scholarly journals Fast prediction of quality parameters in whole seeds of oilseed rape (Brassica napus L.)

2011 ◽  
Vol 49 (No. 4) ◽  
pp. 141-145 ◽  
Author(s):  
V. Míka ◽  
P. Tillmann ◽  
R. Koprna ◽  
P. Nerušil ◽  
V. Kučera
Keyword(s):  
Prediction Accuracy ◽  
Near Infrared ◽  
Quality Parameters ◽  
Breeding Cycle ◽  
Brassica Napus L ◽  
Calibration Equation ◽  
Whole Seed ◽  
Fast Prediction ◽  
Short Time ◽  
Non Destructive

A calibration equation for NIRSystems 6500 instrument was derived at VSTE Jevíčko using the measurement of broad collection of Czech samples of winter rape, allowing sufficiently accurate prediction of content of dry matter (DM), crude protein (XP), crude fat (XL), glucosinolates (GSL), oleic and linoleic acids in an extremely short time. The prediction accuracy was verified on a validation file (n = 60). The coefficients of determinance (R2) were 0.83 for XP, 0.71 for XL, and 0.84 for GSL. The prediction accuracy according to the VSTE equation was compared to the prediction accuracy according to the VDLUFA calibration equation (Kassel, FRG) used in EU near infrared spectroscopy network. It was stated that the former was not distinctly worse. Non-destructive NIR-analysis of the whole seed also allows sowing selected seeds in the year of harvest and thus accelerates the breeding cycle.

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.

Rapid and non-destructive determination of quality parameters in the ‘Tommy Atkins’ mango using a novel handheld near infrared spectrometer

2016 ◽  
Vol 197 ◽  
pp. 1207-1214 ◽  
Author(s):  
Emanuel José Nascimento Marques ◽  
Sérgio Tonetto de Freitas ◽  
Maria Fernanda Pimentel ◽  
Celio Pasquini
Keyword(s):  
Near Infrared ◽  
Quality Parameters ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Non Destructive

scholarly journals Forage Quality Evaluation

1970 ◽  
Vol 66 (1) ◽  
Author(s):  
Lucien CARLIER ◽  
Chris VAN WAES ◽  
Ioan ROTAR ◽  
Mariana VLAHOVA ◽  
Roxana VIDICAN
Keyword(s):  
Near Infrared ◽  
Animal Husbandry ◽  
Quality Parameters ◽  
Near Infrared Reflectance ◽  
Domestic Ruminants ◽  
In Vitro Technique ◽  
Protein Rich ◽  
Non Destructive ◽  
Destructive Methods

The challenge for the research in crop and animal husbandry is how to determine the quality of a speci¬fied crop as a forage for ruminants by the chemical analysis of only a small amount of sample". Since more than hundred years scientists try to give an answer to that question. The most applied is the Weende and Van Soest system, together with the digestibility in vitro technique developed by Tilley and Terry. During the last decennia also non destructive methods, like the Near Infrared Reflectance Spectroscopy NIRS, are used more frequently. Forages contain a lot of quality parameters (protein, fat, sugars, structural carbohydrates, vitamins, … but some of them contain also anti quality components (alkaloids, nitrates, …). The diet of domestic ruminants exists of more than only 1 component. Other diet components may interfere and mostly result in a synergism. The combination of a protein rich forage (legumes) with starch riches ones results in better animal productions than given as sole diet component. Fast and reliable non destructive methods are more attractive and acceptable than laborious, polluting and animal unfriendly ones.

scholarly journals Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 441 ◽  
Author(s):  
Manuela Mancini ◽  
Luca Mazzoni ◽  
Francesco Gagliardi ◽  
Francesca Balducci ◽  
Daniele Duca ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Infrared Region ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Electromagnetic Spectrum ◽  
Least Squares Regression ◽  
Solids Content ◽  
Non Destructive

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.

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 ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Multiple Baseline ◽  
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 baseline 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 peanut.

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