Spectral Technique Research Articles

Improved Discrimination of Mass Spectral Isomers Using the High-Dimensional Consensus Mass Spectral Similarity Algorithm.

This study employs a high-dimensional consensus mass spectral (HDCMS) similarity scoring technique to discriminate isomers collected using an electron ionization mass spectrometer. The HDCMS method was previously introduced and applied to the discrimination of mass spectra of constitutional isomers, methamphetamine and phentermine, collected with direct analysis real-time mass spectrometry (DART-MS). The method formulates the problem of discriminating mass spectra in a mathematical Hilbert space and is hence called "high dimensional." It requires replicate mass spectra to build a Gaussian model and evaluate the inner products between these functions. The resulting measurement variability is used as a signature by which to discriminate spectra. In this work, HDCMS is tested on electron impact ionization (EI) mass spectra of 7 terpene and terpene-related (C10H16 and C10H14) isomers with experimental retention indices that differ by less than 30 and with traditional cosine similarity scores greater than 0.9, on a scale of 0 to 1, when compared with at least one other compound in the test set. Using identical instrument parameters, 15 replicate gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) spectra of each isomer were collected and separated into distinct library and query sets. The HDCMS algorithm discriminated each isomer, indicating the method's potential. Because the method requires replicate measurements, observations from a simple heuristic study of the number of replicates required to discriminate these isomers is presented. The paper concludes with a discussion of compound discrimination using HDCMS and the benefits and drawbacks of applying the method to EI-MS data.

A gas sensor scheme for CO based on optical-feedback linear-cavity enhanced absorption spectroscopy

Trace gases, especially some toxic trace gases, such as carbon monoxide, are of great value for high-precision detection of their concentration in environmental, safety, and health monitoring. To accurately measure CO gas, a novel spectral technique scheme is developed and demonstrated based on cavity-enhanced absorption spectroscopy with a high-quality linear cavity. The scheme can achieve the equal noise absorption sensitivity of 2.37 × 10−8 cm−1 at the cavity loss of 186 ppm, which can achieve the concentration measurement of 11.7 ppm of CO gas at 1564 nm in the near-infrared band. This approach has the potential for expansion to other gas concentration detection applications and can achieve ppb-ppt level concentration detection.

Improved numerical schemes to solve general fractional diabetes models

In this article, we propose a new class of nonlinear fractional differential equations of diabetes disease based on the concept of Caputo fractional derivative. Two numerical techniques are introduced to analyse the solution of the general fractional diabetes model, that describes glucose homeostasis. The first method, which constructed using the nonstandard finite difference technique involves an asymptotically stable difference scheme. This method maintains important properties of the solutions of the studied system, such as the positivity and boundedness. The second method is the Jacobi-Gauss–Lobatto spectral collocation approach, known for its exponential accuracy. By employing this collocation method, the problem is transformed into a set of algebraic nonlinear equations, simplifying the overall task. Numerical simulations were conducted to compare the performance of these two techniques with other standard methods and the analytic solution in specific cases. Our findings show that the Jacobi-Gauss–Lobatto spectral collocation technique provides higher accuracy in solving the fractional diabetes model system, while the nonstandard finite difference approach requires lower computational duration.

Studying microbially induced corrosion on glass using ToF-SIMS.

Microbially induced corrosion (MIC) is an emerging topic that has huge environmental impacts, such as long-term evaluation of microbial interactions with radioactive waste glass, environmental cleanup and disposal of radioactive material, and weathering effects of microbes. Time-of-flight secondary ion mass spectrometry (ToF-SIMS), a powerful mass spectral imaging technique with high surface sensitivity, mass resolution, and mass accuracy, can be used to study biofilm effects on different substrates. Understanding how to prepare biofilms on MIC susceptible substrates is critical for proper analysis via ToF-SIMS. We present here a step-by-step protocol for preparing bacterial biofilms for ToF-SIMS analysis, comparing three biofilm preparation techniques: no desalination, centrifugal spinning (CS), and water submersion (WS). Comparisons of two desalinating methods, CS and WS, show a decrease in the media peaks up to 99% using CS and 55% using WS, respectively. Proper desalination methods also can increase biological signals by over four times for fatty acids using WS, for example. ToF-SIMS spectral results show chemical compositional changes of the glass exposed in a Paenibacillus polymyxa SCE2 biofilm, indicating its capability to probe microbiologically induced corrosion of solid surfaces. This represents the proper desalination technique to use without significantly altering biofilm structure and substrate for ToF-SIMS analysis. ToF-SIMS spectral results showed chemical compositional changes of the glass exposed by a Paenibacillus bacterial biofilm over 3-month inoculation. Possible MIC products include various phosphate phase molecules not observed in any control samples with the highest percent increases when experimental samples were compared with biofilm control samples.

Time Dependent Spectral Ratio Technique for Micro-seismic Exploration in the Niger Delta Region of Nigeria

Abstract: Since the discovery of the hydrocarbon micro-tremors, there have been numerous efforts to understand the causes of these microseisms related to oil and gas. A spectral ratio (SR) time-dependent equation was derived based on geological principles. The equation showed tremendous success in analyzing multi-layered geological terrain and estimating the spectral ratio in the Niger Delta region of Nigeria. This study seeks to develop a reliable model using standard seismic reflection data to analyze microseismic datasets from hydrocarbon reservoirs. Type A-SR acts over a longer duration and can be used to determine hydrocarbon reservoirs. Type B-SR acts in a short time with maximum impact. It can be used to determine gas condensate flow in the hydrocarbon reservoir. It is recommended that this technique be applied in real time to ascertain its accuracy. Keywords: Niger Delta, Microseismic, Amplitude, Special ratio, Geology.

Thermodynamic analysis of MHD Prandtl-Eyring fluid flow through a microchannel: A spectral quasi-linearization approach

In designing efficient micro devices, particularly microchannels used in cooling electronic components and biomedical microfluidic systems, The foremost application explored is the design and optimization of microchannels employed in the electronic device cooling systems. To possess these microchannels from overheating and damaging their gentle electronic components, exact fluid flow and heat transmission regulation are required. To better design cooling systems, engineers can use mathematical models of Prandtl-Eyring fluid flows to antedate temperature and velocity profiles. The entropy generation also helps in optimizing the design for better fluid transport efficiency. Therefore, the present aim is to characterize the impact of dissipative heat along with magnetization in Prandtl-Eyring non-Newtonian fluid via microchannel. The novelty of the study is the assumption of convective thermal boundary conditions that show efficient heat transport phenomena. A set of similarity rules is adopted for the transformation of the governing equations, and a spectral quasi-linearization technique is then utilized for the solution of the designed miniature. One of the special attractions of the proposed study is the analysis of entropy, which is obtained due to the irreversibility processes within the system. However, irreversibility occurs because of heat transfer, diffusion processes, viscous dissipation, etc. The physical behavior of the pertinent factors is deployed graphically, whereas the validation of the result in a particular case is displayed in tabular form. We use a second law analysis to determine the origins of irreversibility in the thermal system. It is evident that an increase in fluid parameters results in a reduction in entropy generation. An augmentation in the Biot number substantially intensifies the Bejan number. The findings suggest that the magnetic parameter and fluid parameter α have a diminishing effect on velocity.

Simultaneous Quantification of Famotidine and PABA by First Order Derivative Spectral Technique of UV Spectrophotometric from FMT-PABA Cocrystals

Simultaneous Quantification of Famotidine and PABA by First Order Derivative Spectral Technique of UV Spectrophotometric from FMT-PABA Cocrystals

A highly accurate and efficient Genocchi‐based spectral technique applied to singular fractional order boundary value problems

This article focuses on an efficient and highly accurate approximate solver for a class of generalized singular boundary value problems (SBVPs) having nonlinearity and with two‐term fractional derivatives. The involved fractional derivative operators are given in the form of Liouville–Caputo. The developed algorithm for solving the generalized SBVPs consists of two main stages. The first stage is devoted to an iterative quasilinearization method (QLM) to conquer the (strong) nonlinearity of the governing SBVPs. Secondly, we employ the generalized Genocchi polynomials (GGPs) to treat the resulting sequence of linearized SBVPs numerically. An upper error estimate for the Genocchi series solution in the norm is obtained via a rigorous error analysis. The main benefit of the presented QLM‐GGPs procedure is that the required number of iteration in the first stage is within a few steps, and an accurate polynomial solution is obtained through computer implementations in the second stage. Three widely applicable test cases are investigated to observe the efficacy as well as the high‐order accuracy of the QLM‐GGPs algorithm. The comparable accuracy and robustness of the presented algorithm are validated by doing comparisons with the results of some well‐established available computational methods. It is apparently shown that the QLM‐GGPs algorithm provides a promising tool to solve strongly nonlinear SBVPs with two‐term fractional derivatives accurately and efficiently.

Towards strain gauge 2.0: Substituting the electric resistance routinely deposited on polyimide film by the optimal pattern for full‐field strain measurement

AbstractThe checkerboard constitutes the best pattern for full‐field strain measurement because it maximizes image gradient. In the experimental mechanics community, employing this pattern is currently strongly limited because depositing it on the surface of specimens raises practical difficulties. A recent study shows, however, that it is technically possible by using a laser engraver. The present paper aims to push this solution forward by printing a checkerboard pattern on a thin polymeric film and then gluing the resulting laser‐engraved film on the specimen surface. The underlying idea is to separate the manufacturing process of this optical strain gauge on the one hand and its use on the other hand to help spread this strain measuring tool in the experimental mechanics community. The polymeric film employed here is the same as that used in the manufacturing process of classic electrical gauges, so one can rely on the know‐how of classic strain gauge bonding to glue this optical strain gauge on the specimen surface. The main difference between the proposed tool and classic electrical gauges is that the strain field beneath the polymeric support is measured instead of localized strain values. The paper is a proof of concept for this strain field measuring tool. The manufacturing and bonding processes are described in the paper. The localized spectrum analysis, a spectral technique developed for processing images of periodic patterns, is used to retrieve the strain fields from checkerboard images. Through two complementary examples, we show the ability of this new type of strain gauge to detect and quantify local details in the strain field beneath. A simplified 1D model is also proposed to assess the minimum width of the strain peak that can reliably be measured with this technique.

Analysis of the Adsorption Behavior of Phenanthrene on Microplastics Based on Two-Dimensional Correlation Spectroscopy.

Microplastics (MPs), an emerging pollutant, widely co-occur with polycyclic aromatic hydrocarbons (PAHs) in the environment. Therefore, the interaction between MPs and PAHs has been the focus of much attention in recent years. In this study, three types of MPs, i.e., polypropylene, polystyrene, and poly(vinyl chloride), with the same main chain were selected as the adsorbents, with phenanthrene (PHE) as the representative PAHs. The adsorption mechanisms were explored from the perspective of the molecular spectral level using a combination of Fourier transform infrared spectroscopy (FT-IR) with a two-dimensional correlation technique. The adsorption kinetics results showed that the adsorption of PHE on the three MPs was dominated by chemisorption. However, the FT-IR analysis results indicated that no new covalent bond was created during the adsorption process. Based on the above research, a generalized two-dimensional (2D) correlation spectral technique was employed to investigate the sequence of functional group changes during the adsorption process for different MPs. Furthermore, the hybrid 2D correlation spectral technique explored the effect of side groups attached to the main chain molecules of MPs on adsorption. The results showed that for all three MPs, the functional groups in the side chain have a higher affinity for PHE, which is due to their higher hydrophobicity. This study provides a feasible way to analyze the adsorption of pollutants on MPs, and the results are important for understanding the adsorption interaction between PAHs and MPs in the aquatic environment.

Coupled thermo-elastic dynamics of rotating pre-twisted blades exposed to thermal shock including nonlinear rotational effects

Rotating blades operating under high-temperature experience intense mechanical and thermal stresses induced by centrifugal forces and thermal shock. In this research, to address this critical yet understudied topic, coupled thermo-elastic dynamics of rotating blades incorporating precise rotational effects is investigated. A comprehensive modeling approach, characterizing blade geometry in terms of pre-twist and pre-set angles is employed based on the theory of surfaces. Thermal strain–displacement field is defined based on third-order shear deformation theory in the model integrated with a third-order expansion of temperature change distribution within the blade. Rotational factors related to Coriolis, centrifugal stiffening, and rotational softening effects are considered. In the case of stiffening effects, two different modeling approaches including direct integration of centrifugal forces (DICFs), and pre-stressed dynamics about steady-state equilibrium deformations (SSEDs) are employed. When incorporating large-amplitude SSEDs in the latter, nonlinear rotational effects are incorporated into the model. To overcome the complexity arising from coupled thermo-elasticity, and rotational motion, the spectral Chebyshev technique is applied to the derived integral boundary value problems and coupled energy equations. Finally, natural frequencies, and thermal and centrifugal deformations are investigated comprehensively by including DICFs and pre-stressed dynamics. Results show that thermo-elastic dynamics of the system is highly affected by the modeling approaches used for centrifugal stiffening effects.

Three phase spectral interferometry for recording high dynamic range optical waveforms with <1 ps resolution over >2 ns records applied to closed-loop pulse shaping

We demonstrate, to our knowledge, a novel spectral interferometry technique that simultaneously captures three spectral interferograms of a signal waveform with a reference pulse. The measured performance is robust to nonidealities and ambient drifts by implementing a precisely calibrated 3×3 polarization maintaining (PM) splitter that provides three phase shift differences nominally spaced 120° apart. The system can achieve long record length by implementing three, high resolution, virtually imaged phase array (VIPA) spectrometers. Here, we experimentally implement this technique and demonstrate the measurement of waveforms with >2ns of record while maintaining <1ps resolution.

Features of melting heat transfer in magnetized squeezing radiative flow of ternary hybrid nanofluid

The increasing need for a steady energy supply to enhance efficiency is progressively growing in both residential and manufacturing industries. This demand can be addressed by utilizing advanced technologies like a melting heat generator to produce significant amounts of heat and prevent overheating. Based on the above applications of melting heat, the consequences of melting heat transfer induction on ternary hybrid nanofluid (T-HNF) exposed to solar radiation mechanism in an erratic squeezing flow are considered. The nanoparticles Copper (Cu), Silicon dioxide (SiO2), Zirconium dioxide (ZrO2) are immersed in base fluid Engine oil (EO) resulting in T-HNF (Cu + SiO2 + ZrO2/EO). The model equation also takes into account the entropy generation minimization and Bejan number. Both the spectral collocation technique (SCT) and finite element scheme (FES) are applied to solve the ordinary differential equations (ODEs) through the Mathematica package. Our results reveal that the impact of three-component nanoparticles increases, while the solar radiation parameter raises the energy profile. Also, an increase in the magnetic field deteriorates the velocity distribution. The research has various potential applications, such as in ice and snow melting, solar thermal energy storage, and the food industry.

Analysis and Comparison of Fourier and Wavelet Transforms: Application for the Study of Seismic Source Parameters, Case of the 2001 Arequipa Earthquake

The purpose of this study is to apply the spectral analysis technique to the aftershocks of the 2001 Arequipa earthquake (Mw=8.4), based on the Fourier and Wavelet transforms.The data corresponds to the world network (IRIS), which has a station called NNA that is located in Peru. Together, 10 records corresponding to replicas registered during a period of 10 days after the main event have been analyzed. The methodology used in this study was based on the SAC software that stands for "Seismic Analysis Code". As a result of the Fourier transform, the fracture radius values obtained are in the range of 0.21 to 1.15km, the stress drop values for the analyzed aftershocks are between 0.60 to 38.08Mpa, the Energy Magnitude is from 3.36 to 4.42Me; for Wavelet: the frequency content which presents the values between 0.18 to 0.30 Hz, The maximum radiated energy between 25.70 to 40.80, the values obtained are in the range of 92.18 to 146.12s. The analysis and comparison of the transforms showed that with the Fourier transform different parameters can be determined by applying spectral analysis, however, with the wavelet transform the maximum radiated energy was determined This study contributes to the literature by finding these parameters of both transforms as it is of vital importance to determine the zones of energy accumulation that would cause earthquakes of great magnitude in the future.

Tensor-based global block-diagonal structure radiation for incomplete multiview clustering

Incomplete multiview clustering (IMVC) has attracted extensive attention in the field of machine learning due to its excellent performance in handling incomplete multiview data. However, existing IMVC methods have certain limitions:1) the completion methods are not flexible enough for cases where view information is arbitrarily missing; 2) the existing methods cannot fully exploit the information contained in the clustering indicator matrix, which is crucial to the clustering results. To solve these problems, we propose a novel method, i.e., tensor-based global block-diagonal structure radiation for incomplete multiview clustering (TGBSR). First, we utilize the information from known samples to construct similarity graphs and integrate these matrices into a third-order tensor. Second, to explore the consensus information among the different similarity graphs, we introduce the spectral embedding technique to obtain the clustering indicator matrix, i.e., U. Third, and more importantly, to fully explore the information contained in the clustering indicator matrix, we introduce a novel matrix, i.e., the UUT, which is low-rank and naturally has an excellent block diagonal structure, and then incorporate it as a new view into the aforementioned tensor, which is constrained by the tensor nuclear norm (TNN), to mine the high-order correlations among all the different views. Finally, we combine all these steps into a unified framework and develop an effective iterative optimization procedure to solve it. The experimental results on several well-known datasets demonstrate the effectiveness of our method. The code is publicly available at https://github.com/hhipp-999/TGBSR.

Detectability of intracranial vessel wall atherosclerosis using black-blood spectral CT: a phantom and clinical study

BackgroundComputed tomography (CT) is the usual modality for diagnosing stroke, but conventional CT angiography reconstructions have limitations.MethodsA phantom with tubes of known diameters and wall thickness was scanned for wall detectability, wall thickness, and contrast-to-noise ratio (CNR) on conventional and spectral black-blood (SBB) images. The clinical study included 34 stroke patients. Diagnostic certainty and conspicuity of normal/abnormal intracranial vessels using SBB were compared to conventional. Sensitivity/specificity/accuracy of SBB and conventional were compared for plaque detectability. CNR of the wall/lumen and quantitative comparison of remodeling index, plaque burden, and eccentricity were obtained for SBB imaging and high-resolution magnetic resonance imaging (hrMRI).ResultsThe phantom study showed improved detectability of tube walls using SBB (108/108, 100% versus conventional 81/108, 75%, p < 0.001). CNRs were 75.9 ± 62.6 (mean ± standard deviation) for wall/lumen and 22.0 ± 17.1 for wall/water using SBB and 26.4 ± 15.3 and 101.6 ± 62.5 using conventional. Clinical study demonstrated (i) improved certainty and conspicuity of the vessels using SBB versus conventional (certainty, median score 3 versus 0; conspicuity, median score 3 versus 1 (p < 0.001)), (ii) improved sensitivity/specificity/accuracy of plaque (≥ 1.0 mm) detectability (0.944/0.981/0.962 versus 0.239/0.743/0.495) (p < 0.001), (iii) higher wall/lumen CNR of SBB of (78.3 ± 50.4/79.3 ± 96.7) versus hrMRI (18.9 ± 8.4/24.1 ± 14.1) (p < 0.001), and (iv) excellent reproducibility of remodeling index, plaque burden, and eccentricity using SBB versus hrMRI (intraclass correlation coefficient 0.85–0.94).ConclusionsSBB can enhance the detectability of intracranial plaques with an accuracy similar to that of hrMRI.Relevance statementThis new spectral black-blood technique for the detection and characterization of intracranial vessel atherosclerotic disease could be a time-saving and cost-effective diagnostic step for clinical stroke patients. It may also facilitate prevention strategies for atherosclerosis.Key points• Blooming artifacts can blur vessel wall morphology on conventional CT angiography.• Spectral black-blood (SBB) images are generated from material decomposition from spectral CT.• SBB images reduce blooming artifacts and noise and accurately detect small plaques.Graphical

Frequency characteristics of collimated blue light generated by four-wave mixing in cesium vapor.

The frequency evaluation of collimated blue light (CBL) generated by parametric four-wave mixing (FWM) in hot atomic vapor is presented. The cesium (133Cs) atoms are excited from the 6S1/2 ground state to 8S1/2 excited state with the 852 and 795 nm pump lasers, producing an optical field at 4.2 µm through an amplified spontaneous emission via population inversion on the 8S1/2 → 7P3/2 transition and the 456 nm CBL via FWM on the 7P3/2 → 6S1/2 transition. The frequency shift of 456 nm CBL has been measured by velocity-selective optical pumping spectral technique when the frequency of any one of two pumping lasers is tuned. The ratio of the frequency shift of 456 nm CBL to the two-photon frequency detuning of two pumping lasers is 0.8912, implying that the generated 4.2 µm light frequency is also correspondingly shifted.

Spectral enhancement of PlanetScope using Sentinal-2 images to estimate soybean yield and seed composition

Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.

Reevaluating soil amplification using multi-spectral HVSR technique in La Chana Neighborhood, Granada, Spain

This work presents a thorough reevaluation of soil amplification in the La Chana neighborhood of Granada through a pioneering application of the horizontal-to-vertical spectral ratio technique on seismic noise data using various spectral approaches. The research recycles old seismic noise data recorded at 34 stations with 2 Hz instruments in the year 2010, supplemented with additional measurements recorded with broadband seismometers at nearby locations in the years 2013 and 2017. Initial traditional processing identifies a narrowband dominant frequency around 1.5 Hz, attributed to artificial or anthropogenic sources. To address this, the Maximum Entropy Algorithm was implemented to smooth the spectral response below 1 Hz, and filter out frequency peaks with very narrow spectral bands, while preserving the narrowband frequency around 1.5 Hz in some records. The Thomson Multitaper method further refined the spectral ratio, emphasizing the detection and suppression of narrow frequency bands that may be related to industrial activity. The results demonstrated the reappearance of the 1.5 Hz frequency, but this time without narrow bandwidths, indicating its possible correlation with the natural ground movement. Fundamental periods, ranging from 0.45 s to 0.88 s, suggest a diverse lithological composition, indicating the presence of layers of sands, clays, conglomerates, and carbonates over a basement that represents the main impedance contrast in the area. The multispectral approach surpasses conventional methods in precision and reliability, providing valuable insights for earthquake risk assessment, urban planning, and engineering decisions in seismically active regions.

Monitoring Biophysical Variables (FVC, LAI, LCab, and CWC) and Cropland Dynamics at Field Scale Using Sentinel-2 Time Series

Biophysical variables play a crucial role in understanding phenological stages and crop dynamics, optimizing ultimate agricultural practices, and achieving sustainable crop yields. This study examined the effectiveness of the Sentinel-2 Biophysical Processor (S2BP) in accurately estimating crop dynamics descriptors, including fractional vegetation cover (FVC), leaf area index (LAI), leaf chlorophyll a and b (LCab), and canopy water content (CWC). The evaluation was conducted using estimation quality indicators (EQIs) and comprehensive ground throughout the entire growing season at the field scale. To identify soil and vegetation pixels, the spectral unmixing technique was employed. According to the EQIs, the best retrievals were obtained for FVC in around 99.9% of the 23,976 pixels that were analyzed during the growth season. For LAI, LCab, and CWC, over 60% of the examined pixels had inputs that were out-of-range. Furthermore, in over 35% of the pixels, the output values for LCab and CWC were out-of-range. The FVC, LAI, and LCab estimates agreed well with ground measurements (R2 = 0.62–0.85), whereas a discrepancy was observed for CWC estimates when compared with ground measurements (R2 = 0.51). Furthermore, the uncertainties of FVC, LAI, LCab, and CWC estimates were 0.09, 0.81 m2/m2, 60.85 µg/cm2, and 0.02 g/cm2 through comparisons to ground FVC, LAI, Cab, and CWC measurements, respectively. Considering EQIs and uncertainty metrics, the order of the estimation accuracy of the four variables was FVC &gt; LAI &gt; LCab &gt; CWC. Our analysis revealed that temporal variations of FVC, LAI, and LCab were primarily driven by field-scale events like sowing date, growing period, and harvesting time, highlighting their sensitivity to agricultural practices. The robustness of S2BP results could be enhanced by implementing a pixel identification algorithm, like embedding spectral unmixing. Overall, this study provides detailed, pixel-by-pixel insights into the performance of S2BP in estimating FVC, LAI, LCab, and CWC, which are crucial for monitoring crop dynamics in precision agriculture.