Time-course analysis system for leaf feeding marks revealed effect of Arabidopsis thaliana trichomes on herbivore insect feeding behavior.

Bioassay with insect herbivore is a common approach to studying plant defense levels. While measuring insect growth rate as a negative indicator of plant defense levels is simple and straightforward, analyzing more detailed feeding behavior parameters of insects, such as feeding rates, leaf area consumed per feeding event, intervals between feeding events, and spatiotemporal patterns of feeding sites on leaves, is more informative. However, such observations are generally time consuming and labor-intensive. Here, we provide a semi-automated system for quantifying feeding behavior parameters of insects feeding on plant leaves. Automated photo scanners record time-course development of feeding marks on leaves. An image analysis pipeline processes the scanned images and extracts leaf area. By analyzing changes in leaf area over time, it detects insect feeding events and calculates the leaf area consumed during each feeding event, providing quantitative parameters of insects feeding behavior. In addition, it visualizes spatio-temporal changes in feeding sites, providing a measure of the complex behavior of insects on leaves. Using this analysis pipeline, we demonstrate that Arabidopsis thaliana trichomes reduce insect feeding rate, but not feeding duration or intervals between feeding events. Our image acquisition system requires only photo a scanner and a laptop computer and does not require any specialized equipment. The analysis software pipeline is provided as an ImageJ macro and R package and is available at no cost. Taken together, our work provides a scalable method for quantitative assessment of insect feeding behavior on leaves, facilitating understanding of plant defense mechanisms.

A Multi-Target Regression Method to Predict Element Concentrations in Tomato Leaves Using Hyperspectral Imaging.

Recent years have seen the development of novel, rapid, and inexpensive techniques for collecting plant data to monitor the nutritional status of crops. These techniques include hyperspectral imaging, which has been widely used in combination with machine learning models to predict element concentrations in plants. When there are multiple elements, the machine learning models are trained with spectral features to predict individual element concentrations; this type of single-target prediction is known as single-target regression. Although this method can achieve reliable accuracy for some elements, there are others that remain less accurate. We aimed to improve the accuracy of element concentration predictions by using a multi-target regression method that sequentially augmented the original input features (hyperspectral imaging) by chaining the predicted element concentration values. To evaluate the multi-target method, the concentrations of 17 elements in tomato leaves were predicted and compared with the single-target regression results. We trained 5 machine learning models with hyperspectral data and predicted element concentration values and found a significant improvement in the prediction accuracy for 10 elements (Mg, P, S, Mn, Fe, Co, Cu, Sr, Mo, and Cd). Furthermore, our multi-target regression method outperformed single-target predictions by increasing the coefficient of determination (R2) for elements such as Mn, Cu, Co, Fe, and Mg by 12.5%, 10.3%, 11%, 10%, and 8.4%, respectively. Hence, our multi-target method can improve the accuracy of predicting 10-element concentrations compared to single-target regression.

Reaction norm for genomic prediction of plant growth: modeling drought stress response in soybean.

KEY MESSAGE: We proposed models to predict the effects of genomic and environmental factors on daily soybean growth and applied them to soybean growth data obtained with unmanned aerial vehicles. Advances in high-throughput phenotyping technology have made it possible to obtain time-series plant growth data in field trials, enabling genotype-by-environment interaction (G × E) modeling of plant growth. Although the reaction norm is an effective method for quantitatively evaluating G × E and has been implemented in genomic prediction models, no reaction norm models have been applied to plant growth data. Here, we propose a novel reaction norm model for plant growth using spline and random forest models, in which daily growth is explained by environmental factors one day prior. The proposed model was applied to soybean canopy area and height to evaluate the influence of drought stress levels. Changes in the canopy area and height of 198 cultivars were measured by remote sensing using unmanned aerial vehicles. Multiple drought stress levels were set as treatments, and their time-series soil moisture was measured. The models were evaluated using three cross-validation schemes. Although accuracy of the proposed models did not surpass that of single-trait genomic prediction, the results suggest that our model can capture G × E, especially the latter growth period for the random forest model. Also, significant variations in the G × E of the canopy height during the early growth period were visualized using the spline model. This result indicates the effectiveness of the proposed models on plant growth data and the possibility of revealing G × E in various growth stages in plant breeding by applying statistical or machine learning models to time-series phenotype data.

Novel lignin-based extracellular barrier in glandular trichome.

Successful biochemical reactions in organisms necessitate compartmentalization of the requisite components. Glandular trichomes (GTs) act as compartments for the synthesis and storage of specialized compounds. These compounds not only are crucial for the survival of plants under biotic and abiotic stresses but also have medical and commercial value for humans. However, the mechanisms underlying compartmentalization remain unclear. Here we identified a novel structure that is indispensable for the establishment of compartments in cucumber GTs. Silica, a specialized compound, is deposited on the GTs and is visible on the surface of the fruit as a white powder, known as bloom. This deposition provides resistance against pathogens and prevents water loss from the fruits1. Using the cucumber bloomless mutant2, we discovered that a lignin-based cell wall structure in GTs, named 'neck strip', achieves compartmentalization by acting as an extracellular barrier crucial for the silica polymerization. This structure is present in the GTs of diverse plant species. Our findings will enhance the understanding of the biosynthesis of unique compounds in trichomes and provide a basis for improving the production of compounds beneficial to humans.

OsbZIP1 regulates phosphorus uptake and nitrogen utilization, contributing to improved yield.

Increasing nutrient uptake and use efficiency in plants can contribute to improved crop yields and reduce the demand for fertilizers in crop production. In this study, we characterized a rice mutant, 88n which showed long roots under low nitrogen (N) or phosphorus (P) conditions. Low expression levels of N transporter genes were observed in 88n root, and total N concentration in 88n shoots were decreased, however, C concentrations and shoot dry weight in 88n were comparable to that in WT. Therefore, 88n showed high nitrogen utilization efficiency (NUtE). mRNA accumulation of Pi transporter genes was higher in 88n roots, and Pi concentration and uptake activity were higher in 88n than in WT. Therefore, 88n also showed high phosphorus uptake efficiency (PUpE). Molecular genetic analysis revealed that the causal gene of 88n phenotypes was OsbZIP1, a monocot-specific ortholog of the A. thaliana bZIP transcription factor HY5. Similar to the hy5 mutant, chlorophyll content in roots was decreased and root angle was shallower in 88n than in WT. Finally, we tested the yield of 88n in paddy fields over 3 years because 88n mutant plants showed higher PUpE and NUtE activity and different root architecture at the seedling stage. 88n showed large panicles and increased panicle weight/plant. Taken together, a mutation in OsbZIP1 could contribute to improved crop yields.

Transcriptome Analysis of Rice Root Tips Reveals Auxin, Gibberellin and Ethylene Signaling Underlying Nutritropism.

Nutritropism is a positive tropism toward nutrients in plant roots. An NH4+ gradient is a nutritropic stimulus in rice (Oryza sativa L.). When rice roots are exposed to an NH4+ gradient generated around nutrient sources, root tips bend toward and coil around the sources. The molecular mechanisms are largely unknown. Here, we analyzed the transcriptomes of the inside and outside of bending root tips exhibiting nutritropism to reveal nutritropic signal transduction. Tissues facing the nutrient sources (inside) and away (outside) were separately collected by laser microdissection. Principal component analysis revealed distinct transcriptome patterns between the two tissues. Annotations of 153 differentially expressed genes implied that auxin, gibberellin and ethylene signaling were activated differentially between the sides of the root tips under nutritropism. Exogenous application of transport and/or biosynthesis inhibitors of these phytohormones largely inhibited the nutritropism. Thus, signaling and de novo biosynthesis of the three phytohormones are necessary for nutritropism. Expression patterns of IAA genes implied that auxins accumulated more in the inside tissues, meaning that ammonium stimulus is transduced to auxin signaling in nutritropism similar to gravity stimulus in gravitropism. SAUR and expansin genes, which are known to control cell wall modification and to promote cell elongation in shoot gravitropism, were highly expressed in the inside tissues rather than the outside tissues, and our transcriptome data are unexplainable for differential elongation in root nutritropism.

IMA peptides regulate root nodulation and nitrogen homeostasis by providing iron according to internal nitrogen status.

Legumes control root nodule symbiosis (RNS) in response to environmental nitrogen availability. Despite the recent understanding of the molecular basis of external nitrate-mediated control of RNS, it remains mostly elusive how plants regulate physiological processes depending on internal nitrogen status. In addition, iron (Fe) acts as an essential element that enables symbiotic nitrogen fixation; however, the mechanism of Fe accumulation in nodules is poorly understood. Here, we focus on the transcriptome in response to internal nitrogen status during RNS in Lotus japonicus and identify that IRON MAN (IMA) peptide genes are expressed during symbiotic nitrogen fixation. We show that LjIMA1 and LjIMA2 expressed in the shoot and root play systemic and local roles in concentrating internal Fe to the nodule. Furthermore, IMA peptides have conserved roles in regulating nitrogen homeostasis by adjusting nitrogen-Fe balance in L. japonicus and Arabidopsis thaliana. These findings indicate that IMA-mediated Fe provision plays an essential role in regulating nitrogen-related physiological processes.

Boric acid intercepts 80S ribosome migration from AUG-stop by stabilizing eRF1.

In response to environmental changes, cells flexibly and rapidly alter gene expression through translational controls. In plants, the translation of NIP5;1, a boric acid diffusion facilitator, is downregulated in response to an excess amount of boric acid in the environment through upstream open reading frames (uORFs) that consist of only AUG and stop codons. However, the molecular details of how this minimum uORF controls translation of the downstream main ORF in a boric acid-dependent manner have remained unclear. Here, by combining ribosome profiling, translation complex profile sequencing, structural analysis with cryo-electron microscopy and biochemical assays, we show that the 80S ribosome assembled at AUG-stop migrates into the subsequent RNA segment, followed by downstream translation initiation, and that boric acid impedes this process by the stable confinement of eukaryotic release factor 1 on the 80S ribosome on AUG-stop. Our results provide molecular insight into translation regulation by a minimum and environment-responsive uORF.

UAV-based individual Chinese cabbage weight prediction using multi-temporal data.

The use of unmanned aerial vehicles (UAVs) has facilitated crop canopy monitoring, enabling yield prediction by integrating regression models. However, the application of UAV-based data to individual-level harvest weight prediction is limited by the effectiveness of obtaining individual features. In this study, we propose a method that automatically detects and extracts multitemporal individual plant features derived from UAV-based data to predict harvest weight. We acquired data from an experimental field sown with 1196 Chinese cabbage plants, using two cameras (RGB and multi-spectral) mounted on UAVs. First, we used three RGB orthomosaic images and an object detection algorithm to detect more than 95% of the individual plants. Next, we used feature selection methods and five different multi-temporal resolutions to predict individual plant weights, achieving a coefficient of determination (R2) of 0.86 and a root mean square error (RMSE) of 436 g/plant. Furthermore, we achieved predictions with an R2 greater than 0.72 and an RMSE less than 560 g/plant up to 53 days prior to harvest. These results demonstrate the feasibility of accurately predicting individual Chinese cabbage harvest weight using UAV-based data and the efficacy of utilizing multi-temporal features to predict plant weight more than one month prior to harvest.

Inhibition of NPR1 Leads to Shoot Growth Improvement under Low-Calcium Conditions in Arabidopsis.

Under low-Ca conditions, plants accumulate salicylic acid (SA) and induce SA-responsive genes. However, the relationship between SA and low-Ca tolerance remains unclear. Here, we demonstrated that the inhibition or suppression of nonexpressor of pathogenesis-related 1 (NPR1) activity, a major regulator of the SA signaling pathway in the defense response, improves shoot growth under low-Ca conditions. Furthermore, mutations in phytoalexin-deficient 4 (PAD4) or enhanced disease susceptibility 1 (EDS1), which are upstream regulators of NPR1, improved shoot growth under low-Ca conditions, suggesting that NPR1 suppressed growth under low-Ca conditions. In contrast, growth of SA induction-deficient 2-2 (sid2-2), which is an SA-deficient mutant, was sensitive to low Ca levels, suggesting that SA accumulation by SID2 was not related to growth inhibition under low-Ca conditions. Additionally, npr1-1 showed low-Ca tolerance, and the application of tenoxicam-an inhibitor of the NPR1-mediated activation of gene expression-also improved shoot growth under low Ca conditions. The low-Ca tolerance of double mutants pad4-1, npr1-1 and eds1-22 npr1-1 was similar to that of the single mutants, suggesting that PAD4 and EDS1 are involved in the same genetic pathway in suppressing growth under low-Ca conditions as NPR1. Cell death and low-Ca tolerance did not correlate among the mutants, suggesting that growth improvement in the mutants was not due to cell death inhibition. In conclusion, we revealed that NPR1 suppresses plant growth under low-Ca conditions and that the other SA-related genes influence plant growth and cell death.

Early differentiation of Casparian strip mediated by nitric oxide is required for efficient K transport under low K conditions in Arabidopsis.

The Casparian strip (CS) is a cell wall modification made of lignin that functions as an apoplastic barrier in the root endodermis to restrict nutrient and water transport between the soil and stele. CS formation is affected by nutritional conditions, and its physiological roles have been discussed. This study found that low K condition affects CS permeability, lignin deposition, and MYB36 mRNA accumulation. To understand the mechanism underlying these findings, we focused on nitric oxide (NO). NO is known to act as a signaling molecule and participates in cell wall synthesis, especially for lignin composition. However, the mechanism by which NO affects lignin deposition and corrects CS formation in the plant roots remains unclear. Through combining fluorescent observation with histological stains, we demonstrated that the root endodermal cell lignification response to low-potassium (K) conditions is mediated by NO through the MYB36-associated lignin-polymerizing pathway. Furthermore, we discovered the noteworthy ability of NO to maintain nutrient homeostasis for adaptation to low K conditions by affecting the correct apoplastic barrier formation of CS. Collectively, our results suggest that NO is required for the lignification and apoplastic barrier formation in the root endodermis during adaptation to low K conditions, which revealing the novel physiological roles of CS under low nutrient conditions and making a significant contribution to CS biology.

Role of Potassium-Dependent Alternative Splicing of MYB59 in the Maintenance of Potassium Concentration in Shoots of Arabidopsis thaliana.

Potassium (K) is a major plant nutrient. K+ is taken up by channel and transporter proteins in roots and translocated from roots to shoots via the xylem. In Arabidopsis thaliana, the K+ transporter NPF7.3 mediates K+ loading into the xylem and the transcription factor MYB59 is responsible for NPF7.3 expression. Here, we demonstrate that MYB59 is regulated by alternative splicing in response to K availability. Three splicing isoforms of MYB59 are detected in roots: an isoform with the first intron spliced out encodes a protein with the full DNA-binding motif (MYB59α), and two isoforms with the first intron retained partially or completely encode a protein missing part of the DNA-binding motif (MYB59ß). Functional analysis showed that only MYB59α is capable of inducing the expression of NPF7.3. The abundance of the MYB59α isoform increased under low K, but the total abundance of MYB59 transcripts did not change, indicating that MYB59α is increased by modification of the splicing pattern in response to low K. Although MYB59α is increased by low K, NPF7.3 expression remained constant independent of K. In addition, there was no significant difference in NPF7.3 expression between an MYB59 knockout mutant and the wild type under normal K. These results suggest that an unknown mechanism is involved in NPF7.3 expression under normal K and switches roles with MYB59 under low K. We propose that the regulation of MYB59 by alternative splicing is required for the maintenance of shoot K concentration in adaptation to low K.

Arabidopsis thaliana RPL13aC affects root system architecture through shoot potassium accumulation.

Plant root system architecture shows complex patterns adapting to different nutritional conditions. In Arabidopsis thaliana, root slanting is a behaviour that is observed when plants are grown on a solid agar plate vertically. However, the regulatory mechanisms of root slanting in response to nutrient conditions are not fully understood. In this study, we found that mutants of A. thaliana ribosome protein RPL13aC, which is expressed in root tips and leaves, exhibit a decreased root-slanting phenotype. Ionomic analysis revealed that rpl13ac mutants have a reduced K content in shoots but not in roots. Because K+ availability has been suggested to affect root coiling, we hypothesized that the decreased root slanting of rpl13ac mutants is caused by the decrease in K content in their shoots. Decapitating shoots or limiting K supply dramatically decreased root slanting in wild-type (WT) plants. We found that the expression of HIGH-AFFINITY K+ TRANSPORTER 5 (HAK5) significantly decreased in the roots of rpl13ac mutants. Mutants of hak5 showed decreased shoot K contents and decreased root slanting, supporting that the decreased shoot K+ accumulation results in less root slanting. K+ replenishment to the shoots of rpl13ac, hak5 mutants and K-starved WT plants recovered their root slanting significantly. These results indicate that plants adjust root slanting in response to K+ accumulation in shoots. Further analysis showed that rpl13ac mutants have abnormal thigmotropic responses, which may be responsible for their defects in root slanting. Altogether, these results revealed K+ -dependent mechanisms that affect root system architecture.

M2 plants derived from different tillers of a chemically mutagenized rice M1 plant carry independent sets of mutations.

Generation of mutant populations with high genetic diversity is key for mutant screening and crop breeding. For this purpose, the single-seed descent method, in which one mutant line is established from a single mutagenized seed, is commonly used. This method ensures the independence of the mutant lines, but the size of the mutant population is limited because it is no greater than the number of fertile M1 plants. The rice mutant population size can be increased if a single mutagenized plant produces genetically independent siblings. Here, we used whole-genome resequencing to examine the inheritance of mutations from a single ethyl methanesulfonate (EMS)-mutagenized seed (M1 ) of Oryza sativa in its progeny (M2 ). We selected five tillers from each of three M1 plants. A single M2 seed was selected from each tiller, and the distributions of mutations induced by EMS were compared. Surprisingly, in most pairwise combinations of M2 siblings from the same parent, ≥85.2-97.9% of all mutations detected were not shared between the siblings. This high percentage suggests that the M2 siblings were derived from different cells of the M1 embryo and indicates that several genetically independent lines can be obtained from a single M1 plant. This approach should allow a large reduction in the number of M0 seeds needed to obtain a mutant population of a certain size in rice. Our study also suggests that multiple tillers of a rice plant originate from different cells of the embryo.

Random regression for modeling soybean plant response to irrigation changes using time-series multispectral data.

Plant response to drought is an important yield-related trait under abiotic stress, but the method for measuring and modeling plant responses in a time series has not been fully established. The objective of this study was to develop a method to measure and model plant response to irrigation changes using time-series multispectral (MS) data. We evaluated 178 soybean (Glycine max (L.) Merr.) accessions under three irrigation treatments at the Arid Land Research Center, Tottori University, Japan in 2019, 2020 and 2021. The irrigation treatments included W5: watering for 5 d followed by no watering 5 d, W10: watering for 10 d followed by no watering 10 d, D10: no watering for 10 d followed by watering 10 d, and D: no watering. To capture the plant responses to irrigation changes, time-series MS data were collected by unmanned aerial vehicle during the irrigation/non-irrigation switch of each irrigation treatment. We built a random regression model (RRM) for each of combination of treatment by year using the time-series MS data. To test the accuracy of the information captured by RRM, we evaluated the coefficient of variation (CV) of fresh shoot weight of all accessions under a total of nine different drought conditions as an indicator of plant's stability under drought stresses. We built a genomic prediction model (MTRRM model) using the genetic random regression coefficients of RRM as secondary traits and evaluated the accuracy of each model for predicting CV. In 2020 and 2021,the mean prediction accuracies of MTRRM models built in the changing irrigation treatments (r = 0.44 and 0.49, respectively) were higher than that in the continuous drought treatment (r = 0.34 and 0.44, respectively) in the same year. When the CV was predicted using the MTRRM model across 2020 and 2021 in the changing irrigation treatment, the mean prediction accuracy (r = 0.46) was 42% higher than that of the simple genomic prediction model (r =0.32). The results suggest that this RRM method using the time-series MS data can effectively capture the genetic variation of plant response to drought.

NAC103 mutation alleviates DNA damage in an Arabidopsis thaliana mutant sensitive to excess boron.

Excess boron (B) is toxic to plants and thereby causes DNA damage and cell death in root meristems. However, the underlying mechanisms which link boron and DNA damage remain unclear. It has been reported that the rpt5a-6 mutant of the 26S proteasome is sensitive to excess boron, resulting in more frequent cell death in root meristem and reduced root elongation. In this study, we showed that a reduction in root growth in the rpt5a mutant in the presence of high boron levels is repressed by a mutation in NAC domain containing transcription factor NAC103, a substrate of the proteasome, which functions in the unfolded protein response pathway. The mutation in NAC103 alleviated excess-B-induced DNA damage and cell death in root meristems of the rpt5a mutant. Superoxide ( O 2 - ) staining with nitroblue tetrazolium revealed that boron stress causes O 2 - accumulation in root tips, which was higher in the rpt5a-6 mutant, whereas the accumulation was lower in the rpt5a-6 nac103-3 double mutant. Our work demonstrates the overall involvement of NAC103 in maintaining healthy root meristem under excess boron conditions in the absence of RPT5A proteasome subunit.

Boric acid transport activity of marine teleost aquaporins expressed in Xenopus oocytes.

Marine teleosts ingest large amounts of seawater containing various ions, including 0.4 mM boric acid, which can accumulate at toxic levels in the body. However, the molecular mechanisms by which marine teleosts absorb and excrete boric acid are not well understood. Aquaporins (Aqps) are homologous to the nodulin-like intrinsic protein (NIP) family of plant boric acid channels. To investigate the potential roles of Aqps on boric acid transport across the plasma membrane in marine teleosts, we analyzed the function of Aqps of Japanese pufferfish (Takifugu rubripes) expressed in Xenopus laevis oocytes. Takifugu genome database contains 16 genes encoding the aquaporin family members (aqp0a, aqp0b, aqp1aa, aqp1ab, aqp3a, aqp4a, aqp7, aqp8bb, aqp9a, aqp9b, aqp10aa, aqp10bb, aqp11a, aqp11b, aqp12, and aqp14). When T. rubripes Aqps (TrAqps) were expressed in X. laevis oocytes, a swelling assay showed that boric acid permeability was significantly increased in oocytes expressing TrAqp3a, 7, 8bb, 9a, and 9b. The influx of boric acid into these oocytes was also confirmed by elemental quantification. Electrophysiological analysis using a pH microelectrode showed that these TrAqps increase B(OH)3 permeability. These results indicate that TrAqp3a, 7, 8bb, 9a, and 9b act as boric acid transport systems, likely as channels, in marine teleosts.

Seawater fish use an electrogenic boric acid transporter, Slc4a11A, for boric acid excretion by the kidney.

Boric acid is a vital micronutrient in animals; however, excess amounts are toxic to them. Little is known about whole-body boric acid homeostasis in animals. Seawater (SW) contains 0.4 mM boric acid, and since marine fish drink SW, their urinary system was used here as a model of the boric acid excretion system. We determined that the bladder urine of a euryhaline pufferfish (river pufferfish, Takifugu obscurus) acclimated to fresh water and SW contained 0.020 and 19 mM of boric acid, respectively (a 950-fold difference), indicating the presence of a powerful excretory renal system for boric acid. Slc4a11 is a potential animal homolog of the plant boron transporter BOR1; however, mammalian Slc4a11 mediates H+ (OH-) conductance but does not transport boric acid. We found that renal expression of the pufferfish paralog of Slc4a11, Slc4a11A, was markedly induced after transfer from fresh water to SW, and Slc4a11A was localized to the apical membrane of kidney tubules. When pufferfish Slc4a11A was expressed in Xenopus oocytes, exposure to media containing boric acid and a voltage clamp elicited whole-cell outward currents, a marked increase in pHi, and increased boron content. In addition, the activity of Slc4a11A was independent of extracellular Na+. These results indicate that pufferfish Slc4a11A is an electrogenic boric acid transporter that functions as a B(OH)4- uniporter, B(OH)3-OH- cotransporter, or B(OH)3/H+ exchanger. These observations suggest that Slc4a11A is involved in the kidney tubular secretion of boric acid in SW fish, probably induced by the negative membrane potential and low pH of urine.

Role of GSL8 in low calcium tolerance in Arabidopsis thaliana.

Calcium (Ca) deficiency affects the yields and quality of agricultural products. Susceptibility to Ca deficiency varies among crops and cultivars; however, its genetic basis remains largely unknown. Genes required for low Ca tolerance in Arabidopsis thaliana have been identified. In this study, we identified a novel gene required for low Ca tolerance in A. thaliana. We isolated a mutant sensitive to low Ca concentrations and identified Glucan synthase-like (GSL) 8 as a gene responsible for low Ca tolerance. GSL8 is a paralog of the previously identified low Ca tolerance gene GSL10, which encodes ß-1,3 glucan(callose) synthase. Under low Ca conditions, the shoot growth of gsl8 mutants were inhibited compared to wild-type plants. A grafting experiment indicated that the shoot, but not root, genotype was important for the shoot growth phenotype. The ectopic accumulation of callose under low Ca conditions was reduced in gsl8 mutants. We further investigated the interaction between GSL8 and GSL10 by testing the gsl8 gsl10 double mutant for sensitivity to low Ca concentrations. The double mutant exhibited a more severe phenotype than the single mutant under 0.3 mM Ca, indicating additive effects of GSL8 and GSL10 with respect to low Ca tolerance. These results establish that GSL genes are required for low Ca tolerance in A. thaliana.

Time-series multispectral imaging in soybean for improving biomass and genomic prediction accuracy.

Multispectral (MS) imaging enables the measurement of characteristics important for increasing the prediction accuracy of genotypic and phenotypic values for yield-related traits. In this study, we evaluated the potential application of temporal MS imaging for the prediction of aboveground biomass (AGB) in soybean [Glycine max (L.) Merr.]. Field experiments with 198 accessions of soybean were conducted with four different irrigation levels. Five vegetation indices (VIs) were calculated using MS images from soybean canopies from early vegetative to early reproductive stage. To predict the genotypic values of AGB, VIs at the different growth stages were used as secondary traits in a multitrait genomic prediction. The prediction accuracy of the genotypic values of AGB from MS and genomic data largely outperformed that of the genomic data alone before the flowering stage (90% of accessions did not flower), suggesting that it would be possible to determine cross-combinations based on the predicted genotypic values of AGB. We compared the prediction accuracy of a model using the five VIs and a model using only one VI to predict the phenotypic values of AGB and found that the difference in prediction accuracy decreased over time at all irrigation levels except for the most severe drought. The difference in the most severe drought was not as small as that in the other treatments. Only the prediction accuracy of a model using the five VIs in the most severe droughts gradually increased over time. Therefore, the optimal timing for MS imaging may depend on the irrigation levels.