Ni-rich layered ternary cathodes are promising candidates thanks to their low toxic Co-content and high energy density (â¼800 Wh/kg). However, a critical challenge in developing Ni-rich cathodes is to improve cyclic stability, especially under high voltage (>4.3 V), which directly affects the performance and lifespan of the battery. In this study, niobium-doped strontium titanate (Nb-STO) is successfully synthesized via a facile solvothermal method and used as a surface modification layer onto the LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode. The results exhibited that the Nb-STO modification significantly improved the cycling stability of the cathode material even under high-voltage (4.5 V) operational conditions. In particular, the best sample in our work could provide a high discharge capacity of â¼190 mAh/g after 100 cycles under 1 C with capacity retention over 84% in the voltage range of 3.0-4.5 V, superior to the pristine NCM811 (â¼61%) and pure STO modified STO-811-600 (â¼76%) samples under the same conditions. The improved electrochemical performance and stability of NCM811 under high voltage should be attributed to not only preventing the dissolution of the transition metals, further reducing the electrolyte's degradation by the end of charge, but also alleviating the internal resistance growth from uncontrollable cathode-electrolyte interface (CEI) evolution. These findings suggest that the as-synthesized STO with an optimized Nb-doping ratio could be a promising candidate for stabilizing Ni-rich cathode materials to facilitate the widespread commercialization of Ni-rich cathodes in modern LIBs.
Self-powered wearable devices with integrated energy supply module and sensitive sensors have significantly blossomed for continuous monitoring of human activity and the surrounding environment in healthcare sectors. The emerging of MXene-based materials has brought research upsurge in the fields of energy and electronics, owing to their excellent electrochemical performance, large surface area, superior mechanical performance, and tunable interfacial properties, where their performance can be further boosted via multi-interface engineering. Herein, a comprehensive review of recent progress in MXenes for self-powered wearable devices is discussed from the aspects of multi-interface engineering. The fundamental properties of MXenes including electronic, mechanical, optical, and thermal characteristics are discussed in detail. Different from previous review works on MXenes, multi-interface engineering of MXenes from termination regulation to surface modification and their impact on the performance of materials and energy storage/conversion devices are summarized. Based on the interfacial manipulation strategies, potential applications of MXene-based self-powered wearable devices are outlined. Finally, proposals and perspectives are provided on the current challenges and future directions in MXene-based self-powered wearable devices.
In this study, two polymorphs of the [1,1'-dibutyl-4,4'-bipyridinium][Ni(mnt)2] salt (1) were synthesized. The dark-green polymorph (designated as 1-g) was prepared under ambient conditions by the rapid precipitation method in aqueous solutions. Subsequently, the red polymorph (labeled as 1-r) was obtained by subjecting 1-g to ultrasonication in MeOH at room temperature. Microanalysis, infrared spectroscopy, thermogravimetry (TG), differential scanning calorimetry (DSC), and powder X-ray diffraction (PXRD) techniques were used to characterize the two polymorphs. Both 1-g and 1-r exhibit structural phase transitions: a reversible phase transition at â¼403 K (â¼268 K) upon heating and 384 K (â¼252 K) upon cooling for 1-g (1-r) within the temperature range below 473 K. Interestingly, on heating 1-r to 523 K, an irreversible phase transition occurred at about 494 K, resulting in the conversion of 1-r into 1-g. Relative to 1-r, 1-g represents a thermodynamically metastable phase wherein numerous high-energy conformations in butyl chains of cations are confined within the lattice owing to quick precipitation or rapid annealing from higher temperatures. Through variable-temperature single crystal and powder X-ray diffractions, UV-visible spectroscopy, dielectric spectroscopy, and DSC analyses, this study delves into the mechanism underlying phase transitions for each polymorph and the manual transformation between 1-g and 1-r as well.
Understanding multiple-factor effects on particle size selectivity by extreme rainfall events in Ala-Shan Gobi desert is of great significance for better estimation of potential Asian dust emission sources. Artificial rainfall simulation experiments were used to investigate the particle size selectivity characteristics by extreme rainfall events under different rainfall intensities (20 mm h-1 and 40 mm h-1), slope gradients (3° and 15°) and gravel coverages (0, 30%, and 60%). Moreover, the relations of clay content (Clc), silt content (Sic), fine particle (< 50 µm) content (Fic) and enrichment ratio of fine particles (ER<50) with multiple factors were regressed and validated. Results show that rainfall intensity significantly (P < 0.05) affect runoff and sediment yield processes, but slope gradient was a dominant factor that changed particle size distribution (PSD). The selectivity of fine particles was higher at low rainfall intensity (20 mm h-1), gentle slope (3°) and moderate gravel coverage (30%), with ER<50 reaching 6.14, which dominate the potential Asian dust emission sources. The interaction were discussed and classified into 'Synergy' and 'Trade-off'. Clc and Fic showed negative exponential relationship with rainfall intensity and slope gradient, but positive exponential relationship with gravel coverage. While Sic and ER<50 showed negative power function relationship with rainfall intensity, slope gradient and gravel coverage. These findings could help to understand the effects of multiple factors on potential sources of Asian dust emission under extreme rainfall events in Gobi region of northwestern China and provide basic science reference for the prediction of dust emission in this region.
The common human coronaviruses (HCoVs) HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1 which are members of the coronavirus family are long co-existed with humans and widely distributed globally. Common HCoVs usually cause mild, self-limited upper respiratory tract infections (URTI), and also associated with lower respiratory tract infections (LRTI), especially in children. However, there are little multicentre studies have been conducted in children of several different areas in China, and the epidemic potential of common HCoVs remains unclear. Understanding of the common HCoVs is valuable for clinical and public health. Herein, we retrospectively analysed the medical records of children with acute lower respiratory tract infection admitted to 9 hospitals from different regions in China from 2014 to 2019. Of the 124 patients who tested positive for coronaviruses, OC43 was the predominant type, accounting for 36.3% (45/124) of the detections. Children aged ≤ 6 months and 12-23 months had the highest detection rate of common HCoVs, and the detection rate gradually declined after 2 years old. These four HCoVs could be detected all year round. Among the areas of our study, the overall positive rate was higher in southern China, especially in Guangzhou (29/124, 23.4%). Moreover, common HCoV-positive patients were codetected with 9 other common respiratory pathogens. 229E (11/13, 84.6%) was the most frequently associated with codetection, with EV/RhV was the most frequently codetected virus. Cough (113/124, 91.1%) and fever (73/124, 58.9%) were the most common symptoms of common HCoVs infection.
Coronavirus Infections , Coronavirus NL63, Human , Coronavirus OC43, Human , Respiratory Tract Infections , Child , Child, Preschool , Humans , China/epidemiology , Respiratory Tract Infections/epidemiology , Retrospective Studies
A thermochromic or mechanochromic material can switch between at least two stable states in response to changes in temperature or static pressure/strain. In this study, we investigated a Ni-dithiolene dianion salt, 1,1'-diheptyl-4,4'-bipyridinium bis(maleonitriledithiolato)nickelate (1), and found that its cations and anions stack alternately to form a uniform mixed stack. These mixed stacks then combine to form a molecular solid through Coulomb and van der Waals interactions. Upon heating, 1 undergoes a reversible phase transition at around 340/320 K during the first heating/cooling cycle, resulting in rapid thermochromism with a color change from green (stable state) to red (metastable state) within a few seconds. This is the first report of a crystal of bis(maleonitriledithiolato)nickelate(II) salt with green color. Additionally, 1 exhibits irreversible mechanochromism, intense near-IR absorbance, and a dielectric anomaly. The structural phase transition is responsible for these properties, as it induces alterations in the π-orbital overlap between the anion and cation within a mixed stack. The intense near-IR absorbance arises from the ion-pair charge transfer transition from [Ni(mnt)2]2- to 4,4'-bipyridinium.
Respiratory syncytial virus (RSV) is the most frequently detected respiratory virus in children with acute lower respiratory tract infection. Previous transcriptome studies have focused on systemic transcriptional profiles in blood and have not compared the expression of multiple viral transcriptomes. Here, we sought to compare transcriptome responses to infection with four common respiratory viruses for children (respiratory syncytial virus, adenovirus, influenza virus, and human metapneumovirus) in respiratory samples. Transcriptomic analysis showed that cilium organization and assembly were common pathways related to viral infection. Compared with other virus infections, collagen generation pathways were distinctively enriched in RSV infection. We identified two interferon-stimulated genes (ISGs), CXCL11 and IDO1, which were upregulated to a greater extent in the RSV group. In addition, a deconvolution algorithm was used to analyze the composition of immune cells in respiratory tract samples. The proportions of dendritic cells and neutrophils in the RSV group were significantly higher than those in the other virus groups. The RSV group exhibited a higher richness of Streptococcus than the other virus groups. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of the host response to RSV. Last, according to host-microbe network interference, RSV may disrupt respiratory microbial composition by changing the immune microenvironment. IMPORTANCE In the present study, we demonstrated the comparative results of host responses to infection between RSV and other three common respiratory viruses for children. The comparative transcriptomics study of respiratory samples sheds light on the significant roles that ciliary organization and assembly, extracellular matrix changes, and microbial interactions play in the pathogenesis of RSV infection. Additionally, it was demonstrated that the recruitment of neutrophils and dendritic cells (DCs) in the respiratory tract is more substantial in RSV infection than in other viral infections. Finally, we discovered that RSV infection dramatically increased the expression of two ISGs (CXCL11 and IDO1) and the abundance of Streptococcus.
The crystalline and electronic structures are two important factors for the design of electrocatalysts. In this work, Co-doped MnO electrocatalysts grown on nickel foam (NF) were prepared by a facile hydrothermal reaction, followed by H2 treatment process. The electrocatalytic performance of MnO was significantly improved after doping with Co and the Co0.1Mn0.9O-NF sample achieved excellent oxygen evolution reaction (OER) performance with low overpotential (370 mV at 10 mA cm-2) and reasonable Tafel slope (85.6 mV dec-1). Significantly, the low work function was obtained in the Co0.1Mn0.9O-NF sample (4.37 eV), which could accelerate the charge transfer process of the OER activity. The excellent OER performance of the Co0.1Mn0.9O-NF sample is also attributed to the rich active sites, which improved electrical conductivity and enlarged electrochemical surface areas.
BACKGROUND: Stringent nonpharmaceutical interventions (NPIs) have been implemented worldwide to combat the COVID-19 pandemic, and the circulation and seasonality of common respiratory viruses have subsequently changed. There have been few multicentre studies or comparisons of the prevalence of respiratory viruses accounting for community-acquired pneumonia (CAP) in hospitalized children between the pre-COVID period and the period after community and school reopening in the setting of the zero-COVID policy. METHODS: We included 1543 children with CAP who required hospitalization from November 1, 2020 to April 30, 2021 (period 1), and 629 children with the same conditions from November 1, 2018, to April 30, 2019 (period 2), in our study. All respiratory samples from these patients were screened for six respiratory viruses (respiratory syncytial virus [RSV], adenovirus [ADV], influenza A virus [Flu A], influenza B virus [Flu B], parainfluenza virus type 1 [PIV1], and parainfluenza virus type 3 [PIV3]) using a multiplex real-time PCR assay. RESULTS AND CONCLUSIONS: The median ages of the enrolled patients at the time of diagnosis were 1.5 years and 1.0 years for period 1 and period 2, respectively. In period 1, viral pathogens were detected in 50.3% (776/1543) of the enrolled patients. The most frequently identified viral pathogen was RSV (35.9%, 554/1543), followed by PIV3 (9.6%, 148/1543), PIV1 (3.6%, 56/1543), ADV (3.4%, 52/1543), Flu A (1.0%, 16/1543), and Flu B (0.8%, 13/1543). The total detection rates of these six viruses in the peak season of CAP were at the pre-COVID level. The prevalence of Flu A decreased dramatically, and circulation activity was low compared to pre-COVID levels, while the incidence of PIV3 increased significantly. There were no significant differences in the detection rates of RSV, ADV, Flu B, and PIV1 between the two periods. Our results showed that respiratory viruses accounted for CAP in hospitalized children at pre-COVID levels as communities and schools reopened within the zero-COVID policy, although the prevalence aetiology spectrum varied.
Adenoviridae Infections , COVID-19 , Pneumonia , Respiratory Syncytial Virus, Human , Respiratory Tract Infections , Humans , Child , Infant , Incidence , Pandemics , COVID-19/epidemiology , Respiratory Syncytial Virus, Human/genetics , Adenoviridae Infections/epidemiology , Hospitalization , China/epidemiology , Adenoviridae
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has becoming globally public health threat. Recently studies were focus on SARS-CoV-2 RNA to design vaccine and drugs. It was demonstrated that virus RNA could play as sponge to host noncoding RNAs to regulate cellular processes. Bioinformatic research predicted a series of motif on SARS-CoV-2 genome where are targets of human miRNAs. In this study, we used dual-luciferase reporter assays to validate the interaction between 3'UTR of SARS-CoV-2 S (S-3'UTR) gene and bioinformatic predicted targeting miRNAs. The growth of 293T cells and HUVECs with overexpressed S-3'UTR was determined, while miRNAs and IL6, TNF-α levels were checked in this condition. Then, miR-296 and miR-602 mimic were introduced into 293T cells and HUVECs with overexpressed S-3'UTR, respectively, to reveal the underlying regulation mechanism. In results, we screened 19 miRNAs targeting the S-3'UTR, including miR-296 and miR-602. In 293T cell, S-3'UTR could inhibit 293T cell growth through down-regulation of miR-296. By reducing miR-602, S-3'UTR could induce HUVECs cell proliferation, alter the cell cycle, reduce apoptosis, and enhanced IL6 and TNF-αlevel. In conclusion, SARS-CoV-2 RNA could play as sponge of host miRNA to disturb cell growth and cytokine signaling. It suggests an important clue for designing COVID-19 drug and vaccine.
COVID-19 , MicroRNAs , 3' Untranslated Regions , COVID-19/genetics , Cell Proliferation , Cytokines/genetics , Humans , Interleukin-6/genetics , Luciferases/genetics , MicroRNAs/metabolism , RNA, Viral , SARS-CoV-2 , Tumor Necrosis Factor-alpha/genetics
Adenoviruses are highly prevalent pathogens responsible for a wide range of clinical diseases, including respiratory tract infection, acute gastroenteritis, and conjunctivitis. However, adenovirus infection is rarely associated with central nervous system involvement. Here, we report a fatal viral sepsis and encephalitis in a child caused by a human adenovirus type 7 infection. We detected human adenovirus type 7 in the patient's nasopharyngeal swab, blood, and cerebrospinal fluid. Our findings indicate clinicians should be aware of the possible central nervous system involvement in adenovirus infection.
Adenoviridae Infections , Adenovirus Infections, Human , Adenoviruses, Human , Encephalitis , Adenoviridae Infections/complications , Adenoviridae Infections/diagnosis , Adenovirus Infections, Human/complications , Adenovirus Infections, Human/diagnosis , Adenoviruses, Human/genetics , Child , Humans , Viremia
Power generation by converting energy from the ambient environment has been considered a promising strategy for developing decentralized electrification systems to complement the electricity supply for daily use. Wet gases, such as water evaporation or moisture in the atmosphere, can be utilized as a tremendous source of electricity by emerging power generation devices, that is, moisture-enabled-electric nanogenerators (MEENGs). As a promising technology, MEENGs provided a novel manner to generate electricity by harvesting energy from moisture, originating from the interactions between water molecules and hydrophilic functional groups. Though the remarkable progress of MEENGs has been achieved, a systematic review in this specific area is urgently needed to summarize previous works and provide sharp points to further develop low-cost and high-performing MEENGs through overcoming current limitations. Herein, the working mechanisms of MEENGs reported so far are comprehensively compared. Subsequently, a systematic summary of the materials selection and fabrication methods for currently reported MEENG construction is presented. Then, the improvement strategies and development directions of MEENG are provided. At last, the demonstrations of the applications assembled with MEENGs are extracted. This work aims to pave the way for the further MEENGs to break through the performance limitations and promote the popularization of future micron electronic self-powered equipment.
Electric Power Supplies , Electricity , Electronics , Water
Human metapneumovirus (HMPV) infection is one of the leading causes of hospitalization in young children with acute respiratory illness. In this study, we prospectively collected respiratory tract samples from children who were hospitalized with acute lower respiratory tract infection in six hospitals in China from 2017 to 2019. HMPV was detected in 145 out of 2733 samples (5.3%) from the hospitalized children. The majority of HMPV-positive children were under the age of two (67.6%), with a median age of one year. HMPV can independently cause acute lower respiratory tract infection in young children, while all patients showed mild clinical symptoms. Of all the co-infected patients, HMPV was most commonly detected with enterovirus (EV) or rhinovirus (RhV) (38.0%, followed by respiratory syncytial virus (RSV) (32.0%). The highest detection rate occurred from March to May in both northern and southern China. Out of 145 HMPV positive samples, 48 were successfully typed, of which 36 strains were subgrouped into subtypes A2c (75%), eight strains were included in subtype B1 (16.7%), and four strains were included in subtype B2 (8.3%). Moreover, 16 A2c strains contained 111-nucleotide duplications in the G gene. Twenty-seven complete HMPV genomes were successfully obtained, and 25 (92.6%) strains belonged to subtype A2c, whereas one strain was included in subgroup B1 and another was included in subgroup B2. A total of 277 mutations were observed in the complete genomes of 25 A2c strains. All results presented here improve our understanding of clinical characteristics and molecular epidemiology of HMPV infection in children.
Metapneumovirus , Paramyxoviridae Infections , Respiratory Syncytial Virus Infections , Respiratory Tract Infections , Humans , Child , Infant , Child, Preschool , Metapneumovirus/genetics , Molecular Epidemiology , Paramyxoviridae Infections/epidemiology , China/epidemiology , Respiratory Syncytial Virus Infections/epidemiology
BACKGROUND: Rhinovirus is a common viral aetiology of upper respiratory infection and is mostly associated with common cold or flu-like illness. Although rhinovirus has been recognized as a pathogen for lower respiratory infections in severe cases credited to advances in molecular detection, central nervous system involvement and multiorgan dysfunction are extremely rare. CASE PRESENTATION: A previously healthy 10-year-old girl developed fever, sore throat and conjunctive injection after contact with an upper respiratory infection patient, followed by seizures, haematuria, and severe diarrhoea. She experienced viral sepsis and multiorgan dysfunction after admission. Cerebral computed tomography showed significant diffuse encephaledema. Cerebrospinal fluid analysis showed significantly elevated protein levels. After her consciousness disturbance improved, she still took a long time to recover from haematuria and diarrhoea. We identified a rarely reported rhinovirus A45 in her oropharyngeal and anal swabs by metagenomic next-generation sequencing, and bacterial culture of blood specimens yielded negative results. CONCLUSIONS: This case presents a patient with severe rhinovirus infection, which was very likely responsible for her central nervous system symptoms and viral sepsis.
Enterovirus , Picornaviridae Infections , Respiratory Tract Infections , Central Nervous System , Child , Diarrhea , Female , Hematuria/complications , Humans , Male , Picornaviridae Infections/complications , Picornaviridae Infections/diagnosis , Rhinovirus , Viremia
Powdery mildew has a negative impact on wheat growth and restricts yield formation. Therefore, accurate monitoring of the disease is of great significance for the prevention and control of powdery mildew to protect world food security. The canopy spectral reflectance was obtained using a ground feature hyperspectrometer during the flowering and filling periods of wheat, and then the Savitzky-Golay method was used to smooth the measured spectral data, and as original reflectivity (OR). Firstly, the OR was spectrally transformed using the mean centralization (MC), multivariate scattering correction (MSC), and standard normal variate transform (SNV) methods. Secondly, the feature bands of above four transformed spectral data were extracted through a combination of the Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA) algorithms. Finally, partial least square regression (PLSR), support vector regression (SVR), and random forest regression (RFR) were used to construct an optimal monitoring model for wheat powdery mildew disease index (mean disease index, mDI). The results showed that after Pearson correlation, two-band optimization combinations and machine learning method modeling comparisons, the comprehensive performance of the MC spectrum data was the best, and it was a better method for pretreating disease spectrum data. The transformed spectral data combined with the CARS-SPA algorithm was able to extract the characteristic bands more effectively. The number of bands screened was more than the number of bands extracted by the OR data, and the band positions were more evenly distributed. In comparison of different machine learning modeling methods, the RFR model performed the best (coefficient of determination, R 2 = 0.741-0.852), while the SVR and PLSR models performed similarly (R 2 = 0.733-0.836). Taken together, the estimation accuracy of spectral data transformation using the MC method combined with the RFR model (MC-RFR) was the highest, the model R 2 was 0.849-0.852, and the root mean square error (RMSE) and the mean absolute error (MAE) ranged from 2.084 to 2.177 and 1.684 to 1.777, respectively. Compared with the OR combined with the RFR model (OR-RFR), the R 2 increased by 14.39%, and the R 2 of RMSE and MAE decreased by 23.9 and 27.87%. Also, the monitoring accuracy of flowering stage is better than that of grain filling stage, which is due to the relative stability of canopy structure in flowering stage. It can be seen that without changing the shape of the spectral curve, and that the use of MC to preprocess spectral data, the use of CARS and SPA algorithms to extract characteristic bands, and the use of RFR modeling methods to enhance the synergy between multiple variables, and the established model (MC-CARS-SPA-RFR) can better extract the covariant relationship between the canopy spectrum and the disease, thereby improving the monitoring accuracy of wheat powdery mildew. The research results of this study provide ideas and methods for realizing high-precision remote sensing monitoring of crop disease status.
Respiratory syncytial virus (RSV) is a common cause of lower respiratory tract infections and responsible for a large proportion of mortality in children and the elderly. There are no licensed vaccines available to date. Prophylaxis and therapeutic RSV-specific antibodies are limited to populations at high risk owing to high cost and uncertain clinical value. Receptors and host factors are two determinants important for virus entry and establishment of infection in vivo. The identification and understanding of viral receptors and host factors can help us to gain insight into the pathogenesis of RSV infection. Herein, we reviewed receptors and host factors that have been reported thus far. RSV could bind to CX3C chemokine receptor 1 and heparan sulfate proteoglycans via the G protein, and to nucleolin, insulin-like growth factor-1 receptor, epidermal growth factor, and intercellular adhesion molecule-1 via the F protein. Seven host restriction factors and 13 host factors essential for RSV infection were reviewed. We characterized the functions and their roles in the life cycle of RSV, trying to provide an update on the information of RSV-related receptors and host factors.
Respiratory Syncytial Virus Infections , Respiratory Syncytial Virus, Human , Antibodies, Viral , Epidermal Growth Factor/metabolism , Humans
Present evidence outlining the association between different types of phytoestrogens and depressive symptoms in the general population is limited and contradictory. Data from the 2007-2010 National Health and Nutrition Examination Survey (NHANES) were used to examine their association. Phytoestrogens were measured in urine samples and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Logistic regression and restricted cubic spline models were used to evaluate associations. In one model, lignans and enterolactone were inversely associated with the prevalence of depressive symptoms. Compared with the lowest quartile (Q1), the odds ratios (ORs; 95% confidence intervals [CIs]) for participants in the highest quartile of lignans and enterolactone were 0.44 (0.27-0.72) and 0.42 (0.26-0.67) for depressive symptoms, respectively. Additionally, the dose-response relationships between urinary lignans or enterolactone and depressive symptoms showed a linear trend. Our results suggest that urinary lignans and enterolactone are inversely associated with the prevalence of depressive symptoms.
Lignans , Phytoestrogens , Depression/epidemiology , Humans , Nutrition Surveys , Odds Ratio
Real-time non-destructive monitoring of water use efficiency (WUE) is important for screening high-yielding high-efficiency varieties and determining the rational allocation of water resources in winter wheat production. Compared with vertical observation angles, multi-angle remote sensing provides more information on mid to lower parts of the wheat canopy, thereby improving estimates of physical and chemical indicators of the entire canopy. In this study, multi-angle spectral reflectance and the WUE of the wheat canopy were obtained at different growth stages based on field experiments carried out across 4 years using three wheat varieties under different water and nitrogen fertilizer regimes. Using appropriate spectral parameters and sensitive observation angles, the quantitative relationships with wheat WUE were determined. The results revealed that backward observation angles were better than forward angles, while the common spectral parameters Lo and NDDAig were found to be closely related to WUE, although with increasing WUE, both parameters tended to become saturated. Using this data, we constructed a double-ratio vegetation index (NDDAig/FWBI), which we named the water efficiency index (WEI), reducing the impact of different test factors on the WUE monitoring model. As a result, we were able to create a unified monitoring model within an angle range of -20-10°. The equation fitting determination coefficient (R 2) and root mean square error (RMSE) of the model were 0.623 and 0.406, respectively, while an independent experiment carried out to test the monitoring models confirmed that the model based on the new index was optimal, with R 2, RMSE, and relative error (RE) values of 0.685, 0.473, and 11.847%, respectively. These findings suggest that the WEI is more sensitive to WUE changes than common spectral parameters, while also allowing wide-angle adaptation, which has important implications in parameter design and the configuration of satellite remote sensing and UAV sensors.
Powdery mildew severely affects wheat growth and yield; therefore, its effective monitoring is essential for the prevention and control of the disease and global food security. In the present study, a spectroradiometer and thermal infrared cameras were used to obtain hyperspectral signature and thermal infrared images data, and thermal infrared temperature parameters (TP) and texture features (TF) were extracted from the thermal infrared images and RGB images of wheat with powdery mildew, during the wheat flowering and filling periods. Based on the ten vegetation indices from the hyperspectral data (VI), TF and TP were integrated, and partial least square regression, random forest regression (RFR), and support vector machine regression (SVR) algorithms were used to construct a prediction model for a wheat powdery mildew disease index. According to the results, the prediction accuracy of RFR was higher than in other models, under both single data source modeling and multi-source data modeling; among the three data sources, VI was the most suitable for powdery mildew monitoring, followed by TP, and finally TF. The RFR model had stable performance in multi-source data fusion modeling (VI&TP&TF), and had the optimal estimation performance with 0.872 and 0.862 of R2 for calibration and validation, respectively. The application of multi-source data collaborative modeling could improve the accuracy of remote sensing monitoring of wheat powdery mildew, and facilitate the achievement of high-precision remote sensing monitoring of crop disease status.
Ascomycota , Triticum , Disease Resistance , Humans , Least-Squares Analysis , Plant Diseases
