Diel growth patterns of young soybean (Glycine max) leaflets are synchronous throughout different positions on a plant

Non-destructive monitoring method for leaf area of Brassica napus based on image processing and deep learning

Introduction

Leaves are important organs for photosynthesis in plants, and the restriction of leaf growth is among the earliest visible effects under abiotic stress such as nutrient deficiency. Rapidly and accurately monitoring plant leaf area is of great importance in understanding plant growth status in modern agricultural production.

Method

In this paper, an image processing-based non-destructive monitoring device that includes an image acquisition device and image process deep learning net for acquiring Brassica napus (rapeseed) leaf area is proposed. A total of 1,080 rapeseed leaf image areas from five nutrient amendment treatments were continuously collected using the automatic leaf acquisition device and the commonly used area measurement methods (manual and stretching methods).

Results

The average error rate of the manual method is 12.12%, the average error rate of the stretching method is 5.63%, and the average error rate of the splint method is 0.65%. The accuracy of the automatic leaf acquisition device was improved by 11.47% and 4.98% compared with the manual and stretching methods, respectively, and had the advantages of speed and automation. Experiments on the effects of the manual method, stretching method, and splinting method on the growth of rapeseed are conducted, and the growth rate of rapeseed leaves under the stretching method treatment is considerably greater than that of the normal treatment rapeseed.

Discussion

The growth rate of leaves under the splinting method treatment was less than that of the normal rapeseed treatment. The mean intersection over union (mIoU) of the UNet-Attention model reached 90%, and the splint method had higher prediction accuracy with little influence on rapeseed.

Establishment of a novel experimental system for studying the photoperiodic response of short-day dicots using soybean 'cotyledon-only plant' as material

Soybean is an important model crop for photoperiodic response studies in plants and contributes significantly to the study of plant development and physiology in the past century. Because soybean plant is much bigger in size and longer in life cycle than Arabidopsis, it needs much more space for growth and time for investigation, which significantly hamper the efficiency of research. In the current study, we tested the photoperiodic response of a distinctive artificially-made cotyledon-only plant (COP) using a photoperiod-sensitive soybean variety Zigongdongdou (ZGDD) and other varieties with diverse sensitivity to photoperiod. ZGDD COPs flowered 39.4 ± 2.5 d after emergence under short-day conditions but maintained vegetative growth under long-day and night break conditions, which is similar to the case in the intact ZGDD plants. The COPs of early-maturing and medium-maturing soybean varieties also grew and flowered normally under natural day-length conditions. At the molecular level, the key genes in the photoperiodic pathway such as E1, GmFT1a, GmFT2a, and GmFT5a in the COPs also showed the same photoperiod sensitivity as in the intact plants. In addition, a simpler material of COP with only one cotyledon and root was generated and found to be sensitive to photoperiod as well. Notably, the COPs are only one-fifth the height of intact plants and one-third the maximum diameter of the intact plants grown in chambers 30 d after emergence. Based on COPs, we established a novel experimental system characterized by an entire photoperiodic response and longer longevity of cotyledons in addition to small plant size, ensuring the consistency, reliability, and stability of plant materials. COPs have the potential to be a novel model material for studies of the developmental biology of soybean and other dicots.

Rethinking temperature effects on leaf growth, gene expression and metabolism: Diel variation matters

Plants have evolved to grow under prominently fluctuating environmental conditions. In experiments under controlled conditions, temperature is often set to artificial, binary regimes with constant values at day and at night. This study investigated how such a diel (24 hr) temperature regime affects leaf growth, carbohydrate metabolism and gene expression, compared to a temperature regime with a field-like gradual increase and decline throughout 24 hr. Soybean (Glycine max) was grown under two contrasting diel temperature treatments. Leaf growth was measured in high temporal resolution. Periodical measurements were performed of carbohydrate concentrations, carbon isotopes as well as the transcriptome by RNA sequencing. Leaf growth activity peaked at different times under the two treatments, which cannot be explained intuitively. Under field-like temperature conditions, leaf growth followed temperature and peaked in the afternoon, whereas in the binary temperature regime, growth increased at night and decreased during daytime. Differential gene expression data suggest that a synchronization of cell division activity seems to be evoked in the binary temperature regime. Overall, the results show that the coordination of a wide range of metabolic processes is markedly affected by the diel variation of temperature, which emphasizes the importance of realistic environmental settings in controlled condition experiments.

Turgor-driven plant growth applied in a soybean functional-structural plant model

BACKGROUND AND AIMS

Turgor pressure within a plant cell represents the key to the mechanistical descriptiion of plant growth, combining the effects of both water and carbon availability. The high level of spatio-temporal variation and diurnal dynamics in turgor pressure within a single plant make it a challenge to model these on the fine spatial scale required for functional-structural plant models (FSPMs). A conceptual model for turgor-driven growth in FSPMs has been established previously, but its practical use has not yet been explored.

METHODS

A turgor-driven growth model was incorporated in a newly established FSPM for soybean. The FSPM simulates dynamics in photosynthesis, transpiration and turgor pressure in direct relation to plant growth. Comparisons of simulations with field data were used to evaluate the potential and shortcomings of the modelling approach.

KEY RESULTS

Model simulations revealed the need to include an initial seed carbon contribution, a more realistic sink function, an estimation of respiration, and the distinction between osmotic and structural sugars, in order to achieve a realistic model of plant growth. However, differences between simulations and observations remained in individual organ growth patterns and under different environmental conditions. This exposed the need to further investigate the assumptions of developmental and environmental (in)sensitivity of the parameters, which represent physiological and biophysical organ properties in the model, in future research.

CONCLUSIONS

The model in its current form is primarily a diagnostic tool, to better understand and model the behaviour of water relations on the scale of individual plant organs throughout the plant life cycle. Potential future applications include its use as a phenotyping tool to capture differences in plant performance between genotypes and growing environments in terms of specific plant characteristics. Additionally, focused experiments can be used to further improve the model mechanisms to lead to better predictive FSPMs, including scenarios of water deficit.

Leaf Fresh Weight Versus Dry Weight: Which is Better for Describing the Scaling Relationship between Leaf Biomass and Leaf Area for Broad-Leaved Plants?

Leaf dry mass per unit area (LMA) is considered to represent the photosynthetic capacity, which actually implies a hypothesis that foliar water mass (leaf fresh weight minus leaf dry weight) is proportional to leaf dry weight during leaf growth. However, relevant studies demonstrated that foliar water mass disproportionately increases with increasing leaf dry weight. Although scaling relationships of leaf dry weight vs. leaf area for many plants were investigated, few studies compared the scaling relationship based on leaf dry weight with that based on leaf fresh weight. In this study, we used the data of three families (Lauraceae, Oleaceae, and Poaceae, subfamily Bambusoideae) with five broad-leaved species for each family to examine whether using different measures for leaf biomass (i.e., dry weight and fresh weight) can result in different fitted results for the scaling relationship between leaf biomass and area. Reduced major axis regression was used to fit the log-transformed data of leaf biomass and area, and the bootstrap percentile method was used to test the significance of the difference between the estimate of the scaling exponent of leaf dry weight vs. area and that of leaf fresh weight vs. area. We found that there were five species across three families (Phoebe sheareri (Hemsl.) Gamble, Forsythia viridissima Lindl., Osmanthus fragrans Lour., Chimonobambusa sichuanensis (T.P. Yi) T.H. Wen, and Hibanobambusa tranquillans f. shiroshima H. Okamura) whose estimates of the scaling exponent of leaf dry weight to area and that of leaf fresh weight to area were not significantly different, whereas, for the remaining ten species, both estimates were significantly different. For the species in the same family whose leaf shape is narrow (i.e., a low ratio of leaf width to length) the estimates of two scaling exponents are prone to having a significant difference. There is also an allometric relationship between leaf dry weight and fresh weight, which means that foliar water mass disproportionately increases with increased leaf dry weight. In addition, the goodness of fit for the scaling relationship of leaf fresh weight vs. area is better than that for leaf dry weight vs. area, which suggests that leaf fresh mass might be more able to reflect the physiological functions of leaves associated with photosynthesis and respiration than leaf dry mass. The above conclusions are based on 15 broad-leaved species, although we believe that those conclusions may be potentially extended to other plants with broad and flat leaves.

Mathematical modeling of diurnal patterns of carbon allocation to shoot and root in Arabidopsis thaliana

We developed a mathematical model to simulate dynamics of central carbon metabolism over complete diurnal cycles for leaves of Arabidopsis thaliana exposed to either normal (120 µmol m-2 s-1) or high light intensities (1200 µmol m- 2 s-1). The main objective was to obtain a high-resolution time series for metabolite dynamics as well as for shoot structural carbon formation (compounds with long residence time) and assimilate export of aerial organs to the sink tissue. Model development comprised a stepwise increment of complexity to finally approach the in vivo situation. The correct allocation of assimilates to either sink export or shoot structural carbon formation was a central goal of model development. Diurnal gain of structural carbon was calculated based on the daily increment in total photosynthetic carbon fixation, and this was the only parameter for structural carbon formation implemented in the model. Simulations of the dynamics of central metabolite pools revealed that shoot structural carbon formation occurred solely during the light phase but not during the night. The model allowed simulation of shoot structural carbon formation as a function of central leaf carbon metabolism under different environmental conditions without structural modifications. Model simulations were performed for the accession Landsberg erecta (Ler) and its hexokinase null-mutant gin2-1. This mutant displays a slow growth phenotype especially at increasing light intensities. Comparison of simulations revealed that the retarded shoot growth in the mutant resulted from an increased assimilate transport to sink organs. Due to its central function in sucrose cycling and sugar signaling, our findings suggest an important role of hexokinase-1 for carbon allocation to either shoot growth or assimilate export.

Non-destructive measurement of soybean leaf thickness via X-ray computed tomography allows the study of diel leaf growth rhythms in the third dimension

Present-day high-resolution leaf growth measurements provide exciting insights into diel (24-h) leaf growth rhythms and their control by the circadian clock, which match photosynthesis with oscillating environmental conditions. However, these methods are based on measurements of leaf area or elongation and neglect diel changes of leaf thickness. In contrast, the influence of various environmental stress factors to which leaves are exposed to during growth on the final leaf thickness has been studied extensively. Yet, these studies cannot elucidate how variation in leaf area and thickness are simultaneously regulated and influenced on smaller time scales. Only few methods are available to measure the thickness of young, growing leaves non-destructively. Therefore, we evaluated X-ray computed tomography to simultaneously and non-invasively record diel changes and growth of leaf thickness and area. Using conventional imaging and X-ray computed tomography leaf area, thickness and volume growth of young soybean leaves were simultaneously and non-destructively monitored at three cardinal time points during night and day for a period of 80 h under non-stressful growth conditions. Reference thickness measurements on paperboards were in good agreement to CT measurements. Comparison of CT with leaf mass data further proved the consistency of our method. Exploratory analysis showed that measurements were accurate enough for recording and analyzing relative diel changes of leaf thickness, which were considerably different to those of leaf area. Relative growth rates of leaf area were consistently positive and highest during 'nights', while diel changes in thickness fluctuated more and were temporarily negative, particularly during 'evenings'. The method is suitable for non-invasive, accurate monitoring of diel variation in leaf volume. Moreover, our results indicate that diel rhythms of leaf area and thickness show some similarity but are not tightly coupled. These differences could be due to both intrinsic control mechanisms and different sensitivities to environmental factors.

Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions

BACKGROUND

Plant growth is a good indicator of crop performance and can be measured by different methods and on different spatial and temporal scales. In this study, we measured the canopy height growth of maize (Zea mays), soybean (Glycine max) and wheat (Triticum aestivum) under field conditions by terrestrial laser scanning (TLS). We tested the hypotheses whether such measurements are capable to elucidate (1) differences in architecture that exist between genotypes; (2) genotypic differences between canopy height growth during the season and (3) short-term growth fluctuations (within 24 h), which could e.g. indicate responses to rapidly fluctuating environmental conditions. The canopies were scanned with a commercially available 3D laser scanner and canopy height growth over time was analyzed with a novel and simple approach using spherical targets with fixed positions during the whole season. This way, a high precision of the measurement was obtained allowing for comparison of canopy parameters (e.g. canopy height growth) at subsequent time points.

RESULTS

Three filtering approaches for canopy height calculation from TLS were evaluated and the most suitable approach was used for the subsequent analyses. For wheat, high coefficients of determination (R(2)) of the linear regression between manually measured and TLS-derived canopy height were achieved. The temporal resolution that can be achieved with our approach depends on the scanned crop. For maize, a temporal resolution of several hours can be achieved, whereas soybean is ideally scanned only once per day, after leaves have reached their most horizontal orientation. Additionally, we could show for maize that plant architectural traits are potentially detectable with our method.

CONCLUSIONS

The TLS approach presented here allows for measuring canopy height growth of different crops under field conditions with a high temporal resolution, depending on crop species. This method will enable advances in automated phenotyping for breeding and precision agriculture applications. In future studies, the TLS method can be readily applied to detect the effects of plant stresses such as drought, limited nutrient availability or compacted soil on different genotypes or on spatial variance in fields.

The relationship between leaf area growth and biomass accumulation in Arabidopsis thaliana

Leaf area growth determines the light interception capacity of a crop and is often used as a surrogate for plant growth in high-throughput phenotyping systems. The relationship between leaf area growth and growth in terms of mass will depend on how carbon is partitioned among new leaf area, leaf mass, root mass, reproduction, and respiration. A model of leaf area growth in terms of photosynthetic rate and carbon partitioning to different plant organs was developed and tested with Arabidopsis thaliana L. Heynh. ecotype Columbia (Col-0) and a mutant line, gigantea-2 (gi-2), which develops very large rosettes. Data obtained from growth analysis and gas exchange measurements was used to train a genetic programming algorithm to parameterize and test the above model. The relationship between leaf area and plant biomass was found to be non-linear and variable depending on carbon partitioning. The model output was sensitive to the rate of photosynthesis but more sensitive to the amount of carbon partitioned to growing thicker leaves. The large rosette size of gi-2 relative to that of Col-0 resulted from relatively small differences in partitioning to new leaf area vs. leaf thickness.