Functional near-infrared spectroscopy in non-invasive neuromodulation

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.

Spatial sensitivity to absorption changes for various near-infrared spectroscopy methods:A compendium review

This compendium review focuses on the spatial distribution of sensitivity to localized absorption changes in optically diffuse media,particularly for measurements relevant to near-infrared spectroscopy.The three temporal domains,continuous wave,frequency domain,and time domain,each obtain different optical data types whose changes may be related to effective homogeneous changes in the absorption coefficient.Sensitivity is the relationship between a localized perturbation and the recovered effective homogeneous absorption change.Therefore,spatial sensitivity maps representing the perturbation location can be generated for the numerous optical data types in the three temporal domains.The review first presents a history of the past 30 years of work investigating this sensitivity in optically diffuse media.These works are experimental and theoretical,presenting one-,two-,and three-dimensional sensitivity maps for different Near-Infrared Spectroscopy methods,domains,and data types.Following this history,we present a compendium of sensitivity maps organized by temporal domain and then data type.This compendium provides a valuable tool to compare the spatial sensitivity of various measurement methods and parameters in one document.Methods for one to generate these maps are provided in Appendix A,including the code.This historical review and comprehensive sensitivity map compendium provides a single source researchers may use to visualize,investigate,compare,and generate sensitivity to localized absorption change maps.

Near-infrared spectroscopy in schizophrenia:A bibliometric perspective

BACKGROUND Compared with current methods used to assess schizophrenia,near-infrared spectroscopy(NIRS)has the advantages of providing noninvasive and real-time monitoring of functional activities of the brain and providing direct and objective assessment information.AIM To explore the research field of NIRS in schizophrenia from the perspective of bibliometrics.METHODS The Web of Science Core Collection was used as the search tool,and the last search date was April 21,2024.Bibliometric indicators,such as the numbers of publications and citations,were recorded.Bibliometrix and VOS viewer were used for visualization analysis.RESULTS A total of 355 articles from 105 journals were included in the analysis.The overall trend of the number of research publications increased.Schizophrenia Research was identified as an influential journal in the field.Kasai K was one of the most influential and productive authors in this area of research.The University of Tokyo and Japan had the highest scientific output for an institution and a country,respectively.The top ten keywords were“schizophrenia”,“activation”,“near-infrared spectroscopy”,“verbal fluency task”,“cortex”,“brain,performance”,“workingmemory”,“brain activation”,and“prefrontal cortex”.CONCLUSION Our study reveals the evolution of knowledge and emerging trends in the field of NIRS in schizophrenia.the research focus is shifting from underlying disease characteristics to more in-depth studies of brain function and physiological mechanisms.

Millet Origin Identification Model Based on Near-infrared Spectroscopy

[Objectives]This study was conducted to clarify the difference of millet from different producing areas in near-infrared spectroscopy(NIRS)modeling.[Methods]Millet samples from six different regions were collected for NIRS analysis,and an origin identification model based on BP neural network was established.The competitive adaptive reweighted sampling(CARS)algorithm was used to extract characteristic wavelength variables,and a CARS-BP model was established on this basis.Finally,the CARS-BP model was compared with support vector machine(SVM),partial least squares discriminant analysis(PLS)and KNN models.[Results]The characteristic wavelengths were extracted by CARS,and the number of variables was reduced from 1845 to 130.The discrimination accuracy of the CARS-BP model for the samples from six producing areas reached 98.1%,which was better than SVM,PSL and KNN models.[Conclusions]NIRS can quickly and accurately identify the origin of millet,providing a new method and way for the origin identification and quality evaluation of millet.

A highly sensitive ratiometric near-infrared nanosensor based on erbium-hyperdoped silicon quantum dots for iron(Ⅲ) detection

Ratiometric fluorescent detection of iron(Ⅲ)(Fe^(3+))offers inherent self-calibration and contactless analytic capabilities.However,realizing a dual-emission near-infrared(NIR)nanosensor with a low limit of detection(LOD)is rather challenging.In this work,we report the synthesis of water-dispersible erbium-hyperdoped silicon quantum dots(Si QDs:Er),which emit NIR light at the wavelengths of 810 and 1540 nm.A dual-emission NIR nanosensor based on water-dispersible Si QDs:Er enables ratiometric Fe^(3+)detection with a very low LOD(0.06μM).The effects of pH,recyclability,and the interplay between static and dynamic quenching mechanisms for Fe^(3+)detection have been systematically studied.In addition,we demonstrate that the nanosensor may be used to construct a sequential logic circuit with memory functions.

Cortical activity in patients with high-functioning ischemic stroke during the Purdue Pegboard Test:insights into bimanual coordinated fine motor skills with functional near-infrared spectroscopy

After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.

Rapid Determination of Hemicellulose Content in Corn Stalks by Near-infrared Spectroscopy Based on Dung Beetle Optimizer

Corn stalks are a kind of common organic fertilizer and feed material in agriculture in China,as well as an important source of modern biomass energy and new materials.Hemicellulose is an important component in corn stalks,and it is very important to determine its content in corn stalks.In this paper,the feasibility of near-infrared spectroscopy(NIRS)combined with chemometrics for rapid detection of hemicellulose content in corn stalks was studied.In order to improve the accuracy of NIRS detection,a new intelligent optimization algorithm,dung beetle optimizer(DBO),was applied to select characteristic wavelengths of NIRS.Its modeling performance was compared with that based on characteristic wavelength selection using genetic algorithm(GA)and binary particle swarm optimization(BPSO),and it was found that the characteristic wavelength selection performance of DBO was excellent,and the regression accuracy of hemicellulose quantitative detection model established by its preferred characteristic wavelengths was better than the above two intelligent optimization algorithms.

Near-infrared cholangiography with intragallbladder indocyanine green injection in minimally invasive cholecystectomy

Laparoscopic cholecystectomy(LC)remains one of the most commonly performed procedures in adult and paediatric populations.Despite the advances made in intraoperative biliary anatomy recognition,iatrogenic bile duct injuries during LC represent a fatal complication and consist an economic burden for healthcare systems.A series of methods have been proposed to prevent bile duct injury,among them the use of indocyanine green(ICG)fluorescence.The most commonly reported method of ICG injection is the intravenous administration,while literature is lacking studies investigating the direct intragallbladder ICG injection.This narrative mini-review aims to assess the potential applications,usefulness,and limitations of intragallbladder ICG fluorescence in LC.Authors screened the available international literature to identify the reports of intragallbladder ICG fluorescence imaging in minimally invasive cholecystectomy,as well as special issues regarding its use.Literature search retrieved four prospective cohort studies,three case-control studies,and one case report.In the three case-control studies selected,intragallbladder near-infrared cholangiography(NIRC)was compared with standard LC under white light,with intravenous administration of ICG for NIRC and with standard intraoperative cholangiography(IOC).In total,133 patients reported in the literature have been administered intragallbladder ICG administration for biliary mapping during LC.Literature includes several reports of intragallbladder ICG administration,but a standardized technique has not been established yet.Published data suggest that NIRC with intragallbladder ICG injection is a promising method to achieve biliary mapping,overwhelming limitations of IOC including intervention and radiation exposure,as well as the high hepatic parenchyma signal and time interval needed in intravenous ICG fluorescence.Evidence-based guidelines on the role of intragallbladder ICG fluorescence in LC require the assessment of further studies and multicenter data collection into large registries.

Near-infrared spectroscopy method for rapid proximate quantitative analysis of nutrient composition in Pacific oyster Crassostrea gigas

Glycogen,amino acids,fatty acids,and other nutrient components affect the flavor and nutritional quality of oysters.Methods based on near-infrared reflectance spectroscopy(NIRS)were developed to rapidly and proximately determine the nutrient content of the Pacific oyster Crassostreagigas.Samples of C.gigas from 19 costal sites were freeze-dried,ground,and scanned for spectral data collection using a Fourier transform NIR spectrometer(Thermo Fisher Scientific).NIRS models of glycogen and other nutrients were established using partial least squares,multiplication scattering correction first-order derivation,and Norris smoothing.The R_(C) values of the glycogen,fatty acids,amino acids,and taurine NIRS models were 0.9678,0.9312,0.9132,and 0.8928,respectively,and the residual prediction deviation(RPD)values of these components were 3.15,2.16,3.11,and 1.59,respectively,indicating a high correlation between the predicted and observed values,and that the models can be used in practice.The models were used to evaluate the nutrient compositions of 1278 oyster samples.Glycogen content was found to be positively correlated with fatty acids and negatively correlated with amino acids.The glycogen,amino acid,and taurine levels of C.gigas cultured in the subtidal and intertidal zones were also significantly different.This study suggests that C.gigas NIRS models can be a cost-effective alternative to traditional methods for the rapid and proximate analysis of various slaughter traits and may also contribute to future genetic and breeding-related studies in Pacific oysters.

Functional Nonparametric Predictions in Food Industry Using Near-Infrared Spectroscopy Measurement

Functional statistics is a new technique for dealing with data thatcan be viewed as curves or images. Parallel to this approach, the Near-InfraredReflectance (NIR) spectroscopymethodology has been used in modern chemistryas a rapid, low-cost, and exact means of assessing an object’s chemicalproperties. In this research, we investigate the quality of corn and cookiedough by analyzing the spectroscopic technique using certain cutting-edgestatistical models. By analyzing spectral data and applying functional modelsto it, we could predict the chemical components of corn and cookie dough.Kernel Functional Classical Estimation (KFCE), Kernel Functional QuantileEstimation (KFQE), Kernel Functional Expectile Estimation (KFEE),Semi-Partial Linear Functional Classical Estimation (SPLFCE), Semi-PartialLinear Functional Quantile Estimation (SPLFQE), and Semi-Partial LinearFunctional Expectile Estimation (SPLFEE) are models used to accuratelyestimate the different quantities present in Corn and Cookie dough. Theselection of these functional models is based on their ability to constructa forecast region with a high level of confidence. We demonstrate that theconsidered models outperform traditional models such as the partial leastsquaresregression and the principal component regression in terms of predictionaccuracy. Furthermore, we show that the proposed models are morerobust than competing models such as SPLFQE and SPLFEE in the sensethat data heterogeneity has no effect on their efficiency.

Synchronous measurements of prefrontal activity and pulse rate variability during online video game playing with functional near-infrared spectroscopy

Interactions between the central nervous system(CNS)and autonomic nervous system(ANS)play a crucial role in modulating perception,cognition,and emotion production.Previous studies on CNS–ANS interactions,or heart–brain coupling,have often used heart rate variability(HRV)metrics derived from electrocardiography(ECG)recordings as empirical measurements of sympathetic and parasympathetic activities.Functional near-infrared spectroscopy(fNIRS)is a functional brain imaging modality that is increasingly used in brain and cognition studies.The fNIRS signals contain frequency bands representing both neural activity oscillations and heartbeat rhythms.Therefore,fNIRS data acquired in neuroimaging studies can potentially provide a single-modality approach to measure task-induced responses in the brain and ANS synchronously,allowing analysis of CNS–ANS interactions.In this proof-of-concept study,fNIRS was used to record hemodynamic changes from the foreheads of 20 university students as they each played a round of multiplayer online battle arena(MOBA)game.From the fNIRS recordings,neural and heartbeat frequency bands were extracted to assess prefrontal activities and shortterm pulse rate variability(PRV),an approximation for short-term HRV,respectively.Under the experimental conditions used,fNIRS-derived PRV metrics showed good correlations with ECG-derived HRV golden standards,in terms of absolute measurements and video game playing(VGP)-related changes.It was also observed that,similar to previous studies on physical activity and exercise,the PRV metrics closely related to parasympathetic activities recovered slower than the PRV indicators of sympathetic activities after VGP.It is concluded that it is feasible to use fNIRS to monitor concurrent brain and ANS activations during online VGP,facilitating the understanding of VGP-related heart–brain coupling.

miR⁃138⁃5p靶向Nir1调控胶质瘤细胞的侵袭

目的 探讨miR-138-5p与PYK2 N端结构域相互作用受体1(PYK2 N-terminal domain-interacting receptor 1,Nir1)之间的关系并判断其是否通过与Nir1结合影响胶质瘤的侵袭。方法 比较不同胶质瘤细胞系中miR-138-5p表达水平及其对胶质瘤细胞U251和H4中Nir1蛋白的影响、转染后胶质瘤细胞侵袭能力,检测miR-138-5p能否与Nir1靶向结合。结果 低侵袭人胶质瘤H4细胞中miR-138-5p的水平显著高于高侵袭性的胶质瘤U251、LN229和U87细胞(P<0.05);在U251、H4细胞中,miR-138-5p过表达组Nir1蛋白表达量较其对照组(miR-negative control,miR-NC)降低;miR-138-5p抑制组中Nir1蛋白表达量较其对照组(inhibitor NC)升高。然而,miR-138-5p过表达组中Nir1的mRNA水平较其对照组无明显改变(P>0.05)。miR-138-5p过表达组穿过基底膜小孔的U251、H4细胞数明显少于其对照组(P<0.05)。miR-138-5p过表达显著降低Nir1-3’-UTR的荧光素酶活性。结论 胶质瘤细胞中miR-138-5p与Nir1结合,可通过降低Nir1的翻译、减少Nir1蛋白的表达抑制胶质瘤细胞的侵袭能力。

Near-infrared spectroscopy(NIRS) evaluation and regional analysis of Chinese faba bean(Vicia faba L.)

To analyze the nutritional composition of faba bean(Vicia faba L.) seed, estimation models were developed for protein, starch, oil, and total polyphenol using near infrared spectroscopy(NIRS). Two hundred and forty-four samples from twelve producing regions were measured in both milled powder and intact seed forms. Partial least squares(PLS) regression was applied for model development. The model based on ground seed powder was generally superior to that based on the intact seed. The optimal seed powder-based models for protein, starch, and total polyphenol had coefficients of correlation(r2) of 0.97, 0.93 and 0.89, respectively. The relationship between nutrient contents and twelve producing areas was determined by two-step cluster analysis. Three distinct groupings were obtained with region-constituent features, i.e., Group 1 of high oil, Group 2 of high protein, and Group 3 of high starch as well as total polyphenol. The clustering accuracy was 79.5%. Moreover, the nutrition contents were affected by seeding date, longitude, latitude, and altitude of plant location. Cluster analysis revealed that the differences in the seed were strongly influenced by geographical factors.

High efficiency and high transmission asymmetric polarization converter with chiral metasurface in visible and near-infrared region

Polarization manipulation of light is of great importance because it could promote development of wireless communications,biosensing,and polarization imaging.In order to use natural light more efficiently,it is highly demanded to design and fabricate high performance asymmetric polarization converters which could covert the natural light to one particular linearly polarized light with high efficiency.Traditionally,polarizers could be achieved by controllers with crystals and polymers exhibiting birefringence.However,the polarizers are bulky in size and the theoretical conversion efficiency of the polarizers is limited to 0.5 with unpolarized light incidence.In this paper,we propose a polarization converter which could preserve high transmission for one linearly polarized light and convert the orthogonal linearly polarized light to its cross-polarized with high transmittance based on a multi-layer chiral metasurface.Theoretical results show that normally incident y-polarized light preserves high transmittance for the wavelength range from 685 nm to 800 nm while the orthogonal normally incident x-polarized light is efficiently converted to the y-polarized light with high transmittance from 725 nm to 748 nm.Accordingly,for unpolarized light incidence,transmittance larger than 0.5 has been successfully achieved in a broadband wavelength range from 712 nm to 773 nm with a maximum transmittance of 0.58 at 732 nm.

Assessment of cerebral oxygenation response to hemodialysis using near-infrared spectroscopy (NIRS):Challenges and solutions

To date,the clinical use of functional near-infrared spectroscopy(NIRS)to detect cerebral ischemia has been largely limited to surgical settings,where motion artifacts are minimal.In this study,we present novel techniques to address the challenges of using NIRS to monitor ambu-latory patients with kidney disease during approximately eight hours of hemodialysis(HD)treatment.People with end-stage kidney disease who require HD are at higher risk for cognitive impairment and dementia than age-matched controls.Recent studies have suggested that HD-related declines in cerebral blood flow might explain some of the adverse outcomes of HD treatment.However,there are currently no established paradigms for monitoring cerebral per-fusion in real-time during HD treatment.In this study,we used NIRS to assess cerebral hemo-dynamic responses among 95 prevalent HD patients during two consecutive HD treatments.We observed substantial signal attenuation in our predominantly Black patient cohort that required probe modifications.We also observed consistent motion artifacts that we addressed by devel-oping a novel NIRS methodology,called the HD cerebral oxygen demand algorithm(HD-CODA),to identify episodes when cerebral oxygen demand might be outpacing supply during HD treatment.We then examined the association between a summary measure of time spent in cerebral deoxygenation,derived using the HD-CODA,and hemodynamic and treatment-related variables.We found that this summary measure was associated with intradialytic mean arterial pressure,heart rate,and volume removal.Future studies should use the HD-CODA to implement studies of real-time NIRS monitoring for incident dialysis patients,over longer time frames,and in other dialysis modalities.

Deep-red and near-infrared organic lasers based on centrosymmetric molecules with excited-state intramolecular double proton transfer activity

Organic lasers that emit light in the deep-red and near-infrared(NIR)region are of essential importance in laser communication,night vision,bioimaging,and information-secured displays but are still challenging because of the lack of proper gain materials.Herein,a new molecular design strategy that operates by merging two excited-state intramolecular proton transfer-active molecules into one excited-state double proton transfer(ESDPT)-active molecule was demonstrated.Based on this new strategy,three new materials were designed and synthesized with two groups of intramolecular resonance-assisted hydrogen bonds,in which the ESDPT process was proven to proceed smoothly based on theoretical calculations and experimental results of steady-state and transient spectra.Benefiting from the effective six-level system constructed by the ESDPT process,all newly designed materials showed low threshold laser emissions at approximately 720 nm when doped in PS microspheres,which in turn proved the existence of the second proton transfer process.More importantly,our well-developed NIR organic lasers showed high laser stability,which can maintain high laser intensity after 12000 pulse lasing,which is essential in practical applications.This work provides a simple and effective method for the development of NIR organic gain materials and demonstrates the ESDPT mechanism for NIR lasing.

Superiority of indocyanine green-enhanced near-infrared fluorescence-guided imaging for laparoscopic lymph node dissection in patients with early-stage endometrial cancer: A retrospective cohort study

Objective:Laparoscopic pelvic lymph node dissection(LPND),which is an effective therapy for endometrial cancer,is challenging because of the complexity of the procedure and the occurrence of postoperative complications.This study aimed to explore whether indocyanine green(ICG)-enhanced nearinfrared(NIR)fluorescence-guided LPND is superior to LPND in the context of early-stage endometrial carcinoma.Methods:In this retrospective study,we included the medical records of 190 patients with early-stage endometrioid adenocarcinoma who underwent LPND at the Department of Obstetrics and Gynecology,Sir Run Run Shaw Hospital,Zhejiang University School of Medicine between January 2019 and January 2021.Depending on whether ICG-enhanced NIR fluorescence guidance was used,the patients were assigned to the ICG group or non-ICG group.Patients were followed-up for one year after surgery.Data on demographic characteristics,pathological results,operative outcomes,and complications were collected and analyzed.Results:The baseline characteristics were comparable between the ICG group and non-ICG group,including age,BMI,pregnancy history,and preoperative hemoglobin.For surgical outcomes,the patients in ICG group had significantly lower intraoperative blood loss(50 mL vs.120 mL,p<0.001),less postoperative pelvic drainage time(4.14±1.44 d vs.5.70±1.89 d,p¼0.001),shorter duration of hospital stay(5.26±1.41 d vs.7.37±1.85 d,p¼0.003),higher number of positive pelvic lymph nodes(PLNs)(1 vs.0,p¼0.003),and more PLN-positive cases(16.0%vs.3.6%,p¼0.003)than the patients in non-ICG group.However,no significant differences were noted in blood transfusion requirement,operative time,hemoglobin level decreases,number of PLNs harvested,or the presence of lymphocysts between the two groups.Conclusion:Our study showed that ICG-enhanced NIR fluorescence-guided operation may improve the accuracy and safety of LPND.

Near-infrared leaf reflectance modeling of Annona emarginata seedlings for early detection of variations in nitrogen concentration

Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can also provide the basis for developing a new vegetation spectral index(VSI).Here,we evaluated whether NIRS combined with statistical modeling can accurately detect early variations in N concentration in leaves of young plants of Annona emargiaata and developed a new VSI for this task.Plants were grown in a hydroponics system with 0,2.75,5.5or 11 mM N for 45 days.Then we measured gas exchange,chlorophylla fluorescence,and pigments in leaves;analyzed complete leaf nutrients,and recorded spectral data for leaves at 966 to 1685 nm using NIRS.With a statistical learning approach,the dimensionality of the spectral data was reduced,then models were generated using two classes(N deficiency,N)or four classes(0,2.75,5.5,11 mM N).The best combination of techniques for dimensionality reduction and classification,respectively,was stepwise regression(PROC STEPDISC)and linear discriminant function.It was possible to detect N deficiency in seedlings leaves with 100%precision,and the four N concentrations with93.55%accuracy before photosynthetic damage to the plant occurred.Thereby,NIRS combined with statistical modeling of multidimensional data is effective for detecting N variations in seedlings leaves of A.emarginata.

Prediction of Crude Protein in Ramie by Near-Infrared Spectroscopy(NIR)

[Objective] This study was conducted to evaluate the feasibility of deter- mining crude protein in ramie using near-infrared （NIR） spectrometer. [Method] Par- tial least square regression （PLSR） was performed to establish a calibration model based on 50 samples for predicting the crude protein content in ramie, and the model was validated with data in the validation set consisting of 10 samples. [Result] The correlation coefficient of the model was 0.98. There was a good correla- tion between the predicted values by the near-infrared prediction model and the measured values by chemical analysis, and the relative error was 3.54% on aver- age between the predicted and the measured values. [Conclusion] The results showed that it is feasible to determine crude protein content in ramie using NIR spectroscopy-based prediction model.

基于RGB-NIR滤波阵列的引入权重系数的加权引导滤波去马赛克方法

针对RGB-NIR传感器多光谱成像技术中的去马赛克问题,提出了一种引入权重系数的加权引导滤波去马赛克算法。算法以残差插值为框架,引入加权引导滤波代替引导滤波,通过边缘感知权重因子实现对边缘的检测,提高引导滤波在边缘处的性能。算法使用G通道图像作为引导图,首先进行G通道图像的插值,然后通过加权引导滤波的方法插值出R、B、NIR通道的图像。此外,为了解决在引导滤波中计算线性系数时采用简单的平均值的问题,引入权重系数,并通过加权平均的方式计算得到更准确的线性系数。在TokyoTech数据集以及实际器件上测试了该算法。在数据集的实验上,提出的算法比现有的高性能算法在彩色图像和红外图像上峰值信噪比分别高0.38 dB和0.88 dB;在实际器件实验中,不论是在红外光源打开还是关闭的情况下,所提出的算法在多个场景下表现出最低的平均NIQE指标。此外,在红外光源变动前后,提出的算法所得到的图像的平均NIQE变化也是最小的。实验结果表明,该算法的性能优于对比的算法,并且拥有更好的鲁棒性。