Determination of the fatty acid composition of the oil in intact-seed mustard by near-infrared reflectance spectroscopy

Near-infrared reflectance spectroscopy (NIRS) was used to estimate the fatty acid composition of the oil in intact-seed samples of Ethiopian mustard (Brassica carinata Braun) within a mutation breeding program that produced seeds with variable fatty acid compositions. Five populations, from 1992 to 1996 crops, were included in this study; and NIRS calibration equations for major fatty acids (palmitic, stearic, oleic, linoleic, linolenic, eicosenoic, and erucic) were developed within each single population. Furthermore, global calibration equations, including samples from the five populations, were developed. After external validation, the NIRS technique permitted us to obtain a reliable and accurate nondestructive estimation of the fatty acid composition of the oil, especially for the major acids—oleic, linoleic, linolenic, and erucic. For these, the r ² in external validation was higher than 0.95 by using both single-and multipopulation equations, and higher than 0.85 for the remaining fatty acids. Moreover, the multipopulation equations provided an accurate estimation of samples from a population not represented in the calibration data set, with values of coefficient of determination in validation (r ²) from 0.80 (palmitic and eicosenoic acids) to 0.97 (erucic acid). The ability of NIRS to discriminate among different fatty acid profiles was mainly due to changes within six spectral regions, 1140–1240, 1350–1400, 1650–1800, 1880–1920, 2140–2200, and 2240–2380 nm, all of them associated with fatty acid absorbers. Thus, NIRS can be used to estimate the fatty acid composition of Ethiopian mustard seeds with a high degree of accuracy, provided that calibration equations be developed from calibration sets that include large variability for the fatty acid composition of the oil.     

Improved Estimation of Oil,Linoleic and Oleic Acid and Seed Hull Fractions in Safflower by NIRS

Near-infrared reflectance spectroscopy (NIRS) of intact seeds allows the non-destructive estimation of seed quality parameters which is highly desirable in plant breeding. Together with yield, oil content and quality, a main aim in safflower (Carthamus tinctorius L.) breeding is the selection of genotypes with a low percentage of empty seeds even under cooler climates. We developed NIRS calibrations for seed oil content, oleic and linoleic acid content, the seed hull fraction and the percentage of empty seeds using seed meal and intact seeds. For the different calibrations 108–534 samples from a safflower breeding program with lines adapted to German conditions, were analyzed with reference analyses (Soxhlet, gas chromatography), and scanned by NIRS as intact seeds and seed meal. Calibration equations were developed and tested through cross validation. The coefficient of determination of the calibration (R ²) for intact seeds ranged from 0.91(oil content), 0.90 (seed hull fraction), 0.84 (empty seeds), 0.73 (linoleic acid) to 0.68 (oleic acid). The coefficient of determination of the cross validation was higher for seed meal than for intact seeds except for the parameter seed hull fraction. The results show that NIRS calibrations are applicable in safflower breeding programs for a fast screening.     

Nondestructive Estimation of Fat Constituents of Sesame (Sesamum indicum L.) Seeds by Near‐Infrared Reflectance Spectroscopy

A rapid and efficient method for oil constituent estimation in intact sesame seeds was developed through near‐infrared reflectance spectroscopy (NIRS) and was used to evaluate a sesame germplasm collection conserved in China. A total of 342 samples were scanned by reflectance NIR in a range of 950–1650 nm, and the reference values for oil content and fatty acid (FA) profiles were measured by Soxhlet and gas chromatograph methods. Useful chemometric models were developed using partial least squares regression with full cross‐validation. The equations had low standard errors of cross‐validation, and high coefficient of determination of cross‐validation (R_c²) values (>0.8) except for stearic acid (0.794). In external validation, r² values of oil and FA composition equations ranged from 0.815 (arachidonic acid) to 0.877 (linoleic acid). The relative predictive determinant (RPD_v) values for all equations were more than 2.0. The whole‐seed NIR spectroscopy equations for oil content and FA profiles can be used for sesame seed quality rapid evaluation. The background information of the 4399 germplasm resources and accessions with high linoleic acid content identified in this study should be useful for developing new sesame cultivars with desirable FA compositions in future breeding programs.     

Determination of the Fatty Acid Composition in Tree Peony Seeds Using Near-Infrared Spectroscopy

Tree peonies (Paeonia Sect Moutan DC) are an emerging oil crop because of their high oil and α‐linolenic acid (ALA) content. This research was to investigate the potential use of near infrared reflectance spectroscopy (NIRS) for estimating the major fatty acids contents, such as palmitic acid (C16:0), oleic acid (C18:1), linoleic acid (C18:2) and linolenic acid (C18:3) in tree peonies. A total of 115 small seed samples and 447 single seeds were selected to calibrate the predictive models. NIRS absorbance spectra were collected using a Fourier transform near infrared (FT‐NIR) spectrometer for the small seed samples, and acousto‐optic tunable filter‐near infrared (AOTF‐NIR) for the single seed samples. Statistical analysis was performed with partial least squares (PLS). For the husked samples, C18:3, C18:1 and C18:2 showed the highest correlation coefficient of validation (R_v; = 0.9756, 0.9467 and 0.8485, respectively) and the ratio of performance to deviation (RPD; = 3.58, 1.91 and 2.17, respectively); however, C16:0 did not reach expectations (R_v = 0.7783, RPD = 1.32). For intact samples, C18:3 showed the best prediction (R_v = 0.9096, RPD = 3.14), followed by C18:2 (R_v = 0.8479, RPD = 1.96). The results for C18:1 were poor (R_v = 0.7237, RPD = 1.70). For single seeds, only the results for C18:3 (R = 0.9150, RPD = 1.73) were good in the husked seed samples. It was concluded that NIRS can be used to rapidly assess the content of the major fatty acids in small samples.     

Near‐infrared spectroscopy for analysis of oil content and fatty acid profile in almond flour

Almond kernels show large variability for oil content and fatty acid profile. The objective of this research was to evaluate the potential of near infrared (NIR) reflectance spectroscopy (NIRS) for the analysis of these traits in almond flour. Ground kernels of 181 accessions collected in 2009 were used for developing calibration equations for oil content and concentrations of individual fatty acids. Calibration equations were developed using second derivative transformation and modified partial least squares regression. They were validated with samples from 179 accessions collected in 2010. The accuracy of calibration equations was measured through the coefficient of determination (r²) in external validation and the ratio of the SD in the validation set to the standard error of prediction (RPD). Both r² and RPD were high for oil content (r² = 0.99; RPD = 9.24) and concentrations of oleic (r² = 0.97; RPD = 5.37) and linoleic acids (r² = 0.98; RPD = 7.35), revealing that calibration equations for these traits are highly accurate. Conversely, the accuracy of the calibration equations for palmitic (r² = 0.54; RPD = 1.41) and stearic acids (r² = 0.52; RPD = 1.44) was too low for allowing their application in practice. NIRS discrimination of oil content and concentrations of oleic and linoleic acids was mainly based on the spectral region from 2240 to 2380 nm. Practical applications : NIRS is a high‐throughput analytical technique that allows fast measurement of several traits in a single analysis without using chemical reagents. We evaluated the feasibility of analyzing oil content and concentrations of palmitic, stearic, oleic, and linoleic acids in almond flour using fruits collected during 2 years from a world germplasm collection. The fruits collected in 2009 were used for NIRS calibration, whereas the fruits collected in 2010 were used for validation. NIRS equations were highly accurate for measuring oil content and concentrations of oleic and linoleic acids, which are important traits defining the quality of almond flour for specific uses in the food industry. These results have applications both in the research laboratory and the food industry, where NIRS is becoming a widely used technique for quality control.     

Performance of near-infrared reflectance spectroscopy (NIRS) in routine analysis of C18 unsaturated fatty acids in intact rapeseed

This study was aimed to evaluate the performance of near-infrared reflectance spectroscopy (NIRS) in the analysis of the oil composition for fatty acids like oleic (C18:1), linoleic (C18:2) and linolenic (C18:3) in zero-erucic acid rapeseed (Brassica napus L.). Intact-seed samples of 1094 lines from a breeding programme for high-oleic acid rapeseed were analyzed by both NIRS and gas chromatography (GC). Previously developed calibration equations were initially used for NIRS analyses. The accuracy of NIRS was considerably improved by including some samples of the actual breeding population into the original calibration set and developing new calibration equations. The inclusion of twenty randomly selected samples led to a reduction of the standard error of performance (SEP) from 2.6% to 1.9% for oleic, from 3.8% to 2.0% for linoleic, and from 1.1% to 0.9% for linolenic acid. The application of the new equations to the remaining population of 1074 samples resulted in coefficients of correlation between NIRS and GC values of 0.95 for oleic, 0.92 for linoleic, and 0.90 for linolenic acid. Furthermore, the effectiveness of a selection for high oleic, high linoleic, or low linolenic acid content based on NIRS data was demonstrated. The results of this study will help potential users to choose the optimal selection strategy in routine analysis of C18 unsaturated fatty acids by NIRS within a breeding programme.     

Estimation of Protein and Fatty Acid Composition in Shell-Intact Cottonseed by Near Infrared Reflectance Spectroscopy

Rapid and accurate analysis of cottonseed protein content and the composition of fatty acids (especially, saturated fatty acids) is often required in cotton production and breeding programs. This study aimed to establish a set of effective estimation models for these parameters. Near infrared reflectance spectroscopy (NIRS) calibration equations using partial least-squares regression for protein concentration, oil concentration, and five fatty acids of shell-intact cottonseeds were established based on 90 varieties, and the prediction abilities of the calibration models were verified using 45 other varieties. The prediction abilities of the NIRS calibration equations were basically consistent with external validation results. Each equation was assessed based on the ratio of performance to deviation (RPD_p). Protein content and seed total fatty acid (STA) content had high RPD_p values (3.687 and 3.530, respectively), whereas cottonseed kernel total fatty acid (KTA) content, linoleic acid (18:2), stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) exhibited relatively high RPD_p (2.866, 2.836, 2.697, 2.676, and 2.506, respectively). The calibration model for oleic acid (18:1) had a low RPD_p (1.945). The results indicated that NIRS can be used to rapidly determine contents of STA, KTA, protein, stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) in shell-intact cottonseed.     

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

A methodological study was conducted to test the potential of near-infrared reflectance spectroscopy (NIRS) to estimate the oil content and fatty acid composition of sunflower seeds. A set of 387 intact-seed samples, each from a single plant, were scanned by NIRS, and 120 of them were selected and further scanned as husked seed, meal, and oil. All samples were analyzed for oil content (nuclear magnetic resonance) and fatty acid composition (gas chromatography), and calibration equations for oil content and individual fatty acids (C_16:0, C_16:1, C_18:0, C_18:1, and C_18:2) were developed for intact seed, husked seed, meal, and oil. For intact seed, the performance of the calibration equations was evaluated through both cross- and external validation, while cross-validation was used in the rest. The results showed that NIRS is a reliable and accurate technique to estimate these traits in sunflower oil (validation r ² ranged from 0.97 to 0.99), meal (r ² from 0.92 to 0.98), and husked seeds (r ² from 0.90 to 0.97). According to these results, there is no need to grind the seeds to scan the meal; similarly accurate results are obtained by analyzing husked seeds. The analysis of intact seeds was less accurate (r ² from 0.76 to 0.85), although it is reliable enough to use for pre-screening purposes to identify variants with significantly different fatty acid compositions from standard phenotypes. Screening of intact sunflower seeds by NIRS represents a rapid, simple, and cost-effective alternative that may be of great utility for users who need to analyze a large number of samples.     

Composition of seeds of cruciferous oil crops

Several species of the Cruciferae family are presently used as oilseed crops, viz.,Brassica campestris (turnip rape and sarson),B. juncea (brown or yellow mustard),B. napus (rape),Crambe abyssinica (crambe), andSinapis alba (white or yellow mustard). Seed oils of these species are characterized by variable but generally large amounts of erucic acid (22:1) in the triacylglycerols, which make up 95–98% of the total lipids of high quality, viable seeds. In addition to erucic acid, the major fatty acids are oleic (typically 10–25%), linoleic (10–20%), linolenic (7–11%) and eicosenoic (5–10%). However cultivars of rapeseed lacking erucic acid and having about 55–60% oleic, 20–25% linoleic and ca. 10% linolenic acid have been developed. The eicosenoic and erucic acids are located exclusively at the 1 and 3 positions of the triacylglycerol. As a consequence, major triacylglycerol types have carbon numbers 54, 56, 58, 60 and 62. The phospholipids of rapeseed are essentially devoid of erucic acid and have palmitic, oleic and linoleic acids as major fatty acids. Sterols generally amount to about 0.5% of the oil with β-sitosterol, campesterol and brassicasterol as major constituents (about 55%, 25% and 15%, respectively, of the total sterols). A few per cent of the total sterol fractions is cholesterol. The tocopherol content of rapeseed oil is about 800 ppm with α- and γ-tocopherol as major components. Cruciferous seeds contain a fairly large number of storage proteins. Thus approximately 50 components have been detected in alkaline extracts ofBrassica napus, a major portion of which are in the molecular weight range 120–150,000. The protein spectrum ofB. napus (rape) is more complex than that ofB. campestris (turnip rape) since the former species is an allotetraploid withB. oleracea (kale, cabbage, etc.) andB. campestris as parents. Approximately 5% of the fat free seed meal is composed of glucosinolates, which are split upon enzymatic hydrolysis to antinutritional factors: isothiocyanates, oxazolidinethiones and nitriles. The different crucifers discussed have both qualitative and quantitative differences with respect to glucosinolate content. One of nine papers presented at the Symposium, “Cruciferous Oilseeds,” ISF-AOCS World Congress, Chicago, September 1970.     

Estimation of Oil Content and Fatty Acid Composition in Cottonseed Kernel Powder Using Near Infrared Reflectance Spectroscopy

Oil content and fatty acid composition in 444 ground cottonseed kernel samples were analyzed using near infrared reflectance spectroscopy (NIRS). Calibration equations were developed for oil and fatty acid contents with the modified partial least squares (MPLS) regression method. The correlations between NIRS and reference values in external validation were in agreement with the predictions in calibration. Each equation was assessed based on the relative prediction determinant for external validation (RPD_v). Equations corresponding to total oil content (RPD_v = 11.495) and linoleic acid (RPD_v = 5.026) showed high accuracy. For palmitic acid (RPD_v = 1.914), myristic acid (RPD_v = 1.724) and oleic acid (RPD_v = 1.999), the equations were predicted with relatively high accuracy while those for palmitoleic acid (RPD_v = 0.686), stearic acid (RPD_v = 0.792), linolenic acid (RPD_v = 0.475) and 1-eicosenoic acid (RPD_v = 0.619) were poorly predicted. The equations for traits with RPD_v > 1.5 could be reliably used in screening samples for breeding programs.     

Isolation of High Oleate Recombinants in Peanut by Near Infra‐Red Spectroscopy and Confirmation With Allele Specific Polymerase Chain Reaction Marker

Near infrared (NIR) spectrophotometer offers rapid, noninvasive, nondestructive, and high‐throughput phenotyping of seed samples for use in agriculture and industry. In this study, a reflectance‐based NIR spectrophotometer was calibrated and used for the isolation of desirable higher‐oleic‐acid peanut recombinants from single‐seed‐derived segregating populations at F₇ and F₈ generations. A calibration model was developed through partial least‐square regression using wet chemistry data from 158 peanut genotypes. Desirable prediction for oil, palmitic acid, oleic acid, and linoleic acid in intact seed was obtained based on this calibration. It detected significant high correlations (r) and coefficient of determination (R²) between the actual gas chromatography values and NIR predicted values of fatty acid profile in another 123 peanut genotypes that were generated from crosses involving a high‐oleate mutant and Spanish bunch varieties with early maturity. From this recombinant single‐seed‐derived progenies, 15 higher‐oleate recombinants were isolated and later genotyped through an in‐house developed polymerase chain reaction‐based allele specific marker. The present study has generated high‐oleate peanut recombinants with early maturity in Spanish bunch background. The breeding materials generated here will be evaluated for yield attributing traits at different locations in future.     

Development of Whole and Ground Seed Near-Infrared Spectroscopy Calibrations for Oil,Protein, Moisture,and Fatty Acids in Salvia hispanica

Chia (Salvia hispanica) is an ancient crop that has experienced an agricultural resurgence in recent decades owing to the high omega 3 fatty acid (ω-3) content of the seeds and good production potential. Analysis of 563 lots of chia grown in Kentucky and 10 lots from Arizona, Australia, Mexico, and Peru was performed. All of these lots were assessed for fatty acid, oil, and protein content, while a subset of 120 samples were assessed for amino acids, fiber, minerals, and trace elements. The mean oil content was 31.3%, ranging from 21.4% to 35.3%. The protein content averaged 22.8%, ranging from 18.2% to 28.2%, and the ω-3 FA α-linolenic acid (ALA) averaged 61.3%, ranging from 33.9% to 69.9%. Using these seed lots, nondestructive near-infrared spectroscopy (NIRS) calibrations were developed for whole and ground seed oil, protein, moisture, and the six major fatty acids. The R² and SE of cross-validation (SECV) values for oil were 0.78 and 0.95, respectively, while those for protein were 0.75 and 1.05, respectively. The NIRS calibrations for fatty acid had R² and SECV greater than 0.6 and less than 10% of actual values for all major fatty acids, respectively. An R² of 0.99 was established for moisture content of whole seeds within the range of 3–10% moisture content. The precision and accuracy of these calibrations is adequate for use by breeders, growers, and food quality experts to quantitatively assess these major constituents without the need for costly and time-consuming chemical analysis.     

Chemical investigation of oil of the seed of “White Todri” (Matthiola incana,R.Br.)

The fixed oil from the seeds of 舠White Todri舡,Matthiola incana, R.Br. (Cruciferae), of Indian origin, has been studied for its component acids. The fatty acid composition was found to be myristic (2.60%), palmitic (4.73%), steric (4.37%), arachidic (2.50%), lignoceric (?) (0.73%), oleic (32.17%), linoleic (21.70%), linolenic (10.70%), erucic (13.10%), and resin acids (7.40%).     

Identification of High Oleic Castor Seeds by Near Infrared Reflectance Spectroscopy

Castor oil contains a high proportion (>80%) of the unusual hydroxy fatty acid ricinoleic acid. Additionally, a mutant with high oleic acid content (>70%) has been developed. Both fatty acids differ in the presence of an OH group in the C18 tail (ricinoleic acid). The objective of this research was to evaluate whether near-infrared reflectance spectroscopy (NIRS) can be used to discriminate between high oleic and high ricinoleic acid seeds. Eight hundred and seventy-two individual seeds collected in 2008, 688 high ricinoleic and 184 high oleic, were scanned by NIRS and further analyzed by GLC. As high oleic/low ricinoleic acid content is recessive and no intermediate fatty acid levels occur, the spectral data was subjected to linear discriminant analysis, which correctly classified all the seeds. The discriminant function was validated with a set of 637 seeds collected in 2009 from segregating populations, which were correctly classified in all cases. NIRS discrimination between oleic and ricinoleic acid was mainly based on spectral regions around 1,400 and 1,914 nm, putatively associated with the absorbance of the OH group. The results confirmed that NIRS provides an effective means of discriminating between high oleic and high ricinoleic acid seeds.     

Fatty acid composition of seed oil triglycerides inCoincya (Brassicaceae)

Oil and triglyceride contents and fatty acid composition were determined for seeds in nine taxa belonging to the genusCoincya (Brassicaceae) on the Iberian Peninsula (Spain and Portugal). The oil content ranges from 11.1 to 24.6%, triglycerides from 68.7 to 88.5%. The major fatty acids were erucic (24.6–30.5%), linolenic (17.7–27.7%), linoleic (13.9–24.6%) and oleic acid (12.3–21.8%).     

Rapid Determination of Degradation in Frying Oils with Near-Infrared Spectroscopy

Measures of free fatty acids (FFA), total polar materials (TPM), and conjugated dienoic acids (CDA), typical indices of oil degradation, were analyzed in daily oil aliquots taken from soybean oils with different linolenic acid concentrations used to fry French fries. The oils also were scanned with a reflectance near-infrared spectrometer using a wavelength range of 350–2,500 nm. By using partial least squares and one-out cross validation, calibrations were developed to quantitatively determine FFA, TPM, and CDA by near-infrared spectroscopy (NIRS). The coefficients of determination (R ²) when compared to the standard methods were 0.973 for FFA, 0.984 for TPM, and 0.902 for CDA. NIRS was an accurate and fast method to determine FFA, TPM, and CDA in oxidized oils. The ability to obtain different parameters simultaneously makes NIRS a potentially valuable tool for food quality assurance.     

Variation in Fatty Acid Composition in Indian Germplasm of Sesame

A germplasm collection of 33 entries comprising 22 sesame (Sesamum indicum L.) cultivars, 4 landraces of S. mulayanum and 7 other accessions of 4 wild species were analyzed for the fatty acid compositions of their seed oil. The entries varied widely in their fatty acid compositions. The percentage content of oleic, linoleic, palmitic and erucic acids ranged between 36.7–52.4, 30.4–51.6, 9.1–14.8 and 0.0–8.0, respectively. Linolenic and arachidonic acids were the minor constituents but varied widely in wild species. Oleic and linoleic were the major fatty acids with mean values of 45.9 and 40.5%, respectively and the mean of their combined values was 86.4%. The polyunsaturated fatty acid (PUFA) compositions ranged from 30.9 to 52.5% showing high variation in PUFA in the germplasm. Linoleic acid content was very high in one landrace (47.8) and one accession each of three wild species, S. mulayanum (49.3), S. malabaricum (48.2) and S. radiatum (51.6%). Use of fatty acid ratios to estimate the efficiency of biosynthetic pathways resulted in high oleic and low linoleic desaturation ratios and consequently high linoleic and very low linolenic acid contents in seed oil. The results of this study provided useful background information on the germplasm and also identified a few accessions having high linoleic acid which can be used for developing cultivars with desirable fatty acid compositions.     

Determination of tocopherols and phytosterols in sunflower seeds by NIR spectrometry

The objective of this work was to develop a near‐infrared reflectance spectrometry (NIRS) calibration estimating the tocopherol and phytosterol contents in sunflower seeds. Approximately 1000 samples of grinded sunflower kernels were scanned by NIRS at 2‐nm intervals from 400 to 2500 nm. For each sample, standard measurements of tocopherol and phytosterol contents were performed. The total tocopherol content was obtained by high‐performance liquid chromatography coupled with a fluorescence detector, while the total phytosterol content was assessed by gas chromatography. For tocopherol, the calibration data set ranged from 175 to 1005 mg/kg oil (mean value around 510 ± 140 mg/kg oil), whereas for the phytosterol content, the calibration data set ranged from 180 to 470 mg/100 g oil (mean value of 320 ± 50 mg/100 g oil). The NIRS calibration showed a relatively good correlation (R² = 0.64) between predicted by NIRS and real values for the total tocopherol content but a poor correlation for the total phytosterol content (R² = 0.27). These results indicate that NIRS could be useful to classify samples with high and low tocopherol content. In contrast, the estimation of phytosterol contents by NIRS needs further investigation. Moreover, in this study, calibration was obtained by a modified partial least‐squares method; the use of other mathematical treatments can be suitable, particularly for total phytosterol content estimation.     

Non-destructive Determination of High Oleic Acid Content in Single Soybean Seeds by Near Infrared Reflectance Spectroscopy

Soybean [Glycine max (L.) Merr] with increased oleic acid is desirable to improve oxidative stability and functionality of soybean seed oil. Recently, soybean genotypes with high oleic acid (≥70 %) were developed by breeding programs. Efficient and effective identification of high oleic acid soybean genotypes using non-destructive near infrared reflectance (NIR) on whole seeds would greatly enhance progress in breeding programs. The objective of this study was to develop a calibration equation for NIR determination of high oleic acid from single soybean seeds. A total of 600 intact, single F₂ seeds were scanned by NIR. Spectral data were collected between 400 and 2,500 nm at 2 nm intervals. The relationship between NIR spectral patterns of each soybean seed and its oleic acid content was examined. The best predicted equations for oleic acid were selected on the basis of minimizing the standard error of cross-validation and increasing the coefficient of determination. Validation demonstrated that the equations for determining total oleic acid and over 50 % oleic acid content had high predictive ability (r ² = 0.91 and r ² = 0.99, respectively). To validate the newly developed equation, F₂ seeds from a different genetic background were tested. Again, high oleic acid from single soybean seeds was accurately predicted from various genetic backgrounds. Therefore, applying the calibration equations to NIR will be useful to rapidly and efficiently select high oleic acid soybean genotypes in breeding programs.     

The role of radical polymerization in the production of thermoregulating microcapsules or polymers from saturated and unsaturated fatty acids

The microencapsulation of linoleic (LinA), oleic, erucic, and palmitic acids (PAs) from styrene and divinylbenzene were studied by using the suspension‐like polymerization technique. All materials exhibited a spherical shape, with a particle size between 166 and 416 μm. The phase change material (PCM) content decreased with the presence of double bonds in the fatty acid molecule. The thermal energy storage (TES) capacity of the microcapsules (MC) containing saturated PA was the highest (123.30 J g^?1). Whereas, the lowest TES capacity was observed for the LinA. TES capacity values from unsaturated fatty acid materials and the high particle yield indicated that these kinds of acids played two different roles, as PCM and also as monomers, in the radical polymerization processes. At high initiator concentrations, the unsaturated fatty acids were observed to react. This was confirmed by Fourier transform infrared where the peak assigned to the C?C bond disappears in the spectrum of MC. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45970.