Application of time lags between light and temperature cycles for growth control based on the circadian clock of Lactuca sativa L. seedlings

The circadian clock plays an important role in agriculture, especially in highly controlled environments, such as plant factories. However, multiple environmental factors have an extremely high degree of freedom, and it is difficult to experimentally search for the optimal design conditions. A recent study demonstrated that the effect of time lags between light and temperature cycles on plant growth could be predicted by the entrainment properties of the circadian clock in Arabidopsis thaliana. Based on this prediction, it was possible to control plant growth by adjusting the time lag. However, for application in plant factories, it is necessary to verify the effectiveness of this method using commercial vegetables, such as leaf lettuce. In this study, we investigated the entrainment properties of the circadian clock and the effect of the time lag between light and temperature cycles on circadian rhythms and plant growth in Lactuca sativa L. seedlings. For evaluation of circadian rhythms, we used transgenic L. sativa L. with a luciferase reporter in the experiment and a phase oscillator model in the simulation. We found that the entrainment properties for the light and temperature stimuli and the effects of time lags on circadian rhythm and growth were similar to those of A. thaliana. Moreover, we demonstrated that changes in growth under different time lags could be predicted by simulation based on the entrainment properties of the circadian clock. These results showed the importance of designing a cultivation environment that considers the circadian clock and demonstrated a series of methods to achieve this.

Time Will Tell: Intercellular Communication in the Plant Clock

Multicellular organisms have evolved local and long-distance signaling mechanisms to synchronize development and response to stimuli among a complex network of cells, tissues, and organs. Biological timekeeping is one such activity that is suggested to be coordinated within an organism to anticipate and respond to daily and seasonal patterns in the environment. New research into the plant clock suggests circadian rhythms are communicated between cells and across long distances. However, further clarity is required on the nature of the signaling molecules and the mechanisms underlying signal translocation. Here we summarize the roles and properties of tissue-specific circadian rhythms, discuss the evidence for local and long-distance clock communication, and evaluate the potential signaling molecules and transport mechanisms involved in this system.

Intrinsic noise, Delta-Notch signalling and delayed reactions promote sustained, coherent, synchronized oscillations in the presomitic mesoderm

Using a stochastic individual-based modelling approach, we examine the role that Delta-Notch signalling plays in the regulation of a robust and reliable somite segmentation clock. We find that not only can Delta-Notch signalling synchronize noisy cycles of gene expression in adjacent cells in the presomitic mesoderm (as is known), but it can also amplify and increase the coherence of these cycles. We examine some of the shortcomings of deterministic approaches to modelling these cycles and demonstrate how intrinsic noise can play an active role in promoting sustained oscillations, giving rise to noise-induced quasi-cycles. Finally, we explore how translational/transcriptional delays can result in the cycles in neighbouring cells oscillating in anti-phase and we study how this effect relates to the propagation of noise-induced stochastic waves.

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana

Individual plant cells have a genetic circuit, the circadian clock, that times key processes to the day-night cycle. These clocks are aligned to the day-night cycle by multiple environmental signals that vary across the plant. How does the plant integrate clock rhythms, both within and between organs, to ensure coordinated timing? To address this question, we examined the clock at the sub-tissue level across Arabidopsis thaliana seedlings under multiple environmental conditions and genetic backgrounds. Our results show that the clock runs at different speeds (periods) in each organ, which causes the clock to peak at different times across the plant in both constant environmental conditions and light-dark (LD) cycles. Closer examination reveals that spatial waves of clock gene expression propagate both within and between organs. Using a combination of modeling and experiment, we reveal that these spatial waves are the result of the period differences between organs and local coupling, rather than long-distance signaling. With further experiments we show that the endogenous period differences, and thus the spatial waves, can be generated by the organ specificity of inputs into the clock. We demonstrate this by modulating periods using light and metabolic signals, as well as with genetic perturbations. Our results reveal that plant clocks can be set locally by organ-specific inputs but coordinated globally via spatial waves of clock gene expression.

Computational modeling and experiments with Arabidopsis thaliana reveal a new mechanism for the coordination of circadian timing across an organism, acting through a combination of organ-specific sensitivity to environmental inputs and local cell-cell coupling.

Leaf-Movement-Based Growth Prediction Model Using Optical Flow Analysis and Machine Learning in Plant Factory

Productivity stabilization is a critical issue facing plant factories. As such, researchers have been investigating growth prediction with the overall goal of improving productivity. The projected area of a plant (PA) is usually used for growth prediction, by which the growth of a plant is estimated by observing the overall approximate movement of the plant. To overcome this problem, this study focused on the time-series movement of plant leaves, using optical flow (OF) analysis to acquire this information for a lettuce. OF analysis is an image processing method that extracts the difference between two consecutive frames caused by the movement of the subject. Experiments were carried out at a commercial large-scale plant factory. By using a microcomputer with a camera module placed above the lettuce seedlings, images of 338 seedlings were taken every 20 min over 9 days (from the 6th to the 15th day after sowing). Then, the features of the leaf movement were extracted from the image by calculating the normal-vector in the OF analysis, and these features were applied to machine learning to predict the fresh weight of the lettuce at harvest time (38 days after sowing). The growth prediction model using the features extracted from the OF analysis was found to perform well with a correlation ratio of 0.743. Furthermore, this study also considered a phenotyping system that was capable of automatically analyzing a plant image, which would allow this growth prediction model to be widely used in commercial plant factories.

Multicellularity enriches the entrainment of Arabidopsis circadian clock

The phase response curve (PRC) of the circadian clock provides one of the most significant indices for anticipating entrainment of outer cycles, despite the difficulty of making precise PRC determinations in experiments. We characterized the PRC of the Arabidopsisthaliana circadian clock on the basis of its phase-locking property to variable periodic pulse perturbations. Experiments revealed that the PRC changed remarkably from continuous to discontinuous fashion, depending on the oscillation amplitude. Our hypothesis of amplitude-dependent adaptability to outer cycles was successfully clarified by elucidation of this transition of PRC as a change in the collective response of the circadian oscillator network. These findings provide an essential criterion against which to evaluate the precision of PRC measurement and an advanced understanding of the adaptability of plant circadian systems to environmental conditions.

High-Throughput Growth Prediction for Lactuca sativa L. Seedlings Using Chlorophyll Fluorescence in a Plant Factory with Artificial Lighting

Poorly grown plants that result from differences in individuals lead to large profit losses for plant factories that use large electric power sources for cultivation. Thus, identifying and culling the low-grade plants at an early stage, using so-called seedlings diagnosis technology, plays an important role in avoiding large losses in plant factories. In this study, we developed a high-throughput diagnosis system using the measurement of chlorophyll fluorescence (CF) in a commercial large-scale plant factory, which produces about 5000 lettuce plants every day. At an early stage (6 days after sowing), a CF image of 7200 seedlings was captured every 4 h on the final greening day by a high-sensitivity CCD camera and an automatic transferring machine, and biological indices were extracted. Using machine learning, plant growth can be predicted with a high degree of accuracy based on biological indices including leaf size, amount of CF, and circadian rhythms in CF. Growth prediction was improved by addition of temporal information on CF. The present data also provide new insights into the relationships between growth and temporal information regulated by the inherent biological clock.

Controlling circadian rhythms by dark-pulse perturbations in Arabidopsis thaliana

Plant circadian systems are composed of a large number of self-sustained cellular circadian oscillators. Although the light-dark signal in the natural environment is known to be the most powerful Zeitgeber for the entrainment of cellular oscillators, its effect is too strong to control the plant rhythm into various forms of synchrony. Here, we show that the application of pulse perturbations, i.e., short-term injections of darkness under constant light, provides a novel technique for controlling the synchronized behavior of plant rhythm in Arabidopsis thaliana. By destroying the synchronized cellular activities, circadian singularity was experimentally induced. The present technique is based upon the theory of phase oscillators, which does not require prior knowledge of the detailed dynamics of the plant system but only knowledge of its phase and amplitude responses to the pulse perturbation. Our approach can be applied to diverse problems of controlling biological rhythms in living systems.