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Spectroscopy approach to methanol detection in waste fat methyl esters
摘要： Second-generation biodiesel manufactured from waste cooking oils (WCO) and inedible animal fats (AF) are one of the alternatives to the first generation (1G) vegetable oil-based biodiesel. In this study, a quality control method is proposed to evaluate methanol content in waste fat methyl esters and is based on near infrared spectroscopy (NIR) combined with multivariate analysis. More specifically, calibration models are constructed using partial least squares regression (PLS) for the prediction of methanol content in rapeseed oil methyl ester (ROME), waste cooking oil methyl ester (WCOME), chicken fat methyl ester (CFME) and pork fat methyl ester (PFME) by Vis-NIR spectrometer. The calibration models are based on the absorbance spectra and computed data from five wavelength regions of 400–2170 nm, 780–2170 nm, 1400–2170 nm, 1400–1600 nm and 1970–2170 nm. For the cases with the highest prediction ability obtained in this study, the coefficient of determination of the model's goodness-of-fit for methanol concentrations range 0–5% (v/v) was R2 N 0.990, and for concentrations 0–1% (v/v) was R2 N 0.994, indicating the spectroscopic approach effectiveness in methanol content detection relevant to the biofuel quality assessment. A pseudo-univariate limits of detection (LODpu) and quantification (LOQpu) as well as ratio of performance to deviation (RPD) were used to confirm the validity and to evaluate the practical applicability of developed models. In addition, the obtained results indicate the possibility of developing a transmission sensor for online monitoring of the production process and the quality of biofuel.
关键词： PLS calibration models,Waste cooking oil,Animal fat biofuel,Vis-NIR spectroscopy
更新于2025-09-23 15:21:21
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The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco
摘要： Soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical reagents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0-20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley–Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350-2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R2) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R2 = 0.93 and RMSE = 0.13 compared to the contact probe protocol with an R2 = 0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for predicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the prediction of SOM for (PG) setup were at: 424, 597, 1432, 1484, 1830 ,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.
关键词： soil organic matter,SOM analysis.,VIS-NIR spectroscopy,reflectance spectra,SOM estimation
更新于2025-09-23 15:21:01
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Effect of fruit moving speed on online prediction of soluble solids content of apple using Vis/NIR diffuse transmission
摘要： The effect of fruit moving speed on online prediction of soluble solids content (SSC) of “Fuji” apples based on visible and near-infrared (Vis/NIR) spectroscopy was studied. Diffuse transmission spectra between 615 and 1,045 nm were collected with a commercial online system at speeds of 0.3 m/s (S1), 0.5 m/s (S2), and 0.7 m/s (S3). Compensation models for SSC of each speed alone (local models) and all speeds (global model) were established using partial least squares (PLS). For global model, spectra of each sample were divided into three parts (P1, P2, and P3), three kinds of spectra partition combinations (P12, P13, and P23) were established. Results showed that S3 performed better and the influence of speed on spectra greatly affected SSC evaluation accuracy between local models. Comparatively, global model was insensitive to fruit moving speed variation and effective wavelengths (EWs) selected by competitive adaptive reweighted sampling (CARS) after Savitzky–Golay smoothing (SGS) achieved better results than local models. Importantly, 36 EWs selected by CARS after SGS of global-P13 model achieved the best results with rp and RMSEP of 0.8419, 0.8895, 0.8948 and 0.6281, 0.5318, 0.5196(cid:1)Brix, respectively. Generally, global-P13 model with EWs is promisingly applied to online SSC prediction of apple by Vis/NIR diffuse transmission.
关键词： soluble solids content,online prediction,effective wavelengths,competitive adaptive reweighted sampling,partial least squares,fruit moving speed,apple,diffuse transmission,Vis/NIR spectroscopy
更新于2025-09-23 15:21:01
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Vis- and NIR-Based Instruments for Detection of Black-Tip Damaged Wheat Kernels: A Comparative Study
摘要： Black-tip (BT) is a non-mycotoxic fungus that attacks wheat kernels, forming a dark brown or black sooty area at the tip of the kernel. Visual inspection, which is the approved reference method for determining the amount of BT in wheat, requires substantial time and has high potential for subjective evaluation. Three spectrometers covering the spectral ranges 950-1636 nm (Spec1), 600-1045 nm (Spec2), and 380-780 nm (Spec3) were evaluated for their ability to predict the presence of BT. Kernels were quantified into four levels: (A) sound, (B) low black-tip symptoms (BTS), (C) high BTS, and (D) BT damaged (BTD). Discriminant classification models were developed to evaluate combinations of levels. The combinations were (1) levels A, B, C, and D separately; (2) A, B+C, and D; and (3) A+B and C+D. Spectral data for 2,760 kernels obtained from 23 hard red winter (HRW) wheat samples, each comprising 30 kernels that were visually selected for each of the four levels of black-tip severity (A, B, C, and D), were collected with each spectrometer. Discriminant calibration models for each spectrometer and classification category were developed based on (1) three combinations of 17 HRW wheat samples, with the six remaining samples used for independent validation, and (2) combinations of 20 randomly selected kernels from each of the 23 HRW wheat samples as calibration samples, with the remaining ten kernels used as validation samples. Discriminant analysis was based on five wavelengths for each model. Spectra pretreatment was the standard normal variate (SNV). Results showed that all three spectrometers were capable of detecting BT damage on wheat kernels. BT classification accuracy was observed to have been affected by wheat varieties for Spec1 and Spec2 (both with NIR wavelengths) but not for Spec3, which was entirely in the visible region. The two-category classification (A+B, C+D) provided higher accuracy than the three-category (A, B+C, D) and four-category (A, B, C, D) classifications. Based on the percent correct classification and Youden’s index, Spec2 performed better in detecting sound and BTD wheat kernels, with classification accuracies of the best two-category classification calibration model ranging from 85.6% to 87.5%, compared to Spec1 at 74.8% to 78.4% and Spec3 at 76.7% to 79.2%. This study also showed the potential of using a five-wavelength model, which equates to the potential for developing simple, less expensive, high-speed photoelectric detection instruments. These instruments can serve as important tools in plant breeding, grading, or grain processing facilities to enable BT detection and, with proper selection of wavelengths, may also find applications in simultaneous single-kernel detection, measurement, and segregation of other chemical characteristics, such as protein and starch content.
关键词： Black-tip damage,Wheat,VIS,NIR,Spectroscopy
更新于2025-09-23 15:21:01
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Effect of the degree of inversion on optical properties of spinel ZnFe <sub/>2</sub> O <sub/>4</sub>
摘要： Spinel ferrites (T[M1?xFex]O[MxFe2?x]O4 with 0 ≤ x ≤ 1, where M is a bivalent metal ion and the superscripts denote tetrahedral and octahedral sites) are materials commonly used in electronics due to their outstanding magnetic properties. Thus, the effect of the degree of inversion, x, on these properties is well known. However, its effect on other properties of these materials has rarely been investigated in detail. Since ferrites gained much attention during the last decade as visible light active photocatalysts and photoelectrocatalysts, understanding the effect of the degree of inversion on the optical properties became necessary. Among photocatalytically and photoelectrocatalytically active spinel ferrites, zinc-ferrite (ZnFe2O4, ZFO) is one of the most widely studied materials. In this work, five ZFO samples with degrees of inversion varying from 0.07 to 0.20 were prepared by a solid-state reaction employing different annealing temperatures and subsequent quenching. Raman and UV-Vis-NIR spectra were measured and analyzed together with theoretical results obtained from ab initio calculations. Changes in the UV-Vis-NIR spectra associated with electronic transitions of tetrahedrally and octahedrally coordinated Fe3+ ions are distinguished. However, the optical band gap of the material remains unchanged as the degree of inversion varies. Based on the experimental and theoretical results, a new assignment for the Raman active internal modes and the electronic transitions of ZFO is proposed.
关键词： ab initio calculations,degree of inversion,zinc ferrite,spinel ferrites,optical properties,UV-Vis-NIR spectroscopy,Raman spectroscopy
更新于2025-09-19 17:15:36
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Surface-Enhanced Absorption Spectroscopy for Optical Fiber Sensing
摘要： Visible and near-infrared spectroscopy are widely used for sensing applications but suffer from poor signal-to-noise ratios for the detection of compounds with low concentrations. Enhancement by surface plasmon resonance is a popular technique that can be utilized to increase the signal of absorption spectroscopy due to the increased near-field created close to the plasmons. Despite interest in surface-enhanced infrared absorption spectroscopy (SEIRAS), the method is usually applied in lab setups rather than real-life sensing situations. This study aimed to achieve enhanced absorption from plasmons on a fiber-optic probe and thus move closer to applications of SEIRAS. A tapered coreless fiber coated with a 100 nm Au film supported signal enhancement at visible wavelengths. An increase in absorption was shown for two dyes spanning concentrations from 5 × 10?8 mol/L to 8 × 10?4 mol/L: Rhodamine 6G and Crystal Violet. In the presence of the Au film, the absorbance signal was 2–3 times higher than from an identically tapered uncoated fiber. The results confirm that the concept of SEIRAS can be implemented on an optical fiber probe, enabling enhanced signal detection in remote sensing applications.
关键词： surface enhancement,SEIRAS,sensing,optical fiber,Vis/NIR spectroscopy,gold
更新于2025-09-16 10:30:52
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A GA-based stacking algorithm for predicting soil organic matter from vis-NIR spectral data
摘要： It has been demonstrated that diffuse reflectance spectroscopy in the visible and near-infrared (vis–NIR) can be exploited to predict chemical and physical soil properties. Immense soil spectral libraries (SSL) are being developed, therefore more elaborate tools that capitalize on contemporary knowledge and techniques need to be established to provide accurate predictions. In this paper, we propose a novel genetic algorithm-based stacking model that makes synergetic use of multiple models developed from different pre-processed spectral sources (termed L1 models). This is a form of ensemble learning where multiple hypotheses are combined to create a more robust and more accurate ensemble hypothesis. The genetic algorithm automatically defines the configuration of the stacked model, by selecting the best cooperating subset of the initial models. Our methodology was tested on the newly developed GEO-CRADLE SSL to predict soil organic matter (SOM). Results showed that the accuracy of prediction of the proposed method ( =0.76, and ratio of performance to inter quartile range RPIQ=2.22) was better than the one attained by the best L1 model ( =0.65, RPIQ=1.93). This approach can thus be effectively utilized to enhance the predictions of soil properties in small and large soil spectral libraries alike.
关键词： model stacking,North Africa,GEO-CRADLE,vis–NIR spectroscopy,soil spectroscopy,Middle East,Balkans
更新于2025-09-10 09:29:36
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Sparse NIR Optimization method (SNIRO) to quantify analyte composition with visible (VIS)/near infrared (NIR) spectroscopy (350nm-2500nm)
摘要： Visual-Near-Infra-Red (VIS/NIR) spectroscopy has led the revolution in high-throughput phenotyping methods used to determine chemical and structural elements of organic materials. In the current state of the art, spectrophotometers used for imaging techniques are either very expensive or too large to be used as a field-operable device. In this study we developed a Sparse NIR Optimization method (SNIRO) that selects a pre-determined number of wavelengths that enable quantification of analytes in a given sample using linear regression. We compared the computed complexity time and the accuracy of SNIRO to Marten’s test, to forward selection test and to LASSO all applied to the determination of protein content in corn flour and meat and octane number in diesel using publicly available datasets. In addition, for the first time, we determined the glucose content in the green seaweed Ulva sp., an important feedstock for marine biorefinery. The SNIRO approach can be used as a first step in designing a spectrophotometer that can scan a small number of specific spectral regions, thus decreasing, potentially, production costs and scanner size and enabling the development of field-operable devices for content analysis of complex organic materials.
关键词： Imaging,VIS/NIR spectroscopy,Ulva sp.,Chemometrics,Multivariate Analysis,Diesel Octane Number,seaweeds,Sparse Linear Regression
更新于2025-09-10 09:29:36
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Application of visible-near infrared spectroscopy to evaluate the quality of button mushrooms
摘要： The Agaricus bisporus mushroom is one of the most cultivated and consumed mushrooms in the world, thanks to its delicacy, nutritional value and flavour. The quality evaluation of the A. bisporus during the harvest is generally established by a visual check by trained operators. This method complies with the request of the Distribution Channel (DC) to retailers and guarantees very low physical damage to the mushrooms; nevertheless, it is subjective and it does not guarantee the highest quality standard for the consumer. The aim of this study was to test the use of visible/near infrared (vis/NIR) reflectance spectroscopy (400–1000 nm) to objectively evaluate the quality parameters of A. bisporus mushrooms. A total of 167 samples of A. bisporus mushrooms were harvested according to the main DC purchasing standards. The vis/NIR analyses were performed the day of sampling just before the physico-chemical analyses (sizes, firmness, soluble solids content and moisture content) used as reference quality parameters. The vis/NIR spectra were correlated to reference measures in order to build predictive models using the partial least squares regression method. Calculated models gave positive results regarding the prediction of the moisture content (r2 (pred) ? 0.78) and firmness (r2 (pred) ? 0.78). Results of this explorative study could be considered encouraging and demonstrate the applicability of vis/NIR spectroscopy on A. bisporus as a rapid technique (i) to monitor the productive process directly at the company, (ii) to standardize the harvest moment, and (iii) to support DC’s buyers’ choices, nowadays exclusively based on product external characteristics.
关键词： quality,vis/NIR spectroscopy,harvest,reflectance,mushrooms,distribution channel
更新于2025-09-10 09:29:36
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Reflectance spectroscopy of ammonium-bearing phyllosilicates
摘要： The identification of NH4-bearing phyllosilicates on Ceres poses the question on the NH4-carrier phase(s) and in this study we describe the laboratory production and IR spectroscopic measurements of a suite of ten NH4-phyllosilicates, starting from the corresponding NH4-free minerals. For each mineral, we prepared three types of powder samples: raw (R), ammoniated (A), and leached (L). All samples have been spectrally characterized by means of visible/infrared spectroscopy in the INAF-IAPS laboratories with the FieldSpec Pro in the 0.35-2.5 μm range, and with the FT-IR, using a Vertex 80 spectrometer operating in the range of 2 to 14 μm. The samples were also measured with the SPectral IMager, an imaging spectrometer operating in the spectral range 0.2 – 5.1 μm, which is a replica of the VIR spectrometer on-board Dawn spacecraft. Reflectance spectra of the ammoniated clays show bands near 1.56 μm, 2.05 μm, 2.12 μm, 3.06 μm, 3.25 μm, 3.55 μm, 4.2 μm, 5.7 μm and 7.0 μm that are related to the presence of nitrogen complexes. Treatment of phyllosilicates with ammonia shows that different minerals behave in different ways: NH4+ ions are easily accepted by the smectites, while other non-expandable structures do not accept these ions. The obtained results can be used to better constrain the NH4-bearing species present on Ceres and, possibly, other bodies of the solar system.
关键词： Reflectance spectroscopy,smectites,VIS-NIR spectroscopy,Ceres,ammonium-bearing phyllosilicates
更新于2025-09-09 09:28:46