Root Cortical Senescence Enhances Drought Tolerance in Cotton.

The root cortical senescence (RCS) is closely associated with root absorptive function. However, characteristics and responses of RCS to drought stress in cotton have received little attention. This study subjected the drought-tolerant variety 'Guoxin 02' and the drought-sensitive variety 'Ji 228' to drought stress (8% PEG6000) and no-stress (0% PEG6000) treatments to determine the characteristics and responses of cotton RCS to drought stress. The results showed that the greater the distance from the root tip, the more severe the RCS occurrence under drought stress compared with non-stress treatment. The occurrence of RCS in 'Guoxin 02' increased by 14.03%-20.18% compared to 'Ji 228' under drought stress. The RCS was negatively correlated with root respiration but positively correlated with root length and leaf water potential. The silencing of RCS-related genes (GhSAG12 and GhbHLH121) can mitigate the drought-induced RCS phenomenon in cotton; however, reduced drought tolerance. Exogenous abscisic acid (ABA) treatment can promote RCS generation. Conversely, ABA synthesis exhibits contrasting effects. In summary, endogenous hormones regulated RCS, which reduced the root metabolic and seemingly achieved more resource redistribution to new roots, thereby fully utilize deep water resources. Thus, the study demonstrates the potential of RCS in improving the drought stress tolerance of cotton.

Melatonin mitigates cadmium toxicity by promoting root development, delaying root senescence, and regulating cadmium transport in cotton.

Cd ions are absorbed and transported from the soil by crop roots, which are the first organ to be exposed to Cd. This results in an increase in cadmium ions in crops, significantly affecting crop growth and yield. Exogenous melatonin (MT) can help reduce cadmium (Cd) stress in cotton, but the specific contribution of roots to this process remains unclear. In order to address this knowledge gap, an in-situ root phenotyping study was conducted to investigate the the phenotype and lifespan of roots under cadmium stress (Cd) and melatonin treatment (Cd + MT). The results showed that MT alleviated the decreases in plant height, leaf area, SPAD value, stem diameter, stomatal conductance and net photosynthetic rate under Cd stress, which further promoted the biomass accumulation in various cotton organs. What is more, the Cd + MT treatment increased root volume, surface area, and length under Cd stress by 25.63 %, 10.58 %, and 21.89 %, respectively, compared with Cd treatment. Interestingly, compared to Cd treatment, Cd + MT treatment also significantly extended the lifespan of roots and root hairs by 6.68 days and 2.18 days, respectively. In addition, Cd + MT treatment reduced the transport of Cd from roots to shoots, particularly to bolls, and decreased the Cd bioconcentration factor in bolls by 61.17 %, compared to Cd treatment. In conclusion, these findings show that applying MT externally helps reduce Cd stress by delaying root senescence, promoting root development and regulating Cd transport. This method can be an effective approach to managing Cd stress in cotton.

In Situ Root Dataset Expansion Strategy Based on an Improved CycleGAN Generator.

The root system plays a vital role in plants' ability to absorb water and nutrients. In situ root research offers an intuitive approach to exploring root phenotypes and their dynamics. Deep-learning-based root segmentation methods have gained popularity, but they require large labeled datasets for training. This paper presents an expansion method for in situ root datasets using an improved CycleGAN generator. In addition, spatial-coordinate-based target background separation method is proposed, which solves the issue of background pixel variations caused by generator errors. Compared to traditional threshold segmentation methods, this approach demonstrates superior speed, accuracy, and stability. Moreover, through time-division soil image acquisition, diverse culture medium can be replaced in in situ root images, thereby enhancing dataset versatility. After validating the performance of the Improved_UNet network on the augmented dataset, the optimal results show a 0.63% increase in mean intersection over union, 0.41% in F1, and 0.04% in accuracy. In terms of generalization performance, the optimal results show a 33.6% increase in mean intersection over union, 28.11% in F1, and 2.62% in accuracy. The experimental results confirm the feasibility and practicality of the proposed dataset augmentation strategy. In the future, we plan to combine normal mapping with rendering software to achieve more accurate shading simulations of in situ roots. In addition, we aim to create a broader range of images that encompass various crop varieties and soil types.

Improved Transformer for Time Series Senescence Root Recognition.

The root is an important organ for plants to obtain nutrients and water, and its phenotypic characteristics are closely related to its functions. Deep-learning-based high-throughput in situ root senescence feature extraction has not yet been published. In light of this, this paper suggests a technique based on the transformer neural network for retrieving cotton's in situ root senescence properties. High-resolution in situ root pictures with various levels of senescence are the main subject of the investigation. By comparing the semantic segmentation of the root system by general convolutional neural networks and transformer neural networks, SegFormer-UN (large) achieves the optimal evaluation metrics with mIoU, mRecall, mPrecision, and mF1 metric values of 81.52%, 86.87%, 90.98%, and 88.81%, respectively. The segmentation results indicate more accurate predictions at the connections of root systems in the segmented images. In contrast to 2 algorithms for cotton root senescence extraction based on deep learning and image processing, the in situ root senescence recognition algorithm using the SegFormer-UN model has a parameter count of 5.81 million and operates at a fast speed, approximately 4 min per image. It can accurately identify senescence roots in the image. We propose that the SegFormer-UN model can rapidly and nondestructively identify senescence root in in situ root images, providing important methodological support for efficient crop senescence research.

The crucial role of lateral root angle in enhancing drought resilience in cotton.

Introduction: Plant responses to drought stress are influenced by various factors, including the lateral root angle (LRA), stomatal regulation, canopy temperature, transpiration rate and yield. However, there is a lack of research that quantifies their interactions, especially among different cotton varieties. Methods: This experiment included two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content) starting from the three-leaf growth stage. Results: The results revealed that different LRA varieties show genetic variation under drought stress. Among them, varieties with smaller root angles show greater drought tolerance. Varieties with smaller LRAs had significantly increased stomatal opening by 15% to 43%, transpiration rate by 61.24% and 62.00%, aboveground biomass by 54% to 64%, and increased seed cotton yield by 76% to 79%, and decreased canopy temperature by 9% to 12% under drought stress compared to the larger LRAs. Varieties with smaller LRAs had less yield loss under drought stress, which may be due to enhanced access to deeper soil water, compensating for heightened stomatal opening and elevated transpiration rates. The increase in transpiration rate promotes heat dissipation from leaves, thereby reducing leaf temperature and protecting leaves from damage. Discussion: Demonstrating the advantages conferred by the development of a smaller LRA under drought stress conditions holds value in enhancing cotton's resilience and promoting its sustainable adaptation to abiotic stressors.

Evaluation of drought-tolerant varieties based on root system architecture in cotton (Gossypium hirsutum L.).

BACKGROUND: Root system architecture (RSA) exhibits significant genetic variability and is closely associated with drought tolerance. However, the evaluation of drought-tolerant cotton cultivars based on RSA in the field conditions is still underexplored. RESULTS: So, this study conducted a comprehensive analysis of drought tolerance based on physiological and morphological traits (i.e., aboveground and RSA, and yield) within a rain-out shelter, with two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content). The results showed that principal component analysis identified six principal components, including highlighting the importance of root traits and canopy parameters in influencing drought tolerance. Moreover, the systematic cluster analysis was used to classify 80 cultivars into 5 categories, including drought-tolerant cultivars, relatively drought-tolerant cultivars, intermediate cultivars, relatively drought-sensitive cultivars, and drought-sensitive cultivars. Further validation of the drought tolerance index showed that the yield drought tolerance index and biomass drought tolerance index of the drought-tolerant cultivars were 8.97 and 5.05 times higher than those of the drought-sensitive cultivars, respectively. CONCLUSIONS: The RSA of drought-tolerant cultivars was characterised by a significant increase in average length-all lateral roots, a significant decrease in average lateral root emergence angle and a moderate root/shoot ratio. In contrast, the drought-sensitive cultivars showed a significant decrease in average length-all lateral roots and a significant increase in both average lateral root emergence angle and root/shoot ratio. It is therefore more comprehensive and accurate to assess field crop drought tolerance by considering root performance.

Long-term nitrogen fertilizer management for enhancing use efficiency and sustainable cotton (Gossypium hirsutum L.).

Optimal management of nitrogen fertilizer profoundly impacts sustainable development by influencing nitrogen use efficiency (NUE) and seed cotton yield. However, the effect of long-term gradient nitrogen application on the sandy loam soil is unclear. Therefore, we conducted an 8-year field study (2014-2021) using six nitrogen levels: 0 kg/hm2 (N0), 75 kg/hm2 (N1), 150 kg/hm2 (N2), 225 kg/hm2 (N3), 300 kg/hm2 (N4), and 375 kg/hm2 (N5). The experiment showed that 1) Although nitrogen application had insignificantly affected basic soil fertility, the soil total nitrogen (STN) content had decreased by 5.71%-19.67%, 6.67%-16.98%, and 13.64%-21.74% at 0-cm-20-cm, 20-cm-40-cm, and 40-cm-60-cm soil layers, respectively. 2) The reproductive organs of N3 plants showed the highest nitrogen accumulation and dry matter accumulation in both years. Increasing the nitrogen application rate gradually decreased the dry matter allocation ratio to the reproductive organs. 3) The boll number per unit area of N3 was the largest among all treatments in both years. On sandy loam, the most optional nitrogen rate was 190 kg/hm2-270 kg/hm2 for high seed cotton yield with minimal nitrogen loss and reduced soil environment pollution.

Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots.

The root is an important organ for crops to absorb water and nutrients. Complete and accurate acquisition of root phenotype information is important in root phenomics research. The in situ root research method can obtain root images without destroying the roots. In the image, some of the roots are vulnerable to soil shading, which severely fractures the root system and diminishes its structural integrity. The methods of ensuring the integrity of in situ root identification and establishing in situ root image phenotypic restoration remain to be explored. Therefore, based on the in situ root image of cotton, this study proposes a root segmentation and reconstruction strategy, improves the UNet model, and achieves precise segmentation. It also adjusts the weight parameters of EnlightenGAN to achieve complete reconstruction and employs transfer learning to implement enhanced segmentation using the results of the former two. The research results show that the improved UNet model has an accuracy of 99.2%, mIOU of 87.03%, and F1 of 92.63%. The root reconstructed by EnlightenGAN after direct segmentation has an effective reconstruction ratio of 92.46%. This study enables a transition from supervised to unsupervised training of root system reconstruction by designing a combination strategy of segmentation and reconstruction network. It achieves the integrity restoration of in situ root system pictures and offers a fresh approach to studying the phenotypic of in situ root systems, also realizes the restoration of the integrity of the in situ root image, and provides a new method for in situ root phenotype study.

Response of in situ root phenotypes to potassium stress in cotton.

Potassium plays a significant role in the basic functions of plant growth and development. Potassium uptake is closely associated with morphological characteristics of the roots. However, the dynamic characteristics of phenotype and lifespan of cotton (Gossypium hirsutum L.) lateral roots and root hairs under low and high potassium stress remain unclear. In this study, potassium stress experiments (low and high potassium, medium potassium as control) were conducted using RhizoPot (an in situ root observation device) to determine the response characteristics of lateral roots and root hairs in cotton under potassium stress. The plant morphology, photosynthetic characteristics, root phenotypic changes, and lifespan of lateral roots and root hairs were measured. Potassium accumulation, aboveground phenotype, photosynthetic capacity, root length density, root dry weight, root diameter, lateral root lifespan, and root hair lifespan under low potassium stress were significantly decreased compared to medium potassium treatment. However, the root hair length of the former was significantly increased than that of the latter. Potassium accumulation and the lateral root lifespan were significantly increased under high potassium treatment, while root length density, root dry weight, root diameter, root hair length, and root hair lifespan were significantly decreased compared to the medium potassium treatment. Notably, there were no significant differences in aboveground morphology and photosynthetic characters. Principal component analysis revealed that lateral root lifespan, root hair lifespan of the first lateral root, and root hair length significantly correlated with potassium accumulation. The root had similar regularity responses to low and high potassium stress except for lifespan and root hair length. The findings of this study enhance the understanding of the phenotype and lifespan of cotton's lateral roots and root hairs under low and high potassium stress.

Morphological and Physiological Mechanisms of Melatonin on Delaying Drought-Induced Leaf Senescence in Cotton.

Leaf senescence reduces the photosynthetic capacity of leaves, thus significantly affecting the growth, development, and yield formation of cotton. Melatonin (MT) is a multipotent substance proven to delay leaf senescence. However, its potential mechanism in delaying leaf senescence induced by abiotic stress remains unclear. This study aimed to explore the effect of MT on delaying drought-induced leaf senescence in cotton seedlings and to clarify its morphological and physiological mechanisms. Drought stress upregulated the leaf senescence marker genes, destroyed the photosystem, and led to excessive accumulation of reactive oxygen species (ROS, e.g., H2O2 and O2-), thus accelerating leaf senescence. However, leaf senescence was significantly delayed when 100 µM MT was sprayed on the leaves of the cotton seedlings. The delay was embodied by the increased chlorophyll content, photosynthetic capacity, and antioxidant enzyme activities, as well as decreased H2O2, O2-, and abscisic acid (ABA) contents by 34.44%, 37.68%, and 29.32%, respectively. MT significantly down-regulated chlorophyll degradation-related genes and senescence marker genes (GhNAC12 and GhWRKY27/71). In addition, MT reduced the chloroplast damage caused by drought-induced leaf senescence and maintained the integrity of the chloroplast lamellae structure under drought stress. The findings of this study collectively suggest that MT can effectively enhance the antioxidant enzyme system, improve photosynthetic efficiency, reduce chlorophyll degradation and ROS accumulation, and inhibit ABA synthesis, thereby delaying drought-induced leaf senescence in cotton.

A method of cotton root segmentation based on edge devices.

The root is an important organ for plants to absorb water and nutrients. In situ root research method is an intuitive method to explore root phenotype and its change dynamics. At present, in situ root research, roots can be accurately extracted from in situ root images, but there are still problems such as low analysis efficiency, high acquisition cost, and difficult deployment of image acquisition devices outdoors. Therefore, this study designed a precise extraction method of in situ roots based on semantic segmentation model and edge device deployment. It initially proposes two data expansion methods, pixel by pixel and equal proportion, expand 100 original images to 1600 and 53193 respectively. It then presents an improved DeeplabV3+ root segmentation model based on CBAM and ASPP in series is designed, and the segmentation accuracy is 93.01%. The root phenotype parameters were verified through the Rhizo Vision Explorers platform, and the root length error was 0.669%, and the root diameter error was 1.003%. It afterwards designs a time-saving Fast prediction strategy. Compared with the Normal prediction strategy, the time consumption is reduced by 22.71% on GPU and 36.85% in raspberry pie. It ultimately deploys the model to Raspberry Pie, realizing the low-cost and portable root image acquisition and segmentation, which is conducive to outdoor deployment. In addition, the cost accounting is only $247. It takes 8 hours to perform image acquisition and segmentation tasks, and the power consumption is as low as 0.051kWh. In conclusion, the method proposed in this study has good performance in model accuracy, economic cost, energy consumption, etc. This paper realizes low-cost and high-precision segmentation of in-situ root based on edge equipment, which provides new insights for high-throughput field research and application of in-situ root.

Predicting F v /F m and evaluating cotton drought tolerance using hyperspectral and 1D-CNN.

The chlorophyll fluorescence parameter Fv/Fm is significant in abiotic plant stress. Current acquisition methods must deal with the dark adaptation of plants, which cannot achieve rapid, real-time, and high-throughput measurements. However, increased inputs on different genotypes based on hyperspectral model recognition verified its capabilities of handling large and variable samples. Fv/Fm is a drought tolerance index reflecting the best drought tolerant cotton genotype. Therefore, Fv/Fm hyperspectral prediction of different cotton varieties, and drought tolerance evaluation, are worth exploring. In this study, 80 cotton varieties were studied. The hyperspectral cotton data were obtained during the flowering, boll setting, and boll opening stages under normal and drought stress conditions. Next, One-dimensional convolutional neural networks (1D-CNN), Categorical Boosting (CatBoost), Light Gradient Boosting Machines (LightBGM), eXtreme Gradient Boosting (XGBoost), Decision Trees (DT), Random Forests (RF), Gradient elevation decision trees (GBDT), Adaptive Boosting (AdaBoost), Extra Trees (ET), and K-Nearest Neighbors (KNN) were modeled with F v /F m. The Savitzky-Golay + 1D-CNN model had the best robustness and accuracy (RMSE = 0.016, MAE = 0.009, MAPE = 0.011). In addition, the F v /F m prediction drought tolerance coefficient and the manually measured drought tolerance coefficient were similar. Therefore, cotton varieties with different drought tolerance degrees can be monitored using hyperspectral full band technology to establish a 1D-CNN model. This technique is non-destructive, fast and accurate in assessing the drought status of cotton, which promotes smart-scale agriculture.

Response of root and root hair phenotypes of cotton seedlings under high temperature revealed with RhizoPot.

Driven by the increase in its frequency and duration, high temperature weather is increasingly seriously affecting crop development. High temperature inhibits the leaf development, flowering, and pollination of cotton, but its effects on the roots and root hair phenotypes and lifespans remain unclear. Thus, this study selected the two cotton varieties Nongda 601 (ND) and Guoxin 9 (GX) as materials and adopted the RhizoPot, an in situ root observation system, to investigate the effects of high temperature (38°C day and 32°C night) on the growth dynamics of the aboveground parts and root phenotypes of cotton at the seedling stage. The results showed that high temperature reduced the net photosynthetic rate and chlorophyll content, decreased the dry matter accumulation and transfer to the root, and lowered the root-shoot ratio (R/S ratio). The root phenotypes changed significantly under high temperature. After 7 d of high temperature stress, the root lengths of ND and GX decreased by 78.14 mm and 59.64 mm, respectively. Their specific root lengths increased by 79.60% and 66.11%, respectively. Their specific root surface areas increased by 418.70 cm2·g-1 and 433.42 cm2·g-1, respectively. Their proportions of very fine roots increased to 99.26% and 97.16%, respectively. After the removal of high temperature (RHT), their root lengths tended to increase, and their proportions of very fine roots continued to increase. The root hairs of ND and GX were also significantly affected by high temperature. In particular, the root hair densities of ND and GX decreased by 52.53% and 56.25%, respectively. Their average root hair lengths decreased by 96.62% and 74.29%, respectively. Their root hair lifespans decreased by 7 d and 10 d, respectively. After the RHT, their average root hair lengths failed to recover. A principal component analysis indicated that the root architectures were significantly affected by root hair density, average root hair length, specific root length, and specific root surface area under high temperatures. In summary, cotton adapts to high temperature environments by increasing the specific root length, specific root surface area, and the proportions of very fine roots, and reducing the lifespan of root hairs.

RhizoPot platform: A high-throughput in situ root phenotyping platform with integrated hardware and software.

Quantitative analysis of root development is becoming a preferred option in assessing the function of hidden underground roots, especially in studying resistance to abiotic stresses. It can be enhanced by acquiring non-destructive phenotypic information on roots, such as rhizotrons. However, it is challenging to develop high-throughput phenotyping equipment for acquiring and analyzing in situ root images of root development. In this study, the RhizoPot platform, a high-throughput in situ root phenotyping platform integrating plant culture, automatic in situ root image acquisition, and image segmentation, was proposed for quantitative analysis of root development. Plants (1-5) were grown in each RhizoPot, and the growth time depended on the type of plant and the experimental requirements. For example, the growth time of cotton was about 110 days. The imaging control software (RhizoAuto) could automatically and non-destructively image the roots of RhizoPot-cultured plants based on the set time and resolution (50-4800 dpi) and obtain high-resolution (>1200 dpi) images in batches. The improved DeepLabv3+ tool was used for batch processing of root images. The roots were automatically segmented and extracted from the background for analysis of information on radical features using conventional root software (WinRhizo and RhizoVision Explorer). Root morphology, root growth rate, and lifespan analysis were conducted using in situ root images and segmented images. The platform illustrated the dynamic response characteristics of root phenotypes in cotton. In conclusion, the RhizoPot platform has the characteristics of low cost, high-efficiency, and high-throughput, and thus it can effectively monitor the development of plant roots and realize the quantitative analysis of root phenotypes in situ.

Cell- and noncell-autonomous AUXIN RESPONSE FACTOR3 controls meristem proliferation and phyllotactic patterns.

In cell-cell communication, noncell-autonomous transcription factors play vital roles in controlling plant stem cell fate. We previously reported that AUXIN RESPONSE FACTOR3 (ARF3), a member of the ARF family with critical roles in floral meristem maintenance and determinacy, has a distinct accumulation pattern that differs from the expression domain of its encoding gene in the shoot apical meristem (SAM). However, the biological meaning of this difference is obscure. Here, we demonstrate that ARF3 expression in Arabidopsis (Arabidopsis thaliana) is mainly activated at the periphery of the SAM by auxin where ARF3 cell autonomously regulates the expression of meristem-organ boundary-specific genes, such as CUP-SHAPED COTYLEDON1-3 (CUC1-3), BLADE ON PETIOLE1-2 (BOP1-2), and TARGETS UNDER ETTIN CONTROL3 (TEC3) to regulate the arrangement of organs in regular pattern, a phenomenon referred to as phyllotaxis. We also show that ARF3 is translocated into the organizing center where it represses cytokinin activity and WUSCHEL expression to regulate meristem activity noncell-autonomously. Therefore, ARF3 acts as a molecular link that mediates the interaction of auxin and cytokinin signaling in the SAM while coordinating the balance between meristem maintenance and organogenesis. Our findings reveal an ARF3-mediated coordination mechanism through cell-cell communication in dynamic SAM maintenance.

Effects of Exogenous Melatonin on Root Physiology, Transcriptome and Metabolome of Cotton Seedlings under Salt Stress.

Root systems are the key organs through which plants absorb water and nutrients and perceive the soil environment and thus are easily damaged by salt stress. Melatonin can alleviate stress-induced damage to roots. The present study investigated the effects of exogenous melatonin on the root physiology, transcriptome and metabolome of cotton seedlings under salt stress. Salt stress was observed to damage the cell structure and disorder the physiological system of cotton seedling roots. After subjecting melatonin-soaked seeds to salt stress, the activities of SOD, CAT and POD in cotton seedling roots increased by 10-25%, 50-60% and 50-60%, respectively. The accumulation of H2O2 and MDA were significantly decreased by 30-60% and 30-50%, respectively. The contents of soluble sugar, soluble protein and K+ increased by 15-30%, 15-30% and 20-50%, respectively, while the Na+ content was significantly reduced. Melatonin also increased auxin (by 20-40%), brassinosteroids (by 5-40%) and gibberellin (by 5-35%) and promoted melatonin content and root activity. Exogenous melatonin maintained the integrity of root cells and increased the number of organelles. Transcriptomic and metabolomic results showed that exogenous melatonin could mitigate the salt-stress-induced inhibition of plant root development by regulating the reactive oxygen species scavenging system; ABC transporter synthesis; plant hormone signal transduction, endogenous melatonin gene expression; and the expression of the transcription factors MYB, TGA and WRKY33. These results provide a new direction and empirical basis for improving crop salt tolerance with melatonin.

Comparative transcriptomics reveals new insights into melatonin-enhanced drought tolerance in naked oat seedlings.

The growth and development of naked oat (Avena nuda L.) seedlings, a grain recognized as nutritious and healthy, is limited by drought. Melatonin plays a positive role in plants under drought stress. However, its function is unclear in naked oats. This study demonstrated that melatonin enhances drought stress tolerance in oat seedlings. Melatonin application alleviated the declining growth parameters of two naked oat varieties, Huazao No.2 (H2) and Jizhangyou No.15 (J15), under drought stress by increasing the chlorophyll content and photosynthetic rate of leaves. Melatonin pretreatment induced differential gene expression in H2 and J15 under drought stress. Subsequently, the differential gene expression responses to melatonin in the two varieties were further analyzed. The key drought response transcription factors and the regulatory effect of melatonin on drought-related transcription factors were assessed, focusing on genes encoding proteins in the ABA signal transduction pathway, including PYL, PP2C, ABF, SNRK2, and IAA. Taken together, this study provides new insights into the effect and underlying mechanism of melatonin in alleviating drought stress in naked oat seedlings.

Recent advances in methods for in situ root phenotyping.

Roots assist plants in absorbing water and nutrients from soil. Thus, they are vital to the survival of nearly all land plants, considering that plants cannot move to seek optimal environmental conditions. Crop species with optimal root system are essential for future food security and key to improving agricultural productivity and sustainability. Root systems can be improved and bred to acquire soil resources efficiently and effectively. This can also reduce adverse environmental impacts by decreasing the need for fertilization and fresh water. Therefore, there is a need to improve and breed crop cultivars with favorable root system. However, the lack of high-throughput root phenotyping tools for characterizing root traits in situ is a barrier to breeding for root system improvement. In recent years, many breakthroughs in the measurement and analysis of roots in a root system have been made. Here, we describe the major advances in root image acquisition and analysis technologies and summarize the advantages and disadvantages of each method. Furthermore, we look forward to the future development direction and trend of root phenotyping methods. This review aims to aid researchers in choosing a more appropriate method for improving the root system.

Seed Priming With Melatonin Promotes Seed Germination and Seedling Growth of Triticale hexaploide L. Under PEG-6000 Induced Drought Stress.

Melatonin (N-acetyl-5-methoxytryptamine, MT) can mitigate abotic stress, including drought stress on a number of crops. However, it is unclear whether and how seed priming with melatonin alleviates the effects of drought stress on seed germination and seedling growth of triticale (Triticale hexaploide L.). In this study, we investigated the effects of seed priming with MT on seed germination, protective enzyme activity, superoxide anion, and hydrogen peroxide in triticale under PEG-6000 induced drought stress. Seed priming with 20 µM MT alleviated the adverse effects of PEG-6000 induced drought stress on seed germination and seedling growth. Triticale seeds primed with 20 µM MT exhibited improved germination potential, germination rate, germ and radicle length. Specifically, MT priming increased the germination rate by 57.67% compared with unprimed seeds. Seed priming with melatonin also alleviated the adverse effects of PEG-6000 induced drought stress on triticale seedlings. MT pretreatment with 20 µM significantly increased the net photosynthetic rate, transpiration rate, stomatal conductance, plant height, leaf area, and relative chlorophyll concentration, enhanced the activities of superoxide dismutase and peroxidase, and decreased reactive oxygen species (ROS) and malonaldehyde content in the seeds (germ and radicle) and seedlings (leaf and root). Collectively, these results suggest that seed priming with melatonin promotes ROS scavenging capacity and enhances energy supply and antioxidant enzyme activities to alleviate the adverse effects of drought stress in triticale.

Wheat Escapes Low Light Stress by Altering Pollination Types.

Although low light stress seriously affects florets fertility and grain number during the reproductive period, crops can be fertilized by heterologous pollen to alleviate the reduction of grain number. However, wheat is strongly autogamous, how to change to outcross after low light remains unclear. To understand the mechanisms of this change process, an approach combined morphological, physiological, and transcriptomic analyses was performed under low light stress imposed at the young microspore stage the booting stage from tetrad to uni-nucleate microspores stage. The results showed that low light stress caused pollen abortion, and the unfertilized ovary is fertilized by heterologous pollen after floret opening. Compared to control, the opening angle of lemma and glume were increased by 11.6-48.6 and 48.4-78.5%, respectively. The outcross of stressed wheat compensated for the 2.1-18.0% of grain number loss. During this process, phytohormones played an important role. Jasmonic acid (JA) and methyl jasmonate (MeJA) levels in spikelets were increased. Meanwhile, lignin and cellulose content decreased, and genes associated with cell wall related GO terms were enriched. Among the differentially expressed genes (DEGs), were identified 88-710 transcription factors genes, of which some homologs in Arabidopsis are proposed to function in lignin and cellulose, influencing the glume and lemma opening. Our finding can provide new insight into a survival mechanism to set seeds through pollination way alteration in the absence of self-fertilization after the stress of adversity.