2022.
Accurate tracking of seed dispersal is critical for understanding gene flow and seed bank dynamics, and for predicting population distributions and spread. Available seed-tracking techniques are limited due to environmental and safety issues or requirements for expensive and specialized equipment. Furthermore, few techniques can be applied to studies of water-dispersed seeds. Here we introduce a new seed-tracking method using safranine to stain seeds/fruits by immersing in () or spraying with () staining solution. The hue difference value between pre- and post-stained seeds/fruits was compared using the HSV color model to assess the effect of staining. A total of 181 kinds of seeds/fruits out of 233 tested species of farmland weeds, invasive alien herbaceous plants and trees could be effectively stained magenta to red in hue (320-360°) from generally yellowish appearance (30-70°), in which the other 39 ineffectively-stained species were distinguishable by the naked eye from pre-stained seeds. The most effectively stained seeds/fruits were those with fluffy pericarps, episperm, or appendages. Safranine staining was not found to affect seed weight or germination ability regardless of whether seeds were stained or . For 44 of 48 buried species, the magenta color of stained seeds clearly remained recognizable for more than 5 months after seeds were buried in soil. Tracking experiments using four species (, f. spontanea, , and ), representing two noxious agricultural weeds, an alien invasive plant, and a tree, respectively, showed that the safranine staining technique can be widely applied for studying plant seed dispersal. Identifying and counting the stained seeds/fruits can be executed by specially complied Python-based program, based on OpenCV library for image processing and Numpy for data handling. From the above results, we conclude that staining with safranine is a cheap, reliable, easily recognized, automatically counted, persistent, environmentally safe, and user-friendly tracking-seed method. This technique may be widely applied to staining most of the seed plant species and the study of seed dispersal in arable land and in disturbed and natural terrestrial or hydrophytic ecological systems.
准确追踪种子传播对于理解基因流动和种子库动态,以及预测种群分布和扩散至关重要。由于环境和安全问题,或需要昂贵的专业设备,现有的种子追踪技术受到限制。此外,很少有技术可应用于对水传播种子的研究。在此,我们介绍一种新的种子追踪方法,即使用番红对种子/果实进行染色,方法是将其浸入()或用()染色溶液喷洒。使用HSV颜色模型比较染色前后种子/果实的色差,以评估染色效果。在233种受试的农田杂草、外来入侵草本植物和树木中,共有181种种子/果实能够被有效地染成从通常的淡黄色外观(30 - 70°)到品红色至红色(320 - 360°)的色调,其中另外39种染色无效的物种可通过肉眼与未染色的种子区分开来。染色效果最显著的种子/果实是那些具有蓬松果皮、外种皮或附属物的。无论种子染色()还是(),均未发现番红染色会影响种子重量或发芽能力。对于48种被掩埋物种中的44种,染色种子的品红色在埋入土壤后5个多月仍清晰可辨。使用分别代表两种有害农业杂草、一种外来入侵植物和一棵树的四个物种(,自发的f.,,和)进行的追踪实验表明,番红染色技术可广泛应用于研究植物种子传播。识别和计数染色的种子/果实可通过基于Python的专门编写的程序执行,该程序基于用于图像处理的OpenCV库和用于数据处理的Numpy。根据上述结果,我们得出结论,番红染色是一种廉价、可靠、易于识别、可自动计数、持久、环境安全且用户友好的种子追踪方法。该技术可广泛应用于对大多数种子植物物种进行染色,以及研究耕地和受干扰的自然陆地或水生生态系统中的种子传播。