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Evaluation of seed components of wild soybean (Glycine soja) collected in Japan using near-infrared reflectance spectroscopy

Published online by Cambridge University Press:  23 January 2017

Chi-Do Wee ,
Masatsugu Hashiguchi ,
Genki Ishigaki ,
Melody Muguerza ,
Chika Oba ,
Jun Abe ,
Kyuya Harada  and
Ryo Akashi
Chi-Do Wee
Affiliation:
Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki 889-2192, Japan
Masatsugu Hashiguchi
Affiliation:
Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
Genki Ishigaki
Affiliation:
Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
Melody Muguerza
Affiliation:
Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
Chika Oba
Affiliation:
Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
Jun Abe
Affiliation:
Graduate School of Agriculture, Hokkaido University, Sapporo 060-8589, Japan
Kyuya Harada
Affiliation:
Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan
Ryo Akashi*
Affiliation:
Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki 889-2192, Japan Faculty of Agriculture, University of Miyazaki, Miyazaki 889-2192, Japan
*
*Corresponding author. E-mail: [email protected]
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Abstract

Seed composition, including the protein, lipid and sucrose contents of 334 accessions of wild soybean (Glycine soja) collected in Japan, was evaluated using near-infrared reflectance spectroscopy (NIRS) technology. The distribution of protein, lipid and sucrose contents and correlations among these three classes of seed components were determined. Protein, lipid and sucrose levels ranged in accessions from 48.6 to 57.0, 9.0 to 14.3 and 1.24 to 3.53%, respectively. Average levels of protein, lipid and sucrose in the accessions were 54, 11 and 2.5%, respectively. High negative correlations were observed between the protein and lipid contents, and the protein and sucrose contents. Mean levels of the three constituents were compared among collection sites classified by climatic conditions. The total protein content of accessions from regions with a high annual mean temperature was high. The protein content of accessions from the II-1 region was higher than those from the III-3 region, and the sucrose content from the II-1 region was lower than those from regions III-2 and IV-3. The lipid content of plants from the II-1 region was lower than those from other regions, and the accessions in region II had a higher protein content and lower sucrose and lipid contents than the other regions. These results provide diverse and wide-ranged protein, lipid and sucrose contents information of Japanese wild soybean resources according to climatic region; thus, providing a foundation for the future development and selection of new soybean varieties with desired traits in global environmental changes.

Keywords

wild soybeanproteinlipidsucroseNIRSclimatic regions
Type
Research Article
Information
Plant Genetic Resources , Volume 16 , Issue 2 , April 2018 , pp. 94 - 102
Copyright
Copyright © NIAB 2017 

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References

Bellaloui, N, Smith, JR, Ray, JD and Gillen, AM (2009) Effect of maturity on seed composition in the early soybean production system as measured on near-isogenic soybean lines. Crop Science 49: 608–620.CrossRefGoogle Scholar
Brim, CA and Burton, JW (1979) Recurrent selection in soybeans (Glycine max). 2. Selection for increased percent protein in seeds. Crop Science 19: 494–498.CrossRefGoogle Scholar
Broich, SL and Palmer, RG (1980) A cluster analysis of wild and domesticated soybean phenotypes. Euphytica 29: 23–32.Google Scholar
Brumm, TJ and Hurburgh, CR (1990) Estimating the processed value of soybeans. Journal of American Oil Chemists’ Society 67: 302–307.Google Scholar
Brumm, TJ and Hurburgh, CR (2006) Changes in long-term soybean compositional patterns. Journal of American Oil Chemists’ Society 83: 981–AR981.Google Scholar
Buning, PH and Diller, M (2000) Rapid analysis of foods using near-infrared spectrometry (NIRS): development, use and new possibilities. Ernahrungs Umschau. 47: 15–20.Google Scholar
Carter, TE Jr, Nelson, RL, Sneller, C and Cui, Z (2004) Genetic diversity in soybean. In: Boerma, HR, Specht, JE eds. Soybean: Improvement, Production, and Uses, 3rd edn. Madison: American Society for Agronomy, pp. 303–416.Google Scholar
Carver, BF, Burton, JW, Carter, TE and Wilson, RF (1986) Response to environmental variation of soybean lines selected for altered unsaturated fatty acid composition. Crop Science 26: 1176–1180.Google Scholar
Choung, MG (2010) Determination of sucrose content in soybean using near-infrared reflectance spectroscopy. Journal of the Korean Society for Applied Biological Chemistry 54: 478–484.Google Scholar
Chung, G and Singh, RJ (2008) Broadening the genetic base of soybean; a multiciplinary approach. Plant Science 27: 295–341.Google Scholar
Dardanelli, JL, Balzarini, M, Martinez, MJ, Cuniberti, M, Resnik, S, Ramunda, SE, Herrero, R and Baigorri, H (2006) Soybean maturity groups, environments, and their interaction define mega-environments for seed composition in Argentina. Crop Science 46: 1939–1947.CrossRefGoogle Scholar
Dong, YS, Zhuang, BC, Zhao, LM, Sun, H and He, MY (2001) The genetic diversity of annual wild soybeans grown in China. Theoretical and Applied Genetics 103: 98–103.Google Scholar
Dornbos, DL and Mullen, RE (1992) Soybean seed protein and oil contents and fatty-acid composition adjustments by drought and temperature. Journal of the American Oil Chemists’ Society 69: 228–231.Google Scholar
Font, RM and de Haro-Bailon, A (2006) The use of near-infrared spectroscopy (NIRS) in the study of seed quality components in plant breeding programs. Industrial Crops and Products 24: 307–313.CrossRefGoogle Scholar
Guan, R, Chang, R, Li, Y, Wang, L, Liu, Z and Qiu, L (2010) Genetic diversity comparison between Chinese and Japanese soybeans (Glycine max (L.) Merr.) revealed by nuclear SSRs. Genetic Resources and Crop Evolution 57: 229–242.CrossRefGoogle Scholar
Hajjar, R and Hodgkin, T (2007) The use of wild relatives in crop improvement; a survey of developments over the last 20 years. Euphytica 156: 1–13.Google Scholar
Han, Y, Zhao, X, Liu, D, Li, Y, Lightfoot, D, Yang, Z, Zhao, L, Zhou, G, Wang, Z, Huang, L, Zhang, Z, Qiu, L, Zheng, H and Li, W (2016) Domestication footprints anchor genomic regions of agronomic importance in soybeans. New Phytologist 209: 871–884.Google Scholar
Hou, A, Chen, P, Shi, A, Zhang, B and Wang, YJ (2009) Sugar variation in soybean seed assessed with a Rapid Extraction and Quantification Method. International Journal of Agronomy 2009: doi:10.1155/2009/484571, 8 p.Google Scholar
Hurburgh, CR (1994) Long-term soybean composition patterns and their effect on processing. Journal of the American Oil Chemists’ Society 71: 1425–1427.Google Scholar
Hurburgh, CR, Brumm, TJ, Guinn, JM and Hartwig, RA (1990) Protein and oil patterns in united-states and world soybean markets. Journal of the American Oil Chemists’ Society 67: 966–973.Google Scholar
Hymowitz, T (1970) On the domestication of the soybean. Economic Botany 24: 408–421.Google Scholar
Hyten, DL, Song, QJ, Zhu, Y, Choi, IY, Nelson, RL and Costa, JM (2006) Impacts of genetic bottlenecks on soybean genome diversity. Proceeding of the National Academy of Science 103: 16666–16671.Google Scholar
Joshi, T, Valliyodan, B, Wu, J, Lee, S, Xu, D and Nguyen, HT (2013) Genomic differences between cultivated soybean, G. max and its wild relative G. soja . BMC Genomics 14 (Suppl. 1): S5.Google Scholar
Kaga, A, Shimizu, T, Watanabe, S, Tsubokura, Y, Katayose, Y, Harada, K, Vaughan, DA and Tomooka, N (2012) Evaluation of soybean germplasm conserved in NIAS genebank and development of mini core collections. Breeding Science 61: 566–592.Google Scholar
Kim, MY, Lee, S, Van, K, Kim, TH, Jeong, SC and Choi, I (2010) Whole-genome sequencing and intensive analysis of the undomesticated soybean genome. Proceeding of the National Academy of Sciences of the United States of America 107: 22032–22037.CrossRefGoogle Scholar
Kim, KS, Diers, BW, Hyten, DL, Roufmian, MA, Shannon, JG and Nelson, RL (2012) Identification of positive yield QTL alleles from exotic soybean germplasm in two backcross populations. Theoretical and Applied Genetics 125: 1353–1369.Google Scholar
Kumar, V, Rani, A, Goyal, L, Dixit, AK, Manjaya, JG, Dev, J and Swamy, M (2010) Sucrose and raffinose family oligosaccharides (RFOs) in soybean seeds as influenced by genotype and growing location. Journal of Agricultural and Food Chemistry. 58: 5081–5085.Google Scholar
Kumar, V, Rani, A, Goyal, L, Pratap, D, Billore, SD and Chauhan, GS (2011) Evaluation of vegetable-type soybean for sucrose, taste-related amino acids, and isoflavone contents. International Journal of Food Properties 14: 1142–1151.Google Scholar
Kuroda, Y, Kaga, A, Tomooka, N and Vaughan, D (2006) Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation. Molecular Ecology 15: 959–974.CrossRefGoogle ScholarPubMed
Lee, J, Yu, J, Hwang, Y, Blake, S, So, Y and Lee, G (2008) Genetic diversity of wild soybean accessions from South Korea and other countries. Crop Science 48: 606–616.Google Scholar
Lee, JD, Shannon, JG and Choung, MG (2011) Application of nondestructive measurement to improve soybean quality by near infrared reflectance spectroscopy. Soybean Applications and Technology 16: 287–304.Google Scholar
Li, Y, Zhao, S, Ma, J, Li, D, Yan, L, Li, J, Qi, X, Guo, X, Zhang, L, He, W, Chang, R, Liang, Q, Guo, Y, Ye, C, Wang, X, Tao, Y, Guan, R, Wang, J, Liu, Y, Jin, L, Zhang, X, Liu, Z, Zhang, L, Chen, J, Wang, K, Nielson, R, Li, R, Chen, P, Li, W, Reif, J, Purugganan, M, Wang, J, Zhang, M, Wang, J and Qiu, L (2013) Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing. BMC Genomics 14: 579.Google Scholar
Maughan, PJ, Saghai, MA and Buss, GR (1995) Microsatellite and amplified sequence length polymorphisms in cultivated and wild soybean. Genome 38: 715–723.Google Scholar
Maughan, PJ, Maroof, MA and Buss, GR (2000) Identification of quantitative trait loci controlling sucrose content in soybean (Glycine max). Molecular Breeding 6: 105–111.Google Scholar
Mizuno, K, Ishiguri, T, Kondo, T and Kato, T (1988) Prediction of forage compositions and sheep responses by Near Infrared Reflectance spectroscopy. I. Evaluation of accuracy. Bulletin of the National Grassland Research Institute 38: 35–47. (Japanese with English Summary).Google Scholar
Openshaw, SJ and Hadley, HH (1978) Maternal effects on sugar content in soybean seeds. Crop Science 18: 581–584.Google Scholar
Piper, EL and Boote, KJ (1999) Temperature and cultivar effects of soybean seed oil and protein concentration. Journal of the American Oil Chemists’ Society 76: 1233–1241.Google Scholar
Sato, T, Zahlner, V, Berghofer, E, Losak, T and Vollmann, J (2012) Near-infrared reflectance calibration for determining sucrose content in soybean breeding using artificial reference samples. Plant Breeding 131: 531–534.Google Scholar
Southgate, DAT (1971) A procedure for the measurement of fats in foods. Journal of the Science of Food and Agriculture 22: 590–591.Google Scholar
Wilcox, JR and Cavins, JF (1995) Backcrossing high seed protein to a soybean cultivar. Crop Science 35: 1036–1041.Google Scholar
Xu, DH, Abe, J, Gai, JY and Shimamoto, Y (2002) Diversity of chloroplast DNA SSRs in wild and cultivated soybeans: evidence for multiple origins of cultivated soybean. Theoretical and Applied Genetics 105: 645–653.Google Scholar
Yaklich, RW, Vinyard, B, Camp, M and Douglass, S (2002) Analysis of protein and oil from soybean northern and southern region uniform tests. Crop Science 42: 1504–1515.Google Scholar
Yoshino, M (1980) The climatic regions of Japan. Erdkunde 34: 81–87.Google Scholar
Zhao, S, Zheng, F, He, W, Wu, H, Pan, S and Lam, H (2015) Impact of nucleotide fixation during soybean domestication and improvement. BMC Plant Biology 15: 81.Google Scholar
Zhou, XL, Carter, TE, Cui, ZL, Miyazaki, S and Burton, JW (2002) Genetic diversity patterns in Japanese soybean cultivars based on coefficient of parentage. Crop Science 42: 1331–1342.CrossRefGoogle Scholar
Zhou, L, Wang, S, Jian, J, Geng, Q, Wen, J, Song, Q, Wu, Z, Li, G, Liu, Y, Dunwell, J, Zhang, J, Feng, J, Niu, Y, Zhang, L, Ren, W and Zhang, Y (2015) Identification of domestication-related loci associated with flowering time and seed size in soybean with the RAD-seq genotyping method. Scientific Reports 5: 9350.Google Scholar
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