Directory UMM :Data Elmu:jurnal:E:European Journal of Agronomy:Vol13.Issue1.Jul2000:

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Environmental effects on the quality of two wheat

genotypes: 1. quantitative and qualitative variation of

storage proteins

E. Triboi

_{*, A. Abad}

_{, A. Michelena}

_{, J. Lloveras}

_{, J.L. Ollier}

_{, C. Daniel}

a_{Station d}_’_{Agronomie INRA}_,₁₂_A

6enue du Bre´zet,63039Clermont-Ferrand,France

b_Uni

6ersitat de Lleida-IRTA,Alcalde Ro6ira Roure177,25198Lleida,Spain

Received 8 June 1999; received in revised form 19 January 2000; accepted 14 April 2000

Abstract

A new method of sequential extraction of proteins followed by quantitative and qualitative determination by reverse-phased high-performance liquid chromatography (RP-HPLC) was used to analyse the effect of environmental conditions (3N fertilisation rates, two varieties, two sites and two growing seasons) on quantitative and qualitative variation of wheat storage proteins. The results showed thatNsupply (fertilisation and site) was the most important environmental factor affecting protein content and composition. The most important effect was quantitative: the total protein, protein unit and subunit contents increased with the supply of nitrogen to the grain. As grain protein increased, the gliadin and glutenin contents and the gliadin to glutenin ratio increased. Gliadin showed a higher correlation with total protein content than glutenin. In the variety Rinconada, glutenin content was higher than that in Bancal. As total glutenin increased, both high and low-molecular weight (HMW and LMW) fractions increased and their ratio (HMW/LMW) did not change significantly, despite a slope of LMW subunits two times greater (0.69) than that of HMW fractions (0.31). The quantity of each HMW subunit (RP-HPLC peak) increased with total HMW-glutenin, but their relative percentage increased for some peaks and decreased for others. The composition of the HMW subunit was more stable in Bancal than in Rinconada. This general pattern of variation was also characteristic of the LMW subunit. Concerning gliadin composition we noted that the content of different gliadin monomers (RP-HPLC peaks) or pools of monomers (a-, b-,g-,v-gliadin) increased with total gliadin content. The proportion of certain peaks was stable whereas the contribution of other peaks was related to the variation in gliadin content and depended on the variety. © 2000 Elsevier Science B.V. All rights reserved.

Keywords:Environment; Protein composition; Gliadin composition; Glutenin composition

www.elsevier.com/locate/eja

Abbre6iations:HMW-GS, high molecular weight glutenins; LMW-GS, low molecular weight glutenins; PC, protein content (%);

QNG, quantity of N per grain (mg N grain−1_).

* Corresponding author. Tel.: +33-473-624424; fax: +33-473-624457. E-mail address:triboi@clermont.inra.fr (E. Triboi).

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 48

1. Introduction

Wheat protein content and baking quality, highly depend on genotypic and environmental factors and it is recognised that variation in protein content and composition significantly modify wheat quality. (Rousset et al., 1985; Bietz, 1988; Borghi et al., 1995).

Many studies have been conducted in an at-tempt to explain wheat quality variation as a function of genetic variation in protein composi-tion. The major storage proteins in wheat are the gliadins and glutenins. Gliadins are subdivided into a, b, g and v units and glutenins into low and high molecular weight (LMW-GS and HMW-GS). The genetic control and the relation-ships between gluten protein composition and quality characteristics are better and better under-stood (Shewry et al., 1989; Colot, 1990; Halford et al., 1992; Gupta and MacRitchie, 1994; Popineau et al., 1994; Weegels et al., 1996; Fido et al., 1997; Martinant et al., 1998; Metakovsky and Branlard, 1998).

With regard to environmental effects several previous studies reported, at different levels of investigation, some variations in protein composition:

the amino-acids composition (g aa/100 g proteins) varies with the N content of the grain (Mosse et al., 1985; Triboi et al., 1990; Bulman et al., 1994; Boila et al., 1995);

the quantity of N and S in the grain increases with N content, but the N/S ratio decreases: this reflects a change in the ratio between protein with lower sulphur content such as certain gliadins and higher sulphur proteins such as glutenins (Byers and Bolton, 1979; Triboi et al., 1990; MacRitchie and Gupta, 1993);

the gliadin/glutenin ratio increases with the quantity of N in the grain (Terce-Laforque and Pernollet, 1982; Triboi et al., 1990; Triboi and Leblevenec, 1995);

the concentration of some gliadin bands, mea-sured by electrophoresis and densitometry, changes with the variation in N supply to the grain (Brandlard and Triboı¨, 1983).

Progress in analytical technology and particu-larly in RP- and SE-HPLC has enabled a better understanding of the effects of protein composi-tion (Marchylo et al., 1989; Lookhart, 1997). As electrophoresis, HPLC not only separates differ-ent gliadin and glutenin subunits but also quantifies individual or pooled subunits. How-ever, this technique has been used in few studies and quantitative determination of protein units and subunits and their relationships with quality have seldom been described (Marchylo et al., 1989; Seilmeier et al., 1990; Sutton et al., 1990; Kolster et al., 1991; Sutton, 1991; Wiesser et al., 1994). Subsequently, the quantitative changes can be accompanied by qualitative changes reflected in the ratios between different components (Triboi and Triboı¨-Blondel, 1998; Daniel et al., 1998a,b). Changes in the ratios between different protein units and subunits have rarely been signalled, and the effects on the technological properties have often not been established.

Generally, two aspects can be considered in the research on environmental effects:

1. the change in grain composition and particu-larly in the quantity and quality of proteins; 2. the relationship between protein changes and

quality parameters.

This paper deals with the first aspect: the effect of environmental conditions (N fertilisation rate, site and growing season) on the quantitative and qualitative variation of wheat glutenin and gliadin units and subunits. A new method of sequential extraction of proteins followed by quantitative determination by RP-HPLC was performed in order to analyse the qualitative changes induced by quantitative variations and to establish the relationships between different protein units and subunits for modelling purposes.

2. Materials and methods 2.1. Field experiments

Bancal and Rinconada bread wheat varieties were grown in irrigated plots of Typic Xerofluvent soils at two sites of the Ebro Valley (Torregrossa and Bell.lloc; Spain) during two growing seasons

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(1994 – 1995 and 1995 – 1996). The soil at Bell.lloc was a deep silty-clay-loam with a high N content and 2.9% organic matter. The soil at Torregrossa was a sandy-loam with a low N content and 1.9% organic matter. Surface irrigation was applied from stem extension (stage 31 Zadoks) until the formation of kernels (Zadoks 70), three times during the growing season with an approximate total of 2000 m3_/_{h. Rinconada and Bancal are}

alternative types of wheat without need for ver-nalisation. The HMW-GS composition is 1, 7+8, 5+10 for Rinconada and 7+9, 5+10 for Bancal.

The experimental design was a split-plot ran-domised complete-block with four replicates. The main plots consisted of wheat cultivars, while the subplots were subjected to three N fertilisation treatments, 0, 100 and 200 kg/ha. Only two field replicates were used in this study, hence 48 sam-ples (two replicates, three N, two varieties, two sites, two years) were analysed for protein composition.

2.2. Sequential extraction of protein

The sequential extraction of protein of whole grain flour was used (Marion et al., 1994; Nicolas et al., 1997). Albumin-globulin was extracted from 833 mg of ground wheat with 25 ml buffer A (0.05 M sodium phosphate pH 7.8, 0.05 M NaCl) for 1 h at 4°C. Samples were centrifuged at 18 000 rpm for 20 min at 4°C. Amphyphilic proteins were extracted from the previous residue with 25 ml of 2% (w/v) Triton X-114 in buffer A, for 1 h at 4°C. After centrifugation (18 000 rpm for 20 min at 4°C), gliadin was extracted from the residue with 25 ml of 70% (v/v) aqueous ethanol for 1 h at 20°C. To obtain glutenin, after centrifu-gation the residue was extracted overnight with 25 ml of buffer B (0.05 M di-sodium tetraborate pH 8.5, 2% (v/v) b-mercaptoethanol, 8 M urea and 1 g/l glicyne) at 20°C. Samples were centrifuged at 18 000 rpm for 20 min. An amount of 3.5 ml of the supernatant was alkylated with 4-vinylpyridine. After alkylation, 3.5 ml of 2-propanol was used to precipitate polysaccharides. Samples were centrifuged at 18 000 rpm for 20 min. Glutenin was in the supernatant.

2.3. RP-HPLC of gliadin and glutenin

The gliadin and glutenin composition of the supernatants was analysed by RP-HPLC Kontron 422/425 system, with a Nucleosil C18 column (300 A, , 5 mm, 30 nm, 250×4.6 mm) at 50°C with a C18 gard column (300 A, , 410 mm).

Two eluants were used: (A) water containing 60% (v/v) acetonitrile and 0.07% (v/v) trifl-uoroacetic acid (TFA); (B) water containing 0.1% (v/v) TFA.

For the gliadin analysis the gradient was: 0 – 1.22 min — 41.7% (A), 8 min — 46.2% (A), 65 min — 83.0% (A), 69 min — 100% (A). The glutenin gradient was: 0 – 6 min — 41.7% (A); 46 min — 66.7% (A); 66 min — 91.7% (A); 67 min — 100% (A). For both analyses, the flow rate was 1.0 ml/min and the injection volume was 75 ml. Detection was at 220 nm with Shimadzu SPD6A. Each class of glutenin was quantified by inte-gration of chromatogram areas, between 29 and 36% of acetonitrile for HMW-GS and between 36 and 51% for LMW-GS. Kontron data system 450-MT2 software was used to integrate the chro-matograms, which were standardised and whose peaks were numbered as shown in Figs. 1 and 2. For each subunit and peak, protein content was expressed as the amount (area, mV/min) per mg of flour or as a proportion (%) of the total gliadin and glutenin unit and subunit area. Total glutenin and gliadin were calculated as the total chro-matogram area (mV/min) per mg of flour.

3. Results

3.1. Grain weight (GW), protein content (% PC) and quantity per grain (QNG)

GW have a coefficient of variation (CV) of 8% (Table 1). N fertilisation (N) was the main factor of variation. An increase in N fertilisation rate significantly reduced grain weight from 47.3 mg/

grain without N to 43.5 mg/grain. Year (Y) and site (S) did not significantly affect grain weight, but the interactions Y*S and Y*N were significant.

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Triboi

Europ

Agronomy

(2000)

–

Table 1

Environmental effect on grain weight, total and storage protein contenta

Grain weight _{Mg N}_/_grain Protein (%) Gliadin areab _{Glutenin area}b _Ratios

(mg)

Gliadin protein Glutenin/protein Gliadin/glutenin

Variety(V)

236 a 15.0 a 16.2 a

46.2 a 1189 a 0.94 a

Bancal 14.7 a 223 a

293 b 13.7 b 18.8 b

Rinconada 44.3 a 1195 a 15.5 b 216 a 0.74 b

Site(S)

291 a 15.6 a 17.9 a

44.5 a 1278 a 0.89 a

Bell.lloc 16.2 a 254 a

185 b 241 b 13.1 b 17.1 a 0.80 b

45.7 a 1107 b 13.9 b Torregrossa

Year(Y)

15.2 a 215 a 248 a 13.9 a 16.0 a 0.87 a

44.5 a

1995 1171 a

283 b 14.8 a 18.9 b 0.81 a

224 a 46.2 a

1996 1214 a 15.0 a

N(kgN/ha)

230 a 12.9 a 16.0 a 0.83 a

0 47.3 a 1172 a 14.7 a 187 a

269 b 14.8 a 17.8 ab 0.86 a

225 b

100 45.3 ab 1180 a 14.9 a

246 b 299 b 12.9 a 18.6 b 0.84 a

43.5 b 1225 a 16.1 b 200

Significance of single interactions

** **

S*Y

** ** ** *

S*N **

Y*N ** *

S*V

* **

Y*V

N*V * *

8.9 8.1 8.7 13.3

9.6

8.0 10.7 3.3

CV (%)

a_{Means in the same column followed by the same letter are not significantly different are}_P_B_0.05.

* Significant atPB0.05. ** Significant at 0.01.

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Variation in the quantity of N per grain (QNG, mg N/grain) was higher than that of grain weight (CV, 10.7%). The QNG depended significantly on the site, with an average of 1278 mg/grain at Bell.lloc and 1107mg at Torregrossa, confirming a

higher soil N supply at Bell.lloc. However, there was a significant interaction between site and N fertilisation, possibly resulting from the higher soil N content at Bell.lloc that reduced the re-sponse of N grain content to N fertilisation.

De-Fig. 1. RP-HPLC of Bancal and Rinconada glutenin. Numbers in chromatogram are peak designation. Peaks eluted before 45 min are HMW, while those eluted after are LMW-glutenin.

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 52

Fig. 2. RP-HPLC of Bancal and Rinconada gliadin. Numbers in chromatogram are peak designation.

spite the fact that the most important factors of variation were different for the two variables (site for QNG and nitrogen for GW), they were not totally independent because the coefficient of vari-ation of their ratio, i.e. protein content (PC%), was smaller (only 3.3%) (Table 1). PC was mainly affected by site and N fertilisation (63% of total

variation). Wheat variety accounted only for 4% of total variation and growing season did not significantly affect PC. The effect of N fertilisa-tion on PC differed between sites since there was no response in Bell.lloc, possibly due to its ini-tially high soil N contents (data not shown) and where the average protein content was already

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very high in the absence of N fertilisation, i.e. 16.4%.

3.2. Gliadin and glutenin content in the flour and in total protein

Gliadin content in the flour was affected only by site (+37% at Bell.lloc) and by N fertilisation

(+32% at 200 N) but not by variety and year (Table 1). These two factors explained 52% of the total variance. Moreover, a significant interaction between site and N fertilisation was observed. At Torregrossa, gliadin content increased by about 80% as a consequence of N fertilisation whereas at Bell.lloc the increase was of about 20%.

In contrast, glutenin content was significantly affected not only by site (+21% at Bell.lloc) and N fertilisation (+30% at 200 N) but also by year (+14% in 1996) and variety (+24% in Rinconada). Several significant interactions be-tween factors were obtained (Table 1). At Torre-grossa, glutenin content was higher in 1995 – 1996 than in 1994 – 1995, whereas no differences were observed at Bell.lloc between glutenin content in the two growing seasons (S*Y interaction). In Rinconada, wheat glutenin content was higher in 1994 – 1995 than in 1995 – 1996, whereas no differ-ences were observed at Bancal. (Y*V interaction). Despite the large variation in gliadin and glutenin contents in flour, their ratio was rela-tively constant. The variety was the main factor of variation: the mean of this ratio was 0.94 for Bancal and 0.74 for Rinconada. This is in agree-ment with several studies (Kolster et al., 1991; Pechanek et al., 1997). However there are also a site effect (Bell.loc 0.89, Torregrossa 0.80) but smaller that variety.

Concerning protein composition, variety and N fertilisation were the main factors affecting both the gliadin to total protein and glutenin to total protein ratios. The year, alone or in interaction with site or variety, was significant only for the glutenin content in total protein. Thus, glutenin seems to be more environmentally dependent than gliadin.

All the modifications in gliadin and glutenin contents of flour were related to total protein content. The coefficients of determination were higher for gliadin than for glutenin (Fig. 3). This is in agreement with previous studies (Gupta et al., 1992), although other authors (Andrews et al., 1994) reported a better correlation with glutenin. To take into consideration only nitrogen accu-mulation and to eliminate the effect of C accumu-lation on N percentage, we calculated the quantity of gliadin, glutenin and total protein per grain. Fig. 3. Amount of gliadin (A) and glutenins in flour (B) as a

function of grain protein content (%) in two bread wheat varieties (Bandal and Rinconada). Data consist of means of two sites (Torregrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N-fertilization rates (0, 100 and 200 kg N/ha). Units of area are mV/min. The number of observations was 24 for each regression.

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 54

Fig. 4. Amount of gliadins (A) and glutenins in flour (B) as a function of grain N content (mg N/grain) in two bread wheat varieties (Bancal and Rinconada). Data consist of means of two sites (Torregrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 kg N/ha). Units of area are mV/min. The number of observations was 24 for each regression.

protein content, the percentage of glutenin did not. In the present study, both the proportion of gliadin and glutenin in total protein increased with increasing total protein content (R2_{, 0.64 and} R2_{, 0.40} _P_B_{0.01 respectively, data not shown).}

The increase in the proportion of gliadin and glutenin was probably related to the decrease in the non-storage protein fraction as shown by Gupta et al., (1992), Jia et al., (1996b). Finally, the gliadin to glutenin ratio, reflecting a qualita-tive change in protein composition, increased with N content per grain (Fig. 5), suggesting that as N accumulation increased, gliadin increased prefer-entially to glutenin.

3.3. Analysis of glutenin composition

Chromatograms of glutenin in Bancal (A) and Rinconada (B) are presented in Fig. 1. The peak areas that were used to determine HMW- and LMW-GS are indicated as well as the name given for every peak. HMW- and LMW-GS content and the HMW/LMW-GS ratio are presented in Table 2.

Fig. 5. The gliadin/glutenin ratio as a function of grain N content (mg N/grain) in two bread wheat varieties (Bancal and Rinconada). Data consist of means of two sites (Torregrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 Kg N/ha). The number of observations was 24 for each regression.

The N content of grain (as well as protein con-tent) also showed a significant linear relationship with the gliadin and glutenin contents, however gliadin was better correlated with the N content of grain than glutenin (Fig. 4).

Protein composition, expressed as gliadin to total protein and glutenin to total protein ratios also changed with protein content. Previous stud-ies (Brandlard and Triboı¨, 1983; Gupta et al., 1992) reported that while the percentage of gliadin in total protein increased with the flour

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Table 2

Environmental effect on glutenin subunit contenta

LMWb _HMW_/_LMW _HMW_/_protein _LMW_/_protein

HMWb

Variety(V)

85 a

Bancal 154 a 0.55 a 5.7 a 10.4 a

191 b 0.56 a 6.5 b

102 b 12.3 b

Rinconada Site(S)

187 a 0.56 a

104 a 6.4 a

Bell.lloc 11.5 a

158 b

Torregrossa 83 b 0.56 a 5.9 b 11.2 a

Year(Y)

157 a 0.61 a 5.9 a 10.1 a

1994–1995 91 a

188 b 0.51 a

96 a 6.4 b

1995–1996 12.5 b

N (kg N/ha)

149 a 0.59 a

81 a 5.7 a

0 10.4 a

176 b 0.53 a

100 92 a 6.1 ab 11.7 b

193 b 0.56 a

107 b 6.6 b

200 11.9 b

Significance of single interactions

S*Y ** * **

S*N * * *

Y*N *

S*V

** **

Y*V **

N*V * * *

9.7 11.9 9.9

CV (%) 10.2 9.4

a_{Means in the same column followed by the same letter are not significantly different are}_P_B_{0.05. CV, coefficient of variation.} b_{Area (mV}

min/mg flour) of high (HMW) and low (LMW) molecular weight glutenin.

* Significant atPB0.05. ** Significant at 0.01.

Like glutenin content, the HMW and LMW glutenin content in flour was significantly affected by variety, site and N fertilisation. The year and its interaction with variety (Y*V) only had an effect on LMW-GS. At Bell.lloc, where the soil had a high N content, N fertilisation increased the quantity of the different subunits by about 12%, whereas at Torregrossa the increase of each sub-unit as a result of N fertilisation was important: 40 and 70% for HMW and LMW-GS respectively (S*N interaction, data not shown).

The composition of total proteins was also modified. The HMW-GS to total protein ratio, and the LMW-GS to total protein ratio changed significantly with N fertilisation, site, year and variety (Table 2). Some single interactions, partic-ularly with N fertilisation (N*S, N*Y, N*V) only had a significant effect on LMW-GS content.

The change in protein composition was also reflected in the variation of the HMW- to LMW-GS ratio. The main factor of variation was N fertilisation, alone or in interaction with year, site and variety. Furthermore, the analysis of variance for this ratio showed a different pattern for the two varieties (V*Y, V*N interactions): contrary to Bancal in Rinconada this ratio changed signifi-cantly with growing season and N fertilisation.

The variation in HMW- and LMW-GS content was related to total glutenin content: HMW- and LMW-GS contents increased with flour glutenin content (Fig. 6A; R2_\_{0.84). The increase in}

LMW-GS seemed to be greater than that in HMW-GS, and consequently the HMW- to LMW-GS ratio be lower (MacRitchie and Gupta, 1993). However, no significant trend in the HMW- to LMW-GS ratio was observed (Fig. 6B)

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 56

3.3.1. Composition of HMW-GS

According to retention time by chromatogra-phy column HMW-GS were divided into 11 peaks (Fig. 1). These peaks were grouped into four pools: 30 –31, 33–36, 37–40 and 41–44. Table 3 presents the average amount and percentage of HMW-GS for each peak and the correlation co-efficients with total HMW-GS.

The data shown a genetic effect on HMW-GS composition. Although there were 11 peaks in the two varieties and the name given for each peak was the same, there were slight differences in the retention time of certain peaks (34, 39, 42). For example the retention times for Bancal and Rinconada were 34.5 and 33.8 min for peak 34, 39.4 and 39.1 for peak 39 and 42.3 and 42.9 for peak 42, respectively. In both varieties, peaks 34 and 39 were the peaks with the highest of HMW-GS content. In Bancal, each of these peaks repre-sented about 25% of total HMW glutenin and in Rinconada, peak 34 represented 18% and peak 39 represented 29% of total HMW glutenin.

Generally, in the two varieties the amount of individual HMW peaks increased significantly as HMW-GS increased (r\0.43). The three major peaks (30, 34 and 39) were those with the highest correlation with the total HMW-glutenin area (r\0.77). The analysis of the percentage of each peak for total HMW glutenin, revealed a different trend in the two varieties. Although in both vari-eties the total amount of individual peaks in-creased as HMW-GS inin-creased, the proportion of every peak with regard to total HMW-GS was different: only the proportion of one pool (41 –44) varied in Bancal wheat, whereas four varied in Rinconada. In the latter variety, the proportion of the three major peaks increased with HMW-GS content, and peak 40 was significantly lower. However, despite their statistical significance, the correlation coefficients of these relations were very small (r0.45; Fig. 7).

3.3.2. LMW composition

LMW-GS were divided into 15 peaks in Bancal and into 17 peaks in Rinconada (Fig. 2). Some of these peaks were pooled and some were consid-ered as individual peaks. Table 4 presents the retention times for different LMW-GS peaks, the average amount and percentage of each peak, and the correlation coefficients with total LMW-GS.

Some LMW-GS peaks were specific to the vari-ety: peaks 49 –7, 51–5 and 59 were present only in Rinconada and peak 58 only in Bancal. In Bancal there were five peaks (49, 51, 52, 53 and 54) and in Rinconada there were three peaks (51 –5, 52 Fig. 6. HMW and LMW-GS (A) and the HMW-/LMW-GS

ratio (B) as a function of glutenin protein in two bread wheat varieties (Bancal and Rinconada). Data consist of means of two sites (Torresgrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 kg N/ha). Units of area are mV/min. The number of observations was 24 for each regression.

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Table 3

Environmental effect on HMW-glutenin composition: RP-HPLC peak characteristics

Bancal

Variety Rinconada

Amount

Peaks Retention Percentage Retention Amount Percentage

time areaa

of HMW r with HMW of HMW r with HMW

Pool30_–31 13.19 15.5 – 11.71 11.5 –

29.7

30 7.76 9.0 – 29.9 6.16 5.9 0.45*

5.43 6.5 – 31.1

31.3 5.55

31 5.6 –

Pool33_–36 35.17 41.5 – 31.35 30.3 –

6.01 7.1 – 33.1

33 33.2 4.01 3.9 –

21.30 25.1 – 33.8

34.5 18.65

34 18.0 0.42*

36.0

36 7.85 9.3 – 36.0 8.69 8.4 –

27.88 32.8 – 39.57 38.9

Pool37_–40 –

4.99 5.9 – 37.8

37.7 5.52

37 5.5 –

21.66 25.4 – 39.1

39 39.4 31.13 29.0 0.45*

1.23 1.5 – 40.3

40.3 2.91

40 3.5 −0.46*

Pool41_–44 8.41 10.1 −0.41* 19.50 19.3 –

7.87 9.4 – 41.1

41.5 8.26

41 8.2 –

42.3

42 0.03 0.03 – 42.9 5.80 5.6 –

0.51

44 43.9 0.6 – 44.2 5.44 5.3 –

a_{Area is given in mV}_min.

* Statistical significant atPB0.05.

and 54) each of which represented more than 10% of total LMW glutenin.

Generally, in the two wheat varieties, the amount of individual LMW-GS peaks increased significantly as LMW-GS increased (r with LMW\0.54). Although the total amount of indi-vidual peaks increased as LMW-GS increased, the percentage of peaks were more constant in Bancal than in Rinconada. In the Bancal variety, only the percentage of peaks 51 and 58 –5 increased signifi-cantly with LMW-GS, whereas in Rinconada the percentage of several peaks changed (Fig. 8); pools 45 –48 and 49–50, peaks 53–9 and 56 de-creased significantly as LMW-GS inde-creased and peaks 51, pool 51 –52 and peak 54 significantly increased (Table 4). These results suggest that the synthesis of certain LMW protein fractions in wheat cultivars also depends on the environment. 3.4. Analysis of gliadins

Gliadin fractions were divided into 23 peaks in Bancal and into 25 peaks in Rinconada (Fig. 2). Some of these peaks were grouped into different pools and some were considered as individual

peaks. Table 5 indicates the most important char-acteristics of the different peaks: retention time, amount of gliadin, percentage of gliadin and cor-relation with the total amount of gliadin.

Peaks 19, 21, 22, 37 and 55 were present in Rinconada and not in Bancal and peaks 33, 58, 58.5, 59 and 59 were present only in Bancal but in small quantity (Table 5).

There were six peaks each of which represented more than 7% of total gliadin subunits: 42, 45, 47, 49, 53, 62 in Bancal and 42, 45, 48, 49, 53 and 54 in Rinconada. Other individual peaks represented less than 7% of total gliadin.

Generally, in the two wheat varieties, the amount of individual peaks increased significantly as gliadin increased (r0.80 – 0.90), but the per-centage of peaks relative to total gliadin showed a different pattern (Fig. 9). For both varieties, as gliadin increased the percentage of certain peaks increased (r\0) while that of certain others de-creased (rB0) (Table 5). Previous research (Brandlard and Triboı¨, 1983) also showed a varia-tion in the proporvaria-tion of gliadin subunits with changes in total protein content.

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 58

4. Discussion

It is now clearly established that grain quality is a function of grain composition, principally in proteins, which depends on the genotype and the environment. The genetic effect is mainly reflected by qualitative variation such as protein polymor-phism and secondly by quantitative variation of total protein or of different units and subunits. In contrast, the environmental effect (growing sea-son, site, fertilisation,....) was mainly reflected by the quantitative variation, such as in total protein or protein unit and subunit contents.

In our experiment, the quantity of nitrogen per grain exhibited a higher variation than grain weight. However, despite the relative

indepen-dence of these two variables their ratio, the protein content (% PC) in dry matter, essentially reflects the variation in protein amount, and the use of two variables, the content or the amount was nearly equivalent. (Figs. 3 and 4).

It is not surprising that the quantity or the content of two major classes of storage proteins, gliadin and glutenin, is significantly related to total protein, modified essentially by the nitrogen supply (fertilisation and site). The significant ‘facts’ are firstly, the difference between the two classes and secondly, the varietal behaviour.

If the quantity of nitrogen (or protein) per grain increases, the gliadin to glutenin ratio in-creases to a maximum potential (if PT=) equal to the ratio between two regression slopes (Fig. 4). Finally, an increase in the gliadin to glutenin ratio with the nitrogen quantity per grain (Fig. 5) or content (%, data not shown) was obtained. Simi-lar results were also found by several authors, despite different methods of analysis of proteins (Blumenthal et al., 1993; Jia et al., 1996a,b).

In all cases, for the same quantity or protein content, there is a significant varietal effect only on the glutenin fraction: in Rinconada, glutenin is higher than in the Bancal variety (Table 1), prob-ably owing to the difference in allelic composition and expression in the two varieties. This is in agreement with the results of Autran (1990) which showed a increase in the percentage of HMW-GS in total protein with the number of HMW-GS, and Halford et al. (1992) who showed that the presence of subunit 1A×1 (or 1A×2) increased the proportion of HMW-GS by about 2% in comparison with a null allele. However, Rinconada has 5 HMW-GS (1, 7+8, 5+10) and Bancal has 4 HMW-GS (7+9, 5+10). More-over, MacRitchie and Gupta (1993) indicated a similar quantity of HMW-GS produced by the loci of alleles GluB1 and GluD1, such that the quantitative superiority of Rinconada could be partially attributed to the quantitative effect pro-duced by the presence of GluA1. We also noted that the total protein content per grain was not different between the two varieties (Table 1); thus, the increase in glutenin content in Rinconada is not accompanied by an increase in total N quan-tity but more probably by a different allocation of Fig. 7. Variation in the percentage of three LMW-GS peaks as

a function of the amount of LMW-GS in Rinconada. Data consist of means of two sites (Torregrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 kg N/ha). Units of area are mV/min.

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Table 4

Environmental effect on LMW-glutenin composition: RP-HPLC peak characteristics

Bancal

Variety Rinconada

Retention Amount Percentage

Peaks Retention Amount Percentage

area

areaa _time

time

of LMW r with LMW of LMW r with LMW

16.3 10.6 –

Pool45_–48 15.09 8.3 −0.76**

2.69 1.7 –

46 45.9 45.6 1.94 1.1 –

0.37 0.3 – 46.4

46.5 3.37

46 –5 1.8 –

47.2

47 6.87 4.4 – 46.8 2.41 1.3 –

0.23 0.1 – 47.4

47.6 2.05

47 –5 0.1 –

6.17 4.0 – 48.7

48 48.6 5.3 2.9 –

17.68 11.54 – 9.51

Pool49_–50 5.1 −0.52**

17.68 11.5 – 49.3

49 49.5 4.97 2.6 –

– – – 49.8

– 4.55

49 –7 2.5 –

20.25 13.0 0.46* 50.6

51 50.8 13.07 6.7 0.56**

21.56 13.9 – 73.38

Pool51_–52 37.7 0.70**

–

51 –5 – – – 51.5 46.91 24.0 –

21.56 13.9 – 52.0

52.0 26.47

52 13.7 –

32.23 21.1 –

Pool52_–53 30.95 16.4 −0.52**

11.81 7.6 – 52.7

52.6 13.08

52 –7 6.8 –

20.41 13.5 – 53.0

53 53.0 17.87 9.6 –

0.837 0.5 – 53.8

53.8 8.14

53 –9 4.5 −0.43*

23.81 15.4 – 54.7

54 54.9 21.10 10.8 0.91**

2.87 2.0 – 56.1

56.1 11.43

56 6.1 −0.57**

18.28 11.7 –

Pool58_–59 8.39 4.3 –

8.70 5.6 – –

57.8 –

58 – –

9.58 6.0 0.46* 58.5 7.01 3.7 –

58 –5 58.5

– – – 59.3 1.38 0.6 –

– 59

a_{Area is given in mV}

min/mg flour.

* Statistical significant atPB_0.05. ** Statistical significant atPB_0.01.

N, in favour of glutenins and at the expanse of soluble fractions, albumin, globulin or amphyphiles.

Concerning the variation in glutenin composi-tion, the content of LMW- and HMW-GS was closely related to that of glutenin. The slope of regression between LMW-GS and total glutenin content (Fig. 6; 0.69) was two times greater than that of HMW-GS (0.31). When calculating this regression with the data on varietal effect of Nico-las (1997) we obtained similar values, 0.33 for HMW-GS and 0.67 for LMW-GS. Moreover, in both experiments the constant term of regression was positive for HMW-GS and negative for LMW-GS. This resulted a decrease in both the relative contribution of HMW-GS to total

glutenin content and of the ratio HMW-GS/

LMW-GS with the increase in total glutenin con-tent. However, in our experiment this ratio was not significantly affected, despite a high variation from 0.34 to 0.70 with a coefficient of variation of 11.9% (Table 2). A similar amplitude of variation was observed by Nicolas (1997) and Pechanek et al. (1997). Nevertheless Pechanek et al. (1997) showed a increase of this ratio with protein con-tent. This contradiction may be due to differences in the methodology used, or to the factor that induced the variation and the interaction with the genotype. For example, Daniel et al. (1998a,b), clearly showed that two environmental factors, temperature and nitrogen supply, acted differ-ently: high temperature increased the proportion

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E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 60

of HMW-GS in total glutenin whereas an increase in nitrogen supply decreased the proportion of HMW-GS.

Our data also showed a different behaviour of the genotype. The Bancal cultivar has a more stable HMW-GS composition than Rinconada. Indeed, with an increase in HMW protein, the proportion of different peaks did not change in Bancal but did in Rinconada (Table 3). This general pattern of variation also characterises the LMW-GS composition: stability in Bancal and some changes in Rinconada. The cause of this different genetic behaviour is not known.

Concerning the variation in gliadin composi-tion, we noted that as in glutenin, the content of different gliadin pools were closely related to gliadin content.

In our experiment, the proportion of thev -sub-group (TRB39 min) in total gliadins was about 5% (Bancal) and 11% (Rinconada), where the lower value was observed in Bancal, in which the faster gliadins (v5-) were missing. There was a good agreement between these values and those noted by Wiesser et al., (1994). The proportion of

the a+b gliadins (39B_TRB53) was 60 – 64%, and that of the l-gliadins 29 – 31%, respectively, for the Rinconada and Bancal varieties. Similar values were obtained by Wiesser et al. (1994) and Pechanek et al., (1997).

As in glutenins, all these gliadin subunits and their constituent peaks were highly correlated with total gliadin content. Their contribution to the total gliadin pool was very variable: the pro-portion of certain peaks was stable whereas the contribution of other peaks was related to the variation in gliadin content (Table 5) (Fig. 9). But, in contrast to glutenin, there are not different behaviour of two varieties in the variation of the proportion of gliadin peaks in the total gliadin.

To understand how the environment can change grain composition and to forecast this change, Triboi and Triboı¨-Blondel (1998) devel-oped a concept to analyse the variation in grain composition: every change is a consequence of the mechanisms of nitrogen allocation between differ-ent types of protein, through the change in rate and duration of synthesis. Thus, the quantity of one compound ‘Q’ is dependent on the rate of synthesis (r) and on the duration of synthesis

Fig. 8. Variation in the percentage of three LMW-GS peaks as a function of the amount of LMW-GS in Rinconada. Data consist of means of two sites (Torregrossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 kg N/ha). Units of area are mV/min.

(15)

Table 5

Environmental effect on gliadin composition: RP-HPLC peak characteristics

Variety Bancal Rinconada

Amount Percentage Retention Percentage

Retention

Peaks Amount

areaa _areaa

time time

of GLI r with GLI of GLI r with GLI

Pool19_–22 – – – 18.4 8.3 0.46*

– – – 19.3

– 4.9

19 2.3 –

–

21 – – – 21.6 10.7 4.8 0.48*

–

22 – – – 22.9–23.2 2.8 1.3 0.48*

4.5 2.0 0.57** 29.1

29.2 5.3

29 2.3 0.71**

6.0 2.7 –

Pool33_–34 1.1 0.4

2.8 1.3 – –

30.4–32.9 –

33 – –

33.1–33.9

34 3.2 1.4 – 34.5 1.1 0.4

– – 37.3

37 – 0.8 0.3 0.51*

5.4 2.4 –

Pool39_–41 4.3 1.9

39.0

39 1.9 0.9 – 39.5 0.9 0.4

40.7

41 3.5 1.5 – 41.0 3.4 1.5 –

29.8 13.2 – 42.2

42.3 28.0

42 13.0 0.66**

Pool43_–46 54.7 24.5 – 43.5 20.1 –

43.6

43 9.3 4.2 – 43.5 3.6 1.6 –

13.5 6.0 0.44** 44.5

44.6 11.2

44 5.1 0.42*

18.4 8.2 – 44.9 17.2 7.9 –

45 44.9

13.6 6.2 −0.63** 46.0

46.2 11.6

46 5.4 −0.47

Pool47_–51 53.8 24.3 −0.75** 52.7 24.6 −0.61**

21.5 9.8 −0.74** 47.9

47 47.9 8.3 3.9

4.5 2.0 – 48.1

48.5 21.4

48 10.0 −0.61**

49.2

49 23.0 10.4 −0.70** 49.0 17.8 8.3 –

50.8

51 4.8 2.1 – 50.6 5.2 2.4 −0.46*

29.3 13.2 – 52.4

Pool53_–54 24.7 −0.65

53.3

53 20.5 9.3 −0.55** 53.1 15.3 7.3 –

54.5

54 8.8 3.9 – 53.6 25.4 12.0 –

5.7 3.6 – –

Pool55_–59 – –

– – – 55.0 8.4 3.9 −0.46*

55 –

1.2 0.5 – 56.6

56.6 3.1

57 1.4 0.68**

56.9

58 1.5 0.7 −0.64** – – –

1.0 0.4 0.52** –

58.5 58.0 – –

0.6 0.3 – –

58.4 –

59 – –

59.4

59.5 1.4 0.6 – – – – –

31.6 14.0

Pool60_–62 0.46* 9.3 4.3 –

14.4 6.4 0.46* 58.5

59.8 2.0

60 1.0

60.6

61 1.0 0.5 −0.67** 59.6 3.3 1.6

16.2 7.1

62 61.5 0.61** 61.2 4.0 1.7 0.60**

a_{Area is given in mV}_min_/_{mg flour.}

* Statistical significant atPB_0.05. ** Statistical significant atPB_0.01.

(D):Q=(r)D+k.

Consequently, to forecast the quantity of one compound ‘Qc’ or the ratio between two com-pounds, it is necessary to estimate three

parame-ters: rate of synthesis, onset time and duration (or stopped date). In a particular case of two storage compounds (c1 and c2) which have same onset time, the

(16)

E.Triboi et al./Europ.J.Agronomy13 (2000) 47 – 64 62

Qci=(rci)Dci

In consequence, if the deposition rate is con-stant, the ratio between the compounds formed at the same time stay constant during grain filling,

equal to the ratio between the two rate of synthe-sis, r1/r2, despite a different synthesis rate and quantity deposited. However, the final ratio de-pends on the date of cessation of synthesis, or on the duration of filling:

rf=r1D1/r2D2

In contrast if the onset time is different, the ratioQ1/Q2changes during filling period. This is a new conceptual approach to analysing grain com-position formation and to comparing the few data on environmental effect.

5. Conclusion

The results presented in this study showed that environment considerably affects protein content and composition.

The most important effect was quantitative. In our study, nitrogen supply was the principal fac-tor of variation. In this case, the protein content of the grain (%) and the quantity of total protein per grain essentially reflected the change in protein quantity per grain, and the two variables were nearly equal in their effects.

Concerning the effect on protein composition, our data confirms the hypothesis put forward by Triboi and Triboı¨-Blondel (1998) who assumed that the quantitative variation in one component can be accompanied by a change in the ratio of its constitutive subcomponents. However, the alloca-tion of nitrogen to different subcomponents and the stability of the proportion of different con-stituents also depends on the genotype.

Finally, these ‘environmental effects’ on protein composition raise some questions about the origin of variation, because environmental factors can induce contrasting effects and about the physio-logical impact on grain growth and end-use. The correlative approach of the relationship between a component such as the quantity of proteins per grain, and their subcomponents — for example the gliadin and glutenin classes — can explain the quantitative variation of one component (quantity of gliadin or glutenin per grain) and also the ratio between two components (gliadin/glutenin). But, if we want to gain an in-depth knowledge of the Fig. 9. Variation in the percentage of four gliadin peaks as a

function of the amount of gliadin in Bancal (A) and Rinconada (B). Data consist of means of two sites (Torre-grossa and Bell.lloc), 2 years (1994 – 1995 and 1995 – 1996) and three N fertilisation rates (0, 100 and 200 kg N/ha). Units of area are mV/min.

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effects of environment on grain composition this correlative approach may be enhanced by the studies of dynamic accumulation and synthesis of different components of grain, which will allow the functional modelling approach of the varia-tion in quality.

Acknowledgements

The authors wish to thank Lucette Leblevenec for excellent technical assistance and are indebted to K. Lynch for revising the English version of the manuscript, (INRA’s translation unit, Jouy-en-Josas, France).

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(1)

Table 4

Environmental effect on LMW-glutenin composition: RP-HPLC peak characteristics

Bancal

Variety Rinconada

Retention Amount Percentage

Peaks Retention Amount Percentage

area

areaa _time

time

of LMW r with LMW of LMW r with LMW

16.3 10.6 –

Pool45_–48 15.09 8.3 −0.76**

2.69 1.7 –

46 45.9 45.6 1.94 1.1 –

0.37 0.3 – 46.4

46.5 3.37

46 –5 1.8 –

47.2

47 6.87 4.4 – 46.8 2.41 1.3 –

0.23 0.1 – 47.4

47.6 2.05

47 –5 0.1 –

6.17 4.0 – 48.7

48 48.6 5.3 2.9 –

17.68 11.54 – 9.51

Pool49_–50 5.1 −0.52**

17.68 11.5 – 49.3

49 49.5 4.97 2.6 –

– – – 49.8

– 4.55

49 –7 2.5 –

20.25 13.0 0.46* 50.6

51 50.8 13.07 6.7 0.56**

21.56 13.9 – 73.38

Pool51_–52 37.7 0.70**

–

51 –5 – – – 51.5 46.91 24.0 –

21.56 13.9 – 52.0

52.0 26.47

52 13.7 –

32.23 21.1 –

Pool52_–53 30.95 16.4 −0.52**

11.81 7.6 – 52.7

52.6 13.08

52 –7 6.8 –

20.41 13.5 – 53.0

53 53.0 17.87 9.6 –

0.837 0.5 – 53.8

53.8 8.14

53 –9 4.5 −0.43*

23.81 15.4 – 54.7

54 54.9 21.10 10.8 0.91**

2.87 2.0 – 56.1

56.1 11.43

56 6.1 −0.57**

18.28 11.7 –

Pool58_–59 8.39 4.3 –

8.70 5.6 – –

57.8 –

58 – –

9.58 6.0 0.46* 58.5 7.01 3.7 –

58 –5 58.5

– – – 59.3 1.38 0.6 –

– 59

a_{Area is given in mV}

min/mg flour.

* Statistical significant atPB_0.05.

** Statistical significant atPB_0.01.

N, in favour of glutenins and at the expanse

of

soluble

fractions,

albumin,

globulin

or

amphyphiles.

Concerning the variation in glutenin

composi-tion, the content of LMW- and HMW-GS was

closely related to that of glutenin. The slope of

regression between LMW-GS and total glutenin

content (Fig. 6; 0.69) was two times greater than

that of HMW-GS (0.31). When calculating this

regression with the data on varietal effect of

Nico-las (1997) we obtained similar values, 0.33 for

HMW-GS and 0.67 for LMW-GS. Moreover, in

both experiments the constant term of regression

was positive for HMW-GS and negative for

LMW-GS. This resulted a decrease in both the

relative

contribution

of

HMW-GS

to

total

glutenin content and of the ratio HMW-GS

/

LMW-GS with the increase in total glutenin

con-tent. However, in our experiment this ratio was

not significantly affected, despite a high variation

from 0.34 to 0.70 with a coefficient of variation of

11.9% (Table 2). A similar amplitude of variation

was observed by Nicolas (1997) and Pechanek et

al. (1997). Nevertheless Pechanek et al. (1997)

showed a increase of this ratio with protein

con-tent. This contradiction may be due to differences

in the methodology used, or to the factor that

induced the variation and the interaction with the

genotype. For example, Daniel et al. (1998a,b),

clearly showed that two environmental factors,

temperature and nitrogen supply, acted

differ-ently: high temperature increased the proportion

(2)

of HMW-GS in total glutenin whereas an increase

in nitrogen supply decreased the proportion of

HMW-GS.

Our data also showed a different behaviour of

the genotype. The Bancal cultivar has a more

stable HMW-GS composition than Rinconada.

Indeed, with an increase in HMW protein, the

proportion of different peaks did not change in

Bancal but did in Rinconada (Table 3). This

general pattern of variation also characterises the

LMW-GS composition: stability in Bancal and

some changes in Rinconada. The cause of this

different genetic behaviour is not known.

Concerning the variation in gliadin

composi-tion, we noted that as in glutenin, the content of

different gliadin pools were closely related to

gliadin content.

In our experiment, the proportion of the

v

-sub-group (TR

B

39 min) in total gliadins was about

5% (Bancal) and 11% (Rinconada), where the

lower value was observed in Bancal, in which the

faster gliadins (

v

5-) were missing. There was a

good agreement between these values and those

noted by Wiesser et al., (1994). The proportion of

the

a

+

b

gliadins (39

B

_TR

B

53) was 60 – 64%,

and that of the

l

-gliadins 29 – 31%, respectively,

for the Rinconada and Bancal varieties. Similar

values were obtained by Wiesser et al. (1994) and

Pechanek et al., (1997).

As in glutenins, all these gliadin subunits and

their constituent peaks were highly correlated

with total gliadin content. Their contribution to

the total gliadin pool was very variable: the

pro-portion of certain peaks was stable whereas the

contribution of other peaks was related to the

variation in gliadin content (Table 5) (Fig. 9).

But, in contrast to glutenin, there are not different

behaviour of two varieties in the variation of the

proportion of gliadin peaks in the total gliadin.

To understand how the environment can

change grain composition and to forecast this

change, Triboi and Triboı¨-Blondel (1998)

devel-oped a concept to analyse the variation in grain

composition: every change is a consequence of the

mechanisms of nitrogen allocation between

differ-ent types of protein, through the change in rate

and duration of synthesis. Thus, the quantity of

one compound ‘Q’ is dependent on the rate of

synthesis (r) and on the duration of synthesis

(3)

Table 5

Environmental effect on gliadin composition: RP-HPLC peak characteristics

Variety Bancal Rinconada

Amount Percentage Retention Percentage

Retention

Peaks Amount

areaa _areaa

time time

of GLI r with GLI of GLI r with GLI

Pool19_–22 – – – 18.4 8.3 0.46*

– – – 19.3

– 4.9

19 2.3 –

–

21 – – – 21.6 10.7 4.8 0.48*

–

22 – – – 22.9–23.2 2.8 1.3 0.48*

4.5 2.0 0.57** 29.1

29.2 5.3

29 2.3 0.71**

6.0 2.7 –

Pool33_–34 1.1 0.4

2.8 1.3 – –

30.4–32.9 –

33 – –

33.1–33.9

34 3.2 1.4 – 34.5 1.1 0.4

– – 37.3

37 – 0.8 0.3 0.51*

5.4 2.4 –

Pool39_–41 4.3 1.9

39.0

39 1.9 0.9 – 39.5 0.9 0.4

40.7

41 3.5 1.5 – 41.0 3.4 1.5 –

29.8 13.2 – 42.2

42.3 28.0

42 13.0 0.66**

Pool43_–46 54.7 24.5 – 43.5 20.1 –

43.6

43 9.3 4.2 – 43.5 3.6 1.6 –

13.5 6.0 0.44** 44.5

44.6 11.2

44 5.1 0.42*

18.4 8.2 – 44.9 17.2 7.9 –

45 44.9

13.6 6.2 −0.63** 46.0

46.2 11.6

46 5.4 −0.47

Pool47_–51 53.8 24.3 −0.75** 52.7 24.6 −0.61** 21.5 9.8 −0.74** 47.9

47 47.9 8.3 3.9

4.5 2.0 – 48.1

48.5 21.4

48 10.0 −0.61**

49.2

49 23.0 10.4 −0.70** 49.0 17.8 8.3 –

50.8

51 4.8 2.1 – 50.6 5.2 2.4 −0.46*

29.3 13.2 – 52.4

Pool53_–54 24.7 −0.65

53.3

53 20.5 9.3 −0.55** 53.1 15.3 7.3 –

54.5

54 8.8 3.9 – 53.6 25.4 12.0 –

5.7 3.6 – –

Pool55_–59 – –

– – – 55.0 8.4 3.9 −0.46*

55 –

1.2 0.5 – 56.6

56.6 3.1

57 1.4 0.68**

56.9

58 1.5 0.7 −0.64** – – –

1.0 0.4 0.52** –

58.5 58.0 – –

0.6 0.3 – –

58.4 –

59 – –

59.4

59.5 1.4 0.6 – – – – –

31.6 14.0

Pool60_–62 0.46* 9.3 4.3 –

14.4 6.4 0.46* 58.5

59.8 2.0

60 1.0

60.6

61 1.0 0.5 −0.67** 59.6 3.3 1.6

16.2 7.1

62 61.5 0.61** 61.2 4.0 1.7 0.60**

a_{Area is given in mV}_{min/mg flour.} * Statistical significant atPB_0.05.

** Statistical significant atPB_0.01.

(D):

Q

=

(r)D

+

k.

Consequently, to forecast the quantity of one

compound ‘Qc’ or the ratio between two

com-pounds, it is necessary to estimate three

parame-ters: rate of synthesis, onset time and duration (or

stopped date). In a particular case of two storage

compounds (c

and

c

) which have same onset

(4)

Qc

=

(r

)Dc

In consequence, if the deposition rate is

con-stant, the ratio between the compounds formed at

the same time stay constant during grain filling,

equal to the ratio between the two rate of

synthe-sis,

r

/

r

, despite a different synthesis rate and

quantity deposited. However, the final ratio

de-pends on the date of cessation of synthesis, or on

the duration of filling:

r

=

r

D

/

r

D

In contrast if the onset time is different, the

ratio

Q

/

Q

changes during filling period. This is a

new conceptual approach to analysing grain

com-position formation and to comparing the few data

on environmental effect.

5. Conclusion

The results presented in this study showed that

environment considerably affects protein content

and composition.

The most important effect was quantitative. In

our study, nitrogen supply was the principal

fac-tor of variation. In this case, the protein content

of the grain (%) and the quantity of total protein

per grain essentially reflected the change in

protein quantity per grain, and the two variables

were nearly equal in their effects.

Concerning the effect on protein composition,

our data confirms the hypothesis put forward by

Triboi and Triboı¨-Blondel (1998) who assumed

that the quantitative variation in one component

can be accompanied by a change in the ratio of its

constitutive subcomponents. However, the

alloca-tion of nitrogen to different subcomponents and

the stability of the proportion of different

con-stituents also depends on the genotype.

Finally, these ‘environmental effects’ on protein

composition raise some questions about the origin

of variation, because environmental factors can

induce contrasting effects and about the

physio-logical impact on grain growth and end-use. The

correlative approach of the relationship between a

component such as the quantity of proteins per

grain, and their subcomponents — for example

the gliadin and glutenin classes — can explain the

quantitative variation of one component (quantity

of gliadin or glutenin per grain) and also the ratio

between two components (gliadin

/

glutenin). But,

if we want to gain an in-depth knowledge of the

Fig. 9. Variation in the percentage of four gliadin peaks as a

(5)

effects of environment on grain composition this

correlative approach may be enhanced by the

studies of dynamic accumulation and synthesis of

different components of grain, which will allow

the functional modelling approach of the

varia-tion in quality.

Acknowledgements

The authors wish to thank Lucette Leblevenec

for excellent technical assistance and are indebted

to K. Lynch for revising the English version of

the manuscript, (INRA’s translation unit,

Jouy-en-Josas, France).

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