Effect of salinity on yield and 2-acetyl-1-pyrroline content in the grains of three fragrant rice cultivars (Oryza sativa L.) in Camargue (France)

Field Crops Research 117 (2010) 154–160

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Effect of salinity on yield and 2-acetyl-1-pyrroline content in the grains of three fragrant rice cultivars (Oryza sativa L.) in Camargue (France) F. Gay a,∗ , I. Maraval b,d , S. Roques c , Z. Gunata d , R. Boulanger b , A. Audebert c , C. Mestres b a

CIRAD, DORAS Centre, Research and Development Building, Kasetsart University, Bangkok 10900, Thailand UMR Qualisud, CIRAD, 73 Rue J.F. Breton, 34398 Montpellier Cedex 5, France UPR AIVA, CIRAD, Avenue Agropolis, 34398 Montpellier Cedex 5, France d UMR Qualisud, Universite de Montpellier II, place E. Bataillon, 34095 Montpellier Cedex 5, France b c

a r t i c l e

i n f o

Article history: Received 10 March 2009 Received in revised form 3 December 2009 Accepted 17 February 2010 Keywords: Oryza sativa Fragrant rice Aromatic quality 2-Acetyl-1-pyrroline Yield components Salinity

a b s t r a c t Aromatic quality of rice grains is known to vary greatly with environmental factors and cultivation methods. Among the environmental factors, soil salinity is thought to have a positive impact on the content of 2-acetyl-1-pyrroline (2AP) in grains, the key volatile compound of rice aroma. This study compared 2AP content in grains of three improved fragrant rice (Oryza sativa L.) varieties grown in two fields, differing mainly in their soil salinity level. The impact of salinity on yield and main yield components was also investigated to understand the relationship between aromatic quality and yield build-up. Soil salinity was monitored by measuring the electrical conductivity (EC) of soil solution samples extracted every week. 2AP content in grains was determined by a newly developed stable isotope dilution method involving solid-phase microextraction (SPME) and GC MS/MS analysis. The results showed an increase of 2AP content in grains with salinity for the three varieties. The relationship between 2AP and mean EC of the crop fitted a single model for the three varieties (R2 = 0.728). In contrast, the impact of salinity on yield and yield components differed greatly between the three varieties. One variety appeared to be very sensitive to salt stress, with significant yield loss up to 40%, while the two other varieties proved to be resistant to the salinity levels experienced by the plants, with no significant yield loss or even higher yields in saline conditions. Nevertheless, the three varieties presented a significant negative correlation between 1000 grain weight (TGW) and the mean EC of the crop, and between TGW and 2AP content. It was concluded that the increase of 2AP content with salinity resulted partially from a 2AP concentration mechanism in smaller size grains. The direct effect of salinity on 2AP synthesis through stimulation of the proline metabolism is further discussed. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Fragrant rices have gained significant market shares in the global rice trade during the last 15 years (Calpe, 2004). Consequently, efforts have been undertaken in many countries to increase or develop the production of this type of rice. Initially these efforts focused mainly on breeding programs to improve or adapt existing fragrant rice varieties to local conditions (FAO, 2001). In most cases, the outcomes of these breeding programs have been limited by two main issues. First, the improvement of fragrant rice varieties has been challenged by the environment by genotype interactions for aromatic quality. Indeed, although genetic factors play a major role in determining rice aroma (Lorieux et al., 1996; Bradbury et al., 2008; Fitzgerald et al., 2008a), environmental factors and cultivation practices have been shown to substantially

∗ Corresponding author. Tel.: +66 2 942 7627; fax: +66 2 942 7628. E-mail address: [email protected] (F. Gay). 0378-4290/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.fcr.2010.02.008

affect the aromatic quality of rice (Champagne, 2008). Moreover, many rice breeders have pointed out the difficulty in obtaining good aromatic quality, and more generally good grain quality, with high yield. Actually, rice varieties with very high aromatic quality have often been reported to have low yield (FAO, 2001). Therefore, it is crucial for the development of fragrant rice production to improve understanding of the impact of environmental factors on aromatic quality of the grains, as well as the relationship between aromatic quality and yield components. Several studies have reported the variability of aromatic quality of the grain when rice has been grown in traditional fragrant rice areas (Rohilla et al., 2000; Itani et al., 2004; Yoshihashi et al., 2004a; Gay et al., 2006). Temperature during grain filling and ripening (Itani et al., 2004), soil type (Sagar and Ali, 1993), timing of field drying and harvest (Arai and Itani, 2000; Champagne et al., 2005) are some environmental factors together with cultivation practices to affect rice aroma. Furthermore, field observations and recent scientific studies support the hypothesis that osmotic stress, i.e. drought and salinity, may have a positive effect on aromatic quality of rice.

F. Gay et al. / Field Crops Research 117 (2010) 154–160 Table 1 Main soil characteristics of the two experimental fields. Soil characteristics

Field 1

Field 2

Clay content (%) Silt content (%) Sand content (%) Organic matter content (%) C/N ratio Cation exchange capacity (me/100g) Saturation rate (%) pH Electric conductivity 2006 (␮S/cm) Electric conductivity 2007 (␮S/cm)

23.80 63.00 13.20 2.54 9.57 9.99 >100 8.41 4100 4600

33.10 59.60 7.40 2.26 9.89 10.33 >100 8.60 10,700 8550

Some very popular fragrant rice varieties are indeed traditionally grown in drought prone rain-fed paddy fields and/or in areas with saline soils or intrusion of saline water from the sea during the rice season (Buu, 2000; Kaojarern et al., 2004). The main evidence comes from the work of Suprasanna et al. (1998) and Yoshihashi et al. (2002) who found, respectively in rice callus and rice plants, that proline, an amino acid well known for its role in plant response to water and salinity stresses (Delauney and Verma, 1993; Bray, 1997; Tamayo and Bonjoch, 2001), is one of the precursors of 2-acetyl1-pyrroline (2AP), the key compound of rice aroma (Buttery and Ling, 1982; Buttery et al., 1983; Maraval et al., 2008). In the field, Yoshihashi et al. (2004b) confirmed that drought stress applied during the milky stage of the ripening phase led to an increase in 2AP content in the grains at harvest. On the other hand, Fitzgerald et al. (2008b) found no effect of salt on 2AP concentration in leaf tissue of Jasmine and Basmati cultivars. Nevertheless, to our knowledge, effect of salinity on 2AP content in the grains and aromatic quality of rice has not been studied yet in field conditions. Rice is generally considered moderately sensitive to salinity. Salinity can indeed substantially reduce rice yield when it exceeds 2000 ␮S cm−1 (Asch and Wopereis, 2001; Grattan et al., 2002). Nevertheless, the response of rice to salinity varies widely between cultivars (Shannon et al., 1998). It depends also on the intensity and timing of stress (Zheng et al., 2001). The seed set and grain filling stages prove to be particularly sensitive to salinity (Khatun and Flowers, 1995; Fabre et al., 2005). Thus, if osmotic stresses at those stages are likely to increase 2AP content of the grains, they are also likely to adversely affect the number and weight of grains and consequently the yield as assumed by Bradbury et al. (2008). The objectives of this paper are to study (i) the effect of salinity on the yield, the yield components and 2AP content in grains at harvest for three fragrant cultivars, (ii) the relationship between 2AP content and yield, and (iii) the relationship between 2AP content and proline and ␥-aminobutyric acid (GABA) concentrations in grains. Our experiments took place in Camargue, the main rice cultivation area of France, where salinity is a major constraint on rice production (Puard et al., 1999). 2. Materials and methods 2.1. Experimental site The experiments were conducted in two fields on the same farm in Camargue, in the South of France (lat.: 43◦ 34 50 N and long.: 4◦ 31 54 E), during the 2006 and 2007 rice cropping seasons. The fields, less than 100 m apart, were chosen along a topographic gradient also corresponding to a natural salinity gradient, as shown by the electrical conductivity value of the soil solution (EC) measured in 2006 and 2007 on soil cores sampled before the beginning of the crop season (Table 1). The other soil characteristics were similar in both fields (Table 1). The crops were sown on May 4 in 2006 and on May 7 in 2007 at 700 seeds m−2 , and harvested between October 13

155

and 16 in 2006 (respectively 162 and 165 days after sowing, DAS), and between September 27 and October 10 in 2007 (respectively 143 and 155 DAS). Fertilisation, weeding, irrigation and pesticide spraying were performed by the farmer on both fields at the same time, following local recommendations for rice cultivation. Mean air temperature and cumulative rainfalls were similar in both cropping seasons. Nevertheless, we observed some significant differences in the pattern of daily values (data not shown). Daily temperatures between panicle initiation and the onset of grain filling were significantly cooler in 2007 than in 2006 (22.8 ◦ C vs. 24.5 ◦ C on average). It did not rain during the first 2 months after sowing in 2006, and 70% of the rainfall occurred during the month before harvest. In 2007, rainfall was concentrated in the first 2 months of the crop season, with 87 mm in the days after sowing, and it did not rain afterwards. 2.2. Experiment design A 40 m × 15 m plot was delimited in each field before sowing. Each plot was then divided into nine 3 m × 15 m sub-plots that were sown with one of the three improved fragrant temperate japonicatype rice (Oryza sativa L.) cultivars commonly used in Camargue – namely Aychade, Giano and Fidji – with a split plot design. The non-fragrant variety Ariette was used on the remaining field area around the plot. Subsequently, the fields are named Field 1 and Field 2, Field 1 being the less salty and Field 2 the more salty. On each sub-plot, a tensionic device (SDEC France, France) was installed at a depth of 15 cm to collect soil solution as described by Cuny et al. (1998). The tensionic is equipped with a “high flow” ceramic cup allowing ions in the soil solution to diffuse passively through it (Moutonnet et al., 1993). Soil solutions were extracted every 8 days, transported to the lab and analysed for electrical conductivity (EC) and pH using a portable multi-meter (Hanna instruments, USA). Extraction of the soil solutions could not be performed after 145 DAS in 2006 and 150 DAS in 2007, because irrigation was stopped for harvesting and the soil was too dry. The main crop development stages were recorded according to the Standard Evaluation System for rice (IRRI, 1988). At physiological maturity, an area of 2 m2 in the centre of each sub-plot was harvested to determine actual yield and the main yield components, i.e. panicle number per square metre (PAN), spikelet number per panicle (SPK), grain sterility (STER), defined as the percentage of empty grains out of total number of grains, and thousand grain weight (TGW). 2.3. Quantitative analysis of 2-acetyl-1-pyrroline in rice grains A stable isotope dilution assay (SIDA) was developed for a precise quantification of 2-acetyl-1-pyrroline (2AP) in rice by using solid-phase microextraction (SPME) in combination with gas chromatography–positive chemical ionization tandem mass spectrometry (GC–PCI-MS/MS). A 50 g subsample of filled grains was taken from the 2 m2 sample of each plot. One part of these subsamples was used to determine the water content of the grains following desiccation at 70 ◦ C for 2 days. The other part was cut and frozen under liquid nitrogen, then ground to a <1 mm size using an analytical crusher (IKAWERKE, Staufen, Germany), and stored in capped vials at −20 ◦ C until analysis. Later, 0.5 g of crushed sample was placed in a 10 mL vial with 4 mL of carbonate buffer (pH 9.0) and 8 ␮L of 2-acetyl-1d2 -pyrroline (2AP-d2 ) solution (27.56 ␮g/mL in ethanol) as internal standard. The vial was then capped with a PTFE septum and magnetically stirred (800 rpm) at 80 ◦ C. After 5 min of equilibration, the fibre (Stable-Flex divinylbenzene/Carboxen/polydimethylsiloxane 50/30 ␮m fibre, Supelco, Bellefonte, PA, USA) was exposed to the headspace for 20 min. After sampling, the analytes retained by

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F. Gay et al. / Field Crops Research 117 (2010) 154–160

fibre were analyzed by CP-3800 gas chromatograph equipped with a capillary column (DB-Wax 30 m × 0.5 mm i.d., film thickness 0.25 ␮m; J&W Scientific, Folson, CA) and coupled with a Saturn 2200 MS–MS ion-trap detector (Varian, Walnut Creek, CA, USA). The 2AP was quantified through area ratio of daughter ions from 2AP and 2AP-d2 , 70 and 72, respectively. All extractions and quantification were done in duplicate. The results are reported on a dry-weight basis. 2.4. Analysis of proline and GABA in grains Proline and GABA were analyzed using a high-pressure liquid chromatography system (LC-9A, Schimadzu Co. Kyoto, Japan) equipped with a degasser, auto-sampler, temperature-controlled column holder and UV spectrophotometric detector (SPD-6A, Schimadzu) at 436 nm. The column, C18 (250 mm × 4.6 mm (i.d.); 5 ␮m particle size; Waters, Ireland), was maintained at 35 ◦ C. Mobile phase A consisted of 2% (v/v) 0.9 M NaH2 PO4 , 8% (v/v) dimethylformamide, and 0.6% triethylamine in water. The pH was adjusted to 6.5 with phosphoric acid. Mobile phase B was acetonitrile–water (80:20, v/v). The elution was performed at 1 mL/min with a linear gradient from 35% B at 0 min to 50% B at 20 min. The column was then rinsed with 100% B then equilibrated with 35% B for at least 10 min. The extraction was performed on 100 mg of crushed grains with 4 mL of 0.1 M sodium carbonate buffer (pH 9) at room temperature with continuous stirring for 1 h. The extract was then filtered through a 0.45 ␮m Millipore filter. 100 ␮L of the extract was pipetted, and 100 ␮L of 2 mg/mL dabsyl (4-(dimethylamino) azobenzene-4 -sulfonyl chloride) in acetonitrile was added. After 10 min at 70 ◦ C, 300 ␮L of 9 mM phosphate buffer (pH 7) was added. Finally, 20 ␮L of the sample was injected in the HPLC. 2.5. Statistical analysis Analysis of variance, regression analysis and multiple comparisons of means with the least significant difference (LSD) test at p < 0.05 were performed with the XLSTAT software (Addinsoft, France). 3. Results 3.1. Salinity of the soil solution The electrical conductivity of the soil solution (EC) was determined every 8–10 days to monitor the change with time of soil salinity level in each sub-plot. The seasonal pattern of EC was similar in the nine sub-plots of each Field × Year pair, despite high variability between sub-plots on some days (data not shown). Therefore, the change with time of the salinity level of each Field × Year pair could be characterised by the average EC of the nine sub-plots (Fig. 1). Both years, the mean EC of field 1 on the first day of measurement, about 10 days after sowing, was around 1000 ␮S cm−1 lower than the EC of the soil sample taken before sowing (Table 1). This rapid decrease in salinity level was most likely due to the flooding of the field just after sowing. In 2007,

Fig. 1. Change with time of the electrical conductivity (EC) of the soil solution in the root zone. Each point represents the mean of nine measurements per field. Error bars represent standard deviation.

the EC of Field 1 remained at the same level during the entire crop season. In 2006, the EC did not vary much until 120 DAS, and then increased rapidly from 987 to 2750 ␮S cm−1 between 120 and 145 DAS. In Field 2, the EC kept decreasing after the initial flooding in both years but with different patterns. In 2006, the Field 2 EC decreased gradually from 6351 ␮S cm−1 at 11 DAS to 1039 ␮S cm−1 at 109 DAS. The EC increased subsequently up to 3233 ␮S cm−1 at 145 DAS, like in Field 1 the same year. Conversely, the Field 2 EC in 2007 dropped sharply in only 7 days, from 5088 ␮S cm−1 at 10 DAS to 2250 ␮S cm−1 at 17 DAS, then remained quite constant around this value until the end of the crop season. We summarized the monitoring of salinity by computing for each Field x Year pair the EC averages during the entire crop season (ECcrop) and during the three main stages of rice development: vegetative stage (ECveg) from sowing to panicle initiation (PI) (about 60 DAS for both experiment), early reproductive stage (ECrep1) from PI to heading (about 110 DAS for both experiments) and late reproductive stage (ECrep2) from heading to harvest time (Table 2). The statistical analysis confirmed that Field 2 had significantly higher levels of salinity than Field 1 during both years, in accordance with the EC values measured on soil samples taken before sowing (Table 1). In addition, Field 2 exhibited higher EC values in 2006, but the salinity level remained above 2000 ␮S cm−1 for any period. 3.2. Effect of salinity on grain yield and yield components Data on the yield and yield components are presented in Table 3 Table 3, along with the results of the LSD test run independently for each variety. Tables 4 and 5 gives the correlation coefficients from the regression analysis between yield, yield components and mean EC during the whole crop season, or for different development stages as defined previously. In this analysis, we used absolute yield values, but also relative values to take into account the significant effect of the year (Table 3). The relative yield was computed

Table 2 Mean electrical conductivity of each field during the crop season and the main crop development stages (vegetative stage, ECveg, early reproductive stage, ECrep1, late reproductive stage, ECrep2). Different letters indicate significant differences between fields based on the LSD test (p < 0.05). Year

Field

ECcrop (␮S cm−1 )

ECveg (␮S cm−1 )

ECrep1 (␮S cm−1 )

ECrep2 (␮S cm−1 )

2006

1 2

1311c 4184a

954c 5399a

1313c 3552a

1966b 2492a

2007

1 2

1084c 2243b

1064c 2547b

1147c 2126b

1028c 2024b

F. Gay et al. / Field Crops Research 117 (2010) 154–160

157

Table 3 Means of yield and yield components for each variety in the two experimental fields in 2006 and 2007. Different letters indicate significant differences between fields based on the LSD test (p < 0.05) run for each variety independently. PAN = number of panicles per square metre; SPK = number of spikelets per panicle; STER = percentage sterility; TGW = thousand grain weight. Variety

Year

Field

Yield (T ha−1 )

PAN (m−2 )

STER (%)

TGW (g)

Aychade

2006

1 2 1 2

6.3a 3.8b 4.4b 4.2b

511a 473a 355c 357c

86.7a 96.6a 80.6a 82.9a

30.5c 43.4a 31.2c 37.1b

26.1a 21.8c 25.4ab 24.5a

1 2 1 2

3.3b 2.9c 4.5a 4.4a

341b 314b 545a 477a

83.2a 101.1a 66.5b 61.3b

24.5b 25.4b 32.4a 26.2b

26.3a 22.0b 26.5a 26.1a

1 2 1 2

4.5a 4.8a 3.3b 4.9a

488a 388a 453a 411a

79.8b 90.9a 77.8b 86.1a

34.5a 23.4b 46.8a 26.9b

26.4a 24.1b 26.2a 25.9a

2007

Fidji

2006 2007

Giano

2006 2007

SPK

Table 4 Correlation coefficients from regression analyses between mean EC during the crop season (ECcrop) and during the three main crop development stages (vegetative stage, ECveg, early reproductive stage, ECrep1, late reproductive stage, ECrep2), and yield, relative yield and yield components. PAN = number of panicles per square metre; SPK = number of spikelets per panicle; STER = number of unfilled grains; TGW = thousand grain weight. Variety

Stage

PAN

SPK

TGW

STER

Yield

Relative yield

−0.582 −0.641* 0.593 −0.088

−0.951*** −0.954*** −0.928*** −0.706* −0.787** −0.793** −0.741** −0.542

AYCHADE

ECcrop ECveg ECrep1 ECrep2

0.037 −0.025 0.022 0.350

0.505 0.460 0.459 0.585

−0.819 −0.842** −0.822** −0.409

FIDJI

ECcrop ECveg ECrep1 ECrep2

−0.570 −0.515 −0.561 −0.716**

0.639* 0.620* 0.575 0.622*

−0.916*** −0.931*** −0.874*** −0.630*

−0.463 −0.402 −0.482 −0.707*

−0.636* −0.597* −0.600* −0.701*

GIANO

ECcrop ECveg ECrep1 ECrep2

−0.397 −0.416 −0.467 −0.131

0.723** 0.797** 0.604* 0.482

−0.868*** −0.876*** −0.881*** −0.530

−0.630* −0.633* −0.557 −0.574

0.487 0.481 0.377 0.593*

* ** ***

**

Table 5 Correlation coefficients from regression analyses between yield, relative yield and yield components. PAN = number of panicles per square metre; SPK = number of spikelets per panicle; STER = number of unfilled grains; TGW = thousand grain weight. Variety

PAN

SPK

AYCHADE Yield Relative yield

0.734* 0.027

0.006 −0.366

0.729* 0.796**

−0.581 −0.830**

FIDJI Yield Relative yield

0.898*** 0.521

−0.897*** −0.611*

0.735** 0.817**

0.569 0.318

GIANO Yield Relative yield

0.296 0.305

*

***

0.916 0.909*** 0.882*** 0.745**

0.463 0.463 0.348 0.540

p < 0.05. p < 0.01. p < 0.001.

for each sub-plot as the ratio between the actual sub-plot yield and the maximum yield achieved by the same variety in the same year. The yield of Aychade and Fidji were significantly lower in Field 2 than in Field 1 in 2006 (Table 3). The reduction was by 45 and 13% for Aychade and Fidji, respectively. Conversely, yield of Giano increased in Field 2 in 2007, with a 48% rise. The yield values, expressed either in absolute or relative terms, of Aychade and Fidji were negatively correlated with crop EC (Table 4). Both varieties showed high correlation (p < 0.001)

**

***

p < 0.05. p < 0.01. p < 0.001.

0.674* 0.665*

TGW

−0.189 −0.121

STER

−0.804** −0.795**

between mean EC at the vegetative and early reproductive stage, i.e. before flowering, and yield values. Only Aychade presented a correlation with mean EC at the late reproductive stage (p < 0.05). The correlation coefficients in Table 5 showed that Aychade yield was mainly positively correlated with TGW and negatively with STER, which were both affected by salinity. A higher salinity probably decreased TGW and increased STER, thereby reducing yield. For Fidji, yield loss was also associated with reduced TGW. Surprisingly, salinity was also positively correlated with SPK. This result contradicts the lack of significant difference between SPK in Field 1 and Field 2 (Table 3). SPK variation appeared indeed mainly linked to the year effect. SPK was higher in 2006, as, fortuitously, were the EC values. The yield increase from Field 1 to Field 2 for Giano was correlated with an increase in SPK and a reduction in STER with salinity (Table 5). These correlations between yield and SPK, and salinity and STER, were not consistent with those observed for Aychade and Fidji (Table 5). Furthermore, correlation between SPK and salinity for Giano could not be explained by a year effect, in contrast to Fidji. These results underline some strong differences in yield build-up strategies and in yield response to salinity between the three genotypes. However, we observed a common negative correlation between TGW and salinity, similarly to Aychade and Fidji, although no correlation between TGW and yield was found (Table 5). Moreover, correlation between TGW and mean EC was strongly significant (p < 0.01) for the three varieties at the vegetative stage and the early reproductive stage, but was only significant (p < 0.05) at the late reproductive stage for Fidji (Table 4).

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F. Gay et al. / Field Crops Research 117 (2010) 154–160

Table 6 Average 2-acetyl-1-pyrroline, proline and GABA content in grains at harvest for each variety in the two experimental fields in 2006 and 2007. Different letters indicate significant differences between fields based on the LSD test (p < 0.05) run for each variety independently. Year

Field

Aychade 2AP (␮g kg−1 )

Fidji Proline (␮g g−1 )

GABA (␮g g−1 )

2AP (␮g kg−1 )

Giano Proline (␮g g−1 )

GABA (␮g g−1 )

2006

1 2

715c 959b

21 25

56 54

560d 880c

11 10

57 56

301c 358b

15 13

45 43

2007

1 2

1440a 1633a

18 17

69 55

1715b 1931a

11 10

61 49

741a 786a

13 12

55 47

3.3. Effect of salinity on 2-acetyl-1-pyroline (2AP) and proline content in rice grains The 2AP contents in rice grains at harvest were significantly higher in 2007, with a 120% average increase. Considering this difference, the 2AP data were converted on a relative basis, as we did for the yield data. The relative 2AP content was computed as the ratio of the actual 2AP content of the sub-plot to the minimum 2AP content for the variety in the year. The 2AP content in grains increased significantly from Field 1 to Field 2 for the 3 varieties in 2006, but only for Fidji in 2007 (Table 6). The relative 2AP content was highly (p < 0.001) correlated with ECcrop for Aychade and Fidji, and strongly (p < 0.01) correlated for Giano (Table 7). Furthermore, Fig. 2 shows that the relationship between ECcrop and 2AP content can fit a single linear regression model for the three varieties (R2 = 0.728). In addition, the relative 2AP content presented the strongest correlation coefficient with ECrep1 for the three varieties, and the lowest with ECrep2 (Table 7). These results suggest that the effect of salinity on 2AP content at harvest was similar for the three varieties, and that it was mainly the result of salinity stress before flowering. Table 5 also shows the proline and GABA contents in grains for each variety in 2006 and 2007. The proline level detected in grains was 10–50 times higher than that of 2AP. No difference in proline concentration was evidenced between fields (salt levels), but a multifactorial analysis performed on all cultivars evidenced that proline level was significantly higher in 2006 (16.5 ␮g g−1 against 12.0 in 2007). GABA level was two to five times higher than proline level. A multifactorial analysis performed on all cultivars evidenced highly significant effects of year and field and of their interaction: surprisingly, GABA level was higher in field 1, i.e. for lower salt level. This effect was particularly important in 2007, with a level of 48 ␮g g−1 in field 2 and of 60 ␮g g−1 in field 1.

Proline (␮g g−1 )

GABA (␮g g−1 )

2AP (␮g kg−1 )

3.4. Correlation between 2AP content, yield and yield components There was no overall correlation between yield and 2AP content. Only Aychade presented a high negative correlation between relative 2AP content and relative yield (R2 = 0.819, p < 0.001), indicating opposite effects of salinity on yield and aromatic quality for this variety. This was not the case for Fidji and Giano. There was however a high (p < 0.001) negative correlation between the relative 2AP content and TGW for the three cultivars (Fig. 3). This result, along with the common correlation found for the three cultivars between seasonal EC and TGW (Table 4), suggests that the increased 2AP content in the grains is closely linked to the reduction of TGW with salinity. This should mean that the increase in 2AP content with salinity results partially from a 2AP concentration mechanism in smaller size grains. In order to assess the importance of this mechanism, we computed the total 2AP weight per grain by multiplying 2AP content by TGW. The total 2AP weight per grain proved to be strongly (p < 0.01) correlated with mean EC during the crop season for Fidji and Giano, but not for Aychade (Table 7). Nevertheless, the relative 2AP weight per grain for the three cultivars was still positively correlated with mean EC during the early reproductive stage. Furthermore, Fidji also presented a significant correlation between ECveg and the total 2AP weight. 4. Discussion Several studies showed that rice becomes sensitive to salinity when EC of the soil solution exceeds 2000 ␮S cm−1 (Asch and Wopereis, 2001; Grattan et al., 2002). According to this threshold, the salinity conditions in our experiments could be ranked as optimal, with no salinity stress, in Field 1, and as stressing condition in Field 2; with low stress intensity in 2007 and moderate stress intensity in 2006. Our results show indeed that those levels

Table 7 Correlation coefficients from regression analyses between relative 2-acetyl-1pyrroline (2AP) content in grains and relative 2AP weight, per grain and mean EC during the crop season (ECcrop) and during the three main crop development stages (vegetative stage, ECveg, early reproductive stage, ECrep1, late reproductive stage, ECrep2). Variety

Stage

Relative 2AP content

Relative 2AP weight

Aychade

ECcrop ECveg ECrep1 ECrep2

0.908*** 0.898*** 0.943*** 0.670*

0.541 0.523 0.642* 0.413

Fidji

ECcrop ECveg ECrep1 ECrep2

0.899*** 0.907*** 0.910*** 0.565

0.803** 0.805** 0.840** 0.504

Giano

ECcrop ECveg ECrep1 ECrep2

0.786** 0.720** 0.834** 0.600*

0.596* 0.499 0.650* 0.573

* ** ***

p < 0.05. p < 0.01. p < 0.001.

Fig. 2. Relationship between the mean electrical conductivity during the crop season (ECcrop) and the relative 2-acetyl-1-pyrroline (relative 2AP) content in grains of the three varieties used in the experiments. Each point represents a sub-plot.

F. Gay et al. / Field Crops Research 117 (2010) 154–160

Fig. 3. Relationship between the thousand grain weight and the relative 2-acetyl1-pyrroline (relative 2AP) content in grains of the three varieties used in the experiments. Each point represents a sub-plot.

of salinity had a significant impact on grain yield, yield components and 2AP content in grains at harvest. Moreover, the stronger impact of EC level before flowering are consistent with the decrease in stress intensity recorded from sowing to harvest. However, the differences between years observed for these variables under nonstressed conditions, i.e. in Field 1, indicate other factors than salt affect yield components and 2AP content. This could be linked to differences in climatic conditions, mainly temperature and rainfall, between both experiments. Thus, the lower concentrations of 2AP in 2006 may be explained by the higher temperatures recorded during grain ripening and the delayed harvest due to heavy rains at the end of the crop season in 2006. This assumption is supported by the study of Itani et al. (2004) who evidenced a negative effect of high temperature after flowering on 2AP in grains, and by that of Champagne et al. (2005) who evidenced a decrease of aromatic quality of rice when harvest was delayed. We therefore used relative values of grain yield and of 2AP content in order to remove year variability and to focus on the effect of salt. Calculation of relative values of a given variable has proven to be useful for studying the effect of abiotic stress on plants (Lecoeur and Guilioni, 1998; Casadebaig et al., 2008). It makes possible to compare data obtained in different experimental conditions and to develop crop models (Casadebaig et al., 2008). The three varieties used in our study showed contrasting responses to salinity in terms of yield loss and yield components. Aychade and Fidji could be rated as highly and moderately sensitive genotype, respectively; yield losses under moderate salinity stress in 2006 were by 50 and 13%, respectively. Significant correlation between EC values and relative yield was evidenced for theses two varieties. Yield losses were mainly due to a significant decrease of individual grain weight (TGW) with salinity. For Aychade, reduction of TGW was combined with higher grain sterility rate (STER). These results are consistent with previous studies on the effect of salt on yield and yield components in rice (Asch et al., 1999; Zheng et al., 2001; Fabre et al., 2005). On the other hand, Giano could be considered as tolerant, with no yield loss under saline conditions and no significant correlation between EC values and relative yield. Nevertheless, TGW was also negatively correlated with salinity for this variety. In fact, lower grain weight was completely offset by more spikelets per panicle (SPK) and lower values of STER, resulting in higher yields in saline conditions for that variety. Lower values of STER with salinity were also observed for Fidji. This result is in opposition with the majority of the studies that found that STER is one of the most salt sensitive yield components of rice (Khatun

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and Flowers, 1995; Asch et al., 1999; Zheng et al., 2001). Further studies are required to understand this surprising results as our experiments were not specifically designed to study this point. The three varieties showed, however, a parallel increase of relative 2AP content in grains with salinity (Fig. 2). This result indicates that there is no systematic opposition between quantitive, i.e. yield, and qualitative performance in term of aroma. The opposite was even observed for Giano which achieved higher yields and higher 2AP content in saline conditions. TGW was in parallel the only yield component showing a significant negative correlation with salinity for the three varieties (Fig. 3). This correlation suggests that the increase of 2AP content with salinity was partially due to a lower dilution of 2AP in grain rather than to a direct effect on the total quantity of 2AP per grain. Nolasco et al. (2004) found a similar negative correlation between the concentration of tocopherol and seed weight in sunflower plants grown under different levels of intercepted radiation. This dilution effect of minor components or secondary metabolites in the main components of grain is frequently the basis of negative relationships found between yield and quality traits or grain composition (Triboi and Triboi-Blondel, 2002; Motzo et al., 2004). The explanation is that yield increase is mainly due to an increase in carbohydrate production and storage without necessarily a parallel increase of minor components (Triboi and Triboi-Blondel, 2002). On the opposite, abiotic stresses may result in an increase of minor over major component by affecting carbohydrate production or partitioning within the plant organs without reducing the accumulation of minor elements in the grain. These findings challenge the hypothesis about the direct relationship between 2AP biosynthesis and the mechanisms of response to osmotic stresses through proline metabolism as proposed by Yoshihashi et al. (2002). However, the positive correlation between total 2AP weight per grain and EC particularly at the early vegetative stage (Table 7) indicates that salinity also affected directly the production of 2AP. Proline indeed accumulates naturally in roots, leaves and grains of rice plants subjected to salinity stress (Lutts et al., 1999; Sultana et al., 1999; Hien et al., 2003). Accumulation of proline and other organic solutes is therefore considered to be a major mechanism in plant tolerance to osmotic stress (Delauney and Verma, 1993; Kishor et al., 1995; Hong et al., 2000). In our experiments, it is likely that high salinity levels before flowering increased proline level in shoots and leaves, which in turn led to increase 2AP biosynthesis. This final step could take place in leaves, presupposing that 2AP could be transported from leaves to grain. Another possibility is the synthesis of 2AP in grains from leaf proline that has been transported through the plant (Tamayo and Bonjoch, 2001). The recent work of Bradbury et al. (2008) suggested that 2AP may derive from a precursor of GABA, another molecule involved in plant response to stress. In our experiments, no clear correlation between proline and GABA contents and salinity level or 2AP content could be evidenced (Table 6). This result could be explained by the weak salinity stress after heading in our experiments. As mentioned above, the direct effect of salinity on 2AP biosynthesis likely occurred before heading. Then, further work should focus in particular on proline and 2AP metabolism in leaves and their relationships with the accumulation of 2AP in grains. 5. Conclusion This study confirms the hypothesis that soil salinity could have a positive impact on the 2AP content of mature rice grains. It shows however that the mechanisms involved in this response are more complex than initially assumed. Indeed, the increase of 2AP with salinity was mainly due to modification of some yield components and physical grain characteristics rather than to direct effect of salinity on 2AP biosynthesis. Our results show that the relationship between yield and aromatic quality, assessed by 2AP content in

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grains, is not simple too. Thus, the increase in 2AP content in grains was not systematically associated with yield loss, thanks to the compensation mechanism between yield components. This work therefore highlights the importance of analysing yield and grain quality characteristic build-up jointly, to improve understanding of the effect of growing conditions on the physical and chemical characteristics of grains at harvest. Acknowledgements This research was funded by the Office National Interprofessionnel des Grandes Cultures (ONIGC) as a part of the “Plan de Relance de la Filiere Riz Camarguaise” project. Thanks are due to Helene Marrou for the management of 2007 experiment, and to the staff of the Centre Franc¸ais du Riz (CFR) for their technical assistance. We would also like to thank Région Languedoc Roussillon and Cirad for supporting the doctoral fellowship of the author I. Maraval. References Arai, E., Itani, T., 2000. Effects of early harvesting of grains on taste characteristics of cooked rice. Food Sci. Technol. Res. 6, 252–256. Asch, F., Dingkhun, M., Wittstock, C., Doerffling, K., 1999. Sodium and potassium uptake of rice panicles as affected by salinity and season in relation to yield and yield components. Plant Soil 207, 133–145. Asch, F., Wopereis, M.C.S., 2001. Responses of field-grown irrigated rice cultivars to varying levels of floodwater salinity in a semi-arid environment. Field Crops Res. 70, 121–137. Bradbury, L.M.T., Gillies, S.A., Brushett, D.J., Waters, D.L.E., Henry, R.J., 2008. Inactivation of an aminoaldehyde dehydrogenase is responsible for fragrance in rice. Plant Mol. Biol. 68, 439–449. Bray, E., 1997. Plant responses to water deficit. Trends Plant Sci. 2 (2), 48–54. Buttery, R.G., Ling, L.C., 1982. 2-Acetyl-1-pyrroline: an important aroma component of cooked rice. Chem. Ind., 958. Buttery, R.G., Ling, L.C., Juliano, B.O., Turnbaugh, J.G., 1983. Cooked rice aroma and 2-acetyl-1-pyrroline. J. Agric. Food Chem. 31, 823–826. Buu, B.C., 2000. Aromatic rices of Vietnam. In: Singh, R.K., Sigh, U.S., Khush, G.S. (Eds.), Aromatic Rices. Science Publishers, Enfield, New Hampshire, pp. 180–183. Calpe, C., 2004. International trade in rice, recent developments and prospects. In: Proceedings of the World Rice Research Conference, Tuskuba, Japan, 5–7 November 2004, pp. 492–494. Casadebaig, P., Debaeke, P., Lecoeur, J., 2008. Thresholds for leaf expansion and transpiration response to soil water deficit in a range of sunflower genotypes. Eur. J. Agric. 28, 646–654. Champagne, E.T., Bett-Garber, K.L., Thompson, J., Mutters, R., Grimm, C.C., McClung, A.M., 2005. Effects of drain and harvest dates on rice sensory and physicochemical properties. Cereal Chem. 82, 369–374. Champagne, E.T., 2008. Rice aroma and flavor: a literature review. Cereal Chem. 85 (4), 445–454. Cuny, H., Wery, J., Gauffres, F., 1998. Diagnosis of nitrate leaching risk in farmers fields with measurement of soil water potential and nitrate content of the soil solution. Agronomie 18, 521–535. Delauney, A.J., Verma, D.P.S., 1993. Proline biosynthesis and osmoregulation in plants. Plant J. 4 (2), 215–223. Fabre, D., Siband, P., Dingkhun, M., 2005. A new diagnostic tool for rice grain filling and its response to stress using grain population weight and size distribution. Field Crops Res. 92, 11–16. FAO, 2001. In: Duffy, R. (Ed.), Specialty Rices of the World: Breeding, Production and Marketing. Science Publishers, Enfield, New Hampshire. Fitzgerald, M.A., Hamilton, N.R.S., Calingacion, M.N., Verhoeven, H.A., Butardo, V.M., 2008a. Is there a second fragrance gene in rice? Plant Biot. J. 6, 416–423. Fitzgerald, T.L., Waters, D.L.A., Henry, R.J., 2008b. The effect of salt on betaine aldehyde dehydrogenase transcript levels and 2-acetyl-1-pyrroline concentration in fragrant and non-fragrant rice (Oryza sativa). Plant Sci.. Gay, F., Hien, P.P., Thu Huong, N.T., Buu, B.C., Quoc, H.T., 2006. Investigation on sources of variability in aromatic quality of a famous traditional scented rice variety grown in Mekong Delta. In: Proceedings of the 2nd International Rice Research Congress, New Delhi, India, 9–13 October 2006, p. 121.

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