Cryptochrome as a sensor of the blue/green ratio of natural radiation in Arabidopsis

Green light is similarly effective in promoting plant biomass as red/blue light: a meta-analysis

Whether green light promotes or represses plant growth is an unresolved but important question, warranting a global meta-analysis of published data. We collected 136 datasets from 48 publications on 17 crop species, and calculated the green light effect for a range of plant traits. For each trait the effect was calculated as the ratio between the trait value attained under a red/blue background light plus green, divided by the value attained under the background light only, both having the same light intensity. Generally, green light strongly increased intrinsic water use efficiency (15%), the shoot-to-root ratio (13%), and decreased stomatal conductance (-15%). Moreover, green light increased fresh weight to a small extent (4%), but not plant dry weight, resulting in a reduced dry matter content (-2%). Hence, green light is similarly effective at increasing biomass as red and blue light. Green light also showed to increase leaf area (7%) and specific leaf area (4%; i.e. thinner leaves). Furthermore, effects of green light were species-dependent, with positive effects on biomass for lettuce and microgreens, and negative effects in basil and tomato. Our data suggest that future research should focus on the role of green light in modulating water loss, its putative role as a shade signal, and the causes for its species-specific effects on crop biomass.

The response of LncRNAs associated with photosynthesis-and pigment synthesis-related genes to green light in Chlamydomonas reinhardtii

The quality of light is an important abiotic factor that affects the growth and development of green plants. Ultraviolet, red, blue, and far-red light all have demonstrated roles in regulating green plant growth and development, as well as light morphogenesis. However, the mechanism underlying photosynthetic organism responses to green light throughout the life of them are not clear. In this study, we exposed the unicellular green alga Chlamydomonas reinhardtii to green light and analyzed the dynamics of transcriptome changes. Based on the whole transcriptome data from C. reinhardtii, a total of 9974 differentially expressed genes (DEGs) were identified under green light. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these DEGs were mainly related to "carboxylic acid metabolic process," "enzyme activity," "carbon metabolism," and "photosynthesis and other processes." At the same time, 253 differentially expressed long non-coding RNAs (DELs) were characterized as green light responsive. We also made a detailed analysis of the responses of photosynthesis- and pigment synthesis-related genes in C. reinhardtii to green light and found that these genes exhibited obvious dynamic expression. Lastly, we constructed a co-expression regulatory network, comprising 49 long non-coding RNAs (lncRNAs) and 20 photosynthesis and pigment related genes, of which 9 mRNAs were also the predicted trans/cis-targets of 8 lncRNAs, these results suggested that lncRNAs may affect the expression of mRNAs related to photosynthesis and pigment synthesis. Our findings give a preliminary explanation of the response mechanism of C. reinhardtii to green light at the transcriptional level.

Green light mediates atypical photomorphogenesis by dual modulation of Arabidopsis phytochromes B and A

Although green light (GL) is located in the middle of the visible light spectrum and regulates a series of plant developmental processes, the mechanism by which it regulates seedling development is largely unknown. In this study, we demonstrated that GL promotes atypical photomorphogenesis in Arabidopsis thaliana via the dual regulations of phytochrome B (phyB) and phyA. Although the Pr-to-Pfr conversion rates of phyB and phyA under GL were lower than those under red light (RL) in a fluence rate-dependent and time-dependent manner, long-term treatment with GL induced high Pfr/Pr ratios of phyB and phyA. Moreover, GL induced the formation of numerous small phyB photobodies in the nucleus, resulting in atypical photomorphogenesis, with smaller cotyledon opening angles and longer hypocotyls in seedlings compared to RL. The abundance of phyA significantly decreased after short- and long-term GL treatments. We determined that four major PHYTOCHROME-INTERACTING FACTORs (PIFs: PIF1, PIF3, PIF4, and PIF5) act downstream of phyB in GL-mediated cotyledon opening. In addition, GL plays opposite roles in regulating different PIFs. For example, under continuous GL, the protein levels of all PIFs decreased, whereas the transcript levels of PIF4 and PIF5 strongly increased compared with dark treatment. Taken together, our work provides a detailed molecular framework for understanding the role of the antagonistic regulations of phyB and phyA in GL-mediated atypical photomorphogenesis.

Effects of green light supplementation with red and blue combinations of LED light spectrums on the growth and transcriptional response of Haematococcus pluvialis

Light management strategy is crucial for improving microalgal production in terms of higher biomass and economically valuable bioactive molecules. However, green light has received less attention in developing light managements for algae and higher plant due to its low absorption rate by chlorophyll. In this study, the effects of green light supplementation, in the combination with red and blue light were investigated in Haematococcus pluvialis. 10% and 20% of green light supplementations were applied in 3:2 ratios of red and blue LED light combinations as an expense of red-light. Growth rates, chlorophyll concentration, and dry weight were measured to assess the growth kinetics of H. pluvialis along with the relative transcript accumulations of four mRNAs: Rubisco, PTOX2, PsaB, and PsbS. Growth rates, chlorophyll concentrations and dry weight were found significantly higher in presence of 10% green light supplementation compared to red and blue light combinations. The relative transcript accumulations of Rubisco and PsbS genes showed significant upregulation at the end of the experiments (with the fold change of 42.91 ± 12.08 and 98.57 ± 27.38, respectively, relative to the beginning of the experiments) compared to combinations of red and blue light (fold change of 19.09 ± 3.0 and 47.77 ± 14.21, respectively, relative to beginning of the experiments). PsaB and PTOX2 transcripts did not show significant accumulation differences between treatments. It seems that green light has a dose dependent additive effect on the growth rate of H. pluvialis. The upregulation of Rubisco and PsbS may indicate green light dependent carbon assimilation and light-harvesting response in H. pluvialis.

Transcriptome Profiling Reveals the Response of Seed Germination of Peganum harmala to Drought Stress

Peganum harmala L. is a perennial herbaceous plant that plays critical roles in protecting the ecological environment in arid, semi-arid, and desert areas. Although the seed germination characteristics of P. harmala in response to environmental factors (i.e., drought, temperature, and salt) have been investigated, the response mechanism of seed germination to drought conditions has not yet been revealed. In this study, the changes in the physiological characteristics and transcriptional profiles in seed germination were examined under different polyethylene glycol (PEG) concentrations (0-25%). The results show that the seed germination rate was significantly inhibited with an increase in the PEG concentration. Totals of 3726 and 10,481 differentially expressed genes (DEGs) were, respectively, generated at 5% and 25% PEG vs. the control (C), with 1642 co-expressed DEGs, such as drought stress (15), stress response (175), and primary metabolism (261). The relative expression levels (RELs) of the key genes regulating seed germination in response to drought stress were in accordance with the physiological changes. These findings will pave the way to increase the seed germination rate of P. harmala in drought conditions.

Combining features selection strategy and features fusion strategy for SPAD estimation of winter wheat based on UAV multispectral imagery

The Soil Plant Analysis Development (SPAD) is a vital index for evaluating crop nutritional status and serves as an essential parameter characterizing the reproductive growth status of winter wheat. Non-destructive and accurate monitorin3g of winter wheat SPAD plays a crucial role in guiding precise management of crop nutrition. In recent years, the spectral saturation problem occurring in the later stage of crop growth has become a major factor restricting the accuracy of SPAD estimation. Therefore, the purpose of this study is to use features selection strategy to optimize sensitive remote sensing information, combined with features fusion strategy to integrate multiple characteristic features, in order to improve the accuracy of estimating wheat SPAD. This study conducted field experiments of winter wheat with different varieties and nitrogen treatments, utilized UAV multispectral sensors to obtain canopy images of winter wheat during the heading, flowering, and late filling stages, extracted spectral features and texture features from multispectral images, and employed features selection strategy (Boruta and Recursive Feature Elimination) to prioritize sensitive remote sensing features. The features fusion strategy and the Support Vector Machine Regression algorithm are applied to construct the SPAD estimation model for winter wheat. The results showed that the spectral features of NIR band combined with other bands can fully capture the spectral differences of winter wheat SPAD during the reproductive growth stage, and texture features of the red and NIR band are more sensitive to SPAD. During the heading, flowering, and late filling stages, the stability and estimation accuracy of the SPAD model constructed using both features selection strategy and features fusion strategy are superior to models using only a single feature strategy or no strategy. The enhancement of model accuracy by this method becomes more significant, with the greatest improvement observed during the late filling stage, with R2 increasing by 0.092-0.202, root mean squared error (RMSE) decreasing by 0.076-4.916, and ratio of performance to deviation (RPD) increasing by 0.237-0.960. In conclusion, this method has excellent application potential in estimating SPAD during the later stages of crop growth, providing theoretical basis and technical support for precision nutrient management of field crops.

Fusion of airborne multimodal point clouds for vegetation parameter correction extraction in burned areas

Most experimental studies use unimodal data for processing, the RGB image point cloud cannot separate the shrub and tree layers according to the visible vegetation index, and the airborne laser point cloud is difficult to distinguish between the ground and grass ranges, to address the above problems, a multi-band information image fusing the LiDAR point cloud and the RGB image point cloud is constructed. In this study, data collected from UAV platforms, including RGB image point clouds and laser point clouds, were used to construct a fine canopy height model (using laser point cloud data) and high-definition digital orthophotos (using image point cloud data), and the orthophotos were fused with a canopy height model (CHM) by selecting the Difference Enhancement Vegetation Index (DEVI) and Normalised Green-Blue Discrepancy Index (NGBDI) after comparing the accuracy of different indices. Morphological reconstruction of CHM + DEVI/NGBDI fusion image, remove unreasonable values; construct training samples, using classification regression tree algorithm, segmentation of the range of the burned areas and adaptive extraction of vegetation as trees, shrubs and grasslands, tree areas as foreground markers using the local maximum algorithm to detect the tree apexes, the non-tree areas are assigned to be the background markers, and the Watershed Transform is performed to obtain the segmentation contour; the original laser point cloud is divided into chunks according to the segmented single-tree contour, and the highest point is traversed to search for the highest point, and corrected for the height of the single-tree elevations one by one. Accuracy analysis of the vegetation information extracted by the method with the measured data showed that the improved method increased the overall recall rate by 4.1%, the overall precision rate by 3.7%, the overall accuracy F1 score by 3.9%, and the tree height accuracy by 8.8%, 1.4%, 1.7%, 6.4%, 1.8%, and 0.3%, respectively, in the six sampling plots. The effectiveness of the improved method is verified, while the higher the degree of vegetation mixing in the region the better the extraction effect of the improved algorithm.

The Effects of Light Spectrum and Intensity, Seeding Density, and Fertilization on Biomass, Morphology, and Resource Use Efficiency in Three Species of Brassicaceae Microgreens

Light is a critical component of indoor plant cultivation, as different wavelengths can influence both the physiology and morphology of plants. Furthermore, fertilization and seeding density can also potentially interact with the light recipe to affect production outcomes. However, maximizing production is an ongoing research topic, and it is often divested from resource use efficiencies. In this study, three species of microgreens-kohlrabi; mustard; and radish-were grown under five light recipes; with and without fertilizer; and at two seeding densities. We found that the different light recipes had significant effects on biomass accumulation. More specifically, we found that Far-Red light was significantly positively associated with biomass accumulation, as well as improvements in height, leaf area, and leaf weight. We also found a less strong but positive correlation with increasing amounts of Green light and biomass. Red light was negatively associated with biomass accumulation, and Blue light showed a concave downward response. We found that fertilizer improved biomass by a factor of 1.60 across species and that using a high seeding density was 37% more spatially productive. Overall, we found that it was primarily the main effects that explained microgreen production variation, and there were very few instances of significant interactions between light recipe, fertilization, and seeding density. To contextualize the cost of producing these microgreens, we also measured resource use efficiencies and found that the cheaper 24-volt LEDs at a high seeding density with fertilizer were the most efficient production environment for biomass. Therefore, this study has shown that, even with a short growing period of only four days, there was a significant influence of light recipe, fertilization, and seeding density that can change morphology, biomass accumulation, and resource input costs.

Impact of varying light spectral compositions on photosynthesis, morphology, chloroplast ultrastructure, and expression of light-responsive genes in Marchantia polymorpha

Marchantia polymorpha is a convenient model for studying light of different spectral compositions on various physiological and biochemical processes because its photoreceptor system is vastly simplified. The influence of red light (RL, 660 nm), far-red light (FRL, 730 nm), blue light (BL, 450 nm), and green light (GL, 525 nm) compared to white light (high-pressure sodium light (HPSL), white LEDs (WL 450 + 580 nm) and white fluorescent light (WFL) on photosynthetic and transpiration rates, photosystem II (PSII) activity, photomorphogenesis, and the expression of light and hormonal signaling genes was studied. The ultrastructure of the chloroplasts in different tissues of the gametophyte M. polymorpha was examined. FRL led to the formation of agranal chloroplasts (in the epidermis and the chlorenchyma) with a high starch content (in the parenchyma), which led to a reduced intensity of photosynthesis. BL increased the transcription of genes for the biosynthesis of secondary metabolites - chalcone synthase (CHS), cellulose synthase (CELL), and L-ascorbate peroxidase (APOX3), which is consistent with the increased activity of low-molecular weight antioxidants. FRL increased the expression of phytochrome apoprotein (PHY) and cytokinin oxidase (CYTox) genes, but the expression of the phytochrome interacting factor (PIF) gene decreased, which was accompanied by a significant change in gametophyte morphology. Analysis of crosstalk gene expression, and changes in morphology and photosynthetic activity was carried out.

Early Identification of Root Damages Caused by Western Corn Rootworms Using a Minimally Invasive Root Phenotyping Robot-MISIRoot

Western corn rootworm (WCR) is one of the most devastating corn rootworm species in North America because of its ability to cause severe production loss and grain quality damage. To control the loss, it is important to identify the infection of WCR at an early stage. Because the root system is the earliest feeding source of the WCR at the larvae stage, assessing the direct damage in the root system is crucial to achieving early detection. Most of the current methods still necessitate uprooting the entire plant, which could cause permanent destruction and a loss of the original root's structural information. To measure the root damages caused by WCR non-destructively, this study utilized MISIRoot, a minimally invasive and in situ automatic plant root phenotyping robot to collect not only high-resolution images but also 3D positions of the roots without uprooting. To identify roots in the images and to study how the damages were distributed in different types of roots, a deep convolution neural network model was trained to differentiate the relatively thick and thin roots. In addition, a color camera was used to capture the above-ground morphological features, such as the leaf color, plant height, and side-view leaf area. To check if the plant shoot had any visible symptoms in the inoculated group compared to the control group, several vegetation indices were calculated based on the RGB color. Additionally, the shoot morphological features were fed into a PLS-DA model to differentiate the two groups. Results showed that none of the above-ground features or models output a statistically significant difference between the two groups at the 95% confidence level. On the contrary, many of the root structural features measured using MISIRoot could successfully differentiate the two groups with the smallest t-test p-value of 1.5791 × 10^-6. The promising outcomes were solid proof of the effectiveness of MISIRoot as a potential solution for identifying WCR infestations before the plant shoot showed significant symptoms.

Effects of weak static magnetic fields on the development of seedlings of Arabidopsis thaliana

To study magnetoreception of Arabidopsis thaliana, we analysed several developmental responses including cryptochrome-independent seed germination and the phytochrome- and cryptochrome-dependent hypocotyl elongation and photo-accumulation of anthocyanins and chlorophylls in weak static magnetic fields ranging from near null to 122 μT. A field of 50 μT accelerated seed germination by about 20 h relative to samples maintained in a near-null field. The double mutant, cry1cry2, lacking cryptochromes 1 and 2 displayed the same magnetic field-induced germination acceleration under blue light as the wild-type strain. Magnetic field-induced germination acceleration was masked in the presence of exogenous sucrose. Stimulus-response curves for hypocotyl elongation in a range between near-null to 122 μT indicated maxima near 9 and 60 μT for the wild-type strain as well as mutant cry1cry2. The photo-accumulation of anthocyanins and chlorophylls could be effectively modulated by magnetic fields in the presence of low-irradiance red and blue light, respectively. The findings indicate that Arabidopsis thaliana possesses light-independent mechanisms of magnetic field reception, which remain presently unidentified. Our results are in better agreement with predictions of the level crossing mechanism (LCM) of magnetoreception rather than those of the cryptochrome-associated radical-pair mechanism (RPM).

Green means go: Green light promotes hypocotyl elongation via brassinosteroid signaling

Although many studies have elucidated the mechanisms by which different wavelengths of light (blue, red, far-red, or ultraviolet-B [UV-B]) regulate plant development, whether and how green light regulates plant development remains largely unknown. Previous studies reported that green light participates in regulating growth and development in land plants, but these studies have reported conflicting results, likely due to technical problems. For example, commercial green light-emitting diode light sources emit a little blue or red light. Here, using a pure green light source, we determined that unlike blue, red, far-red, or UV-B light, which inhibits hypocotyl elongation, green light promotes hypocotyl elongation in Arabidopsis thaliana and several other plants during the first 2-3 d after planting. Phytochromes, cryptochromes, and other known photoreceptors do not mediate green-light-promoted hypocotyl elongation, but the brassinosteroid (BR) signaling pathway is involved in this process. Green light promotes the DNA binding activity of BRI1-EMS-SUPPRESSOR 1 (BES1), a master transcription factor of the BR pathway, thus regulating gene transcription to promote hypocotyl elongation. Our results indicate that pure green light promotes elongation via BR signaling and acts as a shade signal to enable plants to adapt their development to a green-light-dominant environment under a canopy.

Fruit quality and volatile compounds of greenhouse sweet peppers as affected by the LED spectrum of supplementary interlighting

BACKGROUND

Seasonal low light intensity and short photoperiods lead to decreased yield, size, and quality of fruits in the Northern Hemisphere. Recently, supplemental lighting using light-emitting diodes (LEDs) has been introduced to overcome such problems. However, most studies have focused on plant growth or fruit yield but not on taste. This study aimed to evaluate the quality and volatile compounds of greenhouse sweet pepper fruits under three different lighting conditions: natural light only (NL), NL with red/blue interlighting (RB), and NL with red/blue/far-red interlighting (RBFR).

RESULTS

The size, color, firmness, and soluble sugar concentration of the sweet pepper fruit were investigated, and sensory evaluation was conducted by nine trained panelists. Individual fruit fresh weights were higher in the order of RBFR, NL, and RB, with mean values of 219.1, 201.7, and 197.4 g, respectively. Additionally, the composition of volatile compounds demonstrated a distinct clustering pattern by light treatment, implying that the LED interlighting spectra affected the overall taste of sweet pepper fruits. Sensory evaluation indicated that sweetness was higher in the order of RBFR, RB, and NL, with values of 5.28, 4.36, and 3.72, respectively. The soluble sugar results showed the same order as that for the sensory evaluation of sweetness, i.e., RBFR, RB, and NL, with values of 5071, 4647, and 3978 μg ^-1 fresh weight, respectively.

CONCLUSION

Adding far-red to RB interlighting could improve the fruit quality attributes, fruit taste perception, and soluble sugars of sweet peppers compared to those under RB or solely NL. © 2023 Society of Chemical Industry.

Shade avoidance in the context of climate change

When exposed to changes in the light environment caused by neighboring vegetation, shade-avoiding plants modify their growth and/or developmental patterns to access more sunlight. In Arabidopsis (Arabidopsis thaliana), neighbor cues reduce the activity of the photosensory receptors phytochrome B (phyB) and cryptochrome 1, releasing photoreceptor repression imposed on PHYTOCHROME INTERACTING FACTORs (PIFs) and leading to transcriptional reprogramming. The phyB-PIF hub is at the core of all shade-avoidance responses, whilst other photosensory receptors and transcription factors contribute in a context-specific manner. CONSTITUTIVELY PHOTOMORPHOGENIC1 is a master regulator of this hub, indirectly stabilizing PIFs and targeting negative regulators of shade avoidance for degradation. Warm temperatures reduce the activity of phyB, which operates as a temperature sensor and further increases the activities of PIF4 and PIF7 by independent temperature sensing mechanisms. The signaling network controlling shade avoidance is not buffered against climate change; rather, it integrates information about shade, temperature, salinity, drought, and likely flooding. We, therefore, predict that climate change will exacerbate shade-induced growth responses in some regions of the planet while limiting the growth potential in others.

Spectral-conversion film potential for greenhouses: Utility of green-to-red photons conversion and far-red filtration for plant growth

Although green (G, 500 to 600 nm) and far-red (FR, 700 to 800 nm) light play important roles in regulating plant growth and development, they are often considered less useful at stimulating photosynthesis than red (R, 600 to 700 nm) and blue (B, 400 to 500 nm) light. Based on this perception, approaches to modifying the transmission of greenhouse glazing materials include (1) conversion of G photons from sunlight into R photons and (2) exclusion of the near-infrared (>700 nm) fraction of sunlight. We evaluated these approaches using simulated scenarios with light-emitting diodes to determine how partial and complete substitution of G with R light and exclusion of FR light affected the growth of lettuce and tomato grown indoors. The substitution of G with R light had little or no effect on fresh and dry mass of tomato. However, with the presence of FR light, fresh and dry mass of lettuce increased by 22-26% as G light was increasingly substituted with R light. In tomato, excluding FR inhibited plant height, leaf area, and dry mass by 60-71%, 10-37%, and 20-44%, respectively. Similarly, in lettuce, excluding FR inhibited plant diameter, leaf length, and dry mass by 15-23%, 23-33%, or 28-48%, respectively. We conclude that the spectral conversion of G-to-R photons can promote plant growth in at least some crop species, such as lettuce, while the exclusion of FR decreases crop growth and yield.

Light spectra of biophilic LED-sourced system modify essential oils composition and plant morphology of Mentha piperita L. and Ocimum basilicum L

Investigating morphological and molecular mechanisms that plants adopt in response to artificial biophilic lighting is crucial for implementing biophilic approaches in indoor environments. Also, studying the essential oils (EOs) composition in aromatic plants can help unveil the light influence on plant metabolism and open new investigative routes devoted to producing valuable molecules for human health and commercial applications. We assessed the growth performance and the EOs composition of Mentha x piperita and Ocimum basilicum grown under an innovative artificial biophilic lighting system (CoeLux^®), that enables the simulation of natural sunlight with a realistic sun perception, and compared it to high-pressure sodium lamps (control) We found that plants grown under the CoeLux^® light type experienced a general suppression of both above and belowground biomass, a high leaf area, and a lower leaf thickness, which might be related to the shade avoidance syndrome. The secondary metabolites composition in the plants' essential oils was scarcely affected by both light intensity and spectral composition of the CoeLux^® light type, as similarities above 80% were observed with respect to the control light treatments and within both plant species. The major differences were detected with respect to the EOs extracted from plants grown under natural sunlight (52% similarity in M. piperita and 75% in O. basilicum). Overall, it can be speculated that the growth of these two aromatic plants under the CoeLux^® lighting systems is a feasible strategy to improve biophilic approaches in closed environments that include both plants and artificial sunlight. Among the two plant species analyzed, O. basilicum showed an overall better performance in terms of both morphological traits and essential oil composition. To increase biomass production and enhance the EOs quality (e.g., higher menthol concentrations), further studies should focus on technical solutions to raise the light intensity irradiating plants during their growth under the CoeLux^® lighting systems.

Polar day syndrome: differences in growth, photosynthetic traits and sink-size patterns between northern and southern Finnish silver birch (Betula pendula Roth) provenances in native and non-native photoperiods

Continuous light (CL) is available throughout the polar day for plants in the Arctic during the growing season, whereas provenances of the same species experience a very different environment with non-CL (NCL) just a few latitudes to the south. Both provenances need to acclimate to climate warming, yet we lack comprehensive understanding of how their growth, photosynthesis and leaf traits differ. Further, the provenances presumably have morphological and physiological adaptations to their native environments and therefore differ in response to photoperiod. We tested the height growth, leaf longevity, biomass accumulation, biomass allocation and rates of gas exchange of northern (67°N) and southern (61°N) Finnish silver birch (Betula pendula Roth) origins in CL- and NCL-treatments in a 4-month chamber experiment. Irrespective of photoperiod, 67°N had higher area-based photosynthetic rate (Anet), stomatal conductance (gs) and relative height growth rate (RGR), but lower stomatal density and fewer branches and leaves than 61°N. Photoperiod affected height growth cessation, biomass and photosynthetic traits, whereas leaf longevity and many leaf functional traits remained unchanged. In CL, both provenances had lower gs, higher RGR, increased shoot:root ratio and increased sink sizes (more branching, more leaves, increased total plant dry weight) compared with NCL. In NCL, 67°N ceased height growth earlier than in CL, which altered biomass accumulation and distribution patterns. Northern conditions impose challenges for plant growth and physiology. Whether a provenance inhabits and is adapted to an area with or without CL can also affect its response to the changing climate. Northern birches may have adapted to CL and the short growing season with a 'polar day syndrome' of traits, including relatively high gas exchange rates with low leaf biomass and growth traits that are mainly limited by the environment and the earlier growth cessation (to avoid frost damage).

Additional green light induces shade response symptoms in Brassica rapa as evidenced by increased lateral root spread

In some plant species, green light (500 to 570 nm) has been shown to act as a shade signal, which stimulates non-photosynthetic photoreceptors to initiate a response that promotes shading symptoms, including lateral root formation. No studies to date have examined whether green light induces shading symptoms in Brassica rapa specifically. Here, we report increased hypocotyl length, root width, and increased width:depth ratio of root architecture in plants grown under additional green light compared to red and blue light, and white light alone. Results indicate that green light acts as a shade signal in B. rapa to induce shading symptoms, including wider roots.

Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV

Grassland desertification has become one of the most serious environmental problems in the world. Grasslands are the focus of desertification research because of their ecological vulnerability. Their application on different grassland desertification grades remains limited. Therefore, in this study, 19 vegetation indices were calculated for 30 unmanned aerial vehicle (UAV) visible light images at five grades of grassland desertification in the Mu Us Sandy. Fractional Vegetation Coverage (FVC) with high accuracy was obtained through Support Vector Machine (SVM) classification, and the results were used as the reference values. Based on the FVC, the grassland desertification grades were divided into five grades: severe (FVC < 5%), high (FVC: 5-20%), moderate (FVC: 21-50%), slight (FVC: 51-70%), and non-desertification (FVC: 71-100%). The accuracy of the vegetation indices was assessed by the overall accuracy (OA), the kappa coefficient (k), and the relative error (RE). Our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. Excess Green Red Blue Difference Index (EGRBDI), Visible Band Modified Soil Adjusted Vegetation Index (V-MSAVI), Green Leaf Index (GLI), Color Index of Vegetation Vegetative (CIVE), Red Green Blue Vegetation Index (RGBVI), and Excess Green (EXG) accurately assessed grassland desertification at severe, high, moderate, and slight grades. In addition, the Red Green Ratio Index (RGRI) and Combined 2 (COM₂) were accurate in assessing severe desertification. The assessment of the 19 indices of the non-desertification grade had low accuracy. Moreover, our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. This study emphasizes that the applicability of the vegetation indices varies with the degree of grassland desertification and hopes to provide scientific guidance for a more accurate grassland desertification assessment.

Comprehensive insights into the influence of supplemental green light on the photosynthesis of ginger (Zingiber officinale Roscoe)

Although green light is not considered to contribute to the photosynthesis of plants, the photosynthesis of ginger, a dual-purpose vegetable used as a medicine and food, is affected by the green wave band. In this study, the supplementary green band of sunlight (SG) increased the net photosynthetic rate (Pn), maximal photochemical efficiency of PSII (Fv/Fm), and actual photochemical efficiency of PSII (Y(II)) compared with the sunlight treatment (S). The Pn and Fv/Fm of the SG treatment were higher than those of the white light (W) treatment, while the Pn and Fv/Fm of the green light (G) treatment alone were lower than those of the W treatment. Further analysis found that the minimal fluorescence (Fo) of the S treatment increased, especially at noon, while the Fo of the SG treatment decreased. Similarly, the Fo of the W treatment increased significantly, while the Fo of the white-green mixed light (WG) treatment decreased. The relative fluorescence values of the K-J-I bands in the SG and WG treatments were lower than those in the S and W treatments, respectively. The photochemical quenching (qP) of the WG treatment was higher than that of the W treatment, while the primary thermal losses corresponded to the sum of nonregulated heat dissipation and fluorescence emission (Y(NO)) of the WG treatment was lower than that of the W treatment. The SG treatment reduced the accumulation of plastoglobules but increased the accumulation of starch granules and leaf thickness. Moreover, the green band supplemented with white light significantly increased the biomass of the aboveground plant parts and promoted the active growth of the aboveground parts. Supplementing green light plays a regulatory role in ginger based on the following four points. First, it effectively promotes the transfer of electrons between the acceptor side of photosystem II; second, it optimizes ginger photosynthesis; third, it alleviates strong light stress by reducing the accumulation of reactive oxygen species; and fourth, it promotes heat dissipation and reduces the rapid burst of active oxygen in the chloroplast caused by excess energy. In summary, green light can significantly optimize the photosynthetic characteristics of ginger.

Estimating leaf area index of maize using UAV-based digital imagery and machine learning methods

Leaf area index (LAI) is a fundamental indicator of crop growth status, timely and non-destructive estimation of LAI is of significant importance for precision agriculture. In this study, a multi-rotor UAV platform equipped with CMOS image sensors was used to capture maize canopy information, simultaneously, a total of 264 ground‐measured LAI data were collected during a 2-year field experiment. Linear regression (LR), backpropagation neural network (BPNN), and random forest (RF) algorithms were used to establish LAI estimation models, and their performances were evaluated through 500 repetitions of random sub-sampling, training, and testing. The results showed that RGB-based VIs derived from UAV digital images were strongly related to LAI, and the grain-filling stage (GS) of maize was identified as the optimal period for LAI estimation. The RF model performed best at both whole period and individual growth stages, with the highest R2 (0.71–0.88) and the lowest RMSE (0.12–0.25) on test datasets, followed by the BPNN model and LR models. In addition, a smaller 5–95% interval range of R2 and RMSE was observed in the RF model, which indicated that the RF model has good generalization ability and is able to produce reliable estimation results.

Explaining pre-emptive acclimation by linking information to plant phenotype

We review mechanisms for pre-emptive acclimation in plants and propose a conceptual model linking developmental and evolutionary ecology with the acquisition of information through sensing of cues and signals. The idea is that plants acquire much of the information in the environment not from individual cues and signals but instead from their joint multivariate properties such as correlations. If molecular signalling has evolved to extract such information, the joint multivariate properties of the environment must be encoded in the genome, epigenome, and phenome. We contend that multivariate complexity explains why extrapolating from experiments done in artificial contexts into natural or agricultural systems almost never works for characters under complex environmental regulation: biased relationships among the state variables in both time and space create a mismatch between the evolutionary history reflected in the genotype and the artificial growing conditions in which the phenotype is expressed. Our model can generate testable hypotheses bridging levels of organization. We describe the model and its theoretical bases, and discuss its implications. We illustrate the hypotheses that can be derived from the model in two cases of pre-emptive acclimation based on correlations in the environment: the shade avoidance response and acclimation to drought.

Sunflecks in the upper canopy: dynamics of light-use efficiency in sun and shade leaves of Fagus sylvatica

Sunflecks are transient patches of direct radiation that provide a substantial proportion of the daily irradiance to leaves in the lower canopy. In this position, faster photosynthetic induction would allow for higher sunfleck-use efficiency, as is commonly reported in the literature. Yet, when sunflecks are too few and far between, it may be more beneficial for shade leaves to prioritize efficient photosynthesis under shade. We investigated the temporal dynamics of photosynthetic induction, recovery under shade, and stomatal movement during a sunfleck, in sun and shade leaves of Fagus sylvatica from three provenances of contrasting origin. We found that shade leaves complete full induction in a shorter time than sun leaves, but that sun leaves respond faster than shade leaves due to their much larger amplitude of induction. The core-range provenance achieved faster stomatal opening in shade leaves, which may allow for better sunfleck-use efficiency in denser canopies and lower canopy positions. Our findings represent a paradigm shift for future research into light fluctuations in canopies, drawing attention to the ubiquitous importance of sunflecks for photosynthesis, not only in lower-canopy leaves where shade is prevalent, but particularly in the upper canopy where longer sunflecks are more common due to canopy openness.

Performance comparison of RGB and multispectral vegetation indices based on machine learning for estimating Hopea hainanensis SPAD values under different shade conditions

Reasonable cultivation is an important part of the protection work of endangered species. The timely and nondestructive monitoring of chlorophyll can provide a basis for the accurate management and intelligent development of cultivation. The image analysis method has been applied in the nutrient estimation of many economic crops, but information on endangered tree species is seldom reported. Moreover, shade control, as the common seedling management measure, has a significant impact on chlorophyll, but shade levels are rarely discussed in chlorophyll estimation and are used as variables to improve model accuracy. In this study, 2-year-old seedlings of tropical and endangered Hopea hainanensis were taken as the research object, and the SPAD value was used to represent the relative chlorophyll content. Based on the performance comparison of RGB and multispectral (MS) images using different algorithms, a low-cost SPAD estimation method combined with a machine learning algorithm that is adaptable to different shade conditions was proposed. The SPAD values changed significantly at different shade levels (p < 0.01), and 50% shade in the orthographic direction was conducive to chlorophyll accumulation in seedling leaves. The coefficient of determination (R ²), root mean square error (RMSE), and average absolute percent error (MAPE) were used as indicators, and the models with dummy variables or random effects of shade greatly improved the goodness of fit, allowing better adaption to monitoring under different shade conditions. Most of the RGB and MS vegetation indices (VIs) were significantly correlated with the SPAD values, but some VIs exhibited multicollinearity (variance inflation factor (VIF) > 10). Among RGB VIs, RGRI had the strongest correlation, but multiple VIs filtered by the Lasso algorithm had a stronger ability to interpret the SPAD data, and there was no multicollinearity (VIF < 10). A comparison of the use of multiple VIs to estimate SPAD indicated that Random forest (RF) had the highest fitting ability, followed by Support vector regression (SVR), linear mixed effect model (LMM), and ordinary least squares regression (OLR). In addition, the performance of MS VIs was superior to that of RGB VIs. The R ² of the optimal model reached 0.9389 for the modeling samples and 0.8013 for the test samples. These findings reinforce the effectiveness of using VIs to estimate the SPAD value of H. hainanensis under different shade conditions based on machine learning and provide a reference for the selection of image data sources.

Photoreceptors’ gene expression of Arabidopsis thaliana grown with biophilic LED-sourced lighting systems

Using specific photoreceptors, plants can sense light signals fundamental to their growth and development under changing light conditions. Phytochromes sense red and far-red light, cryptochromes and phototropins sense UV-A and blue light, while the UVR8 gene senses UV-B signals. The study of the molecular mechanisms used by plants to respond to artificial biophilic lighting is of pivotal importance for the implementation of biophilic approaches in indoor environments. CoeLux® is a new lighting system that reproduces the effect of natural sunlight entering through an opening in the ceiling, with a realistic sun perceived at an infinite distance surrounded by a clear blue sky. We used the model plant Arabidopsis thaliana to assess the gene expression of the main plant photoreceptors at different light intensities and at different times after exposure to the CoeLux® light type, using high-pressure sodium (HPS) lamps as control light type. Genes belonging to different families of photoreceptors showed a similar expression pattern, suggesting the existence of a common upstream regulation of mRNA transcription. In particular, PHYA, PHYC, PHYD, CRY1, CRY2, PHOT1, and UVR8, showed a common expression pattern with marked differences between the two light types applied; under the HPS light type, the expression levels are raising with the decrease of light intensity, while under the CoeLux® light type, the expression levels remain nearly constant at a high fold. Moreover, we showed that under biophilic illumination the light spectrum plays a crucial role in the response of plants to light intensity, both at the molecular and morphological levels.

Phenolic Compounds Content Evaluation of Lettuce Grown under Short-Term Preharvest Daytime or Nighttime Supplemental LEDs

The study aimed to determine the changes in phenolic compounds content in lettuce (Lactuca sativa L. cv. Little Gem) depending on the preharvest short-term daytime or nighttime supplemental light-emitting diodes (LEDs) to high-pressure sodium lamps (HPS) lighting in a greenhouse during autumn and spring cultivation. Plants were grown in a greenhouse under HPS supplemented with 400 nm, 455 nm, 530 nm, 455 + 530 nm or 660 nm LEDs light for 4 h five days before harvest. Two experiments (EXP) were performed: EXP1—HPS, and LEDs treatment during daytime 6 PM–10 PM, and EXP2—LEDs treatment at nighttime during 10 AM–2 PM. LEDs’ photosynthetic photon flux density (PPFD) was 50 and HPS—90 ± 10 µmol m⁻² s⁻¹. The most pronounced positive effect on total phenolic compounds revealed supplemental 400 and 455 + 530 nm LEDs lighting, except its application during the daytime at spring cultivation, when all supplemental LEDs light had no impact on phenolics content variation. Supplemental 400 nm LEDs applied in the daytime increased chlorogenic acid during spring and chicoric acid during autumn cultivation. 400 nm LEDs used in nighttime enhanced chlorogenic acid accumulation and rutin during autumn. Chicoric and chlorogenic acid significantly increased under supplemental 455 + 530 nm LEDs applied at daytime in autumn and used at nighttime—in spring. Supplemental LEDs application in the nighttime resulted in higher phenolic compounds content during spring cultivation and the daytime during autumn cultivation.

Estimation of Aboveground Vegetation Water Storage in Natural Forests in Jiuzhaigou National Nature Reserve of China Using Machine Learning and the Combination of Landsat 8 and Sentinel-2 Data

Aboveground vegetation water storage (AVWS) is a fundamental ecological parameter of terrestrial ecosystems which participates in plant metabolism, nutrient and sugar transport, and maintains the integrity of the hydraulic system of the plant. The Jiuzhaigou National Nature Reserve (JNNR) is located in the Eastern Tibet Plateau and it is very sensitive to climate change. However, a regional estimate of the AVWS based on observations is still lacking in the JNNR and improving the model accuracy in such mountainous areas is challenging. Therefore, in this study, we combined the Landsat 8 and Sentinel-2 data to estimate AVWS using multivariate adaptive regression splines (MARS), random forest (RF) and extreme gradient boosting (XGBoost) with the linkage of 54 field observations in the JNNR. The results showed that AVWS varied among different forest types. The coniferous forests had the highest AVWS (212.29 ± 84.43 Mg ha−1), followed by mixed forests (166.29 ± 72.73 Mg ha−1) and broadleaf forests (142.60 ± 46.36 Mg ha−1). The average AVWS was 171.2 Mg ha−1. Regardless of the modelling approaches, both Sentinel-2 and Landsat 8 successfully estimated AVWS separately. Prediction accuracy of AVWS was improved by combining Landsat 8 and Sentinel-2 images. Among the three machine learning approaches, the XGBoost model performed best with a model efficiency of 0.57 and root mean square error of 48 Mg ha−1. Predicted AVWS using XGBoost showed a strong spatial pattern of across the study area. The total AVWS was 5.24 × 106 Mg with 67.2% coming from conifer forests. The results highlight the potential of improving the accuracy of AVWS estimation by integrating different optical images and using machine learning approaches in mountainous areas.

Modulated Light Dependence of Growth, Flowering, and the Accumulation of Secondary Metabolites in Chilli

Chili is widely used as a food additive and a flavouring and colouring agent and also has great importance in health preservation and therapy due to the abundant presence of many bioactive compounds, such as polyphenols, flavonoids, carotenoids, and capsaicinoids. Most of these secondary metabolites are strong antioxidants. In the present study, the effect of light intensity and spectral composition was studied on the growth, flowering, and yield of chilli together with the accumulation of secondary metabolites in the fruit. Two light intensities (300 and 500 μmol m-2 s-1) were applied in different spectral compositions. A broad white LED spectrum with and without FR application and with blue LED supplement was compared to blue and red LED lightings in different (80/20 and 95/5%) blue/red ratios. High light intensity increased the harvest index (fruit yield vs. biomass production) and reduced the flowering time of the plants. The amount of secondary metabolites in the fruit varied both by light intensity and spectral compositions; phenolic content and the radical scavenging activity were stimulated, whereas capsaicin accumulation was suppressed by blue light. The red colour of the fruit (provided by carotenoids) was inversely correlated with the absolute amount of blue, green, and far-red light. Based on the results, a schematic model was created, representing light-dependent metabolic changes in chilli. The results indicated that the accumulation of secondary metabolites could be modified by the adjustment of light intensity and spectral composition; however, different types of metabolites required different light environments.

Prediction of Field-Scale Wheat Yield Using Machine Learning Method and Multi-Spectral UAV Data

Accurate prediction of food crop yield is of great significance for global food security and regional trade stability. Since remote sensing data collected from unmanned aerial vehicle (UAV) platforms have the features of flexibility and high resolution, these data can be used as samples to develop regional regression models for accurate prediction of crop yield at a field scale. The primary objective of this study was to construct regional prediction models for winter wheat yield based on multi-spectral UAV data and machine learning methods. Six machine learning methods including Gaussian process regression (GPR), support vector machine regression (SVR) and random forest regression (RFR) were used for the construction of the yield prediction models. Ten vegetation indices (VIs) extracted from canopy spectral images of winter wheat acquired from a multi-spectral UAV at five key growth stages in Xuzhou City, Jiangsu Province, China in 2021 were selected as the variables of the models. In addition, in situ measurements of wheat yield were obtained in a destructive sampling manner for prediction algorithm modeling and validation. Prediction results of single growth stages showed that the optimal model was GPR constructed from extremely strong correlated VIs (ESCVIs) at the filling stage (R2 = 0.87, RMSE = 49.22 g/m2, MAE = 42.74 g/m2). The results of multiple stages showed GPR achieved the highest accuracy (R2 = 0.88, RMSE = 49.18 g/m2, MAE = 42.57 g/m2) when the ESCVIs of the flowering and filling stages were used. Larger sampling plots were adopted to verify the accuracy of yield prediction; the results indicated that the GPR model has strong adaptability at different scales. These findings suggest that using machine learning methods and multi-spectral UAV data can accurately predict crop yield at the field scale and deliver a valuable application reference for farm-scale field crop management.

Combining Spectral and Textural Information from UAV RGB Images for Leaf Area Index Monitoring in Kiwifruit Orchard

The use of a fast and accurate unmanned aerial vehicle (UAV) digital camera platform to estimate leaf area index (LAI) of kiwifruit orchard is of great significance for growth, yield estimation, and field management. LAI, as an ideal parameter for estimating vegetation growth, plays a significant role in reflecting crop physiological process and ecosystem function. At present, LAI estimation mainly focuses on winter wheat, corn, soybean, and other food crops; in addition, LAI on forest research is also predominant, but there are few studies on the application of orchards such as kiwifruit. Concerning this study, high-resolution UAV images of three growth stages of kiwifruit orchard were acquired from May to July 2021. The extracted significantly correlated spectral and textural parameters were used to construct univariate and multivariate regression models with LAI measured for corresponding growth stages. The optimal model was selected for LAI estimation and mapping by comparing the stepwise regression (SWR) and random forest regression (RFR). Results showed the model combining texture features was superior to that only based on spectral indices for the prediction accuracy of the modeling set, with the R2 of 0.947 and 0.765, RMSE of 0.048 and 0.102, and nRMSE of 7.99% and 16.81%, respectively. Moreover, the RFR model (R2 = 0.972, RMSE = 0.035, nRMSE = 5.80%) exhibited the best accuracy in estimating LAI, followed by the SWR model (R2 = 0.765, RMSE = 0.102, nRMSE = 16.81%) and univariate linear regression model (R2 = 0.736, RMSE = 0.108, nRMSE = 17.84%). It was concluded that the estimation method based on UAV spectral parameters combined with texture features can provide an effective method for kiwifruit growth process monitoring. It is expected to provide scientific guidance and practical methods for the kiwifruit management in the field for low-cost UAV remote sensing technology to realize large area and high-quality monitoring of kiwifruit growth, thus providing a theoretical basis for kiwifruit growth investigation.

Layering contrasting photoselective filters improves the simulation of foliar shade

BACKGROUND

Neutral density shade cloth is commonly used for simulating foliar shade, in which it reduces light intensity without altering spectral quality. However, foliar shade also alters spectral quality, reducing the ratio of red to far-red (R:FR) light, altering the ratio of blue to green (B:G) light, and reducing ultraviolet light. Unlike shade cloth, photoselective filters can alter spectral quality, but the filters used in previous literature have not simulated foliar shade well. We examined the spectral quality of sunlight under color temperature blue (CTB), plus green (PG), and neutral density (ND) filters from LEE Filters, Rosco e-colour + and Cinegel brands either alone or layered, hypothesizing that the contrasting filter qualities would improve simulations. As a proof-of-concept, we collected spectral data under foliar shade to compare to data collected under photoselective filters.

RESULTS

Under foliar shade reductions in the R:FR ratio ranged from 0.11 to 0.54 (~ 1.18 in full sun), while reductions in the B:G ratio were as low as 0.53 in deep shade, or were as high as 1.11 in moderate shade (~ 0.87 in full sun). Neutral density filters led to near-neutral reductions in photosynthetically active radiation and reduced the R:FR ratio similar to foliar shade. Color temperature blue filters simulated the increased B:G ratio observed under moderate foliar shade, but did not reduce the R:FR ratio low enough. On their own, PG filters did not simulate any type of foliar shade. Different brands of the same filter type also had disparate effects on spectral quality. Layered CTB and ND filters improved the accuracy of moderate foliar shade simulations, and layering CTB, PG, and ND filters led to accurate simulations of deep foliar shade.

CONCLUSIONS

Layering photoselective filters with contrasting effects on the spectral quality of sunlight results in more accurate simulations of foliar shade compared to when these filters are used separately. Layered filters can re-create the spectral motifs of moderate and deep foliar shade; they could be used to simulate shade scenarios found in different cropping systems. Photoselective filters offer numerous advantages over neutral density shade cloth and could be a direct replacement for researchers currently using neutral density shade cloth.

Effects of Green Light on Elongation Do Not Interact with Far-Red, Unless the Phytochrome Photostationary State (PSS) Changes in Tomato

Simple Summary

This paper focuses on the role of phytochromes (phys) in the interaction between green light and far-red light effects on “shade avoidance syndrome”. We grew wild type and phy mutants of tomato under a set of light conditions with different combinations of green, blue, red, and far-red light. Partial (20%) replacement of red/blue by green light in the absence of far-red light hardly affected the tomato plant morphology. However, when the spectrum contained far-red light, partially replacing red/blue by green light resulted in more elongation, which was associated with a lower phytochrome photostationary state (PSS) value. There was no effect of partial substitution of red/blue with green light when the PSS was kept constant. Thus, this study has revealed an interaction between green and far-red light effects on elongation unless PSS was kept constant. Green light was often a bit neglected in photobiology, but now an increasing number of researchers are realizing that green light deserves more attention. This study advances the understanding of light quality and plant growth and finding the optimal spectrum when growing plants under LED lighting in controlled environment agriculture.

Abstract

Green light (G) could trigger a “shade avoidance syndrome” (SAS) similarly to far-red light. We aimed to test the hypothesis that G interacts with far-red light to induce SAS, with this interaction mediated by phytochromes (phys). The tomato (Solanum lycopersicum cv. Moneymaker) wild-type (WT) and phyA, phyB1B2, and phyAB1B2 mutants were grown in a climate room with or without 30 µmol m⁻² s⁻¹ G on red/blue and red/blue/far-red backgrounds, maintaining the same photosynthetically active radiation (400–700 nm) of 150 µmol m⁻² s⁻¹ and red/blue ratio of 3. G hardly affected the dry mass accumulation or leaf area of WT, phyA, and phyB1B2 with or without far-red light. A lower phytochrome photostationary state (PSS) by adding far-red light significantly increased the total dry mass by enhancing the leaf area in WT plants but not in phy mutants. When the background light did not contain far-red light, partially replacing red/blue with G did not significantly affect stem elongation. However, when the background light contained far-red light, partially replacing red/blue with G enhanced elongation only when associated with a decrease in PSS, indicating that G interacts with far-red light on elongation only when the PSS changes.

Green light reduces elongation when partially replacing sole blue light independently from cryptochrome 1a

Although green light is sometimes neglected, it can have several effects on plant growth and development. Green light is probably sensed by cryptochromes (crys), one of the blue light photoreceptor families. The aim of this study is to investigate the possible interaction between green and blue light and the involvement of crys in the green light response of plant photomorphogenesis. We hypothesize that green light effects on morphology only occur when crys are activated by the presence of blue light. Wild-type Moneymaker (MM), cry1a mutant (cry1a), and two CRY2 overexpressing transgenic lines (CRY2-OX3 and CRY2-OX8) of tomato (Solanum lycopersicum) were grown in a climate chamber without or with green light (30 μmol m^-2  s^-1 ) on backgrounds of sole red, sole blue and red/blue mixture, with all treatments having the same photosynthetic photon flux density of 150 μmol m^-2  s^-1 . Green light showed no significant effects on biomass accumulation, nor on leaf characteristics such as leaf area, specific leaf area, and chlorophyll content. However, in all genotypes, green light significantly decreased stem length on a sole blue background, whereas green light hardly affected stem length on sole red and red/blue mixture background. MM, cry1a, and CRY2-OX3/8 plants all exhibited similar responses of stem elongation to green light, indicating that cry1a, and probably cry2, is not involved in this green light effect. We conclude that partially replacing blue light by green light reduces elongation and that this is independent of cry1a.

Study on the Estimation of Forest Volume Based on Multi-Source Data

We performed a comparative analysis of the prediction accuracy of machine learning methods and ordinary Kriging (OK) hybrid methods for forest volume models based on multi-source remote sensing data combined with ground survey data. Taking Larix olgensis, Pinus koraiensis, and Pinus sylvestris plantations in Mengjiagang forest farms as the research object, based on the Chinese Academy of Forestry LiDAR, charge-coupled device, and hyperspectral (CAF-LiTCHy) integrated system, we extracted the visible vegetation index, texture features, terrain factors, and point cloud feature variables, respectively. Random forest (RF), support vector regression (SVR), and an artificial neural network (ANN) were used to estimate forest volume. In the small-scale space, the estimation of sample plot volume is influenced by the surrounding environment as well as the neighboring observed data. Based on the residuals of these three machine learning models, OK interpolation was applied to construct new hybrid forest volume estimation models called random forest Kriging (RFK), support vector machines for regression Kriging (SVRK), and artificial neural network Kriging (ANNK). The six estimation models of forest volume were tested using the leave-one-out (Loo) cross-validation method. The prediction accuracies of these six models are better, with RLoo2 values above 0.6, and the prediction accuracy values of the hybrid models are all improved to different extents. Among the six models, the RFK hybrid model had the best prediction effect, with an RLoo2 reaching 0.915. Therefore, the machine learning method based on multi-source remote sensing factors is useful for forest volume estimation; in particular, the hybrid model constructed by combining machine learning and the OK method greatly improved the accuracy of forest volume estimation, which, thus, provides a fast and effective method for the remote sensing inversion estimation of forest volume and facilitates the management of forest resources.

The Impact of Light Spectrum and Intensity on the Growth, Physiology, and Antioxidant Activity of Lettuce (Lactuca sativa L.)

This study focused on the physiology, growth and antioxidant activity response of hydroponically grown lettuce (Lactuca sativa L.) under sole-source LED lighting of differing spectra. Lighting spectra were provided by differing combinations of LEDs of three different peak wavelengths, (Blue 435, Blue 450, and Red 663 nm) with ratios of B450/R663: 1.25 ± 0.1, B450/R663: 1.25 ± 0.1, and B450/R663 1:1 at two light intensities of photosynthetically active radiation (PAR) (270 μmol m^-2 s^-1 and 60 μmol m^-2 s^-1). A further experiment was conducted, in which Blue and Red LEDs were supplemented with Green (Blue 450, Red 663, and Green 520 nm) with ratios of B435/R663: 1.25 ± 0.1, B450/R663/G520: 1/0.73/0.26, and B450/R663: 1.25 ± 0.1. LED light intensities under the different spectra were adjusted to deliver the same level of PAR (270 ± 20 μmol m^-2 s^-1). Results from the first experiment showed that increased fraction of blue 435 nm in combination with red light at 663 nm at high irradiance enhanced the physiology of lettuce (i.e., significantly increased assimilation rate, stomatal conductance and transpiration rate) and increased the yield while having no significant effect on antioxidant activity. At the lower irradiance, the B435/R663 significantly increased antioxidant activity compared to other spectra. Results from the second experiment showed no significant effect of the spectra of LEDs on the physiology and yield of lettuce, but antioxidant activity was very significantly induced by B450/R663 at the ratio of 1.25 ± 0.1. However, the amount was still less than that obtained by B435/R663 1.25 ± 0.1 from the first experiment. This study indicates that LED light with a spectrum of B435/R663 at a ratio of 1.25 ± 0.1 significantly improves lettuce yield and antioxidant activity.

Impact of Three Different Light Spectra on the Yield, Morphology and Growth Trajectory of Three Different Cannabis sativa L. Strains

Cannabis is one of the oldest cultivated plants, but plant breeding and cultivation are restricted by country specific regulations. Plant growth, morphology and metabolism can be manipulated by changing light quality and intensity. Three morphologically different strains were grown under three different light spectra with three real light repetitions. Light dispersion was included into the statistical evaluation. The light spectra considered had an influence on the morphology of the plant, especially the height. Here, the shade avoidance induced by the lower R:FR ratio under the ceramic metal halide lamp (CHD) was of particular interest. The sugar leaves seemed to be of elementary importance in the last growth phase for yield composition. Furthermore, the last four weeks of flowering were crucial to influence the yield composition of Cannabis sativa L. through light spectra. The dry flower yield was significantly higher under both LED treatments compared to the conventional CHD light source. Our results indicate that the plant morphology can be artificially manipulated by the choice of light treatment to create shorter plants with more lateral branches which seem to be beneficial for yield development. Furthermore, the choice of cultivar has to be taken into account when interpreting results of light studies, as Cannabis sativa L. subspecies and thus bred strains highly differ in their phenotypic characteristics.

Functional convergence of growth responses to shade and warmth in Arabidopsis

Shade and warmth promote the growth of the stem, but the degree of mechanistic convergence and functional association between these responses is not clear. We analysed the quantitative impact of mutations and natural genetic variation on the hypocotyl growth responses of Arabidopsis thaliana to shade and warmth, the relationship between the abundance of PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and growth stimulation by shade or warmth, the effects of both cues on the transcriptome and the consequences of warm temperature on carbon balance. Growth responses to shade and warmth showed strong genetic linkage and similar dependence on PIF4 levels. Temperature increased growth and phototropism even within a range where damage by extreme high temperatures is unlikely to occur in nature. Both cues enhanced the expression of growth-related genes and reduced the expression of photosynthetic genes. However, only warmth enhanced the expression of genes involved in responses to heat. Warm temperatures substantially increased the amount of light required to compensate for the daily carbon dioxide balance. We propose that the main ecological function of hypocotyl growth responses to warmth is to increase the access of shaded photosynthetic organs to light, which implies functional convergence with shade avoidance.

Accumulation of geranylgeranylated chlorophylls in the pigment-protein complexes of Arabidopsis thaliana acclimated to green light: effects on the organization of light-harvesting complex II and photosystem II functions

Light quality significantly influences plant metabolism, growth and development. Recently, we have demonstrated that leaves of barley and other plant species grown under monochromatic green light (500-590 nm) accumulated a large pool of chlorophyll a (Chl a) intermediates with incomplete hydrogenation of their phytyl chains. In this work, we studied accumulation of these geranylgeranylated Chls a and b in pigment-protein complexes (PPCs) of Arabidopsis plants acclimated to green light and their structural-functional consequences on the photosynthetic apparatus. We found that geranylgeranylated Chls are present in all major PPCs, although their presence was more pronounced in light-harvesting complex II (LHCII) and less prominent in supercomplexes of photosystem II (PSII). Accumulation of geranylgeranylated Chls hampered the formation of PSII and PSI super- and megacomplexes in the thylakoid membranes as well as their assembly into chiral macrodomains; it also lowered the temperature stability of the PPCs, especially that of LHCII trimers, which led to their monomerization and an anomaly in the photoprotective mechanism of non-photochemical quenching. Role of geranylgeranylated Chls in adverse effects on photosynthetic apparatus of plants acclimated to green light is discussed.

Green light attenuates blue-light-induced chloroplast avoidance movement in Arabidopsis and Landoltia punctata

PREMISE

Chloroplast movement to the anticlinal walls in excess light, referred to as chloroplast avoidance movement, is one strategy to prevent high light damage. Chloroplast avoidance movement is mediated by the blue-light photoreceptor phototropin. Since some blue-light effects are reversed by green light, we investigated the effect of green wavelengths on chloroplast avoidance.

METHODS

Chloroplast position was visualized via microscopy and by transmission of red light through the leaves of Arabidopsis thaliana and Landoltia punctata (duckweed).

RESULTS

Green light reduced blue-light-induced chloroplast avoidance movement but only when green light was presented simultaneously with blue light. Green light alone had no effect on chloroplast position. An action spectrum for green-light attenuation of chloroplast avoidance in duckweed revealed peaks at 510, 550, and 590 nm. Blue-light-induced chloroplast avoidance movement in three Arabidopsis mutants with reduced nonphotochemical quenching, npq1, npq4, and npq7 was not affected by green light.

CONCLUSIONS

The action spectrum does not conform to any known photoreceptor. The lack of a green-light response in the npq mutants of Arabidopsis suggests a possible role for the xanthophyll cycle or a signal from the chloroplast in control of chloroplast avoidance movement.

Morpho-Physiological Responses of Arabidopsis thaliana L. to the LED-Sourced CoeLux® System

The CoeLux^® lighting system reproduces the true effect of natural sunlight entering through an opening in the ceiling, with a realistic sun perceived at an infinite distance surrounded by a clear blue sky. It has already been demonstrated that this new lighting system generates long-term positive effects on human beings; however, there are no investigations so far concerning the plant responses to CoeLux^® lighting. To fill this gap, the model plant Arabidopsis thaliana L. was grown at four different distances from the light source, corresponding to four different light intensities (120, 70, 30, 20 μmol m⁻² s⁻¹). High-pressure sodium lamps were used as control light. Plant phenology and morpho-physiological traits were monitored to assess for the first time the ability of plants to grow and develop under the light spectrum and intensity of the CoeLux^® system. Plants grown at the lower light intensities showed a delayed life cycle and were significantly smaller than plants grown with more light. Furthermore, plants grown under the CoeLux^® light type showed an additional deficit when compared to control plants. Overall, our results show that both the light spectrum and intensity of the CoeLux^® system had a strong impact on A. thaliana growth performance.

Wavelength-dependent effects of artificial light at night on phytoplankton growth and community structure

Artificial light at night (ALAN) is a disruptive form of pollution, impacting physiological and behavioural processes that may scale up to population and community levels. Evidence from terrestrial habitats show that the severity and type of impact depend on the wavelength and intensity of ALAN; however, research on marine organisms is still limited. Here, we experimentally investigated the effect of different ALAN colours on marine primary producers. We tested the effect of green (525 nm), red (624 nm) and broad-spectrum white LED ALAN, compared to a dark control, on the green microalgae Tetraselmis suesica and a diatom assemblage. We show that green ALAN boosted chlorophyll production and abundance in T. suesica. All ALAN wavelengths affected assemblage biomass and diversity, with red and green ALAN having the strongest effects, leading to higher overall abundance and selective dominance of specific diatom species, some known to cause harmful algal blooms. Our findings show that green and red ALAN should be used with caution as alternative LED colours in coastal areas, where there might be a need to strike a balance between the effects of green and red light on marine primary producers with the benefit they appear to bring to other organisms.

Improving the Predictive Value of Phytochrome Photoequilibrium: Consideration of Spectral Distortion Within a Leaf

The ratio of active phytochrome (Pfr) to total phytochrome (Pr + Pfr), called phytochrome photo-equilibrium (PPE; also called phytochrome photostationary state, PSS) has been used to explain shade avoidance responses in both natural and controlled environments. PPE is commonly estimated using measurements of the spectral photon distribution (SPD) above the canopy and photoconversion coefficients. This approach has effectively predicted morphological responses when only red and far-red (FR) photon fluxes have varied, but controlled environment research often utilizes unique ratios of wavelengths so a more rigorous evaluation of the predictive ability of PPE on morphology is warranted. Estimations of PPE have rarely incorporated the optical effects of spectral distortion within a leaf caused by pigment absorbance and photon scattering. We studied stem elongation rate in the model plant cucumber under diverse spectral backgrounds over a range of one to 45% FR (total photon flux density, 400-750 nm, of 400 μmol m^-2 s^-1) and found that PPE was not predictive when blue and green varied. Preferential absorption of red and blue photons by chlorophyll results in an SPD that is relatively enriched in green and FR at the phytochrome molecule within a cell. This can be described by spectral distortion functions for specific layers of a leaf. Multiplying the photoconversion coefficients by these distortion functions yields photoconversion weighting factors that predict phytochrome conversion at the site of photon perception within leaf tissue. Incorporating spectral distortion improved the predictive value of PPE when phytochrome was assumed to be homogeneously distributed within the whole leaf. In a supporting study, the herbicide norflurazon was used to remove chlorophyll in seedlings. Using distortion functions unique to either green or white cotyledons, we came to the same conclusions as with whole plants in the longer-term study. Leaves of most species have similar spectral absorbance so this approach for predicting PPE should be broadly applicable. We provide a table of the photoconversion weighting factors. Our analysis indicates that the simple, intuitive ratio of FR (700-750 nm) to total photon flux (far-red fraction) is also a reliable predictor of morphological responses like stem length.

Phytochrome B links the environment to transcription

Phytochrome B (phyB) senses the difference between darkness and light, the level of irradiance, the red/far-red ratio, and temperature. Thanks to these sensory capacities, phyB perceives whether plant organs are buried in the soil, exposed to full sunlight, in the presence of nearby vegetation, and/or under risk of heat stress. In some species, phyB perceives seasonal daylength cues. phyB affects the activity of several transcriptional regulators either by direct physical interaction or indirectly by physical interaction with proteins involved in the turnover of transcriptional regulators. Typically, interaction of a protein with phyB has either negative or positive effects on the interaction of the latter with a third party, this being another protein or DNA. Thus, phyB mediates the context-dependent modulation of the transcriptome underlying changes in plant morphology, physiology, and susceptibility to biotic and abiotic stress. phyB operates as a dynamic switch that improves carbon balance, prioritizing light interception and photosynthetic capacity in open places and the projection of the shoot towards light in the soil, under shade and in warm conditions.

Integration of Visible and Thermal Imagery with an Artificial Neural Network Approach for Robust Forecasting of Canopy Water Content in Rice

A total of 120 rice plant samples were scanned by visible and thermal proximal sensing systems under different water stress levels to evaluate the canopy water content (CWC). The oven-drying method was employed for assessing the canopy’s water state. This CWC is of great importance for irrigation management decisions. The proposed framework is to integrate visible and thermal imaging data using an artificial neural network as a valuable promising implement for accurately estimating the water content of the plant. The RGB-based features included 20 color vegetation indices (VI) and 6 gray level co-occurrence matrix-based texture features (GLCMF). The thermal imaging features were two thermal indicators (T), namely normalized relative canopy temperature (NRCT) and the crop water stress index (CWSI), that were deliberated by plant temperatures. These features were applied with a back-propagation neural network (BPNN) for training the samples with minimal loss on a cross-validation set. Model behavior was affected by filtering high-level features and optimizing hyperparameters of the model. The results indicated that feature-based modeling from both visible and thermal images achieved better performance than features from the individual visible or thermal image. The supreme prediction variables were 21 features: 14VI, 5GLCMF, and 2T. The fusion of color–texture–thermal features greatly improved the precision of water content evaluation (99.40%). Its determination coefficient (R2 = 0.983) was the most satisfied with an RMSE of 0.599. Overall, the methodology of this work can support decision makers and water managers to take effective and timely actions and achieve agricultural water sustainability.

Green Light Improves Photosystem Stoichiometry in Cucumber Seedlings (Cucumis sativus) Compared to Monochromatic Red Light

It has been shown that monochromatic red and blue light influence photosynthesis and morphology in cucumber. It is less clear how green light impacts photosynthetic performance or morphology, either alone or in concert with other wavelengths. In this study, cucumber (Cucumis sativus) was grown under monochromatic blue, green, and red light, dichromatic blue-green, red-blue, and red-green light, as well as light containing red, green, and blue wavelengths, with or without supplemental far-red light. Photosynthetic data collected under treatment spectra at light-limiting conditions showed that both red and green light enhance photosynthesis. However, photosynthetic data collected with a 90% red, 10% blue, 1000 µmol photons m^-2 s^-1, saturating light show significantly lower photosynthesis in the green, red, and red-green treatments, indicating a blue light enhancement due to photosystem stoichiometric differences. The red-green and green light treatments show improved photosynthetic capacity relative to red light, indicating partial remediation by green light. Despite a lower quantum efficiency and the lowest ambient photosynthesis levels, the monochromatic blue treatment produced among the tallest, most massive plants with the greatest leaf area and thickest stems.

Unveiling the shade nature of cyanic leaves: A view from the "blue absorbing side" of anthocyanins

Anthocyanins have long been suggested as having great potential in offering photoprotection to plants facing high light irradiance. Nonetheless, their effective ability in protecting the photosynthetic apparatus from supernumerary photons has been questioned by some authors, based upon the inexact belief that anthocyanins almost exclusively absorb green photons, which are poorly absorbed by chlorophylls. Here we focus on the blue light absorbing features of anthocyanins, a neglected issue in anthocyanin research. Anthocyanins effectively absorb blue photons: the absorbance of blue relative to green photons increases from tri- to mono-hydroxy B-ring substituted structures, reaching up to 50% of green photons absorption. We offer a comprehensive picture of the molecular events activated by low blue-light availability, extending our previous analysis in purple and green basil, which we suggest to be responsible for the "shade syndrome" displayed by cyanic leaves. While purple leaves display overexpression of genes promoting chlorophyll biosynthesis and light harvesting, in green leaves it is the genes involved in the stability/repair of photosystems that are largely overexpressed. As a corollary, this adds further support to the view of an effective photoprotective role of anthocyanins. We discuss the profound morpho-anatomical adjustments imposed by the epidermal anthocyanin shield, which reflect adjustments in light harvesting capacity under imposed shade and make complex the analysis of the photosynthetic performance of cyanic versus acyanic leaves.

Light signalling shapes plant-plant interactions in dense canopies

Plants growing at high densities interact via a multitude of pathways. Here, we provide an overview of mechanisms and functional consequences of plant architectural responses initiated by light cues that occur in dense vegetation. We will review the current state of knowledge about shade avoidance, as well as its possible applications. On an individual level, plants perceive neighbour-associated changes in light quality and quantity mainly with phytochromes for red and far-red light and cryptochromes and phototropins for blue light. Downstream of these photoreceptors, elaborate signalling and integration takes place with the PHYTOCHROME INTERACTING FACTORS, several hormones and other regulators. This signalling leads to the shade avoidance responses, consisting of hyponasty, stem and petiole elongation, apical dominance and life cycle adjustments. Architectural changes of the individual plant have consequences for the plant community, affecting canopy structure, species composition and population fitness. In this context, we highlight the ecological, evolutionary and agricultural importance of shade avoidance.

A Robust Vegetation Index Based on Different UAV RGB Images to Estimate SPAD Values of Naked Barley Leaves

Chlorophyll content in plant leaves is an essential indicator of the growth condition and the fertilization management effect of naked barley crops. The soil plant analysis development (SPAD) values strongly correlate with leaf chlorophyll contents. Unmanned Aerial Vehicles (UAV) can provide an efficient way to retrieve SPAD values on a relatively large scale with a high temporal resolution. But the UAV mounted with high-cost multispectral or hyperspectral sensors may be a tremendous economic burden for smallholder farmers. To overcome this shortcoming, we investigated the potential of UAV mounted with a commercial digital camera for estimating the SPAD values of naked barley leaves. We related 21 color-based vegetation indices (VIs) calculated from UAV images acquired from two flight heights (6.0 m and 50.0 m above ground level) in four different growth stages with SPAD values. Our results indicated that vegetation extraction and naked barley ears mask could improve the correlation between image-calculated vegetation indices and SPAD values. The VIs of ‘L*,’ ‘b*,’ ‘G − B’ and ‘2G − R − B’ showed significant correlations with SPAD values of naked barley leaves at both flight heights. The validation of the regression model showed that the index of ‘G-B’ could be regarded as the most robust vegetation index for predicting the SPAD values of naked barley leaves for different images and different flight heights. Our study demonstrated that the UAV mounted with a commercial camera has great potentiality in retrieving SPAD values of naked barley leaves under unstable photography conditions. It is significant for farmers to take advantage of the cheap measurement system to monitor crops.

GmCRY1s modulate gibberellin metabolism to regulate soybean shade avoidance in response to reduced blue light

Soybean is an important legume crop that displays the classic shade avoidance syndrome (SAS), including exaggerated stem elongation, which leads to lodging and yield reduction under density farming conditions. Here, we compared the effects of two shade signals, low red light to far-red light ratio (R:FR) and low blue light (LBL), on soybean status and revealed that LBL predominantly induces excessive stem elongation. We used CRISPR-Cas9-engineered Gmcry mutants to investigate the functions of seven cryptochromes (GmCRYs) in soybean and found that the four GmCRY1s overlap in mediating LBL-induced SAS. Light-activated GmCRY1s increase the abundance of the bZIP transcription factors STF1 and STF2, which directly upregulate the expression of genes encoding GA2 oxidases to deactivate GA1 and repress stem elongation. Notably, GmCRY1b overexpression lines displayed multiple agronomic advantages over the wild-type control under both dense planting and intercropping conditions. Our study demonstrates the integration of GmCRY1-mediated signals with the GA metabolic pathway in the regulation of LBL-induced SAS in soybean. It also provides a promising option for breeding lodging-resistant, high-yield soybean cultivars in the future.

Morphology, Photosynthetic Traits, and Nutritional Quality of Lettuce Plants as Affected by Green Light Substituting Proportion of Blue and Red Light

Green light, as part of the photosynthetically active radiation, has been proven to have high photosynthetic efficiency once absorbed by plant leaves and can regulate plant physiological activities. However, few studies have investigated the appropriate and efficient way of using the green light for plant production. Thus, the objective of this study was to investigate a moderate amount of green light, partially replacing red and blue light, for plant growth and development. In this experiment, four treatments were set up by adjusting the relative amount of green light as 0 (RB), 30 (G30), 60 (G60), and 90 (G90) μmol m^-2 s^-1, respectively, with a total photosynthetic photon flux density of 200 μmol m^-2 s^-1 and a fixed red-to-blue ratio of 4:1. Lettuce (Lactuca sativa cv. 'Tiberius') plant growth and morphology, stomatal characteristics, light absorptance and transmittance, photosynthetic characteristics, and nutritional quality were investigated. The results showed that: (1) shoot dry weight increased by 16.3 and 24.5% and leaf area increased by 11.9 and 16.2% under G30 and G60, respectively, compared with those under RB. Plant stem length increased linearly with increasing green-to-blue light ratio; (2) light transmittance of lettuce leaf under treatments employing green light was higher than that under RB, especially in the green region; (3) stomatal density increased, whereas stomatal aperture area decreased with the increase in the relative amount of green light; and (4) carbohydrate accumulation increased under G60 and G90. Soluble sugar contents under G60 and G90 increased by 39.4 and 19.4%, respectively. Nitrate contents under G30, G60, and G90 decreased by 26.2, 40.3, and 43.4%, respectively. The above results indicated that 15-30% green light replacing red and blue light effectively increased the yield and nutritional quality of lettuce plants.