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Optical frequency combs have emerged as a new generation of metrological tools, driving advancements in various fields such as free-space two-way time–frequency transfer, low-noise microwave source generation, and gas molecule detection. Among them, fiber combs based on erbium-doped fiber mode-locked lasers have garnered significant attention due to their numerous advantages, including low noise, high system integration, and cost-effectiveness. In this review, we discuss recent developments in erbium-doped fiber combs and analyze the advantages and disadvantages of constructing fiber combs utilizing different erbium-doped mode-locked fiber lasers. First, we provide a brief introduction to the basic principles of optical frequency combs. Then, we explore erbium-doped fiber combs implemented utilizing various mode-locking techniques, such as nonlinear polarization rotation (NPR), real saturable absorber (SA), and nonlinear amplifying loop mirror (NALM). Finally, we present an outlook on the future perspectives of erbium-doped fiber combs.

As part of China’s Tianwen-1 Mars mission, the Mars Surface Composition Detector (MarSCoDe) instrument on the Zhurong rover adopts laser-induced breakdown spectroscopy (LIBS) to perform chemical component detection of the materials on the Martian surface. However, it has always been a challenging issue to achieve high accuracy in LIBS quantification. This study investigated the effect of chemometrics and spectral data preprocessing approaches on LIBS quantification accuracy based on different chemometrics algorithms and diverse preprocessing methods. A total of 2340 LIBS spectra were collected from 39 kinds of geochemical samples by a laboratory duplicate model of the MarSCoDe instrument. The samples and the MarSCoDe laboratory model were placed in a simulated Martian atmosphere environment based on equipment called the Mars-Simulated Detection Environment Experiment Platform (MarSDEEP). To quantify the concentration of MgO in the samples, we employed two common LIBS chemometrics; i.e., partial least squares (PLS) and a back-propagation neural network (BPNN). Meanwhile, in addition to necessary routine preprocessing such as dark subtraction, we used five specific preprocessing approaches, namely intensity normalization, baseline removal, Mg-peak wavelength correction, Mg-peak feature engineering, and concentration range reduction. The results indicated that the performance of the BPNN was better than that of the PLS and that the preprocessing of Mg-peak wavelength correction had the most prominent effect to improve the quantification accuracy. The results of this study are expected to provide inspiration for the processing and analysis of the in situ LIBS data acquired by MarSCoDe on Mars.

Artificial nanostructures with large optical chiral responses have been intensively investigated recently. In this work, we propose a diffractive circular dichroism enhancement technique using stereoscopic plasmonic molecule structures. According to the multipole expansion analysis, the z-component of the electric dipole becomes the dominant chiral scattering mechanism during the interaction between an individual plasmonic molecule and the plane wave at a grazing angle. For a periodical structure with the designed plasmonic molecule, large diffractive circular dichroism can be obtained, which can be associated with the Wood–Rayleigh anomaly. Such a diffractive circular dichroism enhancement is verified by the good agreement between numerical simulations and experimental results. The proposed approach can be potentially used to develop enhanced spectroscopy techniques to measure chiral information, which is very important for fundamental physical and chemical research and bio-sensing applications.

Rhizobia inoculation is widely used in legumes to improve the yield and quality of forage. However, the symbiotic interactions of different legumes are specific. The search for efficient strains plays an important role in legume forage and in practical production. In this study, Desmodium intortum was first inoculated with rhizobia from different regions, and then the production traits, nutritional quality, and fermentation of D. intortum in the rumen were evaluated according to the rhizobia strains. The results showed that, compared with the control, inoculation with different rhizobia strains significantly increased the number of nodules, shoot fresh weight, crude protein content, plant protein yield, and ether extract content of D. intortum, and inoculation with the R3 strain (Bradyrhizobium elkanii) increased these values by 61.0%, 29.6%, 16.1%, 62.9%, and 30.4%, respectively. In the basal diet of Pennisetum purpureum Rich. × P. americana King grass cv. Reyan No.4, D. intortum inoculated with different rhizobia was added (75:25), and the combination of the inoculated R3 and R5 strains increased the rumen’s ammonia-nitrogen (NH3-N) levels and in vitro dry matter digestibility (IVDMD): R3 increased the contents of NH3-N and IVDMD by 50.1% and 12.3%, respectively, while R5 increased them by 50.9% and 15.4%, respectively. Based on a comprehensive evaluation through principal component analysis, R3 was ranked first overall. These results support the development of competitive inoculants from indigenous strains as a strategy to improve the nutritional value of D. intortum and ruminal fermentation.

Photon-counting LiDAR can obtain long-distance, high-precision target3D geographic information, but extracting high-precision signal photons from background noise photons is the key premise of photon-counting LiDAR data processing and application. This study proposes an adaptive noise filtering algorithm that adjusts parameters according to the background photon count rate and removes noise photons based on the local mean Euclidean distance. A simulated photon library that provides different background photon count rates and detection probabilities was constructed. It was then used to fit the distribution relationship between the background photon count rate and the average KNN (K-Nearest Neighbor) distance (k = 2–6) and to obtain the optimal denoising threshold under different background photon count rates. Finally, the proposed method was evaluated by comparing it with the modified density-based spatial clustering (mDBSCAN) and local distance-based statistical methods. The experimental results show that various methods are similar when the background noise rate is high. However, at most non-extreme background photon count rate levels, the F of this algorithm was maintained between 0.97–0.99, which is an improvement over other classical algorithms. The new strategy eliminated the artificial introduction of errors. Due to its low error rates, the proposed method can be widely applied in photon-counting LiDAR signal extraction under various conditions.

A Mars Surface Composition Detector (MarSCoDe) instrument mounted on Zhurong rover of Tianwen-1, adopts Laser-Induced Breakdown Spectroscopy (LIBS), with no sample preparation or dust and coatings ablation required, to conduct rapid multi-elemental analysis and characterization of minerals, rocks and soils on the surface of Mars. To test the capability of MarSCoDe LIBS measurement and quantitative analysis, some methods of multivariate analysis on olivine samples with gradient concentrations were inspected based on the spectra acquired in a Mars-simulated environment before the rover launch in 2020. Firstly, LIBS spectra need preprocessing, including background subtraction, random signal denoising, continuum baseline removal, spectral drift correction and wavelength calibration, radiation calibration, and multi-channel spectra subset merging. Then, the quantitative analysis with univariate linear regression (ULR) and multivariate linear regression (MLR) are performed on the characteristic lines, while principal component regression (PCR), partial least square regression (PLSR), ridge, least-absolute-shrinkage-and-selection-operator (LASSO) and elastic net, and nonlinear analysis with back-propagation (BP) are conducted on the entire spectral information. Finally, the performance on the quantitative olivine analyzed by MarSCoDe LIBS is compared with the mean spectrum and all spectra for each sample and evaluated by some statistical indicators. The results show that: (1) the calibration curve of ULR constructed by the characteristic line of magnesium and iron indicates the linear relationship between the spectral signal and the element concentration, and the limits of detection of forsterite and fayalite is 0.9943 and 2.0536 (c%) analyzed by mean spectra, and 2.3354 and 3.8883 (c%) analyzed by all spectra; (2) the R2 value on the calibration and validation of all the methods is close to 1, and the predicted concentration estimated by these calibration models is close to the true concentration; (3) the shrinkage or regularization technique of ridge, LASSO and elastic net perform better than the ULR and MLR, except for ridge overfitting on the testing sample; the best results can be obtained by the dimension reduction technique of PCR and PLSR, especially with PLSR; and BP is more applicable for the sample measured with larger spectral dataset.

The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and reliable preprocessing methods to correct the spectral drift caused by the changes in environmental conditions, to ensure the analysis accuracy of LIBS scientific data. This paper focuses on the initial spectral drift correction and estimates the accuracy of on-board wavelength calibration on the LIBS calibration target measured by the MarSCoDe LIBS. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship has been changed, and a new on-board calibration is needed to establish the current relationship. An approach of matching based on global iterative registration (MGR) is presented in respect to case (a). It is also compared with the approach of particle swarm optimization (PSO) for case (b). Furthermore, their accuracy is estimated with the comparison to the National Institute of Standards and Technology (NIST) database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum. The the root-mean-square error (RMSE) of the internal accord accuracy for three channels is 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected Ti-alloy spectrum and the NIST database, and the RMSE of the external accord accuracy is 0.232, 0.316 and 0.229 pixels, respectively, for other samples. The overall correction accuracy of the three channels is better than one-third of the sampling interval.

Laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics is an efficient method for rock identification and classification, which has considerable potential in planetary geology. A great challenge facing the LIBS community is the difficulty to accurately discriminate rocks with close chemical compositions. A convolutional neural network (CNN) model has been designed in this study to identify twelve types of rock, among which some rocks have similar compositions. Both the training set and the testing set are constructed based on the LIBS spectra acquired by Mars Surface Composition Detector (MarSCoDe) for China’s Tianwen-1 Mars exploration mission. All the spectra were collected from dedicated rock pellet samples, which were placed in a simulated Martian atmospheric environment. The classification performance of the CNN has been compared with that of three alternative machine learning algorithms, i.e., logistic regression (LR), support vector machine (SVM), and linear discriminant analysis (LDA). Among the four methods, it is on the CNN model that the highest classification correct rate has been obtained, as assessed by precision score, recall score, and the harmonic mean of precision and recall. Furthermore, the classification accuracy is inspected more quantitatively via Brier score, and the CNN is still the best performing model. The results demonstrate that the CNN-based chemometrics are an efficient tool for rock identification with LIBS spectra collected in a simulated Martian environment. Despite the relatively small sample set, this study implies that CNN-supported LIBS classification is a promising analytical technique for Tianwen-1 Mars mission and more planetary explorations in the future.

Depth-resolved information is essential for ocean research. For this study, we developed a shipborne photon-counting lidar for depth-resolved oceanic plankton observation. A pulsed fiber laser with frequency doubling to 532 nm acts as a light source, generating a single pulse at the micro-joule level with a pulse width of less than 1 ns. The receiver is capable of simultaneously detecting the elastic signal at two orthogonal polarization states, the Raman scattering from seawater, and the fluorescence signal from chlorophyll A. The data acquisition system utilizes the photon-counting technique to record each photon event, after which the backscattering signal intensity can be recovered by counting photons from multiple pulses. Benefitting from the immunity of this statistical detection method to the ringing effect of the detector and amplifier circuit, high-sensitivity and high-linearity backscatter signal measurements are realized. In this paper, we analyze and correct the after-pulse phenomenon of high-linearity signals through experiments and theoretical simulations. Through the after-pulse correction, the lidar attenuation coefficient retrieved from the corrected signal are in good agreement with the diffuse attenuation coefficients calculated from the in situ instrument, indicating the potential of this shipborne photon-counting lidar for ocean observation applications.

Geiger-mode single-photon LiDAR is an important tool for long-distance three-dimensional remote sensing. A planar-array-based photon counting LiDAR that uses 32-by-32 fiber arrays coupled to an optical lens as a transceiver unit was developed. Using transmitters and receivers with the same design, the proposed device easily achieves a high-precision alignment of 1024 pixels and flexible detection field-of-view design. The LiDAR uses a set of relay lenses to couple echoes from the receiving fiber arrays to the pixels of a planar-array single-photon detector, which has a resolution enhanced by a factor of four (64-by-64) relative to the fiber array to reduce cross talk from neighboring pixels. The results of field experiments demonstrate that the proposed LiDAR can reconstruct a three-dimensional image from a distance of 1600 m. Even at an acquisition time of only 40 ms, targets with an area of approximately 50% can still be identified from 200 frames. These results demonstrate the potential of the LiDAR prototype for use in instantaneous high-density point-array measurement and long-range wide-FoV 3D imaging, which can be used in remote sensing applications such as airborne surveys and mapping. In the future, we will integrate the proposed LiDAR prototype and the pose measurement system to take the aircraft-based 3D imaging remote sensing experiments.

We report an eye-safe aerosol and cloud lidar with an Erbium-doped fiber laser (EDFL) and a free-space intracavity upconversion detector as the transmitter and receiver, respectively. The EDFL was home-made, which could produce linearly-polarized pulses at a repetition rate of 15 kHz with pulse energies of ~70 μJ and pulse durations of ~7 ns centered at 1550 nm. The echo photons were upconverted to ~631 nm via the sum frequency generation process in a bow-tie cavity, where a Nd:YVO4 and a PPLN crystal served as the pump and nonlinear frequency conversion devices, respectively. The upconverted visible photons were recorded by a photomultiplier tube and their timestamps were registered by a customized time-to-digital converter for distance-resolved measurement. Reflected signals peaked at ~6.8 km from a hard target were measured with a distance resolution of 0.6 m for an integral duration of 10 s. Atmospheric backscattered signals, with a range of ~6 km, were also detectable for longer integral durations. The evolution of aerosols and clouds were recorded by this lidar in a preliminary experiment with a continuous measuring time of over 18 h. Clear boundary and fine structures of clouds were identified with a spatial resolution of 9.6 m during the measurement, showing its great potential for practical aerosol and cloud monitoring.

The Zhurong rover of China’s Tianwen-1 mission started its inspection tour on Mars in May 2021. As a major scientific payload onboard the Zhurong rover, the Mars Surface Composition Detector (MarSCoDe) instrument adopts laser-induced breakdown spectroscopy (LIBS) to detect and analyze the chemical composition of Martian materials. This paper introduces an experimental platform capable of establishing a simulated Martian atmospheric environment, in which a duplicate model of the MarSCoDe flight model is placed. In the simulated environment, the limit vacuum degree can reach 10−5 Pa level, the temperature can change from −190 °C to +180 °C, and different gases can be filled and mixed according to desired proportion. Moreover, the sample stage can move along a track inside the vacuum chamber, enabling the detection distance to vary from 1.5 m to 7 m. Preliminary experimental results indicate that this platform is able to simulate the scenario of MarSCoDe in situ LIBS detection on Mars well.

The Zhurong rover successfully landed in southern Utopia Planitia as part of the Tianwen-1 mission on 15 May 2021. One of the objectives of the Mars Surface Composition Detector (MarSCoDe) onboard the rover is to investigate mineral compositions on the Martian surface by measuring the near-infrared reflectance spectra. Before conducting spectral interpretation, in-flight data calibration is a crucial step due to the significant differences between the laboratory and the Martian environment. The work of the MarSCoDe spectrometer is based on an acousto-optic tunable filter (AOTF). The temperature variation of the AOTF could induce wavelength offset, making mineral identification uncertain. We first analyzed the viewing geometry of the spectral measurements of the calibration targets on the Mars rover according to its attitude to identify the anomalous data. The wavelength offsets were then determined by fitting the absorption positions of CO2 at ~1400 and ~2000 nm, representing the primary composition of the Martian atmosphere. The results showed 2–8 nm wavelength offsets, which correlated well with AOTF temperatures. The artifacts were removed in the wavelength-corrected reflectance spectra, which is critical to identify the material types on Mars, especially water-related minerals.

Owing to their excellent characteristics, Pickering emulsions have been widely used in the development and the application of new carriers for embedding and for delivering active compounds. In this study, β-carotene was successfully encapsulated in a Pickering emulsion stabilized using Desmodium intortum protein isolate (DIPI). The results showed that the encapsulation efficiencies of β-carotene in the control group Tween 20 emulsion (TE) and the DIPI Pickering emulsion (DIPIPE) were 46.7 ± 2.5% and 97.3 ± 0.8%, respectively. After storage for 30 days at 25 °C and 37 °C in a dark environment, approximately 79.4% and 72.1% of β-carotene in DIPIPE were retained. Compared with TE, DIPIPE can improve the stability of β-carotene during storage. In vitro digestion experiments showed that the bioaccessibility rate of β-carotene in DIPIPE was less than that in TE. Cytotoxicity experiments showed that DIPI and β-carotene micelles within a specific concentration range exerted no toxic effects on 3T3 cells. These results indicate that DIPIPE can be used as a good food-grade carrier for embedding and transporting active substances to broaden the application of the protein-based Pickering emulsion system in the development of functional foods.

The main objective of this study is to develop a Hapke photometric model that is suited for Chang’E-1 (CE-1) Interference Imaging Spectrometer (IIM) data. We first divided the moon into three areas including ‘maria’, ‘new highland’ and old ‘highland’ with similar photometry characteristic based on the Hapke parameters of the moon derived from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) multispectral data. Then, we selected the sample data in the ‘maria’ area and obtained a new set of Hapke model’s parameters that can best fit these data. Result shows that photometric correction using Hapke model with these new derived parameters can eliminate the effect of variations in viewing and luminating geometry, especially ‘opposition surge’, more efficiently than the empirical model. The corrected mosaic shows no significant artifacts along the tile boundaries and more detailed information of the image can be exhibited due to a better correction of ‘opposition surge’ at small phase angle (g < 15°).

Numerous Trichoderma strains have been reported to be optimal biofertilizers and biocontrol agents with low production costs and environmentally friendly properties. Trichoderma spp. promote the growth and immunity of plants by multiple means. Interfering with the hormonal homeostasis in plants is the most critical strategy. However, the mechanisms underlying plants’ responses to Trichoderma remain to be further elucidated. Auxin is the most important phytohormone that regulates almost every aspect of a plant’s life, especially the trade-off between growth and defense. The AUXIN RESPONSE FACTOR (ARF) family proteins are key players in auxin signaling. We studied the responses and functions of the PdPapARF1 gene in a hybrid poplar during its interaction with beneficial T. asperellum strains using transformed poplar plants with PdPapARF1 overexpression (on transcription level in this study). We report that PdPapARF1 is a positive regulator for promoting poplar growth and defense responses, as does T. asperellum inoculation. PdPapARF1 also turned out to be a positive stimulator of adventitious root formation. Particularly, the overexpression of PdPapARF1 induced a 32.3% increase in the height of 40-day-old poplar plants and a 258% increase in the amount of adventitious root of 3-week-old subcultured plant clones. Overexpressed PdPapARF1 exerted its beneficial functions through modulating the hormone levels of indole acetic acid (IAA), jasmonic acid (JA), and salicylic acid (SA) in plants and activating their signaling pathways, creating similar results as inoculated with T. asperellum. Particularly, in the overexpressing poplar plants, the IAA level increased by approximately twice of the wild-type plants; and the signaling pathways of IAA, JA, and SA were drastically activated than the wild-type plants under pathogen attacks. Our report presents the potential of ARFs as the crucial and positive responders in plants to Trichoderma inducing.