Shurygin Boris, Konyukhov Ivan, Khruschev Sergei, Solovchenko Alexei
Faculty of Biology, Lomonosov Moscow State University, Leninskie Gory 1/12, 119234 Moscow, Russia.
Institute of Natural Sciences, Derzhavin Tambov State University, 392036 Tambov, Russia.
Plants (Basel). 2022 Oct 22;11(21):2811. doi: 10.3390/plants11212811.
Dormancy is a physiological state that confers winter hardiness to and orchestrates phenological phase progression in temperate perennial plants. Weather fluctuations caused by climate change increasingly disturb dormancy onset and release in plants including tree crops, causing aberrant growth, flowering and fruiting. Research in this field suffers from the lack of affordable non-invasive methods for online dormancy monitoring. We propose an automatic framework for low-cost, long-term, scalable dormancy studies in deciduous plants. It is based on continuous sensing of the photosynthetic activity of shoots via pulse-amplitude-modulated chlorophyll fluorescence sensors connected remotely to a data processing system. The resulting high-resolution time series of JIP-test parameters indicative of the responsiveness of the photosynthetic apparatus to environmental stimuli were subjected to frequency-domain analysis. The proposed approach overcomes the variance coming from diurnal changes of insolation and provides hints on the depth of dormancy. Our approach was validated over three seasons in an apple ( Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods (growing of the cuttings obtained from the trees at different phases of dormancy) and the output of chilling requirement models. We discuss the advantages of the proposed monitoring framework such as prompt detection of frost damage along with its potential limitations.
休眠是一种生理状态,它赋予温带多年生植物抗寒性并协调其物候期进程。气候变化引起的天气波动日益干扰包括果树作物在内的植物的休眠开始和解除,导致生长、开花和结果异常。该领域的研究缺乏用于在线休眠监测的经济实惠的非侵入性方法。我们提出了一个用于落叶植物低成本、长期、可扩展休眠研究的自动框架。它基于通过远程连接到数据处理系统的脉冲幅度调制叶绿素荧光传感器对嫩枝光合活性的连续传感。对所得的指示光合机构对环境刺激响应性的JIP测试参数的高分辨率时间序列进行频域分析。所提出的方法克服了日照日变化带来的差异,并提供了休眠深度的线索。我们的方法在一个苹果(苹果属)果园中经过三个季节的验证,将非侵入性估计结果与传统方法(在休眠不同阶段从树上获取的插条生长情况)以及需冷量模型的输出结果进行了核对。我们讨论了所提出的监测框架的优点,如能及时检测霜冻损害及其潜在局限性。