Displaying publications 1 - 20 of 35 in total

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  1. Ong P, Yeh CW, Tsai IL, Lee WJ, Wang YJ, Chuang YK
    PMID: 37531681 DOI: 10.1016/j.saa.2023.123214
    Consumption of agricultural products with pesticide residue is risky and can negatively affect health. This study proposed a nondestructive method of detecting pesticide residues in chili pepper based on the combination of visible and near-infrared (VIS/NIR) spectroscopy (400-2498 nm) and deep learning modeling. The obtained spectra of chili peppers with two types of pesticide residues (acetamiprid and imidacloprid) were analyzed using a one-dimensional convolutional neural network (1D-CNN). Compared with the commonly used partial least squares regression model, the 1D-CNN approach yielded higher prediction accuracy, with a root mean square error of calibration of 0.23 and 0.28 mg/kg and a root mean square error of prediction of 0.55 and 0.49 mg/kg for the acetamiprid and imidacloprid data sets, respectively. Overall, the results indicate that the combination of the 1D-CNN model and VIS/NIR spectroscopy is a promising nondestructive method of identifying pesticide residues in chili pepper.
    Matched MeSH terms: Spectroscopy, Near-Infrared/methods
  2. Omar AF, MatJafri MZ
    Sensors (Basel), 2013;13(4):4876-83.
    PMID: 23584118 DOI: 10.3390/s130404876
    This study presents a novel application of near infrared (NIR) spectral linearisation for measuring the soluble solids content (SSC) of carambola fruits. NIR spectra were measured using reflectance and interactance methods. In this study, only the interactance measurement technique successfully generated a reliable measurement result with a coefficient of determination of (R2) = 0.724 and a root mean square error of prediction for (RMSEP) = 0.461° Brix. The results from this technique produced a highly accurate and stable prediction model compared with multiple linear regression techniques.
    Matched MeSH terms: Spectroscopy, Near-Infrared/methods*
  3. Ong P, Chen S, Tsai CY, Chuang YK
    PMID: 33744842 DOI: 10.1016/j.saa.2021.119657
    In this study, near-infrared (NIR) spectroscopy was exploited for non-destructive determination of theanine content of oolong tea. The NIR spectral data (400-2500 nm) were correlated with the theanine level of 161 tea samples using partial least squares regression (PLSR) with different wavelengths selection methods, including the regression coefficient-based selection, uninformative variable elimination, variable importance in projection, selectivity ratio and flower pollination algorithm (FPA). The potential of using the FPA to select the discriminative wavelengths for PLSR was examined for the first time. The analysis showed that the PLSR with FPA method achieved better predictive results than the PLSR with full spectrum (PLSR-full). The developed simplified model using on FPA based on 12 latent variables and 89 selected wavelengths produced R-squared (R2) value and root mean squared error (RMSE) of 0.9542, 0.8794 and 0.2045, 0.3219 for calibration and prediction, respectively. For PLSR-full, the R2 values of 0.9068, 0.8412 and RMSEs of 0.2916, 0.3693, were achieved for calibration and prediction. Also, the optimized model using FPA outperformed other wavelengths selection methods considered in this study. The obtained results indicated the feasibility of FPA to improve the predictability of the PLSR and reduce the model complexity. The nonlinear regression models of support vector machine regression and Gaussian process regression (GPR) were further utilized to evaluate the superiority of using the FPA in the wavelength selection. The results demonstrated that utilizing the wavelength selection method of FPA and nonlinear regression model of GPR could improve the predictive performance.
    Matched MeSH terms: Spectroscopy, Near-Infrared*
  4. Husain SF, Chiang SK, Vasu AA, Goh CP, McIntyre RS, Tang TB, et al.
    J Atten Disord, 2023 Nov;27(13):1448-1459.
    PMID: 37341192 DOI: 10.1177/10870547231180111
    OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) provides direct and quantitative assessment of cortical hemodynamic response. It has been used to identify neurophysiological alterations in medication-naïve adults with attention-deficit/hyperactivity disorder (ADHD). Hence, this study aimed to distinguish both medication-naïve and medicated adults with ADHD from healthy controls (HC).

    METHOD: 75 HCs, 75 medication-naïve, and 45 medicated patients took part in this study. fNIRS signals during a verbal fluency task (VFT) were acquired using a 52-channel system and relative oxy-hemoglobin changes in the prefrontal cortex were quantified.

    RESULTS: Prefrontal cortex hemodynamic response was lower in patients than HCs (p ≤ ≤.001). Medication-naïve and medicated patients did not differ in hemodynamic response or symptom severity (p > .05). fNIRS measurements were not associated with any clinical variables (p > .05). 75.8% patients and 76% HCs were correctly classified using hemodynamic response.

    CONCLUSION: fNIRS may be a potential diagnostic tool for adult ADHD. These findings need to be replicated in larger validation studies.

    Matched MeSH terms: Spectroscopy, Near-Infrared/methods
  5. Husain SF, Tang TB, Tam WW, Tran BX, Ho CS, Ho RC
    BMC Psychiatry, 2021 04 20;21(1):201.
    PMID: 33879125 DOI: 10.1186/s12888-021-03195-1
    BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging modality that provides a direct and quantitative assessment of cortical haemodynamic response during a cognitive task. It may be used to identify neurophysiological differences between psychiatric disorders with overlapping symptoms, such as bipolar disorder (BD) and borderline personality disorder (BPD). Hence, this preliminary study aimed to compare the cerebral haemodynamic function of healthy controls (HC), patients with BD and patients with BPD.

    METHODS: Twenty-seven participants (9 HCs, 9 patients with BD and 9 patients with BPD) matched for age, gender, ethnicity and education were recruited. Relative oxy-haemoglobin and deoxy-haemoglobin changes in the frontotemporal cortex was monitored with a 52-channel fNIRS system during a verbal fluency task (VFT). VFT performance, clinical history and symptom severity were also noted.

    RESULTS: Compared to HCs, both patient groups had lower mean oxy-haemoglobin in the frontotemporal cortex during the VFT. Moreover, mean oxy-haemoglobin in the left inferior frontal region is markedly lower in patients with BPD compared to patients with BD. Task performance, clinical history and symptom severity were not associated with mean oxy-haemoglobin levels.

    CONCLUSIONS: Prefrontal cortex activity is disrupted in patients with BD and BPD, but it is more extensive in BPD. These results provide further neurophysiological evidence for the separation of BPD from the bipolar spectrum. fNIRS could be a potential tool for assessing the frontal lobe function of patients who present with symptoms that are common to BD and BPD.

    Matched MeSH terms: Spectroscopy, Near-Infrared
  6. Mohd Hilmi Tan MIS, Jamlos MF, Omar AF, Dzaharudin F, Chalermwisutkul S, Akkaraekthalin P
    Sensors (Basel), 2021 Apr 27;21(9).
    PMID: 33925576 DOI: 10.3390/s21093052
    Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  7. Lee OW, Mao D, Savkovic B, Wunderlich J, Nicholls N, Jeffreys E, et al.
    Ear Hear, 2023 01 14;44(4):776-786.
    PMID: 36706073 DOI: 10.1097/AUD.0000000000001325
    OBJECTIVES: Cardiac responses (e.g., heart rate changes) due to an autonomous response to sensory stimuli have been reported in several studies. This study investigated whether heart rate information extracted from functional near-infrared spectroscopy (fNIRS) data can be used to assess the discrimination of speech sounds in sleeping infants. This study also investigated the adaptation of the heart rate response over multiple, sequential stimulus presentations.

    DESIGN: fNIRS data were recorded from 23 infants with no known hearing loss, aged 2 to 10 months. Speech syllables were presented using a habituation/dishabituation test paradigm: the infant's heart rate response was first habituated by repeating blocks of one speech sound; then, the heart rate response was dishabituated with the contrasting (novel) speech sound. This stimulus presentation sequence was repeated for as long as the infants were asleep.

    RESULTS: The group-level average heart rate response to the novel stimulus was greater than that to the habituated first sound, indicating that sleeping infants were able to discriminate the speech sound contrast. A significant adaptation of the heart rate responses was seen over the session duration.

    CONCLUSION: The dishabituation response could be a valuable marker for speech discrimination, especially when used in conjunction with the fNIRS hemodynamic response.

    Matched MeSH terms: Spectroscopy, Near-Infrared
  8. Chia KS, Abdul Rahim H, Abdul Rahim R
    J Zhejiang Univ Sci B, 2012 Feb;13(2):145-51.
    PMID: 22302428 DOI: 10.1631/jzus.B11c0150
    Visible and near infrared spectroscopy is a non-destructive, green, and rapid technology that can be utilized to estimate the components of interest without conditioning it, as compared with classical analytical methods. The objective of this paper is to compare the performance of artificial neural network (ANN) (a nonlinear model) and principal component regression (PCR) (a linear model) based on visible and shortwave near infrared (VIS-SWNIR) (400-1000 nm) spectra in the non-destructive soluble solids content measurement of an apple. First, we used multiplicative scattering correction to pre-process the spectral data. Second, PCR was applied to estimate the optimal number of input variables. Third, the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models. The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN. Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.
    Matched MeSH terms: Spectroscopy, Near-Infrared/methods*
  9. Mao D, Wunderlich J, Savkovic B, Jeffreys E, Nicholls N, Lee OW, et al.
    Sci Rep, 2021 12 14;11(1):24006.
    PMID: 34907273 DOI: 10.1038/s41598-021-03595-z
    Speech detection and discrimination ability are important measures of hearing ability that may inform crucial audiological intervention decisions for individuals with a hearing impairment. However, behavioral assessment of speech discrimination can be difficult and inaccurate in infants, prompting the need for an objective measure of speech detection and discrimination ability. In this study, the authors used functional near-infrared spectroscopy (fNIRS) as the objective measure. Twenty-three infants, 2 to 10 months of age participated, all of whom had passed newborn hearing screening or diagnostic audiology testing. They were presented with speech tokens at a comfortable listening level in a natural sleep state using a habituation/dishabituation paradigm. The authors hypothesized that fNIRS responses to speech token detection as well as speech token contrast discrimination could be measured in individual infants. The authors found significant fNIRS responses to speech detection in 87% of tested infants (false positive rate 0%), as well as to speech discrimination in 35% of tested infants (false positive rate 9%). The results show initial promise for the use of fNIRS as an objective clinical tool for measuring infant speech detection and discrimination ability; the authors highlight the further optimizations of test procedures and analysis techniques that would be required to improve accuracy and reliability to levels needed for clinical decision-making.
    Matched MeSH terms: Spectroscopy, Near-Infrared*
  10. Raypah ME, Omar AF, Muncan J, Zulkurnain M, Abdul Najib AR
    Molecules, 2022 Apr 03;27(7).
    PMID: 35408723 DOI: 10.3390/molecules27072324
    Honey is a natural product that is considered globally one of the most widely important foods. Various studies on authenticity detection of honey have been fulfilled using visible and near-infrared (Vis-NIR) spectroscopy techniques. However, there are limited studies on stingless bee honey (SBH) despite the increase of market demand for this food product. The objective of this work was to present the potential of Vis-NIR absorbance spectroscopy for profiling, classifying, and quantifying the adulterated SBH. The SBH sample was mixed with various percentages (10−90%) of adulterants, including distilled water, apple cider vinegar, and high fructose syrup. The results showed that the region at 400−1100 nm that is related to the color and water properties of the samples was effective to discriminate and quantify the adulterated SBH. By applying the principal component analysis (PCA) on adulterants and honey samples, the PCA score plot revealed the classification of the adulterants and adulterated SBHs. A partial least squares regression (PLSR) model was developed to quantify the contamination level in the SBH samples. The general PLSR model with the highest coefficient of determination and lowest root means square error of cross-validation (RCV2=0.96 and RMSECV=5.88 %) was acquired. The aquaphotomics analysis of adulteration in SBH with the three adulterants utilizing the short-wavelength NIR region (800−1100 nm) was presented. The structural changes of SBH due to adulteration were described in terms of the changes in the water molecular matrix, and the aquagrams were used to visualize the results. It was revealed that the integration of NIR spectroscopy with aquaphotomics could be used to detect the water molecular structures in the adulterated SBH.
    Matched MeSH terms: Spectroscopy, Near-Infrared/methods
  11. Harun MY, Dayang Radiah AB, Zainal Abidin Z, Yunus R
    Bioresour Technol, 2011 Apr;102(8):5193-9.
    PMID: 21333529 DOI: 10.1016/j.biortech.2011.02.001
    Effects of different physical pretreatments on water hyacinth for dilute acid hydrolysis process (121 ± 3 °C, 5% H(2)SO(4), 60 min) were comparatively investigated. Untreated sample had produced 24.69 mg sugar/g dry matter. Steaming (121 ± 3 °C) and boiling (100 ± 3 °C) for 30 min had provided 35.9% and 52.4% higher sugar yield than untreated sample, respectively. The highest sugar yield (132.96 mg sugar/g dry matter) in ultrasonication was obtained at 20 min irradiation using 100% power. The highest sugar production (155.13 mg sugar/g dry matter) was obtained from pulverized samples. Hydrolysis time was reduced when using samples pretreated by drying, mechanical comminution and ultrasonication. In most methods, prolonging the pretreatment period was ineffective and led to sugar degradations. Morphology inspection and thermal analysis had provided evidences of structure disruption that led to higher sugar recovery in hydrolysis process.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  12. Izneid BA, Fadhel MI, Al-Kharazi T, Ali M, Miloud S
    J Food Sci Technol, 2014 Nov;51(11):3244-52.
    PMID: 26396317 DOI: 10.1007/s13197-012-0880-z
    A portable infrared spectroscopy system has been designed and developed for assessment of quality of mango fruit. This paper describes the design and development of a fruit quality grading device using reflectance mode optical sensor. The experiment was conducted to obtain the best results from the system and the device was correlated according to the measured output. In the experiment, several samples of mango fruits have been monitored for six days to study the relation how fruit quality increases with time as fruit ripens. Between the unripe mango fruit and the ripest one, a range of 3.5 V to 4.2 V was measured by the developed system. The rate of quality increase was calculated as an average of 6.7 mV per day. These results were used to correlate the final hardware and software development of the device. The results demonstrate that, portable near infrared spectroscopy is feasible for evaluating mango quality non-destructively.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  13. Khan AF, Sajjad W, Rahim NA
    Recent Pat Nanotechnol, 2016;10(1):77-82.
    PMID: 27018275
    BACKGROUND: It is well-known that multi-layer films with nanostructure can give novel properties by interfacial phenomenon and quantum confinement effects. Nanostructured multi-layer thin films are presently being analyzed for their vast applications in the area of optoelectronics technology particularly photovoltaics. Hereof, two dimensional thin films with nanostructure are of prime importance due to their structure dependent optical, electrical, and opto-electronic properties. It has been revealed that these films exhibit quantum confinement effects with band gap engineering. The main focus of the research is to evaluate the effect on structural and optical properties with number of layers.

    METHODS: Nanostructured SnO2-Ge multi-layer thin films were fabricated using electron beam evaporation and resistive heating techniques. Alternate layers of SnO2 and Ge were deposited on glass substrate at a substrate temperature of 300 °C in order to obtain uniform and homogeneous deposition. The substrate temperature of 300 °C has been determined to be effective for the deposition of these multi-layer films from our previous studies. The films were characterized by investigating their structural and optical properties. The structural properties of the as-deposited films were characterized by Rutherford Backscattering Spectroscopy (RBS) and Raman spectroscopy and optical properties by Ultra-Violet-Near infrared (UV-VIS-NIR) spectroscopy.

    RESULTS: RBS studies confirmed that the layer structure has been effectively formed. Raman spectroscopy results show that the peaks of both Ge and SnO2 shifts towards lower wavenumbers (in comparison with bulk Ge and SnO2, suggesting that the films consist of nanostructures and demonstrate quantum confinement effects. UV-VIS-NIR spectroscopy showed an increase in the band gap energy of Ge and SnO2 and shifting of transmittance curves toward higher wavelength by increasing the number of layers. The band gap lies in the range of 0.9 to 1.2 eV for Ge, while for SnO2, it lies between 1.7 to 2.1 eV.

    CONCLUSION: Analysis of results suggests that the nanostructured SnO2-Ge multi-layer thin film can work as heterojunction materials with quantum confinement effects. Accordingly, the present SnO2-Ge multi-layer films may be employed for photovoltaic applications. Few relevant patents to the topic have been reviewed and cited.

    Matched MeSH terms: Spectroscopy, Near-Infrared
  14. Alyan E, Saad NM, Kamel N, Rahman MA
    Appl Ergon, 2021 Oct;96:103497.
    PMID: 34139374 DOI: 10.1016/j.apergo.2021.103497
    This study aims to evaluate the effect of workstation type on the neural and vascular networks of the prefrontal cortex (PFC) underlying the cognitive activity involved during mental stress. Workstation design has been reported to affect the physical and mental health of employees. However, while the functional effects of ergonomic workstations have been documented, there is little research on the influence of workstation design on the executive function of the brain. In this study, 23 healthy volunteers in ergonomic and non-ergonomic workstations completed the Montreal imaging stress task, while their brain activity was recorded using the synchronized measurement of electroencephalography and functional near-infrared spectroscopy. The results revealed desynchronization in alpha rhythms and oxygenated hemoglobin, as well as decreased functional connectivity in the PFC networks at the non-ergonomic workstations. Additionally, a significant increase in salivary alpha-amylase activity was observed in all participants at the non-ergonomic workstations, confirming the presence of induced stress. These findings suggest that workstation design can significantly impact cognitive functioning and human capabilities at work. Therefore, the use of functional neuroimaging in workplace design can provide critical information on the causes of workplace-related stress.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  15. Liew, C.Y., Lau, C.Y.
    MyJurnal
    Studies have been carried out to determine the chemical (soluble solid content) and physical (firmness) parameters of locally grown Cavendish banana by near infrared (NIR) spectroscopy. NIR spectra in the wavelength region of 680-2500 nm were obtained from a total of 408 Cavendish bananas of different ripeness indices. Chemometrics using multiple linear regression (MLR) was applied to develop calibration models for prediction of firmness and soluble solid content (SSC) of Cavendish banana. Results showed that NIR spectroscopy had the feasibility for non-destructive determination of the quality of Cavendish banana. The coefficient of determination (R2) for firmness and SSC calibration models at different ripeness indices ranged from 0.78 to 0.86 and 0.75 to 0.96, respectively. The calibration models were validated using independent sets of data and prediction models developed with the root mean square error of prediction (RMSEP) ranged from 0.01 to 0.26 kgf and 0.039 to 0.788 Brix for firmness and SSC, respectively. The multi-index models showed considerable robustness but higher prediction error with RMSEP of 0.336 kgf for firmness and 0.937% Brix for SSC compared to index specific model.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  16. Basri KN, Hussain MN, Bakar J, Sharif Z, Khir MFA, Zoolfakar AS
    Spectrochim Acta A Mol Biomol Spectrosc, 2017 Feb 15;173:335-342.
    PMID: 27685001 DOI: 10.1016/j.saa.2016.09.028
    Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. Additionally, by employing partial least square (PLS) regression, the coefficient of determination (R2) of transflectance and transmission were 0.9987 and 0.9994 with root mean square error of calibration (RMSEC) of 0.5931 and 0.6703 respectively. In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. The result of R2 and RMSEC after variable selection for transflectance and transmission were improved significantly. Based on the result of classification and quantification analysis, the transmission mode has yield better prediction model compared to the transflectance mode to distinguish the pure and adulterated palm oil.
    Matched MeSH terms: Spectroscopy, Near-Infrared/instrumentation; Spectroscopy, Near-Infrared/methods*
  17. Silalahi DD, Midi H, Arasan J, Mustafa MS, Caliman JP
    Sensors (Basel), 2020 Sep 03;20(17).
    PMID: 32899292 DOI: 10.3390/s20175001
    The extraction of relevant wavelengths from a large dataset of Near Infrared Spectroscopy (NIRS) is a significant challenge in vibrational spectroscopy research. Nonetheless, this process allows the improvement in the chemical interpretability by emphasizing the chemical entities related to the chemical parameters of samples. With the complexity in the dataset, it may be possible that irrelevant wavelengths are still included in the multivariate calibration. This yields the computational process to become unnecessary complex and decreases the accuracy and robustness of the model. In multivariate analysis, Partial Least Square Regression (PLSR) is a method commonly used to build a predictive model from NIR spectral data. However, in the PLSR method and common commercial chemometrics software, there is no standard wavelength selection procedure applied to screen the irrelevant wavelengths. In this study, a new robust wavelength selection procedure called the modified VIP-MCUVE (mod-VIP-MCUVE) using Filter-Wrapper method and input scaling strategy is introduced. The proposed method combines the modified Variable Importance in Projection (VIP) and modified Monte Carlo Uninformative Variable Elimination (MCUVE) to calculate the scale matrix of the input variable. The modified VIP uses the orthogonal components of Partial Least Square (PLS) in investigating the informative variable in the model by applying the amount of variation both in X and y{SSX,SSY}, simultaneously. The modified MCUVE uses a robust reliability coefficient and a robust tolerance interval in the selection procedure. To evaluate the superiority of the proposed method, the classical VIP, MCUVE, and autoscaling procedure in classical PLSR were also included in the evaluation. Using artificial data with Monte Carlo simulation and NIR spectral data of oil palm (Elaeis guineensis Jacq.) fruit mesocarp, the study shows that the proposed method offers advantages to improve model interpretability, to be computationally extensive, and to produce better model accuracy.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  18. Yusop Nurida M, Norfadilah D, Siti Aishah MR, Zhe Phak C, Saleh SM
    Int J Anal Chem, 2020;2020:9830685.
    PMID: 32089691 DOI: 10.1155/2020/9830685
    The analytical methods for the determination of the amine solvent properties do not provide input data for real-time process control and optimization and are labor-intensive, time-consuming, and impractical for studies of dynamic changes in a process. In this study, the potential of nondestructive determination of amine concentration, CO2 loading, and water content in CO2 absorption solvent in the gas processing unit was investigated through Fourier transform near-infrared (FT-NIR) spectroscopy that has the ability to readily carry out multicomponent analysis in association with multivariate analysis methods. The FT-NIR spectra for the solvent were captured and interpreted by using suitable spectra wavenumber regions through multivariate statistical techniques such as partial least square (PLS). The calibration model developed for amine determination had the highest coefficient of determination (R2) of 0.9955 and RMSECV of 0.75%. CO2 calibration model achieved R2 of 0.9902 with RMSECV of 0.25% whereas the water calibration model had R2 of 0.9915 with RMSECV of 1.02%. The statistical evaluation of the validation samples also confirmed that the difference between the actual value and the predicted value from the calibration model was not significantly different and acceptable. Therefore, the amine, CO2, and water models have given a satisfactory result for the concentration determination using the FT-NIR technique. The results of this study indicated that FT-NIR spectroscopy with chemometrics and multivariate technique can be used for the CO2 solvent monitoring to replace the time-consuming and labor-intensive conventional methods.
    Matched MeSH terms: Spectroscopy, Near-Infrared
  19. Omar AF, Atan H, Matjafri MZ
    Molecules, 2012 Jun 15;17(6):7440-50.
    PMID: 22706373 DOI: 10.3390/molecules17067440
    Acid content is one of the important quality attributes in determining the maturity index of agricultural product, particularly fruits. Despite the fact that much research on the measurement of acidity in fruits through non-destructive spectroscopy analysis at NIR wavelengths between 700 to 1,000 nm has been conducted, the same response towards individual acids is not well known. This paper presents NIR spectroscopy analysis on aqueous citric, tartaric, malic and oxalic solutions through quantitative analysis by selecting a set of wavelengths that can best be used to measure the pH of the solutions. The aquaphotomics study of the acid solutions has generated R² above 0.9 for the measurement of all acids. The most important wavelengths for pH are located at 918-925 nm and 990-996 nm, while at 975 nm for water.
    Matched MeSH terms: Spectroscopy, Near-Infrared*
  20. Ghani KA, Sudik S, Omar AF, Mail MH, Seeni A
    PMID: 31216502 DOI: 10.1016/j.saa.2019.117241
    Cancer is increasing in incidence and the leading cause of death worldwide. Controlling and reducing cancer requires early detection and technique to accurately detect and quantify predictive biomarkers. Optical spectroscopy has shown promising non-destructive ability to display distinctive spectral characteristics between cancerous and normal tissues from different part of human organ. Nonetheless, not many information is available on spectroscopic properties of cancer cell lines. In this research, the visible-near infrared (VIS-NIR) absorbance spectroscopy measurement of cultured cervical cancer (HeLa) and prostate cancer cells (DU145) lines has been performed to develop spectral signature of cancer cells and to generate algorithm to quantify cancer cells. Spectroscopic measurement on mouse skin fibroblast (L929) was also taken for comparative purposes. In visible region, the raw cells' spectra do not produce any noticeable peak absorbance that provides information on color because the medium used for cells is colorless and transparent. NIR wavelength between 950 and 975 nm exhibit significant peak due to water absorbance by the medium. Development of spectral signature for the cells through the application of regression technique significantly enhances the diverse characteristics between L929, HeLa and DU145. The application of multiple linear regression allows high measurement accuracy of the cells with coefficient of determination above 0.94.
    Matched MeSH terms: Spectroscopy, Near-Infrared/methods*
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