A portable device for detecting fruit quality by diffuse reflectance Vis/NIR spectroscopy

2017 ◽  
Author(s):  
Hongwei Sun ◽  
Yankun Peng ◽  
Peng Li ◽  
Wenxiu Wang
Keyword(s):  
Fruit Quality ◽  
Diffuse Reflectance ◽  
Nir Spectroscopy ◽  
Portable Device

Evaluation of biochemical markers associated with the development of husk scald and the use of diffuse reflectance NIR spectroscopy to predict husk scald in pomegranate fruit

2018 ◽  
Vol 232 ◽  
pp. 240-249 ◽  
Author(s):  
Ebrahiema Arendse ◽  
Olaniyi Amos Fawole ◽  
Lembe Samukelo Magwaza ◽  
Helene Nieuwoudt ◽  
Umezuruike Linus Opara
Keyword(s):  
Biochemical Markers ◽  
Diffuse Reflectance ◽  
Nir Spectroscopy ◽  
Pomegranate Fruit

scholarly journals Synthesis and characterization of μ-hydroxido- and μ-polycarboxylato-bridged iron(III) complexes with 2,2’-bipyridine

2014 ◽  
Vol 79 (8) ◽  
pp. 941-952
Author(s):  
Nikola Tasic ◽  
Jelena Rogan ◽  
Dejan Poleti ◽  
Lidija Radovanovic ◽  
Goran Brankovic
Keyword(s):  
Ligand Exchange ◽  
Diffuse Reflectance ◽  
Nir Spectroscopy ◽  
Octahedral Geometry ◽  
Distorted Octahedral Geometry ◽  
Dsc Analysis ◽  
Ligand Exchange Reaction ◽  
Distorted Octahedral ◽  
Structural Formulae

Four novel polymeric iron(III) complexes with 2,2?-bipyridine (bipy) and different aromatic polycarboxylato ligands as anions of phthalic (pht), isophthalic (ipht), terephthalic (tpht) and pyromellitic (pyr) acid were synthesized by ligand exchange reaction. The complexes were characterized by elemental and TG/DSC analysis, FTIR and diffuse reflectance UV-VIS-NIR spectroscopy and magnetic susceptibility measurements. Based on analytical and spectral data the formulae of the complexes are {[Fe4(bipy)2 (H2O)2(OH)6(pht)3]?2H2O}n (1), {[Fe4(bipy)2(Hipht)2(ipht)2(OH)6]?4H2O}n (2), {[Fe4(bipy)2(Htpht)2(OH)6(tpht)2]?4H2O}n (3) and {[Fe4(bipy)(H2O)8(OH)4 (pyr)2]?H2O}n (4). All complexes are red brown and low-spin with a distorted octahedral geometry and FeO6 or FeN2O4 chromophore. Polycarboxylato ligands have a bridging role in all cases, whereas monodentate COO groups are present in 2 and 3, bridging and chelate COO groups are established in 1 and 4. The thermal behaviour of 1-4 was investigated in detail and the molar dehydration enthalpies were calculated. According to the all those results, the structural formulae of the complexes 1-4 were proposed.

Soil discrimination using diffuse reflectance Vis–NIR spectroscopy in a local toposequence

2013 ◽  
Vol 345 (11-12) ◽  
pp. 446-453 ◽  
Author(s):  
José Francirlei Oliveira ◽  
Michel Brossard ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Stanislas Mayi III ◽  
Edemar Joaquim Corazza ◽  
...  
Keyword(s):  
Diffuse Reflectance ◽  
Nir Spectroscopy

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baselines for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non-destructive quantification of quality parameters in peanuts.

scholarly journals Near-infrared spectroscopy is feasible to discriminate hazelnut cultivars

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Elisabetta Stella ◽  
Roberto Moscetti ◽  
Letizia Carletti ◽  
Giuseppina Menghini ◽  
Francesco Fabrizi ◽  
...  
Keyword(s):  
Amino Acids ◽  
Discriminant Analysis ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Functional Group ◽  
Nir Spectroscopy ◽  
Linear Discriminant ◽  
Minimum Error ◽  
Small Set ◽  
Nm Range

The study demonstrated the feasibility of the near infrared (NIR) spectroscopy use for hazelnut-cultivar sorting. Hazelnut spectra were acquired from 600 fruit for each cultivar sample, two diffuse reflectance spectra were acquired from opposite sides of the same hazelnut. Spectral data were transformed into absorbance before the computations. A different variety of spectral pretreatments were applied to extract characteristics for the classification. An iterative Linear Discriminant Analysis (LDA) algorithm was used to select a relatively small set of variables to correctly classify samples. The optimal group of features selected for each test was analyzed using Partial Least Squares Discriminant Analysis (PLS-DA). The spectral region most frequently chosen was the 1980-2060 nm range, which corresponds to best differentiation performance for a total minimum error rate lower than 1.00%. This wavelength range is generally associated with stretching and bending of the N-H functional group of amino acids and proteins. The feasibility of using NIR Spectroscopy to distinguish different hazelnut cultivars was demonstrated.

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