scholarly journals Determination of oil content, linolenic and erucic acids contents in false flax seeds using IRspectrometry

2021 ◽  
Vol 186 (2) ◽  
pp. 50-59
Author(s):  
S.G. Efimenko ◽  
◽  
S.K. Efimenko ◽  
Keyword(s):  
Acid Content ◽  
Oil Content ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Erucic Acid Content ◽  
Weight Percentage ◽  
False Flax ◽  
Prediction Coefficient ◽  
Flax Seeds

Spectroscopy of near infrared reflection (NIRS) was used for estimation of biochemical indicators in seeds of false flax. The purpose of our work was to develop calibrating models for IR-analyzer MATRIXI for determination of weight percentage of oil, linolenic and erucic acids contents in oil of seeds in unbroken seeds of false flax (winter and spring forms). The researches were conducted in the biochemistry laboratory on false flax samples cultivated in 2016–2020 in the different environments of the Russian Federation. Oil content was determined with NMR-analyzer АМV 1006М according to the technique described in the State Standard 8.597-2010, percentage contents of linolenic and erucic acids in oil was estimated on the gas chromatograph “Chromatech – Kristal 5000” with an automatic dipper on a capillary column SolGelWax 30 m × 0.25 mm × 0.5 µcm. The best indicators of quality of the calibrating models (root mean square error of prediction, coefficient of determination, and meaning of a residual deflection of prediction for a rank reflected on a figure) were obtained by oil content (RMSEP = 0.20%, R 2 = 99.3, and RPD = 12.3), linolenic acid content (RMSEP = 0.35%, R 2 = 98.8, and RPD = 9.2) and erucic acid content (RMSEP = 0.14%, R 2 = 85.7, and RPD = 2.6). In a program OPUS LAB, we received a method “False flax 51” based on the developed calibrating models for a routine analysis for determination of oil content, linolenic and erucic acids contents in oil in the unbroken seeds of false flax in an average (9–20 g) in a cuvette with diameter of 51 mm. this method allows conducting express-estimation of false flax seeds for breeding traits with performance of more than 100 sample per seven hours.

scholarly journals Rapid assessment of oil and moisture content in seeds of oil flax using IR spectrometry

2020 ◽  
Vol 3 (183) ◽  
pp. 63-70
Author(s):  
S.G. Efimenko ◽  
◽  
S.K. Efimenko ◽  
Keyword(s):  
Moisture Content ◽  
High Speed ◽  
Oil Content ◽  
Near Infrared ◽  
Coat Color ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Calibration Models ◽  
Flax Seeds

We used near-infrared reflectance spectroscopy (NIRS) to assess biochemical parameters in whole oil flax seeds, regardless of differences in seed coat color of the samples. At the first stage of work, the set the task to develop calibration models for the MATRIX-I IR analyzer to determine the oil and moisture content in flax seeds. The carried out the research in the laboratory of biochemistry on brown and yellow seed samples of oil flax, grown in 2015-2020 in various agro-ecological conditions of the Russian Federation. We determined the oil content on an AMV 1006M NMR analyzer in accordance with the GOST 8.597- 2010 measurement procedure; we assessed the moisture content by the standard method of GOST 10856- 96. We used the results of determination of the oil and moisture content of the seeds of test lot in accordance with the accuracy indicator of the calibration of GOST 32749-2014 to verify the reliability of the developed models. We received the best indicators of the quality of calibration models (root-mean-square prediction error, coefficient of determination and the value of the residual deviation of prediction for the rank displayed on the graph) by determining the oil content (RMSEP = 0.27 %, R2 = 99.2 and RPD = 11.2) and moisture content (RMSEP = 0.06 %, R2 = 99.9 and RPD = 39). In the OPUS LAB program we developed the “Flax 51” method for mass analysis based on the developed calibration models for the determination of oil and moisture content in whole oil flax seeds (9-20 g) in a sample cell with a diameter of 51 mm. It enables the quick carrying out a preliminary assessment of the breeding material at a high speed – more than 120 samples in 7 hours without seed destruction.

Rapid determination of oil content in dried-ground oil palm mesocarp and kernel using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 338-347 ◽  
Author(s):  
Sudarno ◽  
Divo D Silalahi ◽  
Tauvik Risman ◽  
Baiq L Widyastuti ◽  
F Davrieux ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Oil Palm ◽  
Standard Error ◽  
Oil Content ◽  
Near Infrared ◽  
Cross Validation ◽  
Calibration Model ◽  
Reliable Technique

Near infrared spectroscopy calibrations for rapid oil content determination of dried-ground oil palm mesocarp and kernel were developed. Samples were analyzed, one set using the Soxhlet extraction method for reference analysis and the other set scanned by near infrared spectroscopy instrument for calibration. Successful calibrations were obtained with good accuracy and precision for mesocarp and kernel, based on statistical models. Math treatment and scatter correction had significant effects on the fitting of the calibration model. The best obtained calibration models were demonstrated by multiple correlation coefficient (R2), standard error of calibration, standard error of cross validation, coefficient of determination in cross validation (1-VR) and relative predictive deviation of calibration, which respectively were 0.997, 1.21%, 1.23%, 0.997 and 17.89 for mesocarp and 0.952, 0.47%, 0.53%, 0.94 and 4.00 for kernel. The correlations between reference and predicted values for samples in the validation sets were in agreement with high linearity, high ratio performance to deviation of prediction (≥4.00) and low standard error of prediction samples for both samples. The results demonstrated that near infrared spectroscopy can be used as an alternative and reliable technique to estimate the mesocarp and kernel oil contents in dry matter basis accurately and rapidly.

scholarly journals The effect of herbicides on winter false flax (Camelina sativa (L.) Crantz.)

2021 ◽  
Vol 32 ◽  
pp. 02011
Author(s):  
Oksana Serdyuk ◽  
Victoria Trubina ◽  
Lyudmila Gorlova
Keyword(s):  
Oil Content ◽  
Plant Density ◽  
Central Zone ◽  
Application Rate ◽  
Oil Crops ◽  
False Flax ◽  
Russian Research Institute ◽  
Different Types ◽  
Flax Seeds ◽  
Russian Research

The purpose of the research was to determine the effect of herbicides on winter false flax and to identify the preparation that does not effect negatively on crop plants. The research was carried out in 20182020 at V.S. Pustovoit All-Russian Research Institute of Oil Crops. The experiment scheme included herbicides with active ingredients (a.i.), which effectively decreased the number of weeds on the plots. The effectiveness of the preparations was more than 70% for different types of weeds. However, the variants with the application of preparations with a.i. clopyralid 300 g/l, S-Metolachlor 960 g/l, ethametsulfuronmethyl 750 g/kg significantly decreased the plant density (by 18-32 pcs/m2) and seed yield (by 0.33-0.52 t/ha) of false flax in comparison with the control. The oil content of seeds was significantly decreased in the variants with the herbicides with a.i. S-Metolachlor 960 g/l with the application rate of 1.6 l/ha and ethametsulfuron-methyl 750 g/kg (by 1.2-1.5 %). In other variants, the oil content of false flax seeds differed from the control insignificantly (by 0.3-0.4 %). It has been established that the preparation with a.i. quinmerac 83 g/l + metazachlor 333 g/l with the application rate of 2.0 or 2.5 l/ha should be applied to decrease the number of weeds in the sowings of winter false flax in the central zone of the Krasnodar region. This preparation, without having a toxic effect, increases the yield by 0.15-0.17 t/ha and does not decrease the plant density and oil content of false flax seeds.

Near infrared spectroscopy for rapid determination of solids content of amino resins

2020 ◽  
Vol 28 (5-6) ◽  
pp. 344-350
Author(s):  
M Gonçalves ◽  
NT Paiva ◽  
JM Ferra ◽  
J Martins ◽  
F Magalhães ◽  
...  
Keyword(s):  
Near Infrared ◽  
Rapid Determination ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Water Addition ◽  
Reliable Technique ◽  
Standard Normal Variate ◽  
And Performance ◽  
Solids Content

Near infrared (NIR) spectroscopy is a fast and reliable technique for assessing properties of amino resins. One important property that defines the cost and performance of these resins is the solids content (SC). This work studied the prediction of SC of amino resins by combining NIR spectroscopy with partial least squares (PLS) regression. A total of 990 industrial NIR spectra of amino resins were obtained and split randomly by a ratio of 2/3 for calibration and 1/3 for validation. The best model achieved a root mean-square error of prediction (RMSEP) of 0.32% (m/m) and a coefficient of determination of prediction ([Formula: see text]) of 81%. standard normal variate (SNV) was found to be the NIR pre-processing that provided the best results for model construction. Addition of water to two amino resins showed that the NIR model does not respond to the water addition, despite water making great contribution to the SC value. An inference that can be obtained from this is that the NIR model of amino resins uses NIR properties of amino resins that relate to the SC and from there predict the most probable SC, instead of looking at all the components that affect the SC of amino resins.

Variable selection for the determination of total polar materials in fried oils by near infrared spectroscopy

2018 ◽  
Vol 27 (2) ◽  
pp. 107-114 ◽  
Author(s):  
Mari M Cascant ◽  
Salvador Garrigues ◽  
Miguel de la Guardia
Keyword(s):  
Variable Selection ◽  
Near Infrared ◽  
Low Cost ◽  
Oil Quality ◽  
Analytical Techniques ◽  
Coefficient Of Determination ◽  
Prediction Errors ◽  
Polar Materials ◽  
Selection Of

Total polar materials (TPM) content is considered as the best indicator and the most common parameter to check the quality of deep-frying oils. The development of simpler and quicker analytical techniques than the available methods to monitor oil quality in restaurants and fried food outlets is an important topic related to the human health. This paper reports a comparison of the variable selection of near infrared (NIR) spectra by multiple linear regression (MLR-NIR) with partial least squares (PLS-NIR) models for the quantification of TPM in fried vegetable oils. The use of PLS-NIR offers an alternative in laboratory bench equipment for the determination of TPM in oils employed for frying different kinds of foods with relative prediction errors of 6.5%, a coefficient of determination for prediction of 0.99 and a residual predictive deviation (RPD) of 9.2 when selected wavenumber intervals were employed. MLR-NIR allows the selection of a reduced number of wavenumber in order to develop low cost instruments to evaluate the frying oil quality. Based on the NIR signals at four wavenumbers, the relative prediction error was 12.1%, the coefficient of determination for prediction was 0.96 and the RPD was 5.0.

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