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Nitrogen (N) serves as an essential nutrient for yield formation across diverse crop types. However, agricultural production encounters numerous challenges, notably high N fertilizer rates coupled with low N use efficiency and serious environmental pollution. Deep placement of nitrogen fertilizer (DPNF) is an agronomic measure that shows promise in addressing these issues. This review aims to offer a comprehensive understanding of DPNF, beginning with a succinct overview of its development and methodologies for implementation. Subsequently, the optimal fertilization depth and influencing factors for different crops are analyzed and discussed. Additionally, it investigates the regulation and mechanism underlying the DPNF on crop development, yield, N use efficiency and greenhouse gas emissions. Finally, the review delineates the limitations and challenges of this technology and provides suggestions for its improvement and application. This review provides valuable insight and reference for the promotion and adoption of DPNF in agricultural practice.

The exogenous application of melatonin by the root drenching method is an effective way to improve crop drought resistance. However, the optimal concentration of melatonin by root drenching and the physiological mechanisms underlying melatonin-induced drought tolerance in cotton (Gossypium hirsutum L.) roots remain elusive. This study determined the optimal concentration of melatonin by root drenching and explored the protective effects of melatonin on cotton roots. The results showed that 50 μmol L−1 melatonin was optimal and significantly mitigated the inhibitory effect of drought on cotton seedling growth. Exogenous melatonin promoted root development in drought-stressed cotton plants by remarkably increasing the root length, projected area, surface area, volume, diameter, and biomass. Melatonin also mitigated the drought-weakened photosynthetic capacity of cotton and regulated the endogenous hormone contents by regulating the relative expression levels of hormone-synthesis genes under drought stress. Melatonin-treated cotton seedlings maintained optimal enzymatic and non-enzymatic antioxidant capacities, and produced relatively lower levels of reactive oxygen species and malondialdehyde, thus reducing the drought stress damage to cotton roots (such as mitochondrial damage). Moreover, melatonin alleviated the yield and fiber length declines caused by drought stress. Taken together, these findings show that root drenching with exogenous melatonin increases the cotton yield by enhancing root development and reducing the root damage induced by drought stress. In summary, these results provide a foundation for the application of melatonin in the field by the root drenching method.

Abstract 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.

Reconstructing 3D garment models usually requires laborious data-fetching processes, such as expensive lidar, multiple-view images, or SMPL models of the garments. In this paper, we propose a neat framework that takes single-image inputs for generating pseudo-sparse views of 3D garments and synthesizing multi-view images into a high-quality 3D neural model. Specifically, our framework combines a pretrained pseudo sparse view generator and a volumetric signed distance function (SDF) representation-based network for 3D garment modeling, which uses neural networks to represent both the density and radiance fields. We further introduce a stride fusion strategy to minimize the pixel-level loss in key viewpoints and semantic loss in random viewpoints, which produces view-consistent geometry and sharp texture details. Finally, a multi-view rendering module utilizes the learned SDF representation to generate multi-view garment images and extract accurate mesh and texture from them. We evaluate our proposed framework on the Deep Fashion 3D dataset and achieve state-of-the-art performance in terms of both quantitative and qualitative evaluations.

IntroductionPlant 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.MethodsThis 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. ResultsThe 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. DiscussionDemonstrating 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.

For sparse signal reconstruction (SSR) problem in compressive sensing (CS), by the splitting technique, we first transform it into a continuously differentiable convex optimization problem, and then a new self-adaptive gradient projection algorithm is proposed to solve the SSR problem, which has fast solving speed and pinpoint accuracy when the dimension increases. Global convergence of the proposed algorithm is established in detail. Without any assumptions, we establish global linear convergence rate of the proposed algorithm, which is a new result for constrained convex (rather than strictly convex) quadratic programming problem. Furthermore, we can also obtain an approximate optimal solution in a finite number of iterations. Some numerical experiments are made on the sparse signal recovery and image restoration to exhibit the efficiency of the proposed algorithm. Compared with the state-of-the-art algorithms in SSR problem, the proposed algorithm is more accurate and efficient.

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.

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.

Plant height and above-ground biomass are important growth parameters that affect crop yield. Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland management. However, the feasibility of using these technologies to estimate cotton plant height and above-ground biomass has not been determined. This study proposed a low cost and high-throughput imaging method combined with Canopeo to extract the percentages of green color from high-definition digital images and establish a model to estimate the cotton plant height and above-ground biomass. The plant height and above-ground biomass field trials were conducted at two levels of irrigation (soil water content 70% ± 5% and 40%−45%, respectively) using 80 cotton genotypes. The linear fitting performed well across the different cotton genotypes (PH, R2 = 0.9829; RMSE = 2.4 cm; NRMSE = 11% and AGB, R2 = 0.9609; RMSE = 0.6 g / plant; and NRMSE = 5%), and two levels of irrigation (PH, R2 = 0.9604; RMSE = 2.15 cm; NRMSE = 6% and AGB, R2 = 0.9650; RMSE = 4.51 g/plant; and NRMSE = 17%). All reached a higher fitting degree. Additionally, the most comprehensive model to estimate the cotton plant height and above-ground biomass (Y = 0.4832*X + 11.04; Y = 0.4621*X − 0.3591) was determined using a simple linear regression modeling method. The percentages of green color positively correlated with plant height and above-ground biomass, and each model exhibited higher accuracy (R2 ≥ 0.8392, RMSE ≤ 0.0158, NRMSE ≤ 0.06%). Combining a high-definition digital camera with Canopeo enables the prediction of crop growth in the field. The simple linear regression modeling method and the most comprehensive model enable the rapid estimation of the cotton plant height and above-ground biomass. This method can also be used as a baseline to measure other important crop phenotypes.

In recent years, compressive sensing (CS) problem is being popularly applied in the fields of signal processing and statistical inference. The alternating direction method of multipliers (ADMM) is applicable to the equivalent forms of basis pursuit denoising (BPDN) in CS problem. However, the solving speed and accuracy are adversely affected when the dimension increases greatly. In this paper, a new iterative format of proximal ADMM, which has fast solving speed and pinpoint accuracy when the dimension increases, is proposed to solve BPDN problem. Global convergence of the new type proximal ADMM is established in detail, and we exhibit a R− linear convergence rate under suitable condition. Moreover, we apply this new algorithm to solve different types of BPDN problems. Compared with the state-of-the-art of algorithms in BPDN problem, the proposed algorithm is more accurate and efficient.

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.

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 Fv/Fm. The Savitzky-Golay + 1D-CNN model had the best robustness and accuracy (RMSE = 0.016, MAE = 0.009, MAPE = 0.011). In addition, the Fv/Fm 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.

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.

Abstract Background As damage to the ecological environment continues to increase amid unreasonable amounts of irrigation, soil salinization has become a major challenge to agricultural development. Melatonin (MT) is a pleiotropic signal molecule and indole hormone, which alleviates the damage of abiotic stress to plants. MT has been confirmed to eliminate reactive oxygen species (ROS) by improving the antioxidant system and reducing oxidative damage under adversity. However, the mechanism by which exogenous MT mediates salt tolerance by regulating the photosynthetic capacity and ion balance of cotton seedlings still remains unknown. In this study, the regulatory effects of MT on the photosynthetic system, osmotic modulators, chloroplast, and anatomical structure of cotton seedlings were determined under 0–500 μM MT treatments with salt stress induced by treatment with 150 mM NaCl. Results Salt stress reduces the chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular CO2 concentration, transpiration rate, PSII photochemical efficiency, PSII actual photochemical quantum yield, the apparent electron transfer efficiency, stomata opening, and biomass. In addition, it increases non-photochemical quenching. All of these responses were effectively alleviated by exogenous treatment with MT. Exogenous MT reduces oxidative damage and lipid peroxidation by reducing salt-induced ROS and protects the plasma membrane from oxidative toxicity. MT also reduces the osmotic pressure by reducing the salt-induced accumulation of Na+ and increasing the contents of K+ and proline. Exogenous MT can facilitate stomatal opening and protect the integrity of cotton chloroplast grana lamella structure and mitochondria under salt stress, protect the photosynthetic system of plants, and improve their biomass. An anatomical analysis of leaves and stems showed that MT can improve xylem and phloem and other properties and aides in the transportation of water, inorganic salts, and organic substances. Therefore, the application of MT attenuates salt-induced stress damage to plants. Treatment with exogenous MT positively increased the salt tolerance of cotton seedlings by improving their photosynthetic capacity, stomatal characteristics, ion balance, osmotic substance biosynthetic pathways, and chloroplast and anatomical structures (xylem vessels and phloem vessels). Conclusions Our study attributes help to protect the structural stability of photosynthetic organs and increase the amount of material accumulation, thereby reducing salt-induced secondary stress. The mechanisms of MT-induced plant tolerance to salt stress provide a theoretical basis for the use of MT to alleviate salt stress caused by unreasonable irrigation, fertilization, and climate change.

Melatonin application has obvious improving effects on alleviating the drought-induced inhibition of plant growth. However, the root phenotypic dynamics in wheat treated with melatonin remain unknown. This study was conducted using RhizoPot, a novel and improvised in situ root observation device, with three treatments, including normal water condition (CK), drought condition (Ds, relative water content 45–50%), and 100 µM melatonin treatment under drought condition (MT). Results showed that MT application effectively improves root morphological indicators, including root (specific root) length, surface area, and volume; root length density; and the average root diameter of wheat plants. Also, the inhibitory effect of drought on shoot morphology, including plant height, dry weight, net photosynthesis, and stomatal aperture of leaves, were improved significantly through MT under drought condition. Life span and percent survival of fine root, lateral root, and root hair at different segments were also effectively improved under MT treatment. Compared with those shown under CK and Ds, the melatonin contents in leaves and roots were increased, and the expression levels of melatonin-synthesis-related genes (TaCOMT and TaTDC) were upregulated significantly under MT treatment. The findings of this study may clarify the drought resistance mechanism of wheat treated with melatonin under 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.

Abstract Background Cotton (Gossypium hirsutum L.) is one of the most important cash crops worldwide. Fine roots are the central part of the root system that contributes to plant water and nutrient uptake. However, the mechanisms underlying the response of cotton fine roots to soil drought remains unclear. To elucidate the proteomic changes in fine roots of cotton plants under drought stress, 70–75% and 40–45% soil relative water content treatments were imposed on control (CK) and drought stress (DS) groups, respectively. Then, tandem mass tags (TMT) technology was used to determine the proteome profiles of fine root tissue samples. Results Drought significantly decreased the value of average root diameter of cotton seedlings, whereas the total root length and the activities of antioxidases were increased. To study the molecular mechanisms underlying drought response further, the proteome differences between tissues under CK and DS treatments were compared pairwise at 0, 30, and 45 DAD (days after drought stress). In total, 118 differentially expressed proteins (DEPs) were up-regulated and 105 were down-regulated in the ‘DS30 versus CK30’ comparison; 662 DEPs were up-regulated, and 611 were down-regulated in the ‘DS45 versus CK45’ comparison. The functions of these DEPs were classified according to their pathways. Under early stage drought (30 DAD), some DEPs involved in the ‘Cutin, suberin, and wax synthesis’ pathway were up-regulated, while the down-regulated DEPs were mainly enriched within the ‘Monoterpenoid biosynthesis’ pathway. Forty-five days of soil drought had a greater impact on DEPs involved in metabolism. Many proteins involving ‘Carbohydrate metabolism,’ ‘Energy metabolism,’ ‘Fatty acid metabolism,’ ‘Amino acid metabolism,’ and ‘Secondary metabolite biosynthesis’ were identified as DEPs. Additionally, proteins related to ion transport, stress/defense, and phytohormones were also shown to play roles in determining the fine root growth of cotton plants under drought stress. Conclusions Our study identified potential biological pathways and drought-responsive proteins related to stress/defense responses and plant hormone metabolism under drought stress. Collectively, our results provide new insights for further improving drought tolerance in cotton and other crops.

Late-sowing and high-density cultivation are typical cotton planting models that are widely applied in the Yellow River Valley of China. The model can easily lead to late maturity and reduced yields. Plant topping and ethephon spraying have been shown to improve cotton earliness and yields. However, the optimal topping date and ethephon concentration are yet to be established. A two-year field experiment (2020–2021) was thus conducted to assess the effects of spraying high-concentration ethephon and early topping on the growth, yield, and earliness of cotton under late-sowing and high-density cultivation models. The experiment employed a split-plot design, in which the main plots were sprayed with varying ethephon concentrations (2000 mL/ha, E2000; 4000 mL/ha, E4000; 6000 mL/ha, E6000), while subplots were plant topping dates (T13, 13 July, early-topped; T20, 20 July, suitable-topped; T27, 27 July, late-topped). Higher ethephon concentrations (E4000) increased the earliness of early-topped (T13) plants. Boll-setting and boll-opening rates increased by 12.00% and 16.83% in T13 plants, respectively, relative to T27 plants. However, the shedding rate for T13 plants decreased by 12.00%. Earliness and harvest index (HI) for the T13 plants were higher than those of the T27 plants by 8.01% and 18.91%, respectively. Even though the T13 plant yield decreased slightly, their boll weight increased by 3.99% and 12.27%, respectively, relative to those of the T20 and T27 plants. Earliness increased with increasing ethephon concentration. In conclusion, early topping and higher ethephon concentrations can effectively improve cotton yield and earliness.

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.

Phosphorus (P) deficiency is a common challenge in crop production because of its poor mobility through the soil. The root system plays a significant role in P absorption from the soil and is the initial indicator of low P levels. However, the phenotypic dynamics and longevity of cotton roots under P stress remain unknown. In this study, RhizoPot, an improvised in situ root observation device, was used to monitor the dynamics of root phenotypes of cotton seedlings under P-deficient (PD) and P-replete (PR) conditions. Low P stress reduced P absorption and accumulation in the roots, leading to low dry weight accumulation. Cotton seedlings responded to low P stress by increasing the number of lateral roots, specific root length, branch density, root length density, and length of root hairs. Additionally, the life span of root hairs was prolonged. Low P stress also reduced the average diameter of roots, promoted root extension, expanded the root coverage area, and increased the range of P acquisition. Principal component analysis revealed that the net root growth rate, root length density, root dry weight, P absorption efficiency, average root hair length, and taproot daily growth significantly influenced the cotton root architecture. Collectively, these results show that low P stress reduces the net growth rate of cotton seedling roots and restricts plant growth. Plants respond to P deficiency by extending the life span of root hairs and increasing specific root length and lateral root branch density. This change in root system architecture improves the adaptability of plants to low P conditions. The findings of this study may guide the selection of cotton varieties with efficient P utilization.

The germination of cotton (Gossypium hirsutum L.) seeds is affected by drought stress; however, little is known about the physiological mechanism affecting germination and the effect of melatonin (MT) on cotton seed germination under drought stress. Therefore, we studied the effects of exogenous MT on the antioxidant capacity and epidermal microstructure of cotton under drought stress. The results demonstrated a retarded water absorption capacity of testa under drought stress, significantly inhibiting germination and growth in cotton seeds. Drought stress led to the accumulation of reactive oxygen species (ROS), malondialdehyde (MDA), and osmoregulatory substances (e.g., proline, soluble protein, and soluble sugars); it also decreased the activity of antioxidant enzymes and α-amylase. Drought stress inhibited gibberellin acid (GA3) synthesis and increased abscisic acid (ABA) content, seriously affecting seed germination. However, seeds pre-soaked with MT (100 µM) showed a positive regulation in the number and opening of stomata in cotton testa. The exogenous application of MT increased the germination rate, germination potential, radical length, and fresh weight, as well as the activities of superoxide dismutase (SOD), peroxidase (POD), and α-amylase. In addition, MT application increased the contents of organic osmotic substances by decreasing the hydrogen peroxide (H2O2), superoxide anion (O2-), and MDA levels under drought stress. Further analysis demonstrated that seeds pre-soaked with MT alleviated drought stress by affecting the ABA and GA3 contents. Our findings show that MT plays a positive role in protecting cotton seeds from drought stress.

The root system plays an important role in the growth and development of cotton, and root growth is closely related to shoot growth, both of which are affected by N availability in the soil. However, it is unknown how N affects root growth and the root–shoot relationship under various N rates in the Yellow River Basin, China. Thus, the aim of this study was to assess the impacts of the application rate of N on root growth and the root–shoot relationship, to provide insight into the N regulation of root and shoot growth and N efficiency from the perspective of the root system. A field experiment conducted in 2014 and 2015 was used to determine the effects of N rates (0, 120, 240, and 480 kg ha–1) on root morphology, root distribution, the root–shoot relationship, and cotton yield. A moderate N fertilization rate (240 kg ha–1) increased root length, root surface area, and root biomass in most soil layers and significantly increased total root growth and total root biomass by more than 36.06% compared to the 0 kg ha–1 treatment. In addition, roots in the surface soil layers were more strongly affected by N fertilization than roots distributed in the deeper soil layers. Total root length, total root surface area, and root biomass in the 0–15 cm layer were significantly correlated with shoot biomass and boll biomass. In the 60–75 cm layer, total root length, total root surface area, and root length were significantly positively correlated with seed cotton yield. The application of a moderate level of N markedly increased total shoot biomass, boll biomass, and seed cotton yield. Our results show that increased shoot and boll biomasses were correlated with a significant increase in the root system especially the shallow roots in the moderate N treatment (240 kg ha–1), leading to an increase in cotton seed yield.

Abstract For the extended linear complementarity problem (ELCP), by virtue of a new residual function, we establish a new type of global error bound under weaker conditions. Based on this, we respectively obtain new global error bounds for the vertical linear complementarity problem and the mixed linear complementarity problem. The obtained results presented in this paper supplement some recent corresponding results in the sense that they can provide some error bounds for a more general ELCP. Their feasibility is verified by some numerical experiments.

To improve the accuracy of the diagnosis of the composite failure of the rotor system under underdetermined conditions, a single-channel blind source separation method based on an adaptive multiscale generalized morphology filter (AMGMF) and an adaptive fast ensemble empirical mode decomposition (AFEEMD) algorithm is proposed. First, AMGMF is used to filter out the background noise in the signal and enhance the signal-to-noise ratio (SNR), and then, the filtered signal is decomposed by the AFEEMD algorithm to improve the accuracy of signal decomposition and reduce computation time. Second, the singular value decomposition-based method is used to estimate the number of source signals, and the main components highly correlated with the observed signal are selected according to the number of source signals. Finally, the effective separation of source signals is achieved by the fast independent component analysis (FastICA) algorithm. Simulation tests and multiple rotor fault signals are used to demonstrate the feasibility and effectiveness of the proposed method. Experimental results show that the proposed method has better separation performance than the existing EEMD-PCA-FastICA method.

Abstract Due to updating the Lagrangian multiplier twice at each iteration, the symmetric alternating direction method of multipliers (S-ADMM) often performs better than other ADMM-type methods. In practical applications, some proximal terms with positive definite proximal matrices are often added to its subproblems, and it is commonly known that large proximal parameter of the proximal term often results in ‘too-small-step-size’ phenomenon. In this paper, we generalize the proximal matrix from positive definite to indefinite, and propose a new S-ADMM with indefinite proximal regularization (termed IPS-ADMM) for the two-block separable convex programming with linear constraints. Without any additional assumptions, we prove the global convergence of the IPS-ADMM and analyze its worst-case O ( 1 / t ) $\mathcal{O}(1/t)$ convergence rate in an ergodic sense by the iteration complexity. Finally, some numerical results are included to illustrate the efficiency of the IPS-ADMM.

Melatonin (MT; N-acetyI-5-methoxytryptamine) is an amine hormone involved in abiotic stress resistance. Previous studies have confirmed that melatonin can promote seed germination, mediate physiological regulation mechanisms, and stimulate crop growth under stress. However, the osmotic regulation mechanism by which exogenous melatonin mediates salt tolerance in cotton is still largely unknown. To investigate the effect of salt stress on melatonin concentration in germinating cotton seeds, we analyzed melatonin content over time during seed germination under different treatments. Melatonin content reached its minimum at day 6, while cotton germination rates peaked at day 6, indicating melatonin content and seed germination are correlated. Then we investigated the effects of 10-100 μM melatonin treatments on membrane lipid peroxides and osmotic adjustment substances during cotton seed germination under salt stress. Salt stress led to electrolyte leakage (EL) as well as accumulations of hydrogen peroxide (H2O2), malondialdehyde (MDA), organic osmotic substances (i.e., proline, soluble sugars), and inorganic osmotic substances (i.e., Na+, Cl-). Meanwhile, the contents of melatonin, soluble proteins, and K+ as well as the K+/Na+ balance decreased, indicating that salt stress inhibited melatonin synthesis and damaged cellular membranes, seriously affecting seed germination. However, melatonin pretreatment at different concentrations alleviated the adverse effects of salt stress on cotton seeds and reduced EL as well as the contents of H2O2, MDA, Na+, and Cl-. The exogenous application of melatonin also promoted melatonin, soluble sugar, soluble proteins, proline, and K+/Na+ contents under salt stress. These results demonstrate that supplemental melatonin can effectively ameliorate the repression of cotton seed germination by enhancing osmotic regulating substances and adjusting ion homeostasis under salt stress. Thus, melatonin may potentially be used to protect cotton seeds from salt stress, with the 20 μM melatonin treatment most effectively promoting cotton seed germination and improving salt stress tolerance.

An improved singular value decomposition based on Toeplitz (TopSVD) is proposed to solve the problem of inaccurately estimating source numbers under the condition of a low signal-to-noise (SNR) ratio for blind source separation. First, Toeplitz modifies the covariance of the received data, and singular value decomposition is used to estimate the number of signal sources. The advantages of TopSVD over traditional approaches are demonstrated by simulated signals. The results demonstrate that the proposed method can be used to estimate the number of coherent sources under low SNR conditions; at the same time, it can significantly improve the accuracy of source number estimation under the conditions of a low SNR and coherent signal source with the simple algorithm.

In the era of big data, longer time series fault signals will not only be easy to copy and store, but also reduce the labor cost of manual labeling, which can better meet the needs of industrial big data. Aiming to effectively extract the key classification information from a longer time series of bearing vibration signals and achieve high diagnostic accuracy under noise and different load conditions. The one-dimensional adaptive long sequence convolutional network (ALSCN) is proposed. ALSCN can better extract features directly from high-dimensional original signals without manually extracting features and relying on expert knowledge. By adding two improved multi-scale modules, ALSCN can not only extract important features efficiently from noise signals, but also alleviate the problem of losing key information due to continuous down-sampling. Moreover, a Bayesian optimization algorithm is constructed to automatically find the best combination of hyperparameters in ALSCN. Based on two bearing data sets, the model is compared with traditional model such as SVM and deep learning models such as convolutional neural networks (CNN) et al. The results prove that ALSCN has a higher diagnostic accuracy rate on 5120-dimensional sequences under −5 signal to noise ratio (SNR) with better generalization.

Seed germination is considered the beginning of the spermatophyte lifecycle, and it is a crucial stage in determining subsequent plant growth and development. Although many previous studies have found that melatonin can promote seed germination, the role of melatonin in cotton germination remains unexamined. The main objective of this study is the characterization of potential promotional effects of melatonin (at doses of 0, 10, 20, 50, 100 and 200 μM) on cotton seed germination. This experiment demonstrated that low concentrations of melatonin can promote germination, while high concentrations failed to promote germination and even inhibited germination. Together, these results indicate that a 20 μM melatonin treatment optimally promotes cotton seed germination. Compared with the control, germination potential (GP), germination rate (GR), and final fresh weight (FW) increased by 16.67%, 12.30%, and 4.81%, respectively. Although low concentrations of melatonin showed some improvement in vigor index (VI), germination index (GI), and mean germination time (MGT), these effects were not statistically significant. Antioxidant enzyme activity during seed germination was most prominent under the 20 μM melatonin treatment. Superoxide dismutase (SOD) and peroxidase (POD) activities were significantly increased by 10.37-59.73% and 17.79-47.68%, respectively, compared to the melatonin-free control. Malondialdehyde (MDA) content was reduced by 16.73-40.33%. Two important plant hormones in seed germination, abscisic acid (ABA) and gibberellins (GAs), were also studied. As melatonin concentration increased, ABA content in seeds decreased first and then increased, and GA3 content showed a diametrically opposite trend, in which the 20 μM melatonin treatment was optimal. The 20 μM melatonin treatment reduced ABA content in seeds by 42.13-51.68%, while the 20 μM melatonin treatment increased GA3 content in seeds to about 1.7-2.5 times that of seeds germinated without melatonin. This study provides new evidence suggesting that low concentrations of melatonin can promote cotton seed germination by increasing the activity of antioxidant enzymes, thereby reducing the accumulation of MDA and regulating plant hormones. This has clear applications for improving the germination rate of cotton seeds using melatonin.

Cotton root growth can be affected by different nitrogen fertilizer rates. The objective of the present study was to quantify the effects of nitrogen fertilization rate on cotton root growth and distribution using minirhizotron and soil coring methods. A secondary objective was to evaluate the minirhizotron method as a tool for determining nitrogen application rates using the root distribution as an index. This study was conducted on a Bt cotton cultivar (Jimian 958) under four nitrogen fertilization rates, i.e., 0, 120, 240 and 480 kg ha(-1) (control, low, moderate and high levels, respectively), in the Yellow River basin of China from 2013-2015. The sampling process, details of each method as well as the root morphology and root distribution were measured. The operational processes, time and labor needed for the soil core method were all greater than those for the minirhizotron method. The total root length density and the length density in most soil layers, especially in the upper soil layers, first increased but then decreased as nitrogen fertilization increased, and the same trend was observed for both methods. Compared with N0, the total root length density under moderate nitrogen fertilization by the soil coring method increased by more than 94.82%, in 2014 and 61.11% in 2015; while by the minirhizotron method the corresponding values were 28.24% in 2014 and 57.47%, in 2015. Most roots were distributed in the shallow soil layers (0-60 cm) in each method. However, the root distribution with the soil coring method (>73.11%) was greater than that with the minirhizotron method (>47.07%). The correlations between the root morphology indexes of shallow soil depth measured using the two methods were generally significant, with correlative coefficients greater than 0.334. We concluded that the minirhizotron method could be used for cotton root analysis and most cotton roots distributed in upper soil layers (0-60cm). In addition, a moderate nitrogen rate (240 kg ha-1) could increase root growth, especially in the shallow soil layers. The differences observed with the minirhizotron method were clearer than those observed with the soil coring method.

The objective of this study was to assess the impacts of nitrogen on the physiological characteristics of the source−sink system of upper fruiting branches under various amounts of nitrogen fertilization. A two-year field experiment was conducted with a Bt cotton cultivar in the Yellow River Basin of China. The growth and yield of cotton of the upper fruiting branches were compared under four nitrogen levels: Control (N0, 0 kg ha−1), low nitrogen (N1, 120 kg ha−1), moderate nitrogen (N2, 240 kg ha−1), and high nitrogen (N3, 480 kg ha−1). The results indicated that in the subtending leaves in upper fruiting branches, chlorophyll content, protein content, and peroxidase (POD) activity dramatically increased with nitrogen application, reaching the highest under the moderate nitrogen treatment. The physiological characters in the seeds had the same trends as in the subtending leaves. Furthermore, the moderate nitrogen rate (240 kg ha−1) had a favorable yield and quality. Our results supported that a moderate nitrogen rate (240 kg ha−1) could coordinate the source−sink growth of cotton in the late stage, enhance the yield and fiber quality, and decrease the cost of fertilizer in the Yellow River Basin of China and other similar ecological areas.

Objective. The aim of this study was to investigate the cognitive function characteristics of Parkinson’s disease (PD) with sleep disorders. Methods. Consecutive patients with PD (n=96), patients with primary sleep disorders (n=76), and healthy control subjects (n=66) were assessed. The patients with PD were classified into sleep disorder (PD-SD) and non-sleep disorder (PD-NSD) groups. Results. Among 96 patients with PD, 69 were diagnosed with a sleep disorder. There were 38 sleep disorder cases, 31 RBD cases, and 27 NSD cases. On the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and MoCA subtests, patients in the PD-SD, primary sleep disorder, and PD-NSD groups exhibited lower scores than those in the control group. Moreover, the PD-SD patients exhibited more significant cognitive impairment than was observed in the primary sleep disorder patients. In the PD-SD subgroup, the attention scores on the MoCA and on MoCA subtests were lower in the PD with RBD group than in the PD with insomnia group. Conclusion. PD with sleep disorders may exacerbate cognitive dysfunction in patients. PD associated with different types of sleep disorders differentially affects cognitive functions, and patients with PD with RBD exhibited poorer cognitive function than was seen in patients with PD with insomnia.

A method is proposed to improve the feature extraction of vibration signals of rotating machinery. Firstly, the single-channel vibration signal is decomposed with ensemble empirical mode decomposition (EEMD). Then, the number of fault signals can be estimated with singular-value decomposition (SVD). Finally, the fault signals can be extracted with kernel-independent component analysis (KICA). The advantage of this method is that it can estimate the number of fault signals of single-channel vibration signals and can extract the fault features clearly. Compared with wavelets, empirical mode decomposition (EMD), variational mode decomposition (VMD) and EEMD, the better performance of this method is proven with three experimental analyses of faulty gear, a faulty rolling bearing and a faulty shaft. The results demonstrate that the proposed method is efficient to extract the fault features of single-channel vibration signals of rotating machinery.

We consider the global error bound for the generalized nonlinear complementarity problem over a polyhedral cone (GNCP). By a new technique, we establish an easier computed global error bound for the GNCP under weaker conditions, which improves the result obtained by Sun and Wang (2013) for GNCP.

We revisit the global error bound for the generalized nonlinear complementarity problem over a polyhedral cone (GNCP). By establishing a new equivalent formulation of the GNCP, we establish a sharper global error bound for the GNCP under weaker conditions, which improves the existing error bound estimation for the problem.

The global error bound estimation for the generalized nonlinear complementarity problem over a closed convex cone (GNCP) is considered. To obtain a global error bound for the GNCP, we first develop an equivalent reformulation of the problem. Based on this, a global error bound for the GNCP is established. The results obtained in this paper can be taken as an extension of previously known results.

For the extended mixed linear complementarity problem (EML CP), we first present the characterization of the solution set for the EMLCP. Based on this, its global error bound is also established under milder conditions. The results obtained in this paper can be taken as an extension for the classical linear complementarity problems.