Abstract
The present study substantiates the application of natural sunflower oil for the calibration of pulsed NMR analyzers, as well as for the identification and quality assessment of oilseeds and their products using the NMR method. Being the essential characteristic of sunflower seeds, the oil content is mandatory for the certification of agricultural products and their cost assessment. The first calibration option includes the measurement of oil NMR characteristics with the oil content determined using the Soxhlet exhaustive extraction. The second option involves the calibration of a NMR analyzer using sunflower oil, obtained by pressing identical cultivars and hybrids, as well as that acquired at a retail network. A comparison of the obtained calibration dependencies showed their similar nature. The application of sunflower oil for the calibration of NMR analyzers provides no increase in the oil content measurement error as compared to the first calibration option. Therefore, using natural oil for the calibration of NMR analyzers can considerably simplify the calibration process, reduce the calibration duration from 3–4 days to 3–4 h, as well as to exclude toxic solvents and additional high-value equipment from the process without essential variations in the oil content measurement error.
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Keywords
Introduction
In accordance with GOST 22391-2015 [1], the oil-and-fat industry identifies the seed oil content as the main quality indicator of raw materials during their gathering and processing. The oil content comprises the content of raw fat and accompanying lipoid substances, which, together with fat, pass into the ether extract from the seeds. In accordance with GOST 10857-64 [2], the determination of this indicator is based on the method of Soxhlet exhaustive extraction. A drawback of this method consists in its duration, application of toxic chemical solvents, low productivity, and high requirements to the personnel qualification.
At present, due to the wide development of technical equipment and information technologies, instrumental methods, such as IR spectroscopy and pulsed NMR methods, which can be used to obtain information about the seed oil content, are quite common. The determination of oil content using the method of IR spectroscopy is typically performed in accordance with GOST 32749-2014 [3]. In the case of sunflower seeds, this method is unpopular due to significant errors (up to 2 abs%) and the dependence of measurement results on the seed appearance and their fineness degree. In addition, this method requires the calibration of IR analyzers using a large number of seeds with a certain value of determined indicators obtained using referee methods [4,5,6,7,8].
In the contemporary Russian oil-and-fat industry, the most widespread instrumental method for determining the oil content of seeds and products of their processing involves pulsed nuclear magnetic resonance (NMR). This is explained by its analytical simplicity, lack of a complex sample preparation, high accuracy (error of not more than 0.6 abs%, which is comparable in accuracy with a referee chemical method), promptness (the analysis of one sample takes < 30 s), lack of the effect caused by the operator’s subjectiveness on the analytical results, as well as ease of implementation. Currently, AMV-1006M (V.S. Pustovoit All-Russian Research Institute of Oil Crops, VNIIMK, Russia) is the most common NMR analyzer used at Russian enterprises. The determination of oil content using this instrument is based on the substantiated scientific and methodological approach with the rank of 0.04 [9].
The calibration of operating NMR analyzers for the determination of oil content in sunflower seeds is carried out using GSO 3107-84Footnote 1 state reference materials [10, 11], which were used for the verification of AMV-1006M NMR analyzers until the expiration of their Type Approval Certificate in 2016.
These reference materials (RM) are made on the basis of chemically inert substances-imitators, thermally resistant, resistant to thermal oxidation and ultraviolet effects, as well as having the dielectric properties (of organosilicon liquids) [12,13,14] of oil NM relaxation characteristics.
Imitated values of indicated GSO 3107-84 were assigned using an NMR analyzer, whose calibration and testing were performed using sunflower seeds with the oil content determined by the Soxhlet method of exhaustive extraction. The drawbacks of this calibration method include its duration, high requirements to the operator’s qualification, as well as the application of specially prepared traceable seeds. It should be noted that even specially prepared seeds have a scattering in the measured oil content values in individual samples, isolated from one specimen using the method of exhaustive extraction to 1 abs%. This is explained by the fact that seeds represent a natural heterogeneous object [15, 16].
Let us note that one of the key features of the NMR method comprises a functional dependence between the oil content in the analyzed seed sample and the amplitude of the NMR signal obtained from the protons of triacylglycerins (TAG) contained in the oil.
At present, the NMR method is widely used for determining the oil content of seeds and oil-containing raw materials [17,18,19,20,21,22,23,24],Footnote 2 which is explained by its application simplicity, high metrological characteristics, sample preparation simplicity, ecological safety, as well as the non-destructive nature of analysis. More than 350 enterprises of the Russian oil-and-fat industry currently use AMV-1006M NMR analyzers to quickly obtain information on the oil content at all stages of gathering, storage, and processing of oil seeds.
At the same time, the calibration of quantitative NMR analyzers represents a complex problem.
Currently, several main methods of calibrating quantitative analyzers, used for the quality assessment of lipid-containing raw materials, can be found in literature:
-
using natural samplesFootnote 3,Footnote 4;
-
using imitator RMs produced from chemically inert substances [13, 14, 24];
-
using samples, obtained on the basis of natural components, e.g., oil cakes and oil (see footnote 3) [25].
In this study, we aim to scientifically and experimentally substantiate the application of sunflower oil samples in the calibration of NMR analyzers.
Materials and Methods
Experiments were carried out at the Central Experimental Base of V.S. Pustovoit All-Russian Research Institute of Oil Crops (Krasnodar) in 2021–2022. Traceable sunflower seed samples of VNIIMKFootnote 5 breeding and two samples of commercially distributed oil were prepared, including the refined and deodorized oil of the “BLAGO” trademark (Russia) and non-refined oil of the “STAVROPOL’E” trademark (Russia), acquired in a retail network.
Sunflower samples were cleaned off damaged seeds and waste admixtures. The oil and moisture content of seeds was preliminarily determined using an AMV-1006M NMR analyzer in accordance with GOST 8.597-2010 [26]. The seed samples presented in the study belong to contemporary high-productive varieties. The acid number of the seed oil was determined according to GOST 31933-2012 [24, 27] using the titrimetric method with visual indication.
The determination of the oil content in seeds was carried out by the method of exhaustive extraction in four repetitions for each sample in order to reduce the measurement error, in accordance with the procedure developed based on GOST 10857-64. The duration of extraction was 24 h, at a temperature providing a number of siphonings from 7 to 10 per hour. The completeness of extraction was checked using a watch glass sample. The average value of four measurements was taken as the final result.
The oil from sunflower seeds was obtained using a Laboratoroff PR-L laboratory hand press (LLC Eltemix, Russia) with a force of 12 tons. The obtained oil was further filtered to remove seed particles, trapped in the oil during its pressing, using the FS laboratory filtering paper.
In order to construct the oil content calibration curves, from each oil sample, both obtained by pressing and acquired at a retail network, five weighments evenly distributed in the range from 2000 to 7000 g with the accuracy of 0.001 g were taken using an AND HK-50AG laboratory weights (AND, Japan).
Prior to measuring the oil proton NMR signals, the prepared samples were thermostated at a temperature of 23 ± 0.5 °C for 2 h in a TVL-K(50)B thermostat (CJSC INSOVT, Russia). The thermostating of samples comprises an important stage, since the temperature has the essential effect on the NM relaxation characteristic of oil samples [21].
Measurements were conducted using typical AMV-1006M NMR analyzers of the oil and moisture content (VNIIMK, Russia). In accordance with the analytical procedure, when performing measurements by an AMV-1006M NMR analyzer, the volume of each analyzed seed weighment is equal to 25 cm3.
For the control of NMR analyzers and primary processing of NMR signals, obtained using the studied oil samples, the own software was used [28]. The obtained data were statistically analyzed using Statistica and Excel software.
Results and Discussion
The main characteristics of sunflower seeds used in the study are presented in Table 1.
It is known [2] that, for oilseeds with a moisture content of < 8%, the intensity of NM relaxation characteristics is determined exclusively by the protons of the oil and accompanying substances. This is due to the high degree of connection between water molecules and the protein part of the seeds. The data in Table 1 show that the moisture content of the samples under study is much lower. Therefore, the resulting analytical parameter will further characterize only TAG protons.
The seed samples prepared for the analysis characterize the range of the oil content from 32.1 to 56.3%. The seeds are healthy; their acid number corresponds to the first-class sunflower and does not exceed 0.8 mg KOH/g for all samples.
At the first stage of the study, we obtained the NM relaxation characteristics of the prepared oilseeds and determined their oil content using the Soxhlet method of exhaustive extraction. The obtained calibration curve, describing the dependence of the oil mass on the amplitude of the NMR signal, is shown in Fig. 1.
The resulting curve is characterized by a high correlation coefficient of 0.9999. The main drawback of the described calibration technique is the complexity of implementation, duration, and high requirements for the qualification of personnel.
Table 2 shows the calculated values of the oil mass in sunflower seeds and the actual values obtained by the extraction method.
Table 2 shows that the maximum error in measuring the oil mass in the analyzed sample by the NMR method does not exceed 28 mg, which, in terms of the oil content, taking into account the seed moisture content and the mass of the sample with a volume of 25 cm3, is < 0.29%.
At the next stage, the possibility of using oil, obtained by pressing sunflower seeds, for the calibration of an NMR analyzer was investigated. Figure 2 illustrates the dependence of the oil mass on the amplitude of the NMR signal obtained using the oil pressed from sunflower seeds of three contemporary high-oil varieties (Dzhin, Imidzh, SPK).
According to the presented curve, the variety special features of seeds cause no significant effect on the amplitude of the oil NMR signal and, consequently, on the obtained analytical dependence. The difference between the obtained curve and that shown in Fig. 1 can be explained by the introduction of different amounts of accompanying substances in the process of oil extraction and pressing.
Table 3 provides the calculated values of the oil mass in sunflower seeds according to the calibration of an NMR analyzer using pressed oil.
The application of a calibration curve, obtained using pressed oil, leads to a maximum measurement error of not more than 32 mg or 0.33 abs% in terms of the oil content taking into account the seed moisture content and the mass of the sample with a volume 25 of cm3 in the entire studied range.
At the third stage of the study, two samples of sunflower oil were used: refined and deodorized of the “BLAGO” trademark and non-refined of the “STAVROPOL’E” trademark, acquired at a retail network.
Figure 3 plots the dependence of the oil mass on the amplitude of the NMR signal, obtained using oil acquired at a retail network.
As in the case of pressed oil, the obtained curve of the dependence between the mass of the analyzed oil sample and the amplitude of the oil NMR signal has a linear nature with the high correlation coefficient.
Table 4 provides the calculated values of the oil mass in sunflower seeds according to the calibration of the NMR analyzer using commercially distributed oil.
The application of a calibration curve, obtained using commercially distributed oil, leads to a maximum measurement error of not more than 28 mg or 0.35 abs% in terms of the oil content taking into account the seed moisture content and mass of the sample with a volume 25 of cm3 in the entire studied range.
At the next stage, the oil samples were studied for the temporal stability of NM relaxation characteristics. Three weighments of both refined deodorized and pressed oil were selected for a storage at a temperature of 8 °C in tightly-closed glass cups. Once a week, the samples were taken out of the refrigerator and thermostated at a temperature of 23 ± 0.5 °C for 4 h followed by threefold measurements of the oil NMR signal amplitude. The mean of three measurements was taken as the measurement result. Further, using the obtained earlier calibration equations, the oil masses of the studied samples were calculated and the deviations from the basic value were determined (Table 5).
According to Table 5, the NM relaxation characteristics of the refined oil and, consequently, the calculated values of the oil mass remain stable during the considered storage time. However, for the pressed oil samples, the measured amplitude of the NMR signal of TAG protons considerably altered and led to a decrease in the calculated oil mass value by 570 mg.
Thus, according to the results of the temporal stability study, pressed oil samples can preserve their proton NM relaxation characteristics during not more than 5–7 days, while the refined deodorized samples demonstrate the stability during not < 3 months at a temperature of 8 °C. This can be explained by the presence of a large quantity of free radicals, moisture, and other accompanying substances in pressed oil, facilitating the flow of oxidation processes, which lead to an increase in the quantity of free fatty acids and other products of oxidizing reactions.
Comparative characteristics of the studied methods for calibrating an AMV-1006M NMR analyzer are presented in Table 6.
Conclusion
The conducted research shows that the use of sunflower oil, obtained in different ways, for the calibration of NMR analyzers can significantly facilitate the calibration process, reduce the calibration time from 3–4 days to 3–4 h, as well as to eliminate the use of toxic solvents and additional expensive equipment from the process without significantly increasing the error in determining the oil content of sunflower seeds by the NMR method.
Notes
- 1.
GSO 3107-84 Reference materials of the approved type of oil content and moisture content of sunflower seeds (set). Available via FIF EUM. www.fgis.gost.ru/fundmetrology/registry/19/items/393823. Accessed 12 September 2022 (In Russ.).
- 2.
The minispec Oil content and moisture in seeds and nuts. Available via: URL: http://spectrante.ru/images/pdf_series/Zernovie.pdf. Accessed 12 September 2022 (In Russ.).
- 3.
Measurement of oil component in dried palm mesocarp. Available via: Oxford Instruments. https://nmr.oxinst.com/assets/uploads/18_Measurement_of_Oil_Content_in_Dried_Palm_Mesocarp.pdf. Accessed 12 September 2022.
- 4.
Measurement of oil and water in seeds according to ISO 10565. Available via Oxford Instruments. https://nmr.oxinst.com/assets/uploads/3_3344_MR_Oilseeds_App%20Note_Web.pdf. Accessed 12 September 2022.
- 5.
Sunflower varieties of VNIIMK breeding, Russia:
UMNIK, oil content 30–35%. Available via VNIIMK. https://vniimk.ru/products/belosnezhnyy-sq/. Accessed 12 September 2022 (In Russ.).
DZhIN, oil content 44–46%. Available via VNIIMK. https://vniimk.ru/products/dzhinn/. Accessed 12 September 2022 (In Russ.).
IMIDZh, oil content 48%. Available via VNIIMK. https://vniimk.ru/about/fgup/Кaтaлoг%20BHИИMК.pdf. Accessed 12 September 2022 (In Russ.).
SPK, oil content 46–47%. Available via VNIIMK. https://vniimk.ru/products/spk/. Accessed 12 September 2022 (In Russ.).
BELOSNEZhNYI, oil content 30–35%. Available via VNIIMK. https://vniimk.ru/products/belosnezhnyy-sq/. Accessed 12 September 2022 (In Russ.).
Abbreviations
- RM:
-
Reference material
- TAG:
-
Triacylglycerol
- NMR spectroscopy:
-
Nuclear magnetic resonance spectroscopy
References
GOST 22391-2015 (2019) Sunflower. Specifications. Standartinform, Moscow (in Russian)
GOST 10857-64 (2010) Oil seeds. Methods for determination of oil content. Standartinform, Moscow (in Russian)
GOST 32749-2014 (2019) Oilseeds, oilcakes and oilmeals. Determination of moisture, oil, protein and fiber by near-infrared reflectance. Standartinform, Moscow (in Russian)
Pérez-Vich B, Velasco L, Fernández-Martínez JM (1998) Determination of seed oil content and fatty acid composition in sunflower through the analysis of intact seeds, husked seeds, meal and oil by near-infrared reflectance spectroscopy. J Am Oil Chem Soc 75(5):547–555. https://doi.org/10.1590/fst.20118
Inmaculada M, Virginia V, López-González F, Oiz-Jiménez C, Iris O, Belén G et al (2013) Control of quality and silo storage of sunflower seeds using near infrared technology. Grasas y Aceites 64:30–35. https://doi.org/10.3989/gya.096312
Saha U, Endale D, Tillman P, Johnson W, Gaskin J, Sonon L et al (2017) Analysis of various quality attributes of sunflower and soybean plants by near infrared reflectance spectroscopy: development and validation calibration models. Am J Anal Chem 8:462–492. https://doi.org/10.4236/ajac.2017.87035
Grunvald AK, Leite RS, Terra IM, Carvalho CG, Mandarino JM, Andrade CV et al (2009) Calibration curve to predict oil content using near Infrared Reflectance Spectroscopy (NIR) in sunflower trials in Brazil. In: Rio Grande do Sul, Brasilia, 30 de setembro a 1o de outubro 2009. Embrapa Clima Temperado, Brasilia
Velasco L, Pérez-Vich B, Fernández-Martínez JM (2007) Relationships between seed oil content and fatty acid composition in high stearic acid sunflower. Plant Breed 126:503–508. https://doi.org/10.1111/j.1439-0523.2007.01371.x
Prudnikov SM (2003) The scientific and practical substantiation of methods of identification and quality assessment of oilseeds and products of their processing on the basis of a method of nuclear magnetic relaxation. Dissertation, VS Pustovoit All-Russian Research Institute of Oil Crops (in Russian)
Vityuk BY, Gorelikova IA, Prudnikov SM (2002) A simulator of signals of free precession of nuclear magnetic resonance and spin echoes from oil in oilseeds. RF Patent, No. 2191998 (in Russian)
Vityuk BY, Aspiotis EH (1980) Standard samples for calibration and verification of NMR analyzers of oil content and moisture content of oilseeds. In: collection of works I All-Union meeting of spectroscopy of coordination compounds, Krasnodar, p 16 (in Russian)
Rejhsfel'd VO (eds) (1980) Chemistry and technology of organosilicon elastomers. Leningrad, Chemistry (in Russian)
Bazhant V (2010) Silicones—organosilicon compounds, their derivation properties and application. Moscow, Nauka, p 700 (in Russian)
Gorodov VV (2018) Synthesis and properties of carboxyl-containing polydimethylsiloxanes. Dissertation, Enikolopov Institute of Synthetic Polymeric Materials Russian Academy of Sciences. https://www.dissercat.com/content/sintez-i-svoistva-karboksilsoderzhashchikh-polidimetilsiloksanov/read (in Russian)
Kotlayrova IA, Tereschenko GA, Voloshina OI (2016) Variability of seeds within a head on morphomet-ric traits and seed productivity at the modern sunflower varieties. Oil Crops 1:29–37 (in Russian)
Vasilyeva TA, Boyko YuG (2012) Dependence of the size of sunflower seeds on competition between them within baskets. Oil Crops 1:34–41 (in Russian)
Ren ZH, Liu C, Wang HZ, Zhang XL, Yang PQ (2008) Simultaneous determination of oil content in oilseed by pulsed NMR. In: Proceedings 2nd international conference Bioinformatics and Biomedical Engineering, Institute of Electrical and Electronics Engineers, Shanghai, China, 16–18 May 2008, pp 2244–2247. https://doi.org/10.1109/ICBBE.2008.892
Gambhir PN (1992) Applications of low-resolution pulsed NMR to the determination of oil and moisture in oilseeds. Trends Food Sci Technol 3:191–196
Guy R (1994) Simultaneous determination of oil and water contents in different oilseeds by pulsed nuclear magnetic resonance. J Am Oil Chem Soc 71:1057–1062
Ropp JS, McCarthy MJ (2006) Nuclear magnetic resonance in the analysis of foodstuffs and plant materials. Encyclopedia of analytical chemistry: applications, theory and instrumentation. https://doi.org/10.1002/9780470027318.a1019
Praduman Y (2016) Calibration of NMR spectroscopy for accurate estimation of oil content in sunflower, safflower and castor seeds. Current Science 110(1):73–76. https://doi.org/10.18520/cs/v110/i1/73-80
Robertson JA, Morrison WH (1979) Analysis of oil content of sunflower seed by wide-line NMR. J Am Oil Chem Soc 56:961–964. https://doi.org/10.1007/BF02674143
Hutton WC, Garbow JR, Hayes TR (1999) Nondestructive NMR determination of oil composition in transformed canola seeds. Lipids 34(12):1339–1346. https://doi.org/10.1007/s11745-999-0487-0
Kotyk JJ, Pagel MD, Deppermann KL, Colletti RF, Hoffman NG, Yannakakis EJ et al (2005) High-throughput determination of oil content in corn kernels using nuclear magnetic resonance imaging. J Am Oil Chem Soc 82(12):855–862. https://doi.org/10.1007/s11746-005-1155-5
Prudnikov SM, Agafonov OS, Zverev LV, Vitiuk BY, Gorelikova IA (2019) Simulator of a free procession of nuclear magnetic resonance and spin echo oil with a different mass fraction of oleic acid in sunflower seeds. RF Patent 2677644 (in Russian)
GOST 8.597-2010 (2011) State system for ensuring the uniformity of measurements. Oilseeds and oilseeds residues. Determination of oil and moisture content using pulsed nuclear magnetic resonance spectrometry. Standartinform, Moscow (in Russian)
GOST 31933-2012 (2019) Vegetable oils. Methods for determination of acid value. Standartinform, Moscow (in Russian)
Agafonov OS, Zverev LV, Prudnikov SM (2019) Software package for control, reception, processing and storage of NMR analyzer information. Certificate of registration of a computer program RU 2019666343, 09.12.2019 (in Russian)
Acknowledgments
No financial support in the form of a grant from any organization in the public, commercial, or non-profit sector was obtained for the research. All measurements were carried out using the equipment of the V. S. Pustovoit All-Russian Research Institute of Oil Crops.
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The authors have contributed equally.
Conflict of interest
The article was prepared on the basis of a report presented at the V International Scientific Conference “Reference materials in measurements and technologies” (Yekaterinburg, September 13–16, 2022). The article was admitted for publication after the abstract was revised, the article was formalized and the review procedure was carried out.
The version in the Russian language is published in the journal “Measurement Standards. Reference Materials” 2023;19(2):61–71 (In Russ.). https://doi.org/10.20915/2077-1177-2023-19-2-61-71
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Agafonov, O.S., Prudnikov, S.M. (2024). Determination of Sunflower Seed Oil Content Using Natural Sunflower Oil: Calibration of a Pulsed NMR Analyzer. In: Sobina, E.P., et al. Reference Materials in Measurement and Technology . RMMT 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-49200-6_9
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