Spectral Response Characteristics Research Articles

The Spectral Response Characteristics of Potassium in Camellia oleifera Leaves at Different Growth Stages

The Spectral Response Characteristics of Potassium in Camellia oleifera Leaves at Different Growth Stages

Temporal coherence shapes cortical responses to speech mixtures in a ferret cocktail party

Perceptual segregation of complex sounds such as speech and music simultaneously emanating from multiple sources is a remarkable ability that is common in humans and other animals alike. Unlike animal physiological experiments with simplified sounds or human investigations with spatially broad imaging techniques, this study combines insights from animal single-unit recordings with segregation of speech-like sound mixtures. Ferrets are trained to attend to a female voice and detect a target word, both in presence and absence of a concurrent equally salient male voice. Recordings are made in primary and secondary auditory cortical fields, and in frontal cortex. During task performance, representation of the female words becomes enhanced relative to the male in all, but especially in higher cortical regions. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings underscore the role of the principle of temporal coherence whereby attention to a target voice binds together all neural responses coherently modulated with the target, thus ultimately forming and extracting a common auditory stream.

Impact of rogue waves on semi-submersible platforms: An experimental investigation of wave run-up and air-gap responses

The wave run-up and air-gap responses of semi-submersible platforms under extreme sea conditions are crucial design considerations for ensuring the structural integrity and safety of marine engineering operations. This study investigated the impact of rogue waves on the wave run-up and air-gap responses of semi-submersible platforms using a transient focusing wave group to accurately simulate irregular seas. Comparative model tests were conducted on a semi-submersible platform under both rogue and non-rogue-wave conditions. The platform motions and air-gap responses were analysed using spectral analysis, extreme-value statistics, and wavelet methods. Rogue waves were found to significantly affect the air-gap response spectrum, increasing the nonlinearity of both the wave run-up and air-gap responses. Different locations on the platform exhibited varying statistical and spectral response characteristics. Rogue waves modified the instantaneous properties of wave elevation, thereby increasing the energy levels in the system. This study confirmed that rogue waves significantly influence the air-gap responses and wave run-up of semi-submersible platforms, suggesting that they should be considered when designing and planning the operations of these platforms. This study offers a comprehensive understanding of the complex interactions between rogue waves and large maritime structures and provides insights for improving safety and performance under extreme sea conditions.

The Time Response of a Uniformly Doped Transmission-Mode NEA AlGaN Photocathode Applied to a Solar-Blind Ultraviolet Detecting System

Due to the excellent quantum conversion and spectral response characteristics of the AlGaN photocathode, it has become the most promising III-V group semiconductor photocathode in solar-blind signal photoconversion devices in the ultraviolet band. Herein, the influence factors of the time-resolved characteristics of the AlGaN photocathode are researched by solving the photoelectron continuity equation and photoelectron flow density equation, such as the AlN/AlGaN interface recombination rate, AlGaN electron diffusion coefficient, and AlGaN activation layer thickness. The results show that the response time of the AlGaN photocathode decreases gradually with the increase in AlGaN photoelectron diffusion coefficient and AlN/AlGaN interface recombination rate, but the response time of the AlGaN photocathode gradually becomes saturated with the further increase in AlN/AlGaN interface recombination rate. When the thickness of the AlGaN photocathode is reduced from 250 nm to 50 nm, the response time of the AlGaN photocathode decreases from 63.28 ps to 9.91 ps, and the response time of AlGaN photocathode greatly improves. This study provides theoretical guidance for the development of a fast response UV detector.

Application of terahertz time-domain spectroscopy and chemometrics-based crested porcupine algorithm in identification of different medicinal parts of Angelica sinensis

ObjectiveAngelica sinensis is one of the commonly used Chinese herbal medicine in traditional Chinese medicine clinic, exhibits different pharmacological characteristics due to variations in the content of active ingredients in its head, body, and tail. Therefore, research on the identification methods of different medicinal parts of Angelica sinensis is of great practical significance. Terahertz Time-Domain Spectroscopy (THz-TDS) technology is widely used in the field of nondestructive testing because of its unique electromagnetic wave characteristics. This study explores the feasibility of combining THz-TDS with chemometrics to identify different medicinal parts of Angelica sinensis. MethodsBy comparing the spectral response characteristics of different parts of Angelica sinensis to various optical parameters, the absorption coefficient spectrum in the 0.6–3.0 THz range was selected, and three types of feature extraction algorithms, namely, joint Competitive Adaptive Reweighted Sampling (CARS), Uninformative Variable Elimination (UVE), and Successive Projections Algorithm (SPA), were used to establish the classification models of Extreme Learning Machine (ELM), Random Forest (RF), and Support Vector Machine (SVM) in turn, and optimize the models by using the crown porcupine algorithm (Crested Porcupine Optimizer (CPO) to optimize the model. ResultsThe research results indicate that the CPO optimizer significantly improved the classification accuracy of the models, with the accuracy of the ELM, RF, and SVM models increasing by 4.36%, 1.11%, and 12.22%, respectively. The SPA-CPO-SVM model exhibited the best overall performance, achieving accuracies of 96.11% and 97.96% on the prediction and training sets, respectively, while the number of input features was only 5% of the total feature set. ConclusionThe results show that the fully joint feature extraction strategy and optimization algorithm can play a powerful synergistic effect in model construction, confirming the feasibility of THz-TDS technology to correctly identify different medicinal parts of Angelica sinensis, and providing an important reference for the application of terahertz technology in the identification of Chinese herbal medicines.

High-Performance Broadband Photodetectors Combining Perovskite and Organic Bulk Heterojunction Bifunctional Layers

Perovskite can be used to prepare high-performance photodetectors due to its excellent optical properties. However, the detection range of perovskite photodetectors is mostly limited to the visible light range, restricting their further development and application. In recent years, combining perovskite with organic bulk heterojunctions to prepare photodetectors with broadband detection capability has proven to be an effective strategy. Through this approach, the response spectrum of the photodetector can be flexibly regulated, and organic compounds can improve the perovskite film quality by passivating defects and inhibit the penetration of water molecules in the air, thereby improving the device performance and stability. In this work, we propose and demonstrate the feasibility of combining MAPbI3 perovskite with PTB7-Th:COTIC-4F to prepare high-performance photodetectors with wide spectral response characteristics. With the assistance of an organic bulk heterojunction, the defects of perovskite crystals are effectively passivated, and the detection spectrum of the device is successfully extended to about 1100 nm. As a result, the responsivity achieved is 0.58 A/W, 1.19 A/W, and 1.41 A/W under laser illumination of 532 nm, 808 nm, and 980 nm, with the power density of 5 μW/cm2 at the bias voltage of −0.5 V, respectively, which is one of the best performances among vertical device structures of this type. Moreover, the stability of the final hybrid film has been greatly improved. This work provides a new approach to the preparation of high-performance and broadband perovskite photodetectors.

Spectral properties regulation for the performance improvement of solar-driven methane dry reforming reactor based on the photothermal synergistic catalysis

With the development of chemical industry, many chemical reactions are expected to be directly driven by solar energy. Among them, methane dry reforming (MDR) is a highly promising reaction system. Since all the energy required for MDR comes from solar energy, the temperature distribution and reaction characteristics in the reactor are determined by radiation transportation, and therefore regulating the optical properties according to the spectral distribution characteristics becomes necessary for improving the chemical conversion performance of the reactor. In this paper, aiming at the specific strengthening mechanism of different spectra in photothermal synergistic catalysis, the spectral response characteristics in the reactor were purposefully regulated, so as to achieve the improvement of reactor efficiency and reaction conversion performance. By adjusting the optical properties of compound parabolic concentrator (CPC) and porous catalytic absorber (PCA) in a cavity reactor, the CO2 conversion can be increased by 68.52%, the CH4 conversion can be increased by 54.48%, and the solar-fuel efficiency can be increased to 6.16%. This indicates that the selectivity of different bands of full spectrum can significantly affect the reactor performance. Through the above research, this paper aims to provide a new optimization idea for the photothermal reactor.

Ultraviolet-Visible-Near-Infrared Broadband Photodetector Enabled by Cs2AgBiBr6: Sn/Conjugated Polymer Heterojunction.

Broadband photodetectors covering ultraviolet (UV) to near-infrared (NIR) wavelengths play an essential role in communications, imaging, and biosensing. Developing a single photodetector with a broadband optical response operating at room temperature can significantly reduce the complexity and cost of receiver systems for multispectral applications. In this work, utilizing the porous structure characteristics of Cs2AgBiBr6:Sn thin films, a self-powered detector with broad spectral response (UV-vis-NIR) was achieved by constructing an effective Cs2AgBiBr6:Sn/PDPP3T heterojunction. This photodetector possesses a broad response spectrum from 350 to 950 nm with an average detection rate exceeding 1011 Jones and maintains excellent photoelectric performance over two months. Sn2+ doping effectively reduces the bandgap of Cs2AgBiBr6, enhancing its near-infrared absorption and optimizing energy level alignment with conjugated polymer (diketopyrrolopyrrole-terthiophene, PDPP3T). More importantly, the porous structure derived from Sn doping significantly improves carrier extraction and transport under a near-infrared light response at the heterojunction interface. Utilizing its broad spectral response characteristics in the UV-vis-NIR range, a novel information transfer and encryption system employing full optical modulation has been realized within a single perovskite photodetector. This work provides a new approach to fabricating lead-free double perovskite broadband photodetectors with potential applications in photonic devices.

Hyperspectral Estimation of Chlorophyll Content in Wheat under CO2 Stress Based on Fractional Order Differentiation and Continuous Wavelet Transforms

The leaf chlorophyll content (LCC) of winter wheat, an important food crop widely grown worldwide, is a key indicator for assessing its growth and health status in response to CO2 stress. However, the remote sensing quantitative estimation of winter wheat LCC under CO2 stress conditions also faces challenges such as an unclear spectral sensitivity range, baseline drift, overlapping spectral peaks, and complex spectral response due to CO2 stress changes. To address these challenges, this study introduced the fractional order derivative (FOD) and continuous wavelet transform (CWT) techniques into the estimation of winter wheat LCC. Combined with the raw hyperspectral data, we deeply analyzed the spectral response characteristics of winter wheat LCC under CO2 stress. We proposed a stacking model including multiple linear regression (MLR), decision tree regression (DTR), random forest (RF), and adaptive boosting (AdaBoost) to filter the optimal combination from a large number of feature variables. We use a dual-band combination and vegetation index strategy to achieve the accurate estimation of LCC in winter wheat under CO2 stress. The results showed that (1) the FOD and CWT methods significantly improved the correlation between the raw spectral reflectance and LCC of winter wheat under CO2 stress. (2) The 1.2-order derivative dual-band index (RVI (R720, R522)) constructed by combining the sensitive spectral bands of the CO2 response of winter wheat leaves achieved a high-precision estimation of the LCC under CO2 stress conditions (R2 = 0.901). Meanwhile, the red-edged vegetation stress index (RVSI) constructed based on the CWT technique at specific scales also demonstrated good performance in LCC estimation (R2 = 0.880), verifying the effectiveness of the multi-scale analysis in revealing the mechanism of the CO2 impact on winter wheat. (3) By stacking the sensitive spectral features extracted by combining the FOD and CWT methods, we further improved the LCC estimation accuracy (R2 = 0.906). This study not only provides a scientific basis and technical support for the accurate estimation of LCC in winter wheat under CO2 stress but also provides new ideas and methods for coping with climate change, optimizing crop-growing conditions, and improving crop yield and quality in agricultural management. The proposed method is also of great reference value for estimating physiological parameters of other crops under similar environmental stresses.

A novel single near-infrared luminescence of negative thermal quenching materials for optical temperature measurement

In recent years, upconversion (UC) luminescence has gained attention due to its unique optical properties, and the thermal response spectral characteristics of these materials have been widely utilized in various fields including temperature sensing and biomedical research. However, the photoluminescence (PL) intensity of most rare earth ions doped phosphors decreases with increasing temperature, and the visible fluorescence emission penetration is still limited. In the work, the pure phase of Yb3+ and Er3+ ions co-doped Sc2Mo3O12 was successfully prepared. The Sc2Mo3O12: Yb3+, Er3+ sample showed a single emission of UC near-infrared (NIR) light. The optimum doping concentrations of 0.2 for Yb3+ ions and 0.01 for Er3+ ions were achieved. The possible upconversion luminescence (UCL) mechanism was investigated by analysing the UCL spectra, the down-shift (DS) excitation and emission spectra of Sc2Mo3O12: Yb3+, Er3+ phosphor. The excitation path of NIR emission is mainly through Er3+ from 2H11/2 to 4I9/2 energy level. What's more, the temperature-dependent near-infrared UCL properties of sample is explored in the temperature range from 323 K to 673 K. The enhancement of upconversion luminescence intensity shows a linear relationship with increasing temperature. The study paves a new way for non-contact optical temperature measurement with single near-infrared UCL emission.

Research on driving technology of radio‐over‐fiber (ROF) compact optical transmitter module

AbstractIn response to the problems of communication capacity and spectrum resource constraints, radio over fiber (ROF) technology has gained widespread adoption, and the quality and performance of the optical transmitter module also directly affect the transmission of the link. This paper presents the design of a direct modulation optical transmitter module in the frequency band ranging from 2.6 kHz to 206.8 MHz using OPA690 broadband voltage feedback op‐amp. The module features a tunable bias voltage range from 0 to 5 V to accommodate different threshold voltages for modulation power supply. It offers a gain of 12 dB and a signal‐to‐noise ratio exceeding 50 dB while demonstrating excellent stability, high signal purity, good spectral response characteristics, and compact size advantages. Based on this design, we further optimized the system circuit by adding a fourth‐order Butterworth filter structure, reducing the lower cut‐off frequency to about 500 Hz, increasing the gain by 6 dB, reducing the return loss to −26.91 dB, and the module's signal‐to‐noise ratio exceeding 90 dB. This optimization scheme improves the stability and signal purity of the optical transmitter module and improves the spectral response characteristics. In this paper, Multisim is used to analyze and verify the proposed optical transmitter circuit. In addition, a complete link experiment was carried out using an optical receiving module designed in the same laboratory to verify the feasibility of our proposed module.

Evaluation of the monitoring capability of various vegetation indices and mainstream satellite band settings for grassland drought

In the context of global climate change and increasing human activities, grassland drought has become increasingly severe and complex. The monitoring of grassland drought is crucial for reducing drought-related losses and ensuring national ecological security. This study used the coupled PROSPECT and SAIL radiative transfer models (PROSAIL) to simulate canopy reflectance, considering factors such as grassland growth stages and varying drought conditions. Our objective was to reveal the spectral response characteristics of grasslands to varying drought conditions and identify sensitive spectral bands suitable for drought monitoring during different grassland growth stages. We aligned commonly available satellite bands from moderate resolution imaging spectroradiometer (MODIS), Sentinel 2, Landsat 8, WorldView 2, and Gaofen 2 (GF 2) with these sensitive bands to assess the capabilities of existing satellite data for drought monitoring. Furthermore, this research evaluated the suitability of 16 commonly used remote sensing vegetation indices for grassland drought monitoring, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Ratio Vegetation Index (RVI), Difference Vegetation Index (DVI), Modified Soil Adjusted Vegetation Index (MSAVI), Atmospherically Resistant Vegetation Index (ARVI), Modified Normalized Difference Water Index (MNDWI), Global Vegetation Moisture Index (GVMI), Land Surface Water Index (LSWI), Visible and Shortwave Infrared Drought Index (VSDI), Water index(WI), Moisture Stress Index(MSI), Normalized Difference Water Index(NDWI), Normalized Difference Infrared Index (NDII), Photochemical Reflectance Index (PRI), and Optimized Soil-Adjusted Vegetation Index (OSAVI). The simulation and analysis results revealed: 1) Grassland in different growth stages exhibit similar sensitivities to certain spectral bands, namely those within the ranges of 540 nm–720 nm, 1250 nm–1690 nm, 1805 nm–2190 nm, and 2264 nm–2500 nm, which are more sensitive to various drought conditions. 2) Suitable vegetation indices for both growing and stable stages include NDII, MSI, PRI, LSWI, and GVMI, with silhouette coefficients exceeding 0.6 for the growing stage and 0.7 for the stable stage. The least suitable vegetation index is DVI, with an average silhouette coefficient of 0.15 over the entire growth stage. 3) From the spectral band perspective, among the five assessed satellites, MODIS Band 7 exhibits the highest sensitivity to water content across all satellite bands. MODIS's band configuration is most suitable for monitoring grassland drought during different growth stages, while WorldView 2's band configuration is the least suitable.

Optimization of the MSMGWB models used to predict remote infrared signals of jet engine in various spectral intervals

Further improvements are reported for an optimization method that was used in previous work to determine the best combination of Gauss quadrature schemes and wavenumber subinterval division results for the multi-scale multi-group wide-band k-distribution (MSMGWB) model, which is used in calculation of remote infrared signals of hot combustion gases from hydrocarbon fuels and gray walls in the 3–5 µm spectral interval. In addition, the application range of the MSMGWB model was extended to the 8–14 µm, 7.7–9.7 µm, 3.7–4.8 µm, and 2–2.5 µm spectral intervals. Compared with previous works, the new optimization procedure considered a broader range of thermodynamic state parameter combinations of the combustion gas and the atmosphere. The optimization effect was evaluated further via prediction of remote sensing thermal images in various spectral intervals for solid structures and hot jet of an aero-engine’s supersonic exhaust system. Furthermore, an optimized MSMGWB model that considers the spectral response characteristics of infrared detectors has been established and evaluated.

Synergistic retrieval of mangrove vital functional traits using field hyperspectral and satellite data

Mangroves play a pivotal role in the attainment of United Nations Sustainable Development Goals. Leaf equivalent water thickness (EWT) and leaf mass per area (LMA) are vital functional trait parameters for monitoring heath status of mangroves. However, their inherent spectral response characteristics remain unclear, which presents a challenge for high-precision estimating EWT and LMA using remote sensing images. In this study, we attempted to synergistic retrieval of mangrove EWT and LMA using field hyperspectral and satellite data. Specifically, we proposed a novel Fractional-order assisted Spectral angle Analysis (FSA) approach to accurately identify sensitive spectral domains of EWT and LMA for three mangrove species based on in situ full-spectrum hyperspectral (350–2500 nm) data. We constructed a new spectral matching index (SMI) to screen the satellite-based sensitive spectral bands based on the field-based spectral domains, and further verified their feasibility of estimating EWT and LMA using three optical satellite sensors (Sentinel-2A, SDGSAT-1, and OHS-3D). Finally, we explored the effectiveness of combining SAR and thermal infrared (TIR) images with sensitive spectral bands on improving retrieval performance in estimating EWT and LMA, respectively. Results indicated that FSA approach could capture the sensitive spectral domains of EWT (1125–1868 nm) and LMA (1419–1999 nm) for three mangrove species. The SMI could effectively realize the spectral matching between field-based sensitive domains and satellite-based bands, and perform the synergistic retrieval of mangrove EWT (R2 = 0.65) and LMA (R2 = 0.70). Intriguing finding is that the additional TIR bands significantly enhanced the EWT and LMA inversion accuracy (R2 increased by 9.8 %–68.3 %) when compared to SAR images. We confirmed that EWT displayed an inverse trend of LMA with the flooding frequency increasing. Our works provide a scientific basis for protection and sustainable management of mangroves.

Temporal Coherence Shapes Cortical Responses to Speech Mixtures in a Ferret Cocktail Party.

Segregation of complex sounds such as speech, music and animal vocalizations as they simultaneously emanate from multiple sources (referred to as the "cocktail party problem") is a remarkable ability that is common in humans and animals alike. The neural underpinnings of this process have been extensively studied behaviorally and physiologically in non-human animals primarily with simplified sounds (tones and noise sequences). In humans, segregation experiments utilizing more complex speech mixtures are common; but physiological experiments have relied on EEG/MEG/ECoG recordings that sample activity from thousands of neurons, often obscuring the detailed processes that give rise to the observed segregation. The present study combines the insights from animal single-unit physiology with segregation of speech-like mixtures. Ferrets were trained to attend to a female voice and detect a target word, both in presence or absence of a concurrent, equally salient male voice. Single neuron recordings were obtained from primary and secondary ferret auditory cortical fields, as well as frontal cortex. During task performance, representation of the female words became more enhanced relative to those of the (distractor) male in all cortical regions, especially in the higher auditory cortical field. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings are consistent with the temporal coherence theory whereby attention to a target voice anchors neural activity in cortical networks hence binding together channels that are coherently temporally-modulated with the target, and ultimately forming a common auditory stream.

Research of ultra-narrow band filters based on silicon nitride subwavelength grating used in terahertz detection techniques

As narrow-band pass filters are essential in terahertz(THz) applications, we present a ultra-narrow band filters based on silicon nitride subwavelength grating in this paper. Through rigorous coupled wave analysis, it can be seen that the main role of each structural factor or its influence on the spectral response characteristics are significantly different.Then, according to these laws, we get the design scheme by adjusting the structure factor of the subwavelength grating purposefully and pertinently. It can be seen from the results that the theoretical reflectance at 0.55 THz reaches 99.741%, and the half-peak frequency range is between −171MHz and +53 MHz. At the same time, the low sideband reflectance in the wide frequency band range of 0.2–0.8 THz indicates that the design can be used well for 0.55 THz signal in related THz detection technology.

Enhanced Hyperspectral Sharpening through Improved Relative Spectral Response Characteristic (R-SRC) Estimation for Long-Range Surveillance Applications

The fusion of low-spatial-resolution hyperspectral images (LRHSI) with high-spatial-resolution multispectral images (HRMSI) for super-resolution (SR), using coupled non-negative matrix factorization (CNMF), has been widely studied in the past few decades. However, the matching of spectral characteristics between the LRHSI and HRMSI, which is required before they are jointly factorized, has rarely been studied. One objective of this work is to study how the relative spectral response characteristics (R-SRC) of the LRHSI and HRMSI can be better estimated, particularly when the SRC of the latter is unknown. To this end, three variants of enhanced R-SRC algorithms were proposed, and their effectiveness was assessed by applying them for sharpening data using CNMF. The quality of the output was assessed using the L1-norm-error (L1NE) and receiver operating characteristics (ROC) of target detections performed using the adaptive coherent estimator (ACE) algorithm. Experimental results obtained from two subsets of a real scene revealed a two- to three-fold reduction in the reconstruction error when the scenes were sharpened by the proposed R-SRC algorithms, in comparison with Yokoya’s original algorithm. Experiments also revealed that a much higher proportion (by one order of magnitude) of small targets of 0.015 occupancy in the LRHSI scene could be detected by the proposed R-SRC methods compared with the baseline algorithm, for an equal false alarm rate. These results may suggest the possibility of SR to allow long-range surveillance using low-cost HSI hardware, particularly when the remaining issues of the occurrence of large reconstruction errors and comparatively higher false alarm rate for ‘rare’ species in the scene can be understood and resolved in future research.

Effect of terminal substituent of iso-indigo-based materials on the intermolecular stacking and memory performance.

Attributed to the characteristics of narrow band gap structural units and full spectral response, iso-indigo is often used as an electron acceptor in organic electronic materials. Organic molecules with large conjugated surfaces and strong intermolecular forces can form ordered stacked structures through self-assembly. In this paper, the self-assembly performances of IDCF3 and IDCN are regulated by changing the end groups. The effects of terminal groups on the resistive memory behaviours and reproducibility are investigated. The properties of IDCF3 and IDCN devices are characterized by UV-VIS spectroscopy, cyclic voltammetry and DSC diffraction. The results show that when the end groups with different steric hindrance are introduced into the ends of the molecules with good backbone plane, the conjugated surfaces of the molecules will bend due to the different steric hindrance of the end groups in the form of cambium and layer-ordered packing, which will affect the threshold voltage and device reproducibility.

Comparison of leaf chlorophyll content retrieval performance of citrus using FOD and CWT methods with field-based full-spectrum hyperspectral reflectance data

Citrus is one of the most economically valuable fruit trees in the world, for which leaf chlorophyll content (LCC) serves as a crucial indicator for evaluating its growth and health status. However, the quantitative estimation of LCC using remote-sensing techniques is still challenging owing to unclear sensitive spectral ranges, baseline drift and overlapping spectrum peaks. To resolve these issues, we clarified the spectral response characteristics of citrus LCC using fractional-order derivatives (FOD) and continuous wavelet transform (CWT) methods to determine its sensitive spectral range with in situ full-spectrum leaf hyperspectral data. We proposed a novel method for estimating the LCC of citrus by combining an ensemble learning regression model based on Hyperopt optimization (H-ELR) with partial least squares regression (PLSR) using the ultra-high dimensional feature variables produced by dual- and tri-band combination strategies. We evaluated the retrieval performance of LCC between the FOD- and CWT-based optimal spectral feature variables. Besides, we further examined the feasibility of improving the estimation accuracy of LCC by the combination of their optimal feature variables. Finally, we evaluated the effect of the spectral curve trend changes and different dimensional spectral features on LCC estimation. The results showed that: (1) The FOD- and CWT-based methods improved the correlation between original spectral reflectance and LCC, with the correlation coefficient increasing by 0.046 and 0.054, respectively. We confirmed that 425–740 nm is the optimal spectral range for LCC estimation. (2) We found that the 0.9 order derivative Tri-band index (TBI2 (R571, R1697, R740)) constructed by combining the sensitive spectral bands of leaf water content achieved a high-precision LCC estimation (R2 = 0.876). In addition, the MERIS terrestrial chlorophyll index (MTCI) constructed based on the scale6 of CWT also gained good retrieval accuracy (R2 = 0.806). (3) We demonstrated that a combination of FOD-based and CWT-based sensitive spectral features improves estimation accuracies (R2 = 0.891) of LCC and revealed that the reflectance peaks and slope peaks at 550 and 750 nm are essential variables for predicting the citrus LCC. (4) The combination of PLSR and H-ELR model provided a good retrieval performance of citrus LCC with the kurtosis (γ = 3.2) and skewness (Sk = 0.066) of the residual prediction values. Our proposed method can provide a scientific basis for estimating LCC and other physiological parameters of citrus and other crop types, which is also important to optimize agricultural management practices and improve crop yield.

Early detection of bacterial wilt in bananas caused by Ralstonia solanacearum using reflectance spectroscopy

Bacterial wilt is one of the most important vascular diseases that generate high worldwide losses. The main strategy to control it involves early detection of infected plants that mitigate its spread in the field. This research characterized the spectral response of healthy plants, infected with Ralstonia solanacearum E.F. Smith race 2 and subjected to water stress, in two banana cultivars by spectroscopy reflectance. The spectral data were used to detect vascular wilt during the incubation period of the disease in Gros Michel and Cavendish banana cultivars. The reflectance data were collected from the leaves using a portable spectrometer. Both varieties of healthy plants showed a typical low reflectance in the visible range, with a peak of green of around 12% in Williams and 5% in Gros Michel. In the measured infrared range, the two varieties presented values between 60 and 70% in the latest days post-infection measurements, decreasing to ~ 50% after 12 dpi. The results obtained indicate that plants infected with R. solanacearum have no initial increase in reflectance in the visible (Vis) range, whereas decrease rapidly after 6 dpi in the 700–1000 nm range. This methodology identifies three wavelengths (710, 770, and 965 nm) that allow differentiation between ill and healthy plants after 6 days post-inoculation, with a percentage of correct classification that ranges from 96 to 100%. The spectral response characterization in healthy plants and those subjected to various types of stress is a fundamental input for the development of early disease detection systems based on spectroscopy techniques.