Great Potential For Widespread Application Research Articles

An improved remote sensing reference evapotranspiration estimation by simple satellite data and machine learning

Reference evapotranspiration (ET0) estimation is crucial for efficient irrigation planning, optimized water management and ecosystem modeling, yet it presents significant challenges, particularly when meteorological data availability is limited. This study utilized remote sensing data of land surface temperature (LST), day of year, and latitude, and employed a machine learning approach (e.g., random forest) to develop an improved remote sensing ET0 model. The model performed excellently in 567 meteorological stations in China with an R2 of 0.97, RMSE of 0.40, MBE of 0.00, and MAPE of 0.11 compared to the FAO-PM ET0; it also performed well globally, yielding an average R2 of 0.97 and RMSE of 0.43 across 120 sites in mid-latitude (20°-50°) regions. This model demonstrates simplicity, accuracy, robust and generalization, holding great potential for widespread application, especially in the large-scale, high-resolution estimation of ET0. This study will contribute to advancements in water resources management, agricultural planning, and climate change studies

Improved remote sensing reference evapotranspiration estimation using simple satellite data and machine learning

Reference evapotranspiration (ET0) estimation is crucial for efficient irrigation planning, optimized water management and ecosystem modeling, yet it presents significant challenges, particularly when meteorological data availability is limited. This study utilized remote sensing data of land surface temperature (LST), day of year, and latitude, and employed a machine learning approach (i.e., random forest) to develop an improved remote sensing ET0 model. The model performed excellently in 567 meteorological stations in China with an R2 of 0.97, RMSE of 0.40, MBE of 0.00, and MAPE of 0.11 compared to the FAO-PM ET0; it also performed well globally, yielding an average R2 of 0.97 and RMSE of 0.43 across 120 sites in mid-latitude (20°-50°) regions. This model demonstrates simplicity, accuracy, robust and generalization, holding great potential for widespread application, especially in the large-scale, high-resolution estimation of ET0. This study will contribute to advancements in water resources management, agricultural planning, and climate change studies

Different wettability surfaces composited by polydopamine-based SiO2/TiO2 coatings for efficient water collection and anti-corrosion application

Designing hybrid surfaces with superhydrophilic and superhydrophobic properties represents a promising approach for fog collection. Inspired by the adhesive properties of mussel proteins, a polydopamine (PDA) film was firmly attached to a brass surface through a combination of chemical etching and spontaneous dopamine polymerization. By harnessing the exceptional characteristics of PDA as a "double-sided adhesive," a hybrid surface with mixed wettability was created using a facile and cost-effective method involving SiO2 and TiO2 nanoparticles (NPs). The TiO2 NPs served as the hydrophilic sites for water capture, while the SiO2 NPs acted as the hydrophobic region to induce water droplet rolling. The resulting hybrid surface exhibited a significant improvement in water collection rate, measuring approximately 1.182 g/cm2/h, which was 1.84 times higher than that of the bare brass surface. This demonstrated a remarkable enhancement in fog collection capacity. Moreover, the hybrid surface demonstrated commendable corrosion resistance and remarkable durability, indicating its great potential for widespread application in practical scenarios.

Label-free and selective heparin detection by surface functionalized fiber Fabry-Perot interferometer biosensor

Heparin (Hep) is the most commonly used anticoagulant drug in clinical settings, and precise dosage control is crucial. To enable rapid and accurate quantification of Hep concentration in clinical practice, a label-free and selective fiber-optic Fabry-Perot interferometric (FPI) biosensor detection method based on graphene oxide (GO) was proposed. This method utilizes protamine (PRTM) sulfate as the modified layer and achieves Hep detection through layer-by-layer (LBL) assembly. In this study, we developed a label-free and selective fiber optic FPI biosensor for the detection of Hep using GO. The GO on the surface layer of the fiber optic FPI biosensor was treated with specific functionalization, it enables specific interaction with Hep. The binding of Hep to the functionalized surface induces a change in the luminal light signal, which can be monitored within the cavity for rapid and accurate detection of Hep. The results demonstrate that this biosensor exhibits good sensitivity, with a value of 10.82 nm/mM in the low-concentration control group, and an average limit of detection (LOD) calculated as 31μg/mL in the low-concentration group. This study presents a label-free, selective and efficient method for biomedical science testing that holds great potential for widespread application in clinical medicine.

A polynomial model with line-of-sight constraints for Lagrangian particle tracking under interface refraction

This paper introduces an improvement of the ‘shake-the-box (STB)’ (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) technique using the polynomial calibration model and the line-of-sight constraints (LOSC) to overcome the refractive interface issues in Lagrangian particle tracking (LPT) measurement. The method (named LOSC-LPT) draws inspiration from the two-plane polynomial camera calibration in tomographic particle image velocimetry (Worth, Nickels, Thesis, 2010) and the STB-based open-source Lagrangian particle tracking (OpenLPT) framework (Tan, Salibindla, Masuk, and Ni, Exp. Fluids 61.2, 2019). The LOSC-LPT introduces polynomial mapping functions into STB calibration in conditions involving gas–solid–liquid interfaces at container walls exhibiting large refractive index variations, which facilitates the realization of particle stereo matching, three-dimensional (3D) triangulation, iterative particle reconstruction, and further refinement of 3D particle position by shaking the LOS. Performance evaluation based on synthetic noise-free images with a particle image density of 0.05 particle per pixel in the presence of refractive interfaces demonstrates that LOSC-LPT can detect a higher number of particles and exhibits lower position uncertainty in the reconstructed particles, resulting in higher accuracy and robustness than that achieved with OpenLPT. In the application to an elliptical jet flow in an octagonal tank with refractive interfaces, the use of polynomial mapping results in smaller errors (mean calibration error <0.1 px) and thus more long trajectories identified by LOSC-LPT (13 000) compared with OpenLPT (4500) which uses the pinhole Tsai model (mean calibration error >1.0 px). Moreover, 3D flow-field reconstructions demonstrate that the LOSC-LPT framework can recover a more accurate 3D Eulerian flow field and capture more complete coherent structures in the flow, and thus holds great potential for widespread application in 3D experimental fluid measurements.

Large-FOV 3D localization microscopy by spatially variant point spread function generation.

Accurate characterization of the microscopic point spread function (PSF) is crucial for achieving high-performance localization microscopy (LM). Traditionally, LM assumes a spatially invariant PSF to simplify the modeling of the imaging system. However, for large fields of view (FOV) imaging, it becomes important to account for the spatially variant nature of the PSF. Here, we propose an accurate and fast principal components analysis-based field-dependent 3D PSF generator (PPG3D) and localizer for LM. Through simulations and experimental three-dimensional (3D) single-molecule localization microscopy (SMLM), we demonstrate the effectiveness of PPG3D, enabling super-resolution imaging of mitochondria and microtubules with high fidelity over a large FOV. A comparison of PPG3D with a shift-variant PSF generator for 3D LM reveals a threefold improvement in accuracy. Moreover, PPG3D is approximately 100 times faster than existing PSF generators, when used in image plane-based interpolation mode. Given its user-friendliness, we believe that PPG3D holds great potential for widespread application in SMLM and other imaging modalities.

Highly stable and antifungal properties on the oilseed rape of Cu3(MoO4)2(OH)2 nanoflakes prepared by simple aqueous precipitation

In the last few decades, nanoparticles have been a prominent topic in various fields, particularly in agriculture, due to their unique physicochemical properties. Herein, molybdenum copper lindgrenite Cu3(MoO4)2(OH)2 (CM) nanoflakes (NFs) are synthesized by a one-step reaction involving α-MoO3 and CuCO3⋅Cu(OH)2⋅xH2O solution at low temperature for large scale industrial production and developed as an effective antifungal agent for the oilseed rape. This synthetic method demonstrates great potential for industrial applications. Infrared spectroscopy and X-ray diffraction (XRD) results reveal that CM samples exhibit a pure monoclinic structure. TG and DSC results show the thermal stable properties. It can undergo a phase transition form copper molybdate (Cu3Mo2O9) at about 300 °C. Then Cu3Mo2O9 nanoparticles decompose into at CuO and MoO3 at 791 °C. The morphology of CM powder is mainly composed of uniformly distributed parallelogram-shaped nanoflakes with an average thickness of about 30 nm. Moreover, the binding energy of CM NFs is measured to be 2.8 eV. To assess the antifungal properties of these materials, both laboratory and outdoor experiments are conducted. In the pour plate test, the minimum inhibitory concentration (MIC) of CM NFs against Sclerotinia sclerotiorum (S. sclerotiorum) is determined to be 100 ppm, and the zone of inhibiting S. sclerotiorum is 14 mm. When the concentration is above 100 nm, the change rate of the hyphae circle slows down a little and begins to decrease until to 200 ppm. According to the aforementioned findings, the antifungal effects of a nano CM NFs solution are assessed at different concentrations (0 ppm (clear water), 40 ppm, and 80 ppm) on the growth of oilseed rape in an outdoor setting. The results indicate that the application of CM NFs led to significant inhibition of S. sclerotiorum. Specifically, when the nano CM solution was sprayed once at the initial flowering stage at a concentration of 80 ppm, S. sclerotiorum growth was inhibited by approximately 34%. Similarly, when the solution was sprayed once at the initial flowering stage and once at the rape pod stage, using a concentration of 40 ppm, a similar level of inhibition was achieved. These outcomes show that CM NFs possess the ability to bind with more metal ions due to their larger specific surface area. Additionally, their semiconductor physical properties enable the generation of reactive oxygen species (ROS). Therefore, CM NFs hold great potential for widespread application in antifungal products.

Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy

The accurate evaluation of wake turbulence intensity (TI) is of great significance for the layout optimization of wind farms and research on control strategies. However, the existing engineering wake models still have many shortcomings in evaluating the TI in the wake of horizontal-axis wind turbines (HAWTs), especially in the near wake region. In response to this, this article proposed an analytical model based on the double-Gaussian ellipse function that can describe the three-dimensional added TI distribution in the entire wake region. Firstly, the anisotropy of wake expansion is taken into account in both the horizontal and vertical directions, assuming that the added TI distribution downstream of the HAWT is a double-Gaussian elliptical shape. Secondly, taking into account the self-similarity characteristics of flow TI, the maximum added TI and its position in the entire wake region are evaluated. In addition, considering the influence of the ground effect, the vertical turbulence distribution was corrected. Finally, the proposed added turbulence model was validated and relative error analysis was conducted using large eddy simulation (LES) data, wind field measurement data, and wind tunnel experimental data. The results show that the model had good prediction accuracy in the entire wake region, and its prediction performance was significantly improved compared to traditional models, especially in the near wake region, with the lowest even relative error of 3.66%. This model has significant advantages such as low computational cost, wide applicability, and high accuracy. It can reduce energy losses in wind farms, improve wind energy utilization efficiency, and has great potential for widespread application in large-scale wind farms.

Solvent-free polyurethane coatings based on an in-situ curing strategy at room temperature with self-cleaning, anti-corrosion and anti-graffiti properties

Anti-smudge coatings have attracted extensive attention in recent years owing to their hydrophobic, self-cleaning, anti-graffiti properties and so on. However, most of the anti-smudge coatings are solvent-based and cured at high temperature or using special curing equipment, which negatively impacts the environment and limits their large-scale application in daily life. Herein, we report a solvent-free anti-smudge coating with potential for large-scale and green manufacturing. In detail, polydimethylsiloxane (PDMS) was used as the hydrophobic component, (3-aminopropyl)triethoxysilane (APTES) and 3-glycidoxypropyltrimethoxysilane (GPTMS) were used as the cross-linking agent, and a solvent-free polyurethane (SFPU) anti-smudge coating was in-situ constructed at room temperature for 24 h without any curing equipment. Due to the enrichment of PDMS chains on the surface and the dense cross-linked network of the coating, the as-prepared coating not only exhibited a high contact angle for water (99.3 ± 1.5°) and diiodomethane (69.5 ± 0.9°), but also excellent anti-smudge to contaminants, with both water and oily liquids were easy to slide off the surface of the coating without leaving any traces. Even after writing with an oil-based marker, the ink on the coated surface could be easily wiped off. Further study reveals that the coating surface maintained its original liquid repellency and stain resistance even after 10 d immersion in a 10 wt% NaCl solution, showing durable anti-corrosion properties. In addition, pigments did not affect the anti-graffiti performance of the coating, providing a multi-color scheme for practical application. This convenient, low-energy, environmentally friendly anti-smudge coating has great potential for widespread application in industry and daily life.

Kapok derived microtubular FeCo/CMT with high specific surface area for broadband microwave absorption

Since biomass-derived carbon materials possess the advantages of peculiar morphology and low density. They have received significant attention on microwave absorption materials. We synthesize a one-dimensional hollow FeCo/carbon microtubule (FeCo/CMT) derived from homogeneous kapok fiber using a feasible solvothermal method and calcination process. The graphitization degree and magnetic properties of FeCo/CMT could be controlled by manipulating the calcination temperature. The FeCo/CMT composite with the calcination temperature of 600 °C demonstrated exceptional microwave absorption performance, characterized by strong absorption (−50.6 dB), broadband absorption (12.4–18.0 GHz), thin thickness (2.5 mm), and low loading (10 wt%). The hollow structure, interfacial polarization, and the synergistic effect between FeCo and CMT collectively account for the microwave absorption mechanisms. Considering its outstanding comprehensive characteristics and performance, the biomass-derived hollow FeCo/CMT shows great potential for widespread application as a high-performance microwave absorption material.

Novel fabric-based 3D photothermal evaporator with advanced light-harvesting and thermal management design

Interfacial photothermal evaporation offers a promising and cost-effective method of obtaining freshwater. Traditional photothermal evaporators, when exposed to sunlight, typically have a heating region on their surface with temperature higher than room temperature. This can lead to thermal radiation loss and reduce evaporation efficiency. Therefore, this study presents an innovative design and fabrication of a fabric-based conical roll (FCR) evaporator, which enables low-temperature evaporation without a distinct heating region and facilitates the reversal of the thermal radiation path. In particular, the FCR-7.5-45 evaporator demonstrated remarkable performance even under 2.0 sun illumination, showcasing its advanced light-harvesting capability and excellent thermal management ability attributable to the conical spiral groove structure. The unique cold evaporation surface of the 3D evaporators, combined with this design, resulted in a high evaporation efficiency of 151.53 % and a rapid evaporation rate of 3.47 kg·m−2·h−1 under 1.0 sun illumination. Furthermore, the freshwater produced by the FCR evaporator met the drinking water standards set by international regulatory bodies. This indicates that the photothermal evaporator developed in this project holds great potential for widespread application in desalination and sewage treatment.

Study of γ-Ray Spectrum Measurement Analysis Algorithm of Radioactive Solid Waste Steel Boxes

Abstract In accordance with safety requirements for the near-surface disposal of low and medium-level radioactive solid waste, accurate identification and measurement of radionuclide types and activities within steel boxes containing such waste are necessary. Conventional sampling techniques are impractical due to nonuniform internal filling and radioactive distribution in the steel boxes used for storage. Nondestructive measurement analysis techniques offer significant advantages by providing comprehensive measurements without causing damage to the steel boxes or generating secondary waste. Therefore, nondestructive techniques are widely applicable and superior to chemical analysis methods. This study presents an algorithm for analyzing γ-ray spectrum measurements of radioactive solid waste steel boxes by combining the traditional computed tomography (CT) principle with a discrete treatment approach. The progressive split voxel measurement method is utilized to discretely handle the radioactive solid waste steel boxes during the measurement and calculation process while considering the impact of voxel interactions on detection efficiency. A detection efficiency calibration model is established using Monte Carlo (MC) simulation in conjunction with the algebraic reconstruction technique (ART). Additionally, an inversion correction of the efficiency for the physically coincident portion of the detected voxel volume is performed during the measurement process. The proposed algorithm is initially applied to the analysis platform of steel boxes that store FA-IV-type radioactive solid waste. The algorithm's performance is further investigated and validated using standard radioactive sources with known activity levels. The results indicate that the relative deviation between the reconstruction results and the nominal values of radioactive activities in the steel boxes is less than 30%. These findings align with the expected results and satisfy the measurement analysis and warehousing processing requirements for waste generated from the decommissioning of China's 101 nuclear reactor. The proposed algorithm holds great potential for widespread application in related detection work.

Superelastic and thermal insulating multilayer organic-inorganic hybrid aerogel built from boron nitride nanoribbons and aramid nanofibers

Thermally insulating aramid nanofiber (ANF) aerogels enable a wide range of applications but are limited by their low mechanical elasticity. Efficient design of aerogels’ components and microstructures is crucial yet remains highly challenging for effectively improving the flexibility of ANF aerogels. Here, for the first time, we report the incorporation of boron nitride nanoribbons (BNNRs) into ANF aerogel to form a multilayer BNNR/ANF hybrid aerogel, which is prepared by suspension mixing of BNNRs and ANFs followed by a vacuum-assisted and directional solidification process. Flexible BNNRs with a high aspect ratio are uniformly embedded in the ANF networks, giving the ANF aerogel an extremely high mechanical deformability (up to 60 % compressive strain), capable of retaining its elasticity even after 100 compression cycles or in liquid N2 (−196 °C). Moreover, the introduction of BNNRs does not reduce the thermal insulation capacity of ANF aerogels, while significantly improving their thermal stability and fire resistance. These excellent multifunctionality benefits from the synergistic effect of organic–inorganic components and the multilayer structure of aerogel. This work paves the avenue for developing next-generation elastic and thermal insulating materials with great potential for widespread applications.

A stable dual LiAlO2/Li2SiO3 coating LiNi0.8Co0.1Mn0.1O2 cathode towards ultra-long-life and wide-temperature lithium-ion battery

Ni-rich layered LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode material offers great potential for widespread applications due to its high capacity, non-toxicity, and low cost. However, the instability of the structure, large polarization and occurrence of side reactions during charge-discharge cycles greatly restrict the performance of LiNi0.8Co0.1Mn0.1O2. The stability of NCM811 can be improved through surface coating, but single-phase coating cannot achieve both high electronic conductivity and enhanced Li+ diffusion. Herein, LiAlO2 and Li2SiO3 are applied to prepare dual coating NCM811 (AS-NCM811) and build 3D Li+ diffusion channels and surface protection to improve both Li+ diffusion efficiency and electronic conductivity of NCM811. In addition, using LiAlO2 and Li2SiO3 in AS-NCM811 can enhance structural stability and reduce the likelihood of undesired side reactions occurring, which is verified by ex-situ X-ray diffraction and transmission electron microscopy. As a result, the AS-NCM811-based battery exhibits a remarkable cyclic ability and rate performance in widen temperature range (room temperature (RT) to 55 °C). AS-NCM811 shows an RT initial discharge capacity of 180.8 mAh g−1, while achieve a high-capacity retention of 92.6 % (100 cycles, 1C). Even at 55 °C, AS-NCM811 also retains 68.4 % of its capacity (143.5 mAh g−1) after 200 cycles under 1C. Overall, these findings pave a novel dual-coating way for the application of Ni-rich layered cathodes in high energy-density lithium-ions battery.

Graphene Oxide and Polymer Humidity Micro-Sensors Prepared by Carbon Beam Writing.

In this study, novel flexible micro-scale humidity sensors were directly fabricated in graphene oxide (GO) and polyimide (PI) using ion beam writing without any further modifications, and then successfully tested in an atmospheric chamber. Two low fluences (3.75 × 1014 cm-2 and 5.625 × 1014 cm-2) of carbon ions with an energy of 5 MeV were used, and structural changes in the irradiated materials were expected. The shape and structure of prepared micro-sensors were studied using scanning electron microscopy (SEM). The structural and compositional changes in the irradiated area were characterized using micro-Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), Rutherford back-scattering spectroscopy (RBS), energy-dispersive X-ray spectroscopy (EDS), and elastic recoil detection analysis (ERDA) spectroscopy. The sensing performance was tested at a relative humidity (RH) ranging from 5% to 60%, where the electrical conductivity of PI varied by three orders of magnitude, and the electrical capacitance of GO varied in the order of pico-farads. In addition, the PI sensor has proven long-term sensing stability in air. We demonstrated a novel method of ion micro-beam writing to prepare flexible micro-sensors that function over a wide range of humidity and have good sensitivity and great potential for widespread applications.

Prussian blue analog-derived nickel iron phosphide-reduced graphene oxide hybrid as an efficient catalyst for overall water electrolysis

Efficient and bifunctional nonprecious catalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) are essential for the production of green hydrogen via water electrolysis. Transition metal (Ni, Co, Fe, etc.) phosphides are frequently documented HER catalysts, whereas their bimetallic oxides are efficient OER catalysts, thus enabling bifunctional catalysis for water electrolysis via proper operation. Herein, phosphide-reduced graphene oxide (rGO) hybrids were prepared from graphene oxide (GO)-incorporated bimetal Prussian blue analog (PBA) precursors. The hybrids could experience partial surface oxidation to create oxide layers with OER activities, and the hybrids also possessed considerable HER properties, therefore enabling bifunctional catalytic features for water electrolysis. The typical NiFeP-rGO hybrid demonstrated an overpotential of 250 mV at 10 mA cm−2 and good durability for OER, as well as moderate HER catalytic features (overpotential of 165 mV at −10 mA cm−2 and acceptable catalytic stability). Due to the bifunctional catalytic features, the NiFeP-rGO-based symmetric water electrolyzer demonstrated a moderate input voltage and high faradaic efficiency (FE) for O2 and H2 production. The current work provides a feasible way to prepare OER and HER bifunctional catalysts by facile phosphorization of PBA-associated precursors and spontaneous surface oxidation. Given the oxidation/reduction bifunctional catalytic behaviors, phosphide-rGO hybrid catalysts have great potential for widespread application in fields beyond water electrolysis, such as electrochemical pollution abatement, sensors, energy devices and organic syntheses.

Mechanical Properties of Metal Matrix Composites: Short Review

This paper provides an overview of the increasing R&amp;D activity in metal matrix composites worldwide, with a particular focus on cast particulate metal matrix composites. Large-scale applications of cast aluminum alloy MMCs in everyday use in the transportation and consumer durables industries are expected to advance rapidly over the next decade. India has great potential for widespread application of cast composites, especially in the fields of transportation, energy and electrical machinery. Widespread use of composites can result in significant material and energy savings and, in some cases, reduced pollution. It is important to organize engineering education and short courses to make students and engineering professionals aware of his MMC. India already has an excellent infrastructure for composites development and a long track record of world-class cast metal matrix composites research. Today there is a need to catalyze prototypes and series production of selected composite components and use them in various sectors, especially in railways, cars, trucks, buses, scooters and other electrical machines. This requires a well-funded strategy to bring together the world-class foundry composites talent already present in India to form a viable development group. We will then establish a manufacturing facility that incorporates the process engineering capabilities that already exist in the country. Cast composites must be developed for use in power generation equipment, aerospace electronic packaging systems, and smart structures.

Band Alignment Engineering of Semiconductor Nanocrystal Heterostructures Toward Emerging Applications

Due to the superb tunable properties of quantum dots (QDs), they have been largely studied in the past few decades for many promising applications. However, for a single nanocrystal QD, its properties are largely limited due to limited tunability of the composition, charge carrier dynamics, band alignment, and so on. Thus, to solve the problem, and enhance their physical, chemical, electrical, and optical properties, the heterostructure nanocrystals (NCs), which combine single NCs with other materials of either semiconductor or metal, are proposed. In these heterostructures, their properties can be modified through tailoring the band alignment, and therefore providing a great potential for widespread applications. Here, an overview of strategies for band alignment engineering, synthesis methods, and the corresponding applications, such as lighting devices, lasers, photocatalysis, biological applications are offered.

Remote sensing image gap filling based on spatial-spectral random forests

Remote sensing images play a significant role in global land cover monitoring. However, due to the influence of cloud contamination, optical remote sensing images inevitably contain a large number of missing data, which severely limits their applicability. Existing cloud removal methods generally use only the effective information from a single band of temporally close known images, which is insufficient to predict accurately the changes between the known and cloudy images. In this paper, we proposed a spatial-spectral random forest (SSRF) method for thick cloud removal by gap filling, which uses spatially adjacent and multispectral information of known images simultaneously based on random forests. With its capability to fit nonlinear relations and adaptively assign variable contributions, SSRF can handle the potentially complex relationship between the known and cloudy images, thus, producing more accurate predictions. Based on the Landsat 8 OLI and Sentinel-2 MSI data in 13 regions, the effectiveness of SSRF was demonstrated through experiments on both simulated and real cloudy images. The results show that in urban areas with strong heterogeneity and agricultural areas with complex temporal changes, SSRF can yield satisfactory predictions both visually and quantitatively. Moreover, SSRF is more accurate than two popular benchmark methods. In addition, SSRF is less affected by cloud size and the time interval between the known and cloudy images, and can still produce reliable predictions when the used known images are also contaminated by clouds which reduce the amount of available neighborhood information. SSRF is also less affected by the omission error in cloud detection caused by thin clouds. SSRF is simple to implement and has great potential for widespread application.

Applications of THz Spectral Imaging in the Detection of Agricultural Products

Agricultural products need to be inspected for quality and safety, and the issue of safety of agricultural products caused by quality is frequently investigated. Safety testing should be carried out before agricultural products are consumed. The existing technologies for inspecting agricultural products are time-consuming and require complex operation, and there is motivation to develop a rapid, safe, and non-destructive inspection technology. In recent years, with the continuous progress of THz technology, THz spectral imaging, with the advantages of its unique characteristics, such as low energies, superior spatial resolution, and high sensitivity to water, has been recognized as an efficient and feasible identification tool, which has been widely used for the qualitative and quantitative analyses of agricultural production. In this paper, the current main performance achievements of the use of THz images are presented. In addition, recent advances in the application of THz spectral imaging technology for inspection of agricultural products are reviewed, including internal component detection, seed classification, pesticide residues detection, and foreign body and packaging inspection. Furthermore, machine learning methods applied in THz spectral imaging are discussed. Finally, the existing problems of THz spectral imaging technology are analyzed, and future research directions for THz spectral imaging technology are proposed. Recent rapid development of THz spectral imaging has demonstrated the advantages of THz radiation and its potential application in agricultural products. The rapid development of THz spectroscopic imaging combined with deep learning can be expected to have great potential for widespread application in the fields of agriculture and food engineering.