alexa Variation in Glucosinolate and Tocopherol Concentrations in a Germplasm Collection of Brassica juncea (L.) Czern. + Coss. | OMICS International
ISSN: 2161-1009
Biochemistry & Analytical Biochemistry
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Variation in Glucosinolate and Tocopherol Concentrations in a Germplasm Collection of Brassica juncea (L.) Czern. + Coss.

Shilpa Gupta1*, Manjeet Kaur Sangha1, Gurpreet Kaur2, Amarjeet Kaur Atwal2, Prabhjot Kaur2, Hitesh Kumar2, Shashi Banga2 and Surinder Singh Banga2

1Department of Biochemistry, Punjab Agricultural University, Ludhiana, Punjab- 141004, India

2Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab-141004, India

*Corresponding Author:
Shilpa Gupta
Department of Biochemistry
Punjab agricultural University
Ludhiana, Punjab-141004, India
E-mail: [email protected]

Received Date: March 22, 2012; Accepted Date: October 19, 2012; Published Date: October 23, 2012

Citation: Gupta S, Sangha MK, Kaur G, Atwal AK, Kaur P, et al. (2012) Variation in Glucosinolate and Tocopherol Concentrations in a Germplasm Collection of Brassica juncea (L.) Czern. + Coss. Biochem Anal Biochem 1:121. doi: 10.4172/2161-1009.1000121

Copyright: © 2012 Gupta S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Detailed analysis of the leaves and seeds of 97 individual plants of a RIL population derived from the cross of NUDH-YJ-04, a tall and late flowering European juncea having low glucosinolates and RL-1359, a semi dwarf and early flowering Indian juncea having high glucosinolates, grown at a field site revealed a wide variation in total concentrations of seed glucosinolates, leaf glucosinolates, tocopherols and oil. Their contents lied in the ranges of 28.85 to 115.88 μmole/g seed, 0.82-102.30 μmole/g leaf, 32.29 to 1250 ppm and 34.96-45.00% respectively. Such variation studies are imperative for map based cloning and QTL mapping of key genes associated with the studied traits which in turn can help us in exploring the genetic view of these biochemicals.


Glucosinolates; Tocopherols; NIRS (Near Infrared Reflectance Spectroscopy); NMR (Nuclear Magnetic Resonance); Brassica juncea


Modern cultivars and breeding lines of Indian mustard (Brassica juncea (L.) Czern. + Coss.) yield high-quality oil, high-protein seed meal, and are relatively resistant to heat stress, water stress, pod-shattering and fungal diseases. This species has therefore been recognised as a potentially valuable alternative oilseed to rapeseed (B. napus L. and B. campestris L.) in all over world [1,2]. However, the usefulness of the crop is still severely limited by the unacceptably high glucosinolate content of the seed meal. There are 3 serious problems associated with breeding and selection for reduced seed glucosinolate content in Brassica species. Firstly, the biochemistry and inheritance of seed glucosinolate content and composition are poorly understood. It is likely that mustard seed glucosinolate content and composition, like the glucosinolate traits of rapeseed [3], are determined by the genotype of the maternal plant rather than by the embryo itself, but the precise nature and extent of this maternal influence is not known. Consequently, it is never entirely clear how to interpret seed analysis data in variable populations. Secondly, seed glucosinolate content is also markedly influenced by a range of environmental and physiological effects such as sulfur nutrition [4], time of sowing [5] and pod position on the plant [6]. Thirdly, until very recently plant breeders have to rely either on rapid but inaccurate and variable ‘quick tests’, such as glucose assays, or on expensive and time-consuming chromatographic procedures to obtain data on seed glucosinolates [7]. This has severely restricted the number of accurate analyses that can be performed during routine screening of breeding lines. With an awareness of these problems, and with the recent development of an efficient, accurate and reproducible High Performance Liquid Chromatography (HPLC) method for glucosinolate analysis [8], leaf and seed glucosinolate variation between individual plants of B. juncea has been recorded along with tocopherols variation.

Glucosinolates are alkyl-N-hydroximine sulphate esters with a β-D-thioglucopyranoside group attached to the hydroximine carbon in Z-configuration to the sulphate group [1-3]. These natural products are biosynthetically produced from amino acids and are present in all plants of the order Capparales and in a few other plants [1,4-6]. Most glucosinolate containing genera are clustered within the families Capparaceae, Caricaceae and Brassicaceae, the latter including the genus Brassica. More than 140 glucosinolates have been identified up to now, of which about 30 are present in Brassica species [4,7,8]. The concentration and composition of the glucosinolates in different plants, but also within a plant (in the seeds, roots or leaves), can vary greatly and also change during plant development [9-12].

Tocopherols have long been known as one of the most potent classes of fat-soluble antioxidants occurring in nature. More recently, beneficial biological roles for natural tocopherols, which are independent of their antioxidant/radical scavenging abilities, have also been suggested, although a definitive function in human health and disease prevention has not been established. Vegetable oils are the most abundant source of naturally occurring tocopherols. Therefore, oilseed crops such as canola and soybean represent the best target for biotechnological costefficient production of tocopherols for use as dietary supplements and food additives. They occur as a family of four derivatives (alpha-, beta-, gamma-and delta-tocopherol; the alpha-derivative is also known as vitamin E), differing in the methylation of the chroman head group. The main biochemical function of the tocopherols is believed to be the protection of polyunsaturated fatty acids against peroxidation [13]. The vitamin E activity of the tocopherols is quite different, alphatocopherol being the most efficient of the four tocopherol-derivatives. However, among them it shows the lowest antioxidant effect in vitro, gamma-tocopherol being the most effective of the four tocopherols [14]. The richest dietary sources of vitamin E are edible oils. Because of their high antioxidative value and health benefits, tocopherols are an interesting goal for improvement of oil quality. For Brassica juncea L.) only very limited information on the variation in tocopherol content is available. In a study on B. napus, Richard et al. [15] reported that, oil contained 358 μg/g of γ-tocopherol (range of 241-924 μg/g) and 181 μg/g of α-tocopherol (range of 108-336 μg/g) and in B. juncea it was 379 μg/g (range of 163-777 μg/g) and 200 μg/g (range of 76-335 μg/g) respectively and the concentration of β-tocopherol was relatively low in both species with averages of 25 μg/g (range of 11-64 μg/g) for B. napus and 16 μg/g (range of 4-57 μg/g) for B. juncea. Goffman et al. and Marwede et al. [16,17] also investigated a collection of 91 species of the family Brassicaceae and observed a wide variability of total tocopherol content in seed oils ranging from <70 ppm to 2500 ppm.

As part of a comprehensive study to provide information on levels and variation of GSs and tocopherols in cruciferous vegetables (2, 3, 5, 19), we have analyzed the GS and tocopherol contents in the leaves and seeds of 97 cultivars.

Materials and Methods

Plant material

Seeds of the brown-seeded Indian (RL-1359) and European (NUDH-YJ-04) Brassica juncea were obtained from the Oilseeds section, Department of Plant Breeding and Genetics, Punjab agricultural University, Ludhiana. From the cross of these two mustard lines, a RIL population was developed upto F6 generation. Leaves and seeds were collected from individual F6 plants and assayed for total glucosinolate and tocopherol concentration. NUDH-YJ-04 is a tall and late flowering European juncea having low glucosinolates and RL-1359 is semi dwarf and early flowering Indian juncea having high glucosinolates.

Glucosinolate estimation

In seeds, glucosinolates have been estimated by NIRS (Near Infrared Reflectance Spectroscopy) following the method of Font et al. [18]. NIRS is a secondary technique which is calibrated against a primary reference method usually a wet laboratory assay. NIRS exploits the fact that many natural products absorbs NIR radiation at specific wavelength (1100-2500 nm) due to absorption of NIR radiation by specific bonds e.g. N-H bonds (proteins), O-H bonds (moisture/sugars) and C-H bonds (organic molecules). Thus a sample’s NIR spectrum will be composite of all the absorbance from all the molecular bonds in the sample. Calibration equations are developed by establishing mathematical relationship between NIR spectra and reference values from wet analysis using chemometric techniques. The dust free intact seeds (about 2 g) of Brassica juncea were packed in a standard ring cup and then scanned.

In Leaves, glucosinolates have been estimated by colorimetry using the method of Kumar et al. [19]. Glucosinolate estimation is based on the formation of a complex between hydrolytic products of glucosinolates and sodium tetrachloropalladate (II) and this complex is then analyzed colorimetrically. This method is rapid as compared to other colorimetric methods. The amount of glucosinolate-palladium complex formed or the rate of its formation is used to determine the quantity of glucosinolates. Seeds were crushed in methanol and centrifuged at 5000 rpm. Sodium tetrachloropalladate was added to the supernatant and glucosinolate content was read at 405 nm in ELISA reader. Total glucosinolate content was calculated using following regression equations:

i. Total glucosinolate conc.( μmol/g) = (O.D405 - 0.046) × 82

ii. Total glucosinolate conc.( μmol/g) = (O.D405 - 0.169) × 115.74

For expectedly low glucosinolates (O.D405 < 0.8) equation (i) is used.

For expectedly high glucosinolates (O.D405 > 0.8) equation (ii) is used.

Tocopherol estimation

Total tocopherol estimation has been done. Seeds were crushed in ethanol following centrifugation at 4000 rpm for 10 min. After adding double distilled water and xylene to supernatant, mixture was again centrifugated at 5000 rpm for 5 min. Xylene layer from the supernatant was carefully pipetted into test tube containing bathophenanthroline reagent, FeCl3 reagent and orthophosphoric acid. Absorbance of test, standard and blank was read at 536 nm against xylene as reference within 30 seconds in UV spectrophotometer (Model 2600). Total tocopherol content was calculated from the standard curve prepared using 2-20 μg of α-tocopherol in absolute ethanol.


Oil content estimation

Oil content estimation has been done following the method of Alexander et al. [20]. Nuclear Magnetic Resonance (NMR) is a non-destructive method and a form of radio frequency spectroscopy which provides accurate counts of hydrogen nuclei in liquid oils even in a surrounding matrix of starch, proteins and other macromolecules. The Newport Analyzer (Model MKIIIA) was standardized with standard sample (4 g seeds with a known oil content) and brought the read out value at the desired oil per cent by operating the instrument at the following conditions: Gate width: 1.5 gs Rf level: 100 μAmp and integration time: 32 sec. Dried seeds of unknown sample (4 g) were weighed and read the value of the oil content. This gave directly the oil percent in seeds. Oil content of the standard sample was estimated by Soxhlet method.

Results and Discussion

Seed glucosinolate variation

Glucosinolates are antinutrional components and the international standards for canola varieties require glucosinolate level to be <30 μmole/g seed. In the RIL population 95 lines along with two parents were screened for total glucosinolates and the range observed was 28.85 to 115.88 μmole/g tissue, with mean value of 69.39 ± 0.26 (Table 1). The frequency distribution of glucosinolates in these 95 lines also showed a near normal distribution (Figure 1). Most of the inbred lines were in the range of 41 to 60 μmole/g seed glucosinolate content (21), 45 had occurred in a range of 61-80 μmole/g seed and 15 had in range of 81-100 μmole/g seed while range of 21-40 and 101-120 showed lesser number of lines i.e., 8 and 7 respectively and it was found that there was no line in 0-20 μmole/g seed. Many authors have reported the seed glucosinolate variation earlier [21,22]. Kumar et al. [19] reported the range of 85-250 μmole/g defatted seed meal.

Tissue RL-1359 NUDH-YJ-04 Range Mean±CV
Glucoinolate Seeds (µmole/g seed) 102.15 53.50 28.85-115.88 69.39±0.26
Glucosinolate Leaves (µmole/g leaf) 86.92 10.17 0.82-102.30 44.18±0.64
Tocopherol Seeds (ppm) 280.76 145.87 32.29-1250 599.60±0.62
Oil seeds (%) 39.87 40.93 34.96-45.00 34.96±0.73

Table 1: Distribution of different biochemical’s in individuals of B. juncea.


Figure 1: Frequency distribution of glucosinolates in seeds of B. juncea individuals.

Leaf glucosinolate variation

In the RIL population range for glucosinolate content in leaves was 0.82-102.30 μmole/g tissue with mean ± CV value of 44.18 ± 0.64. RL-1359 had a high glucosinolate content of 86.92 μmole/g DW leaf and NUDH-YJ-04 had a low glucosinolate content of 10.17 μmole/g DW leaf (Table 1). The frequency distribution of glucosinolate content in these 97 lines showed a discrete distribution (Figure 2). Out of these 97 lines, 29 lines had glucosinolate content in range of 0-25 μmole/g DW leaf tissue, 31 lines had 26-50 μmole/g DW leaf range, 21 genotypes had 51-75 μmole/g DW leaf range, 15 lines had glucosinolates in range of 76-100 μmole/g DW leaf with only single individual in 101-125 μmole/g DW leaf range. Lewis and Fenwick [23] also reported the variation in glucosinolate content in B. oleracea ranging from 42.1-94.5 mg/100 g FW tissue with mean value of 62.3 mg/100 g. Alemayehu and Becker [24] also found significant variation for glucosinolates in leaves of six inbred lines of B. carinata. Hill et al., Bradshaw and Wilson and Krzymanski et al. [25-27] found significant variation among Brassica lines for glucosinolate content. Remarkable variation in glucosinolate content and profiles from different tissues within one plant may reflect different control mechanism operating on the glucosinolate biosynthetic pathway in different tissues or it may simply result from alterations in substrate availability [28]. Since, glucosinolates are known to arise from amino acid precursors [29], a comparative study of glucosinolate and amino acid profiles in different tissues should prove informative. Dynamic changes of glucosinolate levels in any particular tissue also depend upon regulation of de novo biosynthesis, degradation and mobilization of glucosinolates [30], with the capacity for the de novo synthesis varying according to the type of tissue concerned. Moreover, the chemical structure and glucosinolate concentrations in plants vary considerably, depending on the stage of development, tissue type and environmental conditions [11,31], suggesting a storage function for these compounds which are required at specific stages of development [32]. Wide variation in glucosinolate content among genotypes, also suggest differences in their health promoting properties and the opportunity for enhancement of their levels through genetic manipulation [33].


Figure 2: Frequency distribution of glucosinolates in leaves of B. juncea individuals.

Seed tocopherol variation

Tocopherols are important anti-oxidants and variation for its content is reported in table 1. Tocopherols ranged from 32.29 to 1250 ppm with mean ± CV value of 550.20 ± 0.62. Tocopherol content showed a frequency distribution with both the parents lying in the nearby range (Figure 3). 21 lines had tocopherols range from 0-250 ppm, 19 genotypes ranged from 251-500, 25 from 501-750, 18 from 751-1000 and 14 had range from 1001-1250. Richards et al. and Goffman and Becker [15,34] also reported the variation in total tocopherol content in B. napus that may be due to strong influence of environment due to which tocopherol content differ significantly between cultivars. Large variation in tocopherol content may be due to allelic variation at additional loci. Goffman and Becker and Schultz [34,35] reported the occurrence of multiple allele at a limited number of loci that control the tocopherol content. Variability in tocopherol content suggests the potential health benefits that accrue with consumption are genotype dependent. Seker et al. [36] reported the total tocopherol range of 83.9-173.8 ppm for rapeseed varieties. Przybylski and Mag [37] reported that total tocopherols in crude canola oil ranged from 430-2680 ppm. Tocopherols are most powerful natural fat soluble antioxidant which protect the human body from the free radicals that may lead to ageing process and cause some chronic diseases including cancer, cardiovascular diseases, cataract and retard lipid oxidative rancidity in foods as well as enhance the shelf life of oils containing high content of PUFAs [38,39]. Oil extracts with high tocopherol content can be used in application where a high level of antioxidant protection is needed [40]. In rapeseed varieties, total tocopherols markedly increased during maturation stages [41].


Figure 3: Frequency distribution of tocopherols in seeds of B. juncea individuals.

Oil content variation

Seed quality improvement researches in rapeseed-mustard have so far been focused on improving its fatty acid composition to meet the international nutritive norms of oil quality. Oil content ranges from 34.96-45.00% with mean ± CV value of 41.62 ± 0.73. Parents showed 39.87% and 40.93% oil content in RL-1359 and NUDH-YJ-04 respectively (Table 1). The frequency distribution showed a discrete distribution with more genotypes in 37-45% range (Figure 4). There was no individual in 0-9%, 10-18% and 19-27% oil content range while just 2 individuals were in 28-36% and 95 were in 37-45% range. Si et al. [42] also reported significant variation for seed oil concentration in B. napus in the range of 36 to 46%.


Figure 4: Frequency distribution of oil content in seeds of B. juncea individuals.

The wide range in total glucosinolate concentrations found in this study indicates that there is potential for further reduction of glucosinolate levels by screening different accessions. However, additional sources of naturally occurring or induced genetic variation in total glucosinolate content appear to be essential to achieve the Canola standard for Indian mustard. Also such studies are imperative for map based cloning and QTL mapping of key genes associated with the studied traits which inturn can help us in exploring the genetic view of these biochemicals.


We thank Department of Biotechnology, Government of India for funding this work. The present work was the part of the DBT project entitled “Tagging and marker assisted transfer of low glucosinolate trait in B. juncea”.


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