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.

Highly Reliable Van Der Waals Memory Boosted by a Single 2D Charge Trap Medium.

Charge trap materials that can store carriers efficiently and controllably are desired for memory applications. 2D materials are promising for highly compacted and reliable memory mainly due to their ease of constructing atomically uniform interfaces, however, remain unexplored as being charge trap media. Here it is discovered that 2D semiconducting PbI2 is an excellent charge trap material for nonvolatile memory and artificial synapses. It is simple to construct PbI2 -based charge trap devices since no complicated synthesis or additional defect manufacturing are required. As a demonstration, MoS2 /PbI2 device exhibits a large memory window of 120 V, fast write speed of 5 µs, high on-off ratio around 106 , multilevel memory of over 8 distinct states, high reliability with endurance up to 104 cycles and retention over 1.2 × 104 s. It is envisioned that PbI2 with ionic activity caused by the natively formed iodine vacancies is unique to combine with unlimited 2D materials for versatile van der Waals devices with high-integration and multifunctionality.

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.

QTL mapping and BSA-seq map a major QTL for the node of the first fruiting branch in cotton.

Understanding the genetic basis of the node of the first fruiting branch (NFFB) improves early-maturity cotton breeding. Here we report QTL mapping on 200 F2 plants and derivative F2:3 and F2:4 populations by genotyping by sequencing (GBS). BC1F2 population was constructed by backcrossing one F2:4 line with the maternal parent JF914 and used for BSA-seq for further QTL mapping. A total of 1,305,642 SNPs were developed between the parents by GBS, and 2,907,790 SNPs were detected by BSA-seq. A high-density genetic map was constructed containing 11,488 SNPs and spanning 4,202.12 cM in length. A total of 13 QTL were mapped in the 3 tested populations. JF914 conferred favorable alleles for 11 QTL, and JF173 conferred favorable alleles for the other 2 QTL. Two stable QTL were repeatedly mapped in F2:3 and F2:4, including qNFFB-D3-1 and qNFFB-D6-1. Only qNFFB-D3-1 contributed more than 10% of the phenotypic variation. This QTL covered about 24.7 Mb (17,130,008-41,839,226 bp) on chromosome D3. Two regions on D3 (41,779,195-41,836,120 bp, 41,836,768-41,872,287 bp) were found by BSA-seq and covered about 92.4 Kb. This 92.4 Kb region overlapped with the stable QTL qNFFB-D3-1 and contained 8 annotated genes. By qRT-PCR, Ghir_D03G012430 showed a lower expression level from the 1- to 2-leaf stage and a higher expression level from the 3- to 6-leaf stage in the buds of JF173 than that of JF914. Ghir_D03G012390 reached the highest level at the 3- and 5-leaf stages in the buds of JF173 and JF914, respectively. As JF173 has lower NFFB and more early maturity than JF914, these two genes might be important in cell division and differentiation during NFFB formation in the seedling stage. The results of this study will facilitate a better understanding of the genetic basis of NFFB and benefit cotton molecular breeding for improving earliness traits.

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.

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.

Physiological and Comparative Transcriptomic Analysis Provide Insight Into Cotton (Gossypium hirsutum L.) Root Senescence in Response.

Nitrogen (N) deficiency is one of the pivotal environmental factors that induce leaf senescence. However, little is known regarding the impact of low N on root senescence in cotton. Thus, the objective of this study was to investigate the effect of low nitrogen on root senescence. In this study, the molecular mechanism of cotton root senescence in response to nitrogen deficiency was investigated by combing physiological and transcriptomic analysis when no nitrogen and normal nitrogen (138mg N·kg-1 soil). The results showed that: (1) nitrogen starvation induced the premature senescence of leaf, while delaying root senescence. (2) The increase in catalase (CAT) activity at 60, 80, and 100days after emergence (DAE), combined with decrease of malonaldehyde content at 60, 80, and 100 DAE, and the content of abscisic acid (ABA), all of these contributed to the delay of root senescence by low nitrogen treatment. (3) To study the molecular mechanisms underlying root senescence, the gene expression profiling between low nitrogen and normal nitrogen treatments were compared pairwise at 20, 40, 60, 80, and 100 DAE. A total of 14,607 genes were identified to be differentially expressed at these five points. (5) Most genes involved in glutathione (GSH) and ascorbate peroxidase (APX) synthesis were upregulated, while ABA, apoptosis, caspase, and cell cycle-related differentially expressed genes (DEGs) were downregulated. Coupled with the physiology data, these results provide new insights into the effect of nitrogen starvation on root senescence.