research article genetic variability in glucosinolates in seed...

Research ArticleGenetic Variability in Glucosinolates in Seed of Brassica junceaInterest in Mustard Condiment

Othmane Merah123

1Departement Environnement et Agronomie ENESAD 26 Boulevard Docteur Petitjean BP 87999 21079 Dijon France2Laboratoire de Chimie Agro-Industrielle (LCA) INP-ENSIACET Universite Federale de Toulouse-Midi-Pyrenees118 Route de Narbonne 31030 Toulouse Cedex 4 France3Laboratoire de Chimie Agro-Industrielle (LCA) INRA 31030 Toulouse France

Correspondence should be addressed to Othmane Merah othmanemerahensiacetfr

Received 11 March 2015 Revised 3 June 2015 Accepted 4 June 2015

Academic Editor Patricia Valentao

Copyright copy 2015 Othmane Merah This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Brassica juncea is mostly used for oil production which implies selection of genotypes with low glucosinolates level and high oilcontent In contrast condiment production needs varieties with high level in some glucosinolates including sinigrin The geneticvariability was studied mostly by molecular toolsThe objectives were almost the decrease of glucosinolates level in order to use theoilcake for animal feed The aim of this work is to study the genetic variability for different glucosinolates and their relationshipswith agronomical traits within a large collection of Brassica juncea genotypes for condiment uses A collection of 190 genotypesfrom different origins was studied in Dijon (France) Oil content and total glucosinolates and sinigrin and gluconapin levelswere measured Flowering and maturation durations seed yield and yield components were also measured Large variability wasobserved between genotypes for the measured traits within the studied collection Total glucosinolates varied twofold betweenextreme genotypes Values of sinigrin content varied from 0 to more than 134120583molsdotgminus1 Correlations between glucosinolates traitsand both phenological and agronomical characters are presented and discussed for their potential for industrial condiment uses

1 Introduction

Several studies have demonstrated the influence of nutri-tional factors on the risk of developing cancer Diet com-position is one of the numerous factors that can act toincrease cancer prevention It acts both as a risk factor (foodconsumed in excess promotes the development of cancer)and protection (nutrients or foods known for their protectiveeffect against cancers) A number of studies support thatBrassicaceae species present chemoprevention against cancerforms in humans due to the high levels of glucosinolates [1ndash4]The hydrolysis of glucosinolate generates volatile compoundssuch as isothiocyanates epithionitriles and nitriles Thesemolecules are produced when myrosinase (thioglucosidase)cleaves the thioglycoside linkage of glucosinolates At neutralpH the hydrolysis of glucosinolates results in productionof isothiocyanates and nitriles whereas epithionitriles areformed in the presence of ferrous ions and epithiospecifierproteins [5 6] Recent studies have reported that other

proteins (including PEN2 family 1 glycosyl hydrolase) maycatalyze the hydrolysis of glucosinolates [7ndash9]

Cruciferous plants are edible as vegetables or as oil Brownmustard (Brassica juncea L Czern) is one of the three oilseedBrassica species As it is the case in India and China thebrown mustard is used for oil production which involvedbreeding varieties with low glucosinolates and low erucic acidlevels in grains [10] No information is available concerningthe study of glucosinolate content for industrial condimentproduction Indeed in Burgundy (east of France) mustardis used for the production of the condiment ldquoMoutarde deDijonrdquo In this case some glucosinolates including gluconapin(GNA 3-butenyl Gls) must be present at a low level but con-versely high sinigrin (SIN 2-propenylGls) content is requiredfor its hot taste Following seeds crush in the presence ofwater sinigrin undergoes hydrolysis by a myrosinase releaseallyl isothiocyanate which is a volatile compound responsiblefor the flavour of the mustard condiment

Hindawi Publishing CorporationJournal of ChemistryVolume 2015 Article ID 606142 6 pageshttpdxdoiorg1011552015606142

2 Journal of Chemistry

Table 1Weather conditions recorded fromMarch toAugust in 2002and the mean of twenty last years in Dijon (east of France)

Weather conditions 20 years 2002Rainfall (R mm) 3229 712Evapotranspiration (ET mm) 4557 2460RET 080 029Temperature (∘C) 143 149

Studies of glucosinolate content have concerned rapeseed(by lowering it) broccoli rocket and Diplotaxis green parts(for cancer prevention and nutritional values) brown mus-tard for allelopathic activities and green manure [11ndash13]

Breeders need large variability to initiate selection pro-grams Therefore study of genetic diversity of glucosinolatesin large brown mustard collection would help breeders ingenitors screening in order to achieve high sinigrin levelimprovement However themajority of works donewere per-formed to decrease glucosinolates [14ndash16] and erucic acid orto raise seed oil content [17 18] Other studies usedmolecularmarkers to structure genetic diversity [16 17] Neverthelessthese reports did not help breeders in genotypes choice inorder to perform crosses to manage the glucosinolates levelin seed The few studies which focussed on glucosinolatesevaluation were done on few genotypes or performed ongreen tissues or both [11ndash13] However breeders need to knowthe genetic diversity of glucosinolates for screening genitors

Therefore this study aims to evaluate variability of glu-cosinolates in seeds within a large collection of genotypesfor use inmustard condiment and to investigate relationshipsbetween them and agronomical traits

2 Materials and Methods

21 PlantMaterial and CropManagement Acollection of 190genotypes from different geographic origins were used in thisstudy

Genotypes were cultivated under rainfed conditions inthe experimental field of ENESA (Etablissement NationaldrsquoEnseignement Superieur Agronomique) of Dijon (north-east of France 47∘191015840N and 5∘11015840E) during spring season of2002 A randomized complete block with two replicates pergenotype design was used for the evaluation of the collectionSeeds were sown in two 5m rows per plot (70 cm spacingrow and 5 cm interplant spacing) Intergenotypes spacingwas90 cm The sowing was done at 17 March 2002 Harvest tookplace from 18 to 21 August

22 Weather Conditions Rainfall temperature and evap-otranspiration were obtained from meteorological stationlocalised on the INRA experimental field at Dijon Cumula-tive rainfalls during the cropping season (March to August)were more than four times lower than mean value of rainfallrecorded in the last twenty years for this region (Table 1)However the precipitations were unequally distributedIndeed nearly 72 of the rainfalls occur during the last threemonths of the growing cycle This increase of precipitationswas accompanied with an increase of temperatures which in

turn raises the evaporative demand at the end of the plantcycle

23 Traits Measurements In order to determine floweringand mutation durations dates of beginning and end offlowering as well as maturation were noted The dates ofbeginning (DBF) and end (DEF) of flowering were notedwhen 10 and 90 of plants in each plot flowered Thedate of maturation (DM) was noted when seeds reached ahumidity of 9 The durations of flowering and maturationwere calculated as

flowering duration (FD) = DEFminusDBF

seed filling duration (SFD) = DMminusDEF(1)

At the end of flowering plant height (in cm) was measuredand the number of plants by row and the number of siliquesby row were counted

Atmaturity the number of pods by plant was determinedThe plants were harvested by plot and seeds weighed todetermine seed yield by plot Seed yield by plant (SYP)was then calculated by dividing by the number of plants byplot Thousand seedsrsquo weight (TSW) was also determined byweighing three samples of thousand seeds for each genotypein each plot

Sinigrin (SIN) gluconapin (GNA) and total glucosino-lates (GSL) contents in the seed were directly determined byHPLC (ISO 9167-1method) on samples of 50 g seeds Contentof glucosinolates was expressed in 120583molg of seed

24 Statistical Analyses All data were subjected to analysis ofvariance using GLM procedure of SAS Association betweenmeasured traits was examined using the CORR procedure ofSAS

3 Results

The analysis of variance showed large genotypic variabilityfor the measured traits (Table 2) The mean value of totalglucosinolates within the studied collection was more than103 120583molsdotgminus1 The difference between extreme genotypesfor this trait was twofold (Figure 1) The most importantcomponent of these glucosinolates was SIN which variedfrom 0 to 1342 120583molsdotgminus1 The gluconapin level presented aless large range of variation than for SIN (Figure 1)Themeanvalue of SIN was nearly three times higher than that of GNAOil content increased by more than 16 between extremegenotypes Three groups of genotypes can be distinguishedThe first one is composed of 58 genotypes containing low SIN(less than 30 of total GLS) and high GNA One hundredtwenty four genotypes composed the second group and arecharacterized by high level of SIN Eight other genotypesconstitute a third group with an intermediate level of SINranged from 35 to 65 of total GLS

Large genotypic differences were also observed for theflowering duration (FD) and the seed filling duration (SFD)within the collection (Table 2) Twelve daysrsquo difference for FDwas observed between extreme genotypes These differenceswere more marked for SFD since some genotypes took nearly

Journal of Chemistry 3

Table 2 Mean standard deviation and minimal and maximal values of seed glucosinolates compositions as well as agronomical traitsmeasured on a collection of 190 genotypes Genotypic effect for each trait is also displayed

Trait Mean Standard deviation Minimum Maximum Genotype effectFlowering duration (FD days) 250 22 210 330 lowastlowastlowast

Seed filling duration (SFD days) 467 50 350 630 lowastlowastlowast

Plant height (cm) 1765 260 1050 2300 lowastlowastlowast

Number of seedspod 144 27 31 204 lowastlowast

Thousand seedsrsquo weight (TSW g) 32 09 16 73 lowastlowastlowast

Seed yieldplant (SYP g) 105 26 31 178 lowastlowastlowast

Seed total glucosinolates content (GLS 120583molsdotgminus1) 1033 142 680 1530 lowastlowastlowast

Seed sinigrin content (SIN 120583molsdotgminus1) 730 354 00 1342 lowastlowastlowast

Seed gluconapin content (GNA 120583molsdotgminus1) 270 374 00 1063 mdashOil content ( DM) 413 34 310 474 lowastlowastlowast

lowastlowast and lowastlowastlowast significance at 001 and 0001 probability level respectively

Seed total glucosinolates (120583molmiddotgminus1)60 70 80 90 100 110 120 130 140 150 gt150

Num

ber o

f gen

otyp

es

0

10

20

30

40

50

60

(a)

Seed sinigrin content (120583molmiddotgminus1)

Num

ber o

f gen

otyp

es

0

10

20

30

40

50

0 10 20 30 40 50 60 70 80 90 100 110 120 130 gt130

(b)

Seed gluconapin content (120583molmiddotgminus1)

Num

ber o

f gen

otyp

es

0 10 20 30 40 50 60 70 80 90 100 gt100

0

20

40

60

80

100

120

140

(c)

Figure 1 Distribution of seed total glucosinolates sinigrin and gluconapin values assessed on a collection of 190 genotypes


Table 3 Correlations between seed total glucosinolates sinigrin and gluconapin and agronomical traits measured on a collection of 190genotypes

Trait Seed total glucosinolates Seed sinigrin content Seed gluconapin contentFlowering duration (FD) 007 001 002Seed filling duration (SFD) 032lowastlowastlowast minus055lowastlowastlowast 065lowastlowastlowast

Plant height minus004 073lowastlowastlowast minus071lowastlowastlowast

Number of seedspod minus026lowastlowast minus015 004Thousand seedsrsquo weight (TSW) minus021lowast minus047lowastlowastlowast 052lowastlowast

Seed yieldplant (SYP) minus018lowast minus045lowastlowastlowast 035lowastlowastlowast

Seed total glucosinolates content (GLS) mdash 007 032lowastlowastlowast

Seed sinigrin content (SIN) mdash mdash minus092lowastlowastlowast

lowast lowastlowast and lowastlowastlowast significance at 005 001 and 0001 probability level respectively

twice the time for seed filling compared to others The sametrend was reported for plant height (Table 2) where the tallestgenotypes were twice as high as the shortest ones The mostmarked differences were noticed for TSW number of seedsper pod and SYP for which contrasting genotypes differed bynearly 450 500 and 600 respectively between extremeaccessions

Correlation analysis showed that both total glucosinolatesand GNA were positively related to both SFD and TSW(Table 3) Moreover GNA is correlated positively to SYP andnegatively to plant height and SIN This latter trait is associ-ated negatively with TSW SYP and SFD and positively withplant height A positive correlation was observed betweenSYP and TSW (119903 = 037lowastlowastlowast)

4 Discussion

Large genotypic variability was observed within the studiedcollection for all measured traits The observed values fortotal glucosinolates were similar to those observed by Lion-neton et al [21] within a mapping doubled haploid popula-tion The concentration range of glucosinolates observed inour study was largely higher than those reported in otherstudies for glucosinolate content in mustard seeds [22ndash25]However most of those studies focused on varieties devotedto oil and meal production and thus with low glucosinolatecontents [14 15 17 18]

Detailed analysis of these glucosinolates showed largegenotypic differences for both sinigrin and gluconapin levelsin our collection As previously reported SINwas consistentlydominant over GNA [10 19 20]

The relationships observed between SFD and total glu-cosinolates GNA and SIN mirrored the fact that geno-types which have longer seed filling duration are richer inglucosinolates and in GNA and are poorer in SIN In thesame way heavy seeds seem poorer in SIN according to thenegative correlation observed between TSW and SIN Thissuggests that SIN accumulation in the seeds could occur inthe early phase of maturation and then stop whatever theseed growth and the duration of seed filling are as proposedby biosynthesis pathway of both glucosinolates (Figure 2)Conversely GNA could accumulate in a later phase of seedgrowth taking profit from the long maturation Moreover forgenotypes richest in GNA SIN serves as precursor for GNA

synthesis (Figure 2) This balance could explain the absenceof a significant relationship between total glucosinolate andSIN content On the other hand tall plants are richer in SINand poorer in GNA These interesting correlations were notapproached in other works and the biological explanationsof these correlations need further investigations Howeverwe can assume that the association between plant heightand seed SIN resulted from the positive relationship betweenvegetative biomass (not measured here) and plant heightnoticed in other studies [24 25] Previous reports showed thatseed SIN is positively related to green tissue SIN level [19 2023ndash26] suggesting that a part of seed sinigrin was providedby translocation from green tissues This is confirmed by thedetailed study of Zukalova et al [20] showing that duringgrowth SIN decreases in the vegetative parts of the plantwhile it increases in the generative ones According to theseauthors this result proves unambiguously that pod SIN istransported into seeds One can then assume that transport ofSIN from the green parts to the pods and then to the seeds cancontinue as long as these organs are alive and progressivelystop when they senesce SIN accumulation would thendecrease when the leaves turn yellow and stop when they fallConversely GNA would continue to accumulate after leaffall by using a different process [18]

Broad genotypic differences were also observed for agro-nomical traits Similar values were reported in Chinese andIndian brown mustard collections [14] These authors alsoshowed that TSW is the most important yield componentOur study also pointed out the role of TSW since thecorrelation with yield is significantly positive Other workshave reported similar associations between yield and yieldcomponents [10 24 25]

5 Conclusion

Our results provide evidence for large genotypic variabilitywithin the studied brown mustard collection mostly forglucosinolates and sinigrin levels in seedsThese results are ofinterest for industrial uses Indeed breeders need to combineagronomic and nutritional traits in the same genotypes Someintriguing correlations between different glucosinolates andagronomic traits need to be more thoroughly investigatedMoreover relationships between glucosinolates profiles inseed and different green organs would help to increase our


Methionine Homomethionine Dihomomethionine Trihomomethionine

Methylthiopropyl Methylthiobutyl Methylthiopentyl

Methylsulphinylpropyl Methylsulphinylbutyl Methylsulphinylpentyl

Methylsulphinylpropyl Butenyl Pentenyl

Hydroxybutenyl HydroxypentenylHydroxybutenyl Propenyl

GSL-ELONG GSL-ELONG

GSL-PRO

cytP450 cytP450 cytP450

GSL-OX GSL-OX GSL-OX

GSL-ALK GSL-ALK GSL-ALK

GSL-ALKGSL-OHP GSL-OH GSL-OH

Chain elongation

Skeletonformation

Chain modification

Figure 2 Simplified model of the biosynthesis pathway of aliphatic glucosinolate in Brassica [19 20]

knowledge and would help our understanding of the biolog-ical relationships between these traits Moreover industrialproduction requires seeds with high sinigrin content (80ndash100 120583molsdotgminus1) and high seed yield This objective could beeasily achieved by combining both traits in new selectedgenotypes Some studied genotypes showed high levels ofglucosinolates and SIN and could be used for mustardcondiment or for experiments or to be introduced in breedingprograms for improvement of glucosinolates level in generaland SIN content in particular

Conflict of Interests

The author declares that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

The author is grateful to Thierry Guinet for technical helpduring experimentation

References

[1] M Bjorkman I Klingen A N E Birch et al ldquoPhytochem-icals of Brassicaceae in plant protection and human healthmdashinfluences of climate environment and agronomic practicerdquoPhytochemistry vol 72 no 7 pp 538ndash556 2011

[2] B Abbaoui K M Riedl R A Ralston et al ldquoInhibitionof bladder cancer by broccoli isothiocyanates sulforaphaneand erucin characterizationmetabolism and interconversionrdquoMolecular Nutrition and Food Research vol 56 no 11 pp 1675ndash1687 2012

[3] N H Kadir J T Rossiter and N J Gooderham ldquoThe chemo-preventive properties of cruciferous vegetables is oxidativestress in cancer cell cytotoxicity induced by glucosinolatehydrolysis productsrdquo Toxicology vol 290 no 2-3 pp 118ndash1192011

[4] K Sakao S Desineni E-R Hahm and S V Singh ldquoPhenethylisothiocyanate suppresses inhibitor of apoptosis family proteinexpression in prostate cancer cells in culture and in vivordquo TheProstate vol 72 no 10 pp 1104ndash1116 2012

[5] E Penas R I Limon C Vidal-Valverde and J Frias ldquoEffect ofstorage on the content of indole-glucosinolate breakdown prod-ucts and vitamin C of sauerkrauts treated by high hydrostaticpressurerdquo LWTmdashFood Science and Technology vol 53 no 1 pp285ndash289 2013

[6] Z-Y Li Y Wang W-T Shen and P Zhou ldquoContent determi-nation of benzyl glucosinolate and anti-cancer activity of itshydrolysis product in Carica papaya Lrdquo Asian Pacific Journalof Tropical Medicine vol 5 no 3 pp 231ndash233 2012

[7] Z Zhao W Zhang B A Stanley and S M Assmann ldquoFunc-tional proteomics of Arabidopsis thaliana guard cells uncoversnew stomatal signaling pathwaysrdquoThe Plant Cell vol 20 no 12pp 3210ndash3226 2008

[8] P BednarekM Pislewska-Bednarek A Svatos et al ldquoA glucosi-nolate metabolism pathway in living plant cells mediates broad-spectrum antifungal defenserdquo Science vol 323 no 5910 pp 101ndash106 2009

[9] N K Clay AMAdio C Denoux G Jander and FMAusubelldquoGlucosinolate metabolites required for an Arabidopsis innateimmune responserdquo Science vol 323 no 5910 pp 95ndash101 2009

[10] E Lionneton G Aubert S Ochatt and O Merah ldquoGeneticanalysis of agronomic and quality traits in mustard (Brassicajuncea)rdquo Theoretical and Applied Genetics vol 109 no 4 pp792ndash799 2004

[11] M Handiseni J Brown R Zemetra andMMazzola ldquoEffect ofBrassicaceae seed meals with different glucosinolate profiles onRhizoctonia root rot in wheatrdquo Crop Protection vol 48 pp 1ndash52013

[12] L C Ascencion W Liang and T Yen ldquoControl of Rhizoctoniasolani damping-off disease after soil amendment with drytissues of Brassica results from increase in Actinomycetespopulationrdquo Biological Control vol 82 pp 21ndash30 2015


[13] L Bell M J Oruna-Concha and C Wagstaff ldquoIdentificationand quantification of glucosinolate and flavonol compoundsin rocket salad (Eruca sativa Eruca vesicaria and Diplotaxistenuifolia) by LCndashMS highlighting the potential for improvingnutritional value of rocket cropsrdquo Food Chemistry vol 172 pp852ndash861 2015

[14] J S ChauhanMK Tyagi S Kumar P Tyagi N B Singh and SK Yadav ldquoDevelopment selection and characterization of lowerucic acid low glucosinolates lines in Indianmustard (Brassicajuncea L)rdquo in Proceedings of the 11th International RapeseedCongress 2002

[15] Y S Sodhi A Mukhopadhyay N Arumugam et al ldquoGeneticanalysis of total glucosinolate in crosses involving a highglucosinolate Indian variety and a low glucosinolate line ofBrassica junceardquoPlant Breeding vol 121 no 6 pp 508ndash511 2002

[16] R Augustine A Mukhopadhyay and N C Bisht ldquoTargetedsilencing of BjMYB28 transcription factor gene directs develop-ment of low glucosinolate lines in oilseed Brassica junceardquo PlantBiotechnology Journal vol 11 no 7 pp 855ndash866 2013

[17] A Agnihotri and N Kaushik ldquoTowards nutritional qualityimprovement in Indian mustard (Brassica juncea [L] Czernand Cross) var Pusa Boldrdquo in Proceedings of the 11th Interna-tional Rapeseed Congress pp 501ndash503 Copenhagen DenmarkJuly 2003

[18] V Beniwal H Aggarwal A Kumar and V Chhokar ldquoLipidcontent and fatty acid change in the developing silique wallof mustard (Brassica juncea L)rdquo Biocatalysis and AgriculturalBiotechnology vol 4 no 1 pp 122ndash125 2015

[19] N Rangkadilok M E Nicolas R N Bennett R R PremierD R Eagling and P W J Taylor ldquoDevelopmental changes ofsinigrin and glucoraphanin in three Brassica species (BrassicanigraBrassica juncea andBrassica oleracea var italica)rdquo ScientiaHorticulturae vol 96 no 1ndash4 pp 11ndash26 2002

[20] H Zukalova J Vasak D Nerad and P Stranc ldquoThe role ofglucosinolates of Brassica genus in the crop systemrdquo RostlinnaVyroba vol 48 no 4 pp 181ndash189 2002

[21] E Lionneton G Aubert S Ochatt and O Merah ldquoCandidategene approach and QTL mapping identified loci involved inglucosinolate biosynthesis in brown mustardrdquo Agroindustriavol 3 no 1 pp 343ndash345 2004

[22] F C Ogbonnaya G Halloran E Pang and N Gororo ldquoMolec-ular analysis of genetic diversity in Brassica juncea and B nigragermplasm accessionsrdquo in Proceedings of the 11th InternationalRapeseed Congress pp 489ndash491 Copenhagen Denmark July2003

[23] K Juerges and W Thies ldquoQuantitative analysis of the indoleglucosinolates content in seeds and leaves of Brassica napus andBrassica campestrisrdquo Zeitschrift fur Pflanzenzuchtung vol 84pp 168ndash178 1980

[24] K Das P K Barua and G N Hazarika ldquoGenetic variabilityand correlation in Indian mustardrdquo Journal of the AgriculturalScience Society of North-East India vol 11 pp 262ndash264 1998

[25] H R Mahla S J Jambhulkar D K Yadav and R SharmaldquoGenetic variability correlation and path analysis in Indianmustard [(Brassica juncea (L)]rdquo Indian Journal of Genetics andPlant Breeding vol 63 pp 171ndash172 2003

[26] Y J Xu L Zhu M G Sun M Z Gian and F R ChenldquoGlucosinolate content of the rape plant and organs in variousgrowing periods and its early predictionrdquo Acta AgronomicaSinica vol 9 pp 107ndash116 1983

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Advances in

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Hindawi Publishing Corporationhttpwwwhindawicom

Analytical Methods in Chemistry

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Volume 2014

Bioinorganic Chemistry and ApplicationsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

SpectroscopyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Medicinal ChemistryInternational Journal of


Chromatography Research International


Applied ChemistryJournal of



Theoretical ChemistryJournal of


Journal of

Spectroscopy

Analytical ChemistryInternational Journal of


Journal of


Quantum Chemistry


Organic Chemistry International

ElectrochemistryInternational Journal of



CatalystsJournal of


Table 1Weather conditions recorded fromMarch toAugust in 2002and the mean of twenty last years in Dijon (east of France)

Weather conditions 20 years 2002Rainfall (R mm) 3229 712Evapotranspiration (ET mm) 4557 2460RET 080 029Temperature (∘C) 143 149

Studies of glucosinolate content have concerned rapeseed(by lowering it) broccoli rocket and Diplotaxis green parts(for cancer prevention and nutritional values) brown mus-tard for allelopathic activities and green manure [11ndash13]

Breeders need large variability to initiate selection pro-grams Therefore study of genetic diversity of glucosinolatesin large brown mustard collection would help breeders ingenitors screening in order to achieve high sinigrin levelimprovement However themajority of works donewere per-formed to decrease glucosinolates [14ndash16] and erucic acid orto raise seed oil content [17 18] Other studies usedmolecularmarkers to structure genetic diversity [16 17] Neverthelessthese reports did not help breeders in genotypes choice inorder to perform crosses to manage the glucosinolates levelin seed The few studies which focussed on glucosinolatesevaluation were done on few genotypes or performed ongreen tissues or both [11ndash13] However breeders need to knowthe genetic diversity of glucosinolates for screening genitors

Therefore this study aims to evaluate variability of glu-cosinolates in seeds within a large collection of genotypesfor use inmustard condiment and to investigate relationshipsbetween them and agronomical traits

2 Materials and Methods

21 PlantMaterial and CropManagement Acollection of 190genotypes from different geographic origins were used in thisstudy

Genotypes were cultivated under rainfed conditions inthe experimental field of ENESA (Etablissement NationaldrsquoEnseignement Superieur Agronomique) of Dijon (north-east of France 47∘191015840N and 5∘11015840E) during spring season of2002 A randomized complete block with two replicates pergenotype design was used for the evaluation of the collectionSeeds were sown in two 5m rows per plot (70 cm spacingrow and 5 cm interplant spacing) Intergenotypes spacingwas90 cm The sowing was done at 17 March 2002 Harvest tookplace from 18 to 21 August

22 Weather Conditions Rainfall temperature and evap-otranspiration were obtained from meteorological stationlocalised on the INRA experimental field at Dijon Cumula-tive rainfalls during the cropping season (March to August)were more than four times lower than mean value of rainfallrecorded in the last twenty years for this region (Table 1)However the precipitations were unequally distributedIndeed nearly 72 of the rainfalls occur during the last threemonths of the growing cycle This increase of precipitationswas accompanied with an increase of temperatures which in

turn raises the evaporative demand at the end of the plantcycle

23 Traits Measurements In order to determine floweringand mutation durations dates of beginning and end offlowering as well as maturation were noted The dates ofbeginning (DBF) and end (DEF) of flowering were notedwhen 10 and 90 of plants in each plot flowered Thedate of maturation (DM) was noted when seeds reached ahumidity of 9 The durations of flowering and maturationwere calculated as

flowering duration (FD) = DEFminusDBF

seed filling duration (SFD) = DMminusDEF(1)

At the end of flowering plant height (in cm) was measuredand the number of plants by row and the number of siliquesby row were counted

Atmaturity the number of pods by plant was determinedThe plants were harvested by plot and seeds weighed todetermine seed yield by plot Seed yield by plant (SYP)was then calculated by dividing by the number of plants byplot Thousand seedsrsquo weight (TSW) was also determined byweighing three samples of thousand seeds for each genotypein each plot

Sinigrin (SIN) gluconapin (GNA) and total glucosino-lates (GSL) contents in the seed were directly determined byHPLC (ISO 9167-1method) on samples of 50 g seeds Contentof glucosinolates was expressed in 120583molg of seed

24 Statistical Analyses All data were subjected to analysis ofvariance using GLM procedure of SAS Association betweenmeasured traits was examined using the CORR procedure ofSAS

3 Results

The analysis of variance showed large genotypic variabilityfor the measured traits (Table 2) The mean value of totalglucosinolates within the studied collection was more than103 120583molsdotgminus1 The difference between extreme genotypesfor this trait was twofold (Figure 1) The most importantcomponent of these glucosinolates was SIN which variedfrom 0 to 1342 120583molsdotgminus1 The gluconapin level presented aless large range of variation than for SIN (Figure 1)Themeanvalue of SIN was nearly three times higher than that of GNAOil content increased by more than 16 between extremegenotypes Three groups of genotypes can be distinguishedThe first one is composed of 58 genotypes containing low SIN(less than 30 of total GLS) and high GNA One hundredtwenty four genotypes composed the second group and arecharacterized by high level of SIN Eight other genotypesconstitute a third group with an intermediate level of SINranged from 35 to 65 of total GLS

Large genotypic differences were also observed for theflowering duration (FD) and the seed filling duration (SFD)within the collection (Table 2) Twelve daysrsquo difference for FDwas observed between extreme genotypes These differenceswere more marked for SFD since some genotypes took nearly














Num

ber o

f gen

otyp

es

0

10

20

30

40

50

60

(a)


Num

ber o

f gen

otyp

es

0

10

20

30

40

50

0 10 20 30 40 50 60 70 80 90 100 110 120 130 gt130

(b)


Num

ber o

f gen

otyp

es

0 10 20 30 40 50 60 70 80 90 100 gt100

0

20

40

60

80

100

120

140

(c)













4 Discussion






5 Conclusion








GSL-ELONG GSL-ELONG

GSL-PRO





Chain elongation

Skeletonformation

Chain modification





Acknowledgment


References





































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of














Num

ber o

f gen

otyp

es

0

10

20

30

40

50

60

(a)


Num

ber o

f gen

otyp

es

0

10

20

30

40

50

0 10 20 30 40 50 60 70 80 90 100 110 120 130 gt130

(b)


Num

ber o

f gen

otyp

es

0 10 20 30 40 50 60 70 80 90 100 gt100

0

20

40

60

80

100

120

140

(c)













4 Discussion






5 Conclusion








GSL-ELONG GSL-ELONG

GSL-PRO





Chain elongation

Skeletonformation

Chain modification





Acknowledgment


References





































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of












4 Discussion






5 Conclusion








GSL-ELONG GSL-ELONG

GSL-PRO





Chain elongation

Skeletonformation

Chain modification





Acknowledgment


References





































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of







GSL-ELONG GSL-ELONG

GSL-PRO





Chain elongation

Skeletonformation

Chain modification





Acknowledgment


References





































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

























Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

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