Key words: Brassica napus, fatty acid composition, intact single seeds, NIRS, oil content, seed weight

Transcription

1 Euphytica 106: 79 85, Kluwer Academic Publishers. Printed in the Netherlands. 79 Estimation of seed weight, oil content and fatty acid composition in intact single seeds of rapeseed (Brassica napus L.) by near-infrared reflectance spectroscopy Leonardo Velasco, Christian Möllers & Heiko C. Becker Institut für Pflanzenbau und Pflanzenzüchtung, Georg-August-Universität, Von-Siebold-Str. 8, D Göttingen, Germany; ( Present address: Instituto de Agricultura Sostenible (CSIC), Apartado 4084, E-14080, Córdoba, Spain) Received 16 March 1998; accepted 3 October 1998 Key words: Brassica napus, fatty acid composition, intact single seeds, NIRS, oil content, seed weight Abstract The potential of near-infrared reflectance spectroscopy (NIRS) for the simultaneous analysis of seed weight, total oil content and its fatty acid composition in intact single seeds of rapeseed was studied. A calibration set of 530 single seeds was analysed by both NIRS and gas-liquid chromatography (GLC) and calibration equations for the major fatty acids were developed. External validation with a set of 75 seeds demonstrated a close relationship between NIRS and GLC data for oleic (r = 0.92) and erucic acid (r = 0.94), but not for linoleic (r = 0.75) and linolenic acid (r = 0.73). Calibration equations for seed weight and oil content were developed from a calibration set of 125 seeds. A gravimetric determination was used as reference method for oil content. External validation revealed a coefficient of correlation between NIRS and reference methods of 0.92 for both traits. The performance of the calibration equations for oleic and erucic acid was further studied by analysing two segregating F 2 seed populations not represented in the calibration set. The results demonstrated that a reliable selection for both fatty acids in segregating populations can be made by using NIRS. We concluded that a reliable estimation of seed weight, oil content, oleic acid and erucic acid content in intact, single seeds of rapeseed is possible by using NIRS technique. Abbreviations: GLC, gas-liquid chromatography; NIRS, near-infrared reflectance spectroscopy; NITS, nearinfrared transmittance spectroscopy; R, reflectance; SD, standard deviation of the reference method values; SECV, standard error of cross-validation; SEP, standard error of performance. Introduction Near-infrared spectroscopy, working either in reflectance (NIRS) or transmittance (NITS), is widely used for the analysis of quality traits of intact seeds from different crops, especially cereals and oilseeds (Williams & Sobering, 1992). The technique is nondestructive, fast, cost-effective and permits the simultaneous analysis of many traits in a single measurement (Shenk & Westerhaus, 1993). Near-infrared analyses of intact seeds are commonly made on bulk samples of variable size, depending on the instrument and device used. Furthermore, instruments including single-seed sample holders are available (Downey, 1994). The use of these devices has permitted the development of single-seed calibration equations for the analysis of oil and protein content in corn and soybean (Orman & Schumann, 1992; Dyer & Feng, 1995; Abe et al., 1995), protein content in wheat (Abe et al., 1995) and oil content in meadowfoam (Limnanthes spp.; Patrick & Jolliff, 1997). Furthermore, Sato et al. (1995) pointed out the potential of NIRS to predict linoleic acid content in husked sunflower seeds. Nevertheless, NIRS technique has not been applied to the analysis of single seeds of rapeseed.

2 80 In this species, NIRS is currently used for the analysis of bulk samples of intact seeds for oil, protein and glucosinolate content, and the fatty acid composition of the seed oil (Velasco & Becker, 1998). These authors reported reliable analyses of oleic, linoleic, linolenic, and erucic acid by using very small samples of 60 mg intact seeds. A further improvement in the application of NIRS technique for rapeseed breeding would imply the reduction of the sample size to a single seed. The analysis of single seeds for oil content and fatty acid composition in a nondestructive way is of paramount importance in oilseed breeding. The advantages of single-seed selection for the fatty acid composition of the seed oil are widely recognised (Röbbelen, 1990). Furthermore, Silvela et al. (1989) demonstrated in maize (Zea mays L.) that a procedure based on selection between single kernels within an ear is more efficient to increase oil content than a procedure based on selection between plants in a row. The objective of this work was to study the potential of NIRS to estimate the oil content, its fatty acid composition, and the seed weight of intact, single seeds of rapeseed. Materials and methods Materials A total of 765 intact single seeds of B. napus were analysed by NIRS and used to develop and validate the various calibration equations. The seeds were chosen from a wide range of breeding materials. The corresponding plants were grown during the years 1994, 1995 or 1996, either in the field or in greenhouses. Furthermore, two F 2 seed populations segregating for the fatty acid composition of the seed oil were used to study the performance of the calibration equations for oleic and erucic acid in routine analysis. The first population was developed from the cross between the cultivar Wotan (zero erucic and about 60% oleic acid) and a high oleic acid mutant (about 80%) derived from this cultivar (Rücker & Röbbelen, 1995). The second population was developed from the cross between the cultivars Duplo (zero erucic) and Janetzki (about 40% erucic acid). The corresponding F 1 plants were grown in the greenhouse in 1994 and 1995, respectively. A total of 156 F 2 seeds of each population were analysed. NIRS analyses An special adapter for single-seed analysis was developed by using standard polyvinyl sheets of about 0.5 mm thickness and a cover of aluminium foil. The adapter was about 2 mm thick, with a total diameter of 37 mm and a central hole of 3 mm diameter. For NIRS scanning, the adapter was inserted in a NIRS standard ring cup (ref. IH-0307, Infrasoft International, Port Matilda, USA) and a single seed was placed in the central hole. The hole was sealed with aluminium foil. The absorbance spectra (log 1/R) from 400 to 2500 nm were recorded at 2 nm intervals on a monochromator NIR Systems model 6500 (NIR Systems, Inc., Silver Spring, MD). The method permitted the analysis of about 40 single seeds per hour. Mathematical procedures on the spectral information were carried out with ISI software, version 3.10 (Infrasoft International). Original reflectance spectra were corrected prior to calibration for oil content and individual fatty acids by applying a second derivative transformation, standard normal variate, and de-trend scatter correction. According to previous results in the analysis of bulk samples of Ethiopian mustard (Brassica carinata A. Braun; Velasco et al., 1997) only second derivative transformation was applied to the spectra before calibrating for seed weight. Second derivative was calculated from the log (1/R) spectra at gaps of 10 nm and a smoothing over segments of length 10 nm. The spectral region between 1460 and 1560 nm was excluded for calibration because the single-seed adapter itself showed strong absorption in this range. Consequently, calibration equations were developed by using the spectral information from 1100 to 1460 and from 1560 to 2500 nm and modified partial least squares (MPLS) regression. Cross validation was used to prevent overfitting (Shenk & Westerhaus 1993). Analysis of the seed oil content (reference method) Individual seeds were weighed on a lab balance model M2P (Sartorius, Göttingen, Germany) with a readability of mg, placed in previously-weighed 1 ml glass vials, 0.5 ml of a solution i-propanol:petrolether (2:3) were added to the vials and the seeds were finely crushed with an stainless steel rod. The vials were periodically stirred and they were centrifuged after 2 h. The supernatant was transferred into 5 ml vials. The extraction process was repeated four times, the last one overnight (about 12 h). The vials containing the defatted meal were weighed after the solvent

3 81 was completely evaporated. The total seed oil content was expressed as percentage of the seed weight on an as is basis. The moisture content of the individual seeds was not determined. The moisture content of the bulk samples from which the seeds were chosen was analysed by NIRS, ranging from about 3% to 6% of total seed weight. Analysis of the fatty acid composition of the seed oil (reference method) Single seeds were placed in cups of a round bottomed microtiter tray. Fifty µl of a solution 10% i-propanol in petrolether was added and the seeds were crushed with a stainless steel rod. The solvent was evaporated in a stream of warm air. Fifty µl of 0.5 m Na-methylate in methanol was added. After 20 min at room temperature, 200 µl i-octane was added. One hundred eighty µl of the upper phase was pipetted after keeping further 20 min into a septum vial and then 2.5 µl was injected at a split rate of 1:70 into a Perkin Elmer gas chromatograph model 8600 (Perkin Elmer Corporation, Norwalk, CT, USA) equipped with a fused silica capillary column FFAP, 25 m 0.25 mm 0.25 µm film thickness (Macherey & Nagel GmbH + Co. Kg, Düren, Germany). The oven, detector, and injector temperature were 200, 250, and 250 C, respectively. The carrier gas was nitrogen, at a pressure of 100 kpa. Individual fatty acids were expressed as% of the total fatty acids. Design of the experiment A total of 605 seeds were analysed by GLC and used for the development and validation of NIRS calibration equations for individual fatty acids. They were randomly divided into a calibration (n = 530) and a validation (n = 75) set. A previous study in rapeseed demonstrated that a calibration equation for oleic acid developed from a calibration set consisting exclusively of zero erucic acid samples was more efficient for the analysis of zero erucic/high oleic acid samples than an equation developed from a calibration set including both samples with and without erucic acid (Velasco et al., 1998). Accordingly, a set of 248 zero erucic acid seeds was extracted from the set of 605 seeds analysed by GLC, randomly divided into a calibration (n = 219) and validation set (n = 29) and used for the development of a second calibration equation for oleic acid content. After the calibration equations were developed, they were used to evaluate two F 2 segregating popu- Figure 1. External validation plots (n = 35) of the calibration equations for seed weight, expressed in mg (a), and oil content, expressed as% of the seed weight (b), in single intact seeds of rapeseed. Seed weight and oil content are expressed on an as is basis. lations described above, also analysed by GLC. The population segregating for high oleic acid content was analysed with both calibration equations for this fatty acid. One hundred sixty seeds not used in the study of individual fatty acids were analysed for total oil content and used for the development (n = 125) and validation (n = 35) of equations for seed weight and oil content. Results NIRS calibration Table 1 shows the cross-validation and external validation statistics for the calibration equations developed for seed weight, seed oil content and fatty acid composition in intact single seeds of rapeseed. Calibration equations for seed weight and oil content showed a close relationship between NIRS and reference values, with a coefficient of correlation of 0.92 in external validation. The ratio of SEP to the SD of the reference values was 0.41 and 0.39, respectively. Figure 1

4 82 Table 1. Cross-validation and external validation statistics of the NIRS calibration equations developed to estimate seed weight (mg), total oil content (% of seed weight), and percentage of fatty acids (% of the total fatty acids) in single intact seeds of rapeseed a Cross-validation b External validation b Trait n Mean Range r SECV n Mean Range r SEP SEP/SD Seed weight Oil content Oleic acid Oleic acid c Linoleic acid Linolenic acid Erucic acid a Seed weight and oil content on an as is basis. b SECV = standard error of cross-validation, SEP = standard error of performance, SD = standard deviation of the reference method values. c Calibration equation for oleic acid from a calibration set including only zero-erucic acid seeds, extracted from the original calibration set (n = 530). shows the validation plots of the calibration equations for both traits. Reliable calibration equations were developed for oleic (r = 0.93, SEP/SD = 0.37) and erucic acid (r = 0.94, SEP/SD = 0.34), but not for linoleic (r = 0.75, SEP/SD = 0.65) and linolenic acid (r = 0.73, SEP/SD = 0.70). The additional calibration equation for oleic acid developed from a calibration set containing exclusively zero-erucic acid seeds showed a similar performance (r = 0.91; SEP/SD = 0.42) to the equation for this fatty acid developed within the whole range of values. Figure 2 shows the external validation plots of the calibration equations for oleic (both whole and restricted calibration set) and erucic acid. In the latter, the calibration equation predicted negative erucic acid values for some of the zero erucic seeds (Figure 2c). These negative values have to be interpreted in the light of NIRS errors, defined as differences between estimated and actual values. For a trait having zero as actual value, NIRS estimation will result in either a positive or a negative figure. Analysis of F 2 populations Two populations of F 2 seeds were analysed by both NIRS and GLC in order to test the reliability of the calibration equations for individual fatty acids in the analysis of populations not used in the calibration/validation process. The first population derived from a cross between two zero-erucic acid lines containing about 60% and 80% oleic acid, respectively. It was analysed for oleic acid content by using the two calibration equations previously developed, i.e., from the whole calibration set and from the zero-erucic set. In both cases, NIRS predictions were characterised by a high bias or systematic error, which has been previously reported in NIRS analysis of the fatty acid composition of the seed oil of rapeseed populations not represented in the calibration set (Velasco et al., 1998). The effect of bias led to an NIRS underestimation of oleic acid content, as shown in Figure 3a for the zero-erucic equation. The SEP (bias corrected) in the comparison of NIRS vs. GLC values was 9.0% with the equation developed from the whole calibration set and 2.8% with the equation developed from a zero-erucic calibration set, demonstrating clearly a better performance of the calibration equation developed from the zero-erucic calibration set for the analysis of zero erucic/high oleic acid seeds. Both values were very similar to the SEP obtained through external validation of the respective calibration equations (Table 1). The second population was obtained from a cross between a zero-erucic line and a line with about 40% of this fatty acid. Figure 3b shows the scatter plot of NIRS vs. GLC values for erucic acid in this population. NIRS estimations were also characterised by a high bias, resulting in an overestimation of erucic acid content. The SEP (bias corrected) was 8.1%, slightly higher than the SEP obtained in external validation (Table 1). Discussion The seeds of rapeseed are extremely small in comparison with other crops for which NIRS/NITS analyses on single seeds have been previously reported, e.g. maize, soybean or wheat. Seed weight in the 160 seeds used in study for the calibrations of seed weight and oil

5 83 Figure 3. Scatter plots of F 2 populations of single seeds segregating for oleic acid (a) and erucic acid (b), respectively, analysed by both NIRS and GLC. Individual fatty acids are expressed as% of the total fatty acids. Figure 2. External validation plots of the calibration equations for oleic acid (a = original validation set, n = 75; b = validation set extracted from the original, including only the zero-erucic acid seeds, n = 29) and erucic acid (c; n = 75) in single intact seeds of rapeseed. Individual fatty acids are expressed as% of the total fatty acids. content ranged from 2.8 to 8.6 mg. As an example, the typical seed weight of soybean cultivars falls within the range of 120 to 280 mg (Hume et al., 1985). Patrick & Jolliff (1997) analysed the oil content in meadowfoam seeds ranging from 3 to 32 mg by NITS. They found a considerably higher NITS error in the analysis of seeds of under 5 mg weight. According to these results, the small seed weight of rapeseed appeared to represent a major limitation for the analysis of single seeds by NIRS. Nevertheless, the results obtained in the calibration equation for oil content were very similar to those obtained in meadowfoam by using NITS (Patrick & Jolliff, 1997). These authors developed two calibration equations for this trait, obtaining a coefficient of correlation between NITS and reference method of 0.95 in cross-validation (as compared with 0.94 in rapeseed, Table 1) and a SECV of 3.6% (ratio SECV to SD of 0.33 as compared with 0.35 in rapeseed, data not shown) in the best one. Therefore, it is concluded that the small seed size of rapeseed is not a limitation for the reliable analysis of oil content in single seeds by NIRS. A comparison of the precision and reliability obtained in the analysis of oil content in rapeseed with the previous studies in maize or soybean is not possible, because either the authors did not report the results obtained (Dyer & Feng, 1995) or these were incompletely reported (Orman & Schumann, 1992). The latter authors found a coefficient of correlation between NITS and reference method of 0.87 in crossvalidation and an SECV of 1.3% in the analysis of maize kernels by NITS. Nevertheless, the mean value of oil content and standard deviation of the calibration set was not reported.

6 84 As expected, NIRS estimation of oil content in single seeds of rapeseed showed a higher error than the estimation of this trait in bulk samples. Daun et al. (1994), using a similar NIRS instrument to the one used in this work but a sample size of 120 g, reported an r of 0.99 in validation and a ratio of SEP to SD of Very similar statistics were obtained with reduced sample size, for example 12 g in rapeseed (Biston et al., 1987), 3 g and 60 mg in Ethiopian mustard (Velasco, 1996). These results were considerably more accurate than those obtained in external validation of the single-seed equation, i.e. r of 0.92 and ratio SEP to SD of Nevertheless, the advantages that the possibility of analysing the total oil content in a single seed of rapeseed by NIRS offers to the plant breeders largely compensates for the loss of accuracy. As far as we know this is the first NIRS calibration equation developed for the estimation of the weight of single seeds. The accuracy of this equation was very similar to that obtained by Velasco et al. (1997) in the equation for 1000-seed weight in bulk samples (3 g) of Ethiopian mustard. The authors used a similar range of seed weight (1000-seed weight between 1.1 and 8.3 g in validation), reporting an r of 0.93 in external validation (vs in single seeds) and SEP of 0.61 g (vs mg in the single-seed equation). In that work, the existence of correlations between seed size and major traits such as oil or protein content was suggested as a possible factor contributing to NIRS discrimination of different values of seed weight. Similarly, Vollmann et al. (1997), found that a significant negative correlation between oil content and seed size could contribute to NIRS analysis of seed weight in bulk samples of Camelina sativa. Nevertheless, no significant correlation between oil content and seed size was found in the set of single seeds of rapeseed used for NIRS calibration of seed weight (r = 0.08). Therefore, NIRS discrimination of seed weight was probably caused by differences in total absorbance or by the detection of spectral changes associated to the relative occupation of the adapter hole by the seed. The results obtained in the calibration, external validation and further application in routine analysis of the calibration equations for oleic and erucic acid demonstrated a high reliability for their application in plant breeding. Nevertheless, the reliability of the calibration equations for linoleic and linolenic acid content was considerably lower, and they can not be considered as adequate to be applied in routine analyses. A previous study on the analysis of the fatty acid composition of bulk intact seed samples of rapeseed by NIRS (Velasco & Becker, 1998) demonstrated that the reduction of the sample size from 3 g to 60 mg had a more detrimental effect on the calibration equations for linoleic and linolenic acid than on the equations for oleic and erucic acid, which resulted scarcely affected. The authors suggested the narrower range of variation for linoleic and linolenic acid in the calibration set as the possible explanation for the higher susceptibility to the reduction of the sample size. In the development of NIRS calibration equations for individual fatty acids from 60 mg samples of intact rapeseed, Velasco & Becker (1998) obtained a coefficient of correlation between NIRS and GLC in crossvalidation of 0.98 for oleic and erucic acid (vs in single seeds) and a ratio SECV to SD of 0.20 for both fatty acids, as compared with a ratio of 0.33 and 0.35 for oleic and erucic acid, respectively, obtained in the single-seed calibration equations. Therefore, the loss of accuracy derived from the use of single seeds was relatively small, taking into account the about 10-fold reduction of sample size. Parameters of accuracy and reliability of calibration equations for individual fatty acids in single seeds of other oilseeds have not been reported. The application of the calibration equations for oleic and erucic acid to the evaluation of two populations not represented in the calibration sets revealed a close relationship between NIRS and GLC values. These results demonstrate that NIRS has a great potential for single-seed selections selection for these fatty acids. For example, in the cross for erucic acid content 1 out of 16 seeds are expected to be free of this fatty acid. These genotypes can be more clearly identified by GLC, but even with NIRS they can be easily selected after a pre-screening that would only include few other genotypes (Figure 3b). NIRS estimations showed in both cases a certain bias or systematic error; whereas oleic acid was systematically underestimated, erucic acid was systematically overestimated (Figure 3). A previous study on NIRS analysis of fatty acids in bulk samples of rapeseed reported the presence of a high bias in the analysis of samples from populations not represented in the calibration process (Velasco et al., 1998). They were successful in reducing drastically the bias by including a few samples of the new population into the calibration set and developing new calibration equations. A similar strategy could be also used in the analysis of single seeds. Nevertheless, the presence of bias is not a major problem in plant breeding screenings, since it does not affect the relative classification of the samples.

7 85 The possibility of analysing intact single seeds of rapeseed for oil content and percentage of oleic and erucic acid with a high degree of reliability by a fast, nondestructive and cost-effective NIRS technique is very advantageous in rapeseed breeding. Programmes focused on the modification of the seed oil composition demand large numbers of chromatographic analyses by the half-seed technique (Downey & Harvey, 1963). Such analyses are rather tedious and timeconsuming, demanding 1) to germinate the seeds, 2) to remove a cotyledon, 3) to extract and methylate its oil and 4) to separate and quantify the individual fatty acids by chromatography. For large screenings for oleic and erucic acid content, where savings in time and costs together with a reasonable reliability are more important than a very high accuracy, this process may be avoided by using NIRS technique. Even when a more accurate selection is desired, a combination of NIRS pre-screening followed by further GLC halfseed analyses on selected seeds would help to reduce considerably time and costs. In conclusion, the NIRS calibration equations developed in this study permit the simultaneous analysis of seed weight, oil content, oleic and erucic acid content of the seed oil in a single intact seed of rapeseed in a nondestructive, fast, cost-effective and reliable way. Their application in plant breeding will enable large screenings for oil content and specific fatty acid profiles at a single-seed level, which opens up a new way in rapeseed breeding for seed quality. Acknowledgements Christine Reuter provided skilful technical assistance. The first author was supported by a grant from the Dirección General de Enseñanza Superior (Ministerio de Educación y Cultura, Spain). References Abe, H., T. Kusama, S. Kawano & M. Iwamoto, Nondestructive determination of protein content in a single kernel of wheat and soybean by near infrared spectroscopy. In: A.M.C. Davies & P. Williams (Eds), Near Infrared Spectroscopy: the Future Waves, pp NIR Publications, Chichester, UK. Biston, R., P. Dardenne, M. Cwikowski, J.-P. Wathelet & M. Severin, Analysis of quality parameters of whole rapeseed by NIRS. In: J.-P. Wathelet (Ed), Glucosinolates in Rapeseed: Analytical Aspects, pp Martinus Nijhoff, Dordrecht, The Netherlands. Daun, J.K., K.M. Clear & P. Williams, Comparison of three whole seed near-infrared analyzers for measuring quality components of canola seed. J Am Oil Chem Soc 71: Downey, G., Grain analysis by NIRS: is the harvest in?. In: G.D. Batten, P.C. Flinn, L.A. Welsh & A.B. Blakeney (Eds), Leaping Ahead with Near Infrared Spectroscopy, pp Royal Australian Chemical Institute, Lorne, Australia. Downey, R.K. & B.L. Harvey, Methods of breeding for oil quality in rape. Can J Plant Sci 43: Dyer, D.J. & P. Feng, Near infrared applications in the development of genetically altered grains. In: A.M.C. Davies & P. Williams (Eds), Near Infrared Spectroscopy: the Future Waves, pp NIR Publications, Chichester, UK. Hume, D.J., S. Shanmugasundaram & W. D. Beversdorf, Soybean (Glycine max (L.) Merrill). In: R.J. Summerfield & E.H. Roberts (Eds), Grain Legume Crops, pp Williams Collins Sons & Co., London. Orman, B.A. & R.A. Schumann, Jr., Nondestructive singlekernel oil determination of maize by near-infrared transmission spectroscopy. J Am Oil Chem Soc 69: Patrick, B.E. & G.D. Jolliff, Nondestructive single-seed oil determination of meadowfoam by near-infrared transmission spectroscopy. J Am Oil Chem Soc 74: Röbbelen, G., Mutation breeding for quality improvement. A case study for oilseed crops. Mutation Breeding Review, no. 6, FAO/IAEA Division of Nuclear Techniques in Food and Agriculture. Vienna, Austria. Rücker, B. & G. Röbbelen, Development of high oleic acid rapeseed. 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De Haro, Use of near infrared reflectance spectroscopy to screen Ethiopian mustard for seed weight. Agron J 89: Velasco, L. & H.C. Becker, Estimating the fatty acid composition of the oil in intact-seed rapeseed (Brassica napus L.) by near-infrared reflectance spectroscopy. Euphytica 101: Velasco, L., A. Schierholt & H.C. Becker, Performance of near infrared reflectance spectroscopy (NIRS) in routine analysis of C18 unsaturated fatty acids in intact rapeseed. Fett/Lipid 100: Vollmann, J., A. Damboeck, S.J.H. Kuyt & P. Ruckenbauer, Determination of camelina seed weight using near-infrared reflectance spectroscopy. Plant Var Seeds 10: Williams, P. & D. Sobering, Whole-seed grain analysis by near-infrared transmittance and reflectance: a comparison. In: K.I. Hildrum, T. Isaksson, T. Næs & A. Tandberg (Eds), Near Infra-red Spectroscopy. Bridging the Gap between Data Analysis and NIR Applications, pp Ellis Horwood, Chichester, UK.

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