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Effect of variety and environment on the contents of crude nutrients and amino acids in organically produced cereal and legume grains

  • Stephanie WittenEmail author
  • Herwart Böhm
  • Karen Aulrich
Article
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Abstract

Cereals and home-grown grain legumes are main feedstuffs for monogastric animals. Thus, knowledge on variations of their crude nutrient and amino acid composition is of great interest in animal nutrition. Genetic and environmental factors are known to be able to affect the nutrient composition of crops. Thus, the aim of the study was to analyse a selection of grains of organic cereal and grain legume species for their crude nutrient and amino acid contents and to determine the effect of variety and environmental conditions on the variations. Furthermore, the use of equations to predict amino acid contents from the crude protein content of cereals and grain legumes was tested. The contents of the crude nutrients and 18 amino acids of 835 samples of ten different cereal and grain legume species were analysed. Selected nutrients were subjected to correlation analyses. Furthermore, generalised linear models with multiple comparisons were conducted to assess the effect of species as well as of variety, harvest site and harvest year on the analysed ingredients. The contents of all crude nutrients and amino acids varied depending on the species and the considered nutrient. The lowest variation coefficients (1.3–2.6% in cereals and 3.1, 3.5 and 6.8% in field peas, field beans and blue lupins, respectively) were observed for the contents of nitrogen-free extracts. The crude protein contents varied widely, specifically in winter rye (coefficient of variation: CV = 17.4%). However, compared to table values, the cereals and grain legumes of the present study tended to contain low amounts of crude protein and high amounts of starch. Due to the wide variations, there is no distinct consistency between table values and the results of this study. High negative correlations between starch and crude protein contents were observed in eight species. Furthermore, the amino acid profile of cereals and grain legumes varied depending on the crude protein contents. Higher crude protein contents were often related to lower contents of several essential amino acids in favour of glutamine/glutamic acid, proline and phenylalanine in cereals as well as of arginine in grain legumes. Furthermore, variety, harvest site and harvest year affected the contents of the analysed ingredients depending on the species. However, the environmental factors had a greater influence than the variety. The observed variations must be regarded in diet formulation. Equations can be used to estimate the amino acid contents of cereals and grain legumes from their crude protein content. However, additional analysis results are needed to improve the predictability with equations.

Keywords

Organic farming Harvest site Cultivation year Protein 

Notes

Funding

The project was supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) under the Federal Programme for Ecological Farming and Other Forms of Sustainable Agriculture (Grant number 2811OE054).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

13165_2019_261_MOESM1_ESM.pdf (2.5 mb)
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References

  1. Abdel-Maksoud A, Yan F, Cerrato S, Coto C, Wang ZL, Waldroup PW (2010) Effect of dietary crude protein, lysine level and amino acid balance on performance of broilers 0 to 18 days of age. Int J Poult Sci 9:21–27 ISSN: 1682-8356CrossRefGoogle Scholar
  2. Agroscope (2011–2016) Feedbase - the Swiss Feed Database, University of Zurich (CH), Agroscope. https://www.feedbase.ch/. Accessed 25 June 2018
  3. Ajinomoto Animal Nutrition Group (2003–2013) Ajinomoto Heartland (since April 2018 Ajinomoto Animal Nutrition North America) amino acid database, http://www.aaalysine.com/. Last Acces 25th June 2018
  4. Ajinomoto Animal Nutrition Group (2014) Ajinomoto Eurolysine S.A.S. Laboratory Analysis Database, http://ajinomoto-eurolysine.com/feedstuffs-amino-acid-database.html, Last Access 25th of June 2018
  5. Blair R (2008) Nutrition and Feeding of Organic Poultry. CABI, Wallingford (UK).  https://doi.org/10.1079/9781845934064.0000
  6. Blok MC, Dekker RA (2017) Table ‘standardized ileal digestibility of amino acids in feedstuffs for poultry’. Wageningen Livestock Research.  https://doi.org/10.18174/426333
  7. Boisen S, Hvelplund T, Weisbjerg MR (2000) Ideal amino acid profiles as a basis for feed protein evaluation. Livest Prod Sci 64:239–251.  https://doi.org/10.1016/S0301-6226(99)00146-3 CrossRefGoogle Scholar
  8. Brookes G, Barfoot P (2018a) Environmental impacts of genetically modified (GM) crop use 1996–2016: impacts on pesticide use and carbon emissions. GM Crops Food 9:1–69.  https://doi.org/10.1080/21645698.2018.1476792 CrossRefGoogle Scholar
  9. Brookes G, Barfoot P (2018b) Farm income and production impacts of using gm crop technology 1996–2016. GM Crops Food 9:59–89.  https://doi.org/10.1080/21645698.2018.1464866 CrossRefGoogle Scholar
  10. Bryden WL, Li X, Ravindran G, Hew LI, Ravindran V (2009) Ileal digestible amino acid values in feedstuffs for poultry. Australian Government: Rural Industries Research and Development Corporation Publication No. 09/071 (AU). ISBN: 1 74151 870 9Google Scholar
  11. Burstin J, Gallardo K, Mir RR, Varshney RK, Duc G (2011) Improving protein content and nutrition quality (Chapter 20). In: Pratap A, Kumar J (Ed.), Biology and breeding of food legumes, International Crops Research Institutes of the Semi-Arid Tropics. CABI, Wallingford (UK). ISBN : 9781845937669Google Scholar
  12. Calcagno V (2013) Glmulti: model selection and multimodel inference made easy. R Package Version 1.0.7. https://cran.R-project.org/package=glmulti
  13. Casey R, Short MN (1981) Variation in amino acid composition of legumin from Pisum. Phytochemistry 20:21–23.  https://doi.org/10.1016/0031-9422(81)85210-7
  14. Casey R, Sharman JE, Wright DJ, Bacon JR, Guldager P (1982) Quantitative variability in Pisum seed globulins: its assessment and significance. Plant Food Hum Nutr 31:333–346.  https://doi.org/10.1007/BF01094045 CrossRefGoogle Scholar
  15. Cohen SA, Michaud DP (1993) Synthesis of a fluorescent derivatizing reagent, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate, and its application for the analysis of hydrolysate amino acids via high-performance liquid chromatography. Anal Biochem 211:279–287.  https://doi.org/10.1006/abio.1993.1270 CrossRefGoogle Scholar
  16. Dangour AD, Dodhia SK, Hayter A, Allen E, Lock K, Uauy R (2009) Nutritional quality of organic foods: a systematic review. Am J Clin Nutr 90:680–685.  https://doi.org/10.3945/ajcn.2009.28041 CrossRefGoogle Scholar
  17. Derbyshire E, Wright DJ, Boulter D (1976) Legumin and vicilin, storage proteins of legume seeds. Phytochemistry 15:3–24.  https://doi.org/10.1016/S0031-9422(00)89046-9 CrossRefGoogle Scholar
  18. DLG (2006–2010) DLG-Datenbank Futtermittel [DLG-Database for Feedstuffs], Deutsche Landwirtschafts-Gesellschaft eV http://www.datenbankfuttermittel.net, last access 11th July 2018
  19. DLG (2014). DLG-Futterwerttabellen Schwein, 7. Auflage [DLG-Feed value tables for swine, 7th Edition]. DLG e.V., Frankfurt am Main (DE). ISBN: 978-3-7690-0664-3Google Scholar
  20. Draper SR (1973) Amino acid profiles of chemical and anatomical fractions of oat grains. J Sci Food Agric 24:1241–1250.  https://doi.org/10.1002/jsfa.2740241013 CrossRefGoogle Scholar
  21. EC (2007) Council Regulation (EC) No 834/2007 of 28 June 2007 on Organic Production and Labelling of Organic Products and Repealing Regulation (EEC) No 2092/91Google Scholar
  22. EC (2008) Commission regulation (EC) no 889/2008 of 5 September 2008 laying down detailed rules for the implementation of council regulation (EC) no 834/2007 on organic production and labelling of organic products with regard to organic production, Labelling and ControlGoogle Scholar
  23. EC (2009) Commission Regulation (EC) No 152/2009 of 27 January 2009 Laying Down the Methods of Sampling and Analysis for the Official Control of FeedGoogle Scholar
  24. EU (2014) Commision implementing regulation (EU) no 836/2014 of 31 July 2014 amending regulation (EC) no 889/2008 laying down detailed rules for the implementation of council regulation (EC) no 834/2007 on organic production and labelling of organic products with regard to organic production, Labelling and ControlGoogle Scholar
  25. Evonik (2016) Evonik Nutrition & Care GmbH. Aminodat 5.0, Version 1.03Google Scholar
  26. Gronle A (2014) Agronomic aspects of intercropping spring or winter peas and cereals as influenced by ploughing system. Dissertation, University of Kassel (DE)Google Scholar
  27. Gueguen J, Barbot J (1988) Quantitative and qualitative variability of pea (Pisum Sativum L.) protein composition. J Sci Food Agric 42:209–224.  https://doi.org/10.1002/jsfa.2740420304 CrossRefGoogle Scholar
  28. Hanell U, L-baeckström G, Svensson G (2004) Quality studies on wheat grown in different cropping systems: a holistic perspective. Acta Agric Scand Sec B — Soil & Plant Sci 54:254–263.  https://doi.org/10.1080/09064710410030302 Google Scholar
  29. Henriet C, Aimé D, Térézol M, Kilandamoko A, Rossin N, Combes-Soia L, Labas V, Serre R-F, Prudent M, Kreplak J, Vernoud V, Gallardo K (2019) Water stress combined with S-deficiency in pea affects yield components but mitigates S-deficiency effect on seed transcriptome, rebalancing seed composition. J Exp Bot:erz114.  https://doi.org/10.1093/jxb/erz114
  30. Hothorn T, Bretz F, Westfall P (2008) Simultaneous inference in general parametric models. Biom J 50:346–363.  https://doi.org/10.1002/bimj.200810425 CrossRefGoogle Scholar
  31. Hughes RK, Desforges N, Selwood C, Smith R, Speirs CI, Sinnaeve G, Gorton PG, Wiseman J, Jumel K, Harding SE, Hill SE, Street V, Wang TL, Hedley CL (2001) Genes affecting starch biosynthesis exert pleiotropic effects on the protein content and composition of pea seeds. J Sci Food Agric 81:877–882.  https://doi.org/10.1002/jsfa.856 CrossRefGoogle Scholar
  32. INRA-CIRAD-AFZ (2018) Inra-Cirad-Afz feed tables - composition and nutritive values of feeds for cattle, sheep, goats, pigs, poultry, rabbits, horses and salmonids, https://feedtables.com/. Last Access 1st August 2018
  33. Ivarsson E, Neil M (2018) Variations in nutritional and antinutritional contents among faba bean cultivars and effects on growth performance of weaner pigs. Livest Sci 212:14–21.  https://doi.org/10.1016/j.livsci.2018.03.017 CrossRefGoogle Scholar
  34. Jackson P, Boulter D, Thurman DA (1969) A comparison of some properties of vicilin and legumin isolated from seeds of Pisum sativum, Vicia faba and Cicer arietinum. New Phytol 68:25–33.  https://doi.org/10.1111/j.1469-8137.1969.tb06416.x
  35. Jezierny D, Mosenthin R, Bauer E (2010) The use of grain legumes as a protein source in pig nutrition: a review. Anim Feed Sci Technol 157:111–128.  https://doi.org/10.1016/j.anifeedsci.2010.03.001 CrossRefGoogle Scholar
  36. Jezierny D, Mosenthin R, Sauer N, Roth S, Piepho HP, Rademacher M, Eklund M (2011) Chemical composition and standardised ileal digestibilities of crude protein and amino acids in grain legumes for growing pigs. Livest Sci 138:229–243.  https://doi.org/10.1016/j.livsci.2010.12.024
  37. JKI (2018) Julius-Kühn-Institute, Geoportal, http://geoportal.julius-kuehn.de/map?app=oeko. Last Access: 1st of August 2018
  38. Jørgensen H, Gabert VM, Fernández JA (1999) Influence of nitrogen fertilization on the nutritional value of high-lysine barley determined in growing pigs. Anim Feed Sci Technol 79:79–91.  https://doi.org/10.1016/S0377-8401(99)00011-5 CrossRefGoogle Scholar
  39. Kim JC, Mullan BP, Simmins PH, Pluske JR (2003) Variation in the chemical composition of wheats grown in Western Australia as influenced by variety, growing region, season, and post-harvest storage. Aust J Agric Res 54:541–550.  https://doi.org/10.1071/Ar02183 CrossRefGoogle Scholar
  40. Kotlarz A, Sujak A, Strobel W, Grzesiak W (2011) Chemical composition and nutritive value of protein of the pea seeds - effect of harvesting year and variety. Veg Crop Res Bul 75:57–69.  https://doi.org/10.2478/v10032-011-0018-2 CrossRefGoogle Scholar
  41. Krejčířová L, Capouchová I, Petr J, Bicanová E, Kvapil R (2006) Protein composition of winter wheat from organic and conventional farming. Zemdirbyste 93:285–296 ISSN: 1392-3196Google Scholar
  42. Krejčířová L, Capouchová I, Petr J, Bicanová E, Faměra O (2007) The effect of organic and conventional growing systems on quality and storage protein composition of winter wheat. Plant Soil Environ 53:499–505.  https://doi.org/10.17221/2304-Pse Google Scholar
  43. Kyntäjä A, Partanen K, Siljander-Rasi H, Jalava T (2014) Tables of composition and nutritional values of organically produced feed materials for pigs and poultry. MTT Report 164 (FI). ISBN: 978-952-487-571-4Google Scholar
  44. Lenth RV (2016) Least-squares means: the R package lsmeans. J Stat Softw 69:1–33.  https://doi.org/10.18637/jss.v069.i01
  45. Longstaff M, McNab JM (1986) Influence of site and variety on starch, hemicellulose and cellulose composition of wheats and their digestibilities by adult cockerels. Br Poult Sci 27:435–449.  https://doi.org/10.1080/00071668608416901 CrossRefGoogle Scholar
  46. Metayer JP, Grosjean F, Castaing J (1993) Study of variability in French cereals. Anim Feed Sci Technol 43:87–108.  https://doi.org/10.1016/0377-8401(93)90145-A CrossRefGoogle Scholar
  47. Moore S (1963) On the Determination of Cystine as Cysteic Acid. J Biol Chem 1963 238: 235–237Google Scholar
  48. Murphy KM, Hoagland LA, Reeves PG, Baik B-K, Jones SS (2009) Nutritional and quality characteristics expressed in 31 perennial wheat breeding lines. Renew Agr Food Syst 24:285–292.  https://doi.org/10.1017/S1742170509990159 CrossRefGoogle Scholar
  49. Nikolopoulou D, Grigorakis K, Stasini M, Alexis MN, Iliadis K (2007) Differences in chemical composition of field pea (Pisum sativum) species: effects of cultivation area and year. Food Chem 103:847–852.  https://doi.org/10.1016/j.foodchem.2006.09.035 CrossRefGoogle Scholar
  50. O'Kane FE, Vereijken JM, Gruppen H, Boekel MAJS (2006) Gelation behavior of protein isolates extracted from 5 species of Pisum sativum L. J Food Sci 70:C132–C137.  https://doi.org/10.1111/j.1365-2621.2005.tb07073.x CrossRefGoogle Scholar
  51. Peoples MB, Brockwell J, Herridge DF, Rochester IJ, Alves BJR, Urquiaga S, Boddey RM, Dakora FD, Bhattarai S, Maskey SL, Sampet C, Rerkasem B, Khan DF, Hauggaard-Nielsen H, Jensen ES (2009) The contributions of nitrogen-fixing crop legumes to the productivity of agricultural systems. Symbiosis 48:1–17.  https://doi.org/10.1007/bf03179980 CrossRefGoogle Scholar
  52. Peterson BG, Carl P (2014) Performanceanalytics: econometric tools for performance and risk analysis. R Package Version 1.4.3541Google Scholar
  53. R Core Team (2017) R: a language and environment for statistical computing, version 3.4.0. http://www.R-project.org/, R Foundation for Statistical Computing, Vienna, Austria
  54. Rodehutscord M, Rückert C, Maurer HP, Schenkel H, Schipprack W, Bach Knudsen KE, Schollenberger M, Laux M, Eklund M, Siegert W, Mosenthin R (2016) Variation in chemical composition and physical characteristics of cereal grains from different genotypes. Arch Anim Nutr 70:87–107.  https://doi.org/10.1080/1745039X.2015.1133111 CrossRefGoogle Scholar
  55. Rubio LA, Pérez A, Ruiz R, Guzmán MÁ, Aranda-Olmedo I, Clemente A (2013) Characterization of pea (Pisum Sativum) seed protein fractions. J Sci Food Agric 94:280–287.  https://doi.org/10.1002/jsfa.6250 CrossRefGoogle Scholar
  56. Shewry PR (2007) Improving the protein content and composition of cereal grain. J Cereal Sci 46:239–250.  https://doi.org/10.1016/j.jcs.2007.06.006 CrossRefGoogle Scholar
  57. Shewry PR, Halford NG (2002) Cereal seed storage proteins: structures, properties and role in grain utilization. J Exp Bot 53:947–958.  https://doi.org/10.1093/jexbot/53.370.947 CrossRefGoogle Scholar
  58. Shewry PR, Piironen V, Lampi A-M, Edelmann M, Kariluoto S, Nurmi T, Fernandez-Orozco R, Andersson AAM, Åman P, Fraś A, Boros D, Gebruers K, Dornez E, Courtin CM, Delcour JA, Ravel C, Charmet G, Rakszegi M, Bedo Z, Ward JL (2010) Effects of genotype and environment on the content and composition of phytochemicals and dietary fiber components in rye in the Healthgrain diversity screen. J Agric Food Chem 58:9372–9383.  https://doi.org/10.1021/jf100053d CrossRefGoogle Scholar
  59. Shewry PR, Van Schaik F, Ravel C, Charmet G, Rakszegi M, Bedo Z, Ward JL (2011) Genotype and environment effects on the contents of vitamins B1, B2, B3, and B6 in wheat grain. J Agric Food Chem 59:10564–10571.  https://doi.org/10.1021/jf202762b CrossRefGoogle Scholar
  60. Simpson DJ (2001) Proteolytic degradation of cereal prolamins—the problem with proline. Plant Sci 161:825–838.  https://doi.org/10.1016/S0168-9452(01)00482-4 CrossRefGoogle Scholar
  61. Stockdale EA, Shepherd MA, Fortune S, Cuttle SP (2006) Soil fertility in organic farming systems – fundamentally different? Soil Use Manag 18:301–308.  https://doi.org/10.1111/j.1475-2743.2002.tb00272.x CrossRefGoogle Scholar
  62. Sundrum A (2001) Managing amino acids in organic pig diets, Proceedings of the 4th NAHWOA-Workshop, 24–27.03.2001, Wageningen (NL) (2001), pp 181–191Google Scholar
  63. Teuscher P, Grüninger B, Ferdinand N (2005) Risk management in sustainable supply chain management (SSCM): lessons learnt from the case of Gmo-free soybeans. Corp Soc Responsib Environ Mgmt 13:1–10.  https://doi.org/10.1002/csr.81 CrossRefGoogle Scholar
  64. VDLUFA (2012) VDLUFA Methodenbuch Band III Die Chemische Untersuchung von Futtermitteln einschl. 1.-8. Ergänzungslieferung [VDLUFA Method Book Volume III The chemical analyses of feedstuffs incl. 1st-8th Supplemental Delivery], VDLUFA Verlag, Darmstadt (DE)Google Scholar
  65. Watson CA, Atkinson D, Gosling P, Jackson LR, Rayns FW (2006) Managing soil fertility in organic farming systems. Soil Use Manag 18:239–247.  https://doi.org/10.1111/j.1475-2743.2002.tb00265.x CrossRefGoogle Scholar
  66. Weißmann F, Bussemas R (2014) Praktische Möglichkeiten zur Verbesserung der Eiweißversorgung der Monogastrier im Ökologischen Landbau [Possibilities to improve the protein supply of monogastric animals in organic farming]. In: Praxisbefragung zur Aminosäurelücke und praktische Möglichkeiten zur Verbesserung der Eiweißversorgung der Monogastrier in der Fütterung im Ökologischen Landbau [Survey on the amino acid gap and possibilities to improve the protein supply of monogastric animals in organic farming], Thünen Working Paper 23Google Scholar
  67. Witten S, Aulrich K (2018) Effect of variety and environment on the amount of thiamine and riboflavin in cereals and grain legumes. Anim Feed Sci Technol 238:39–46.  https://doi.org/10.1016/j.anifeedsci.2018.01.022 CrossRefGoogle Scholar
  68. Würschum T, Leiser WL, Jähne F, Bachteler K, Miersch M, Hahn V (2018) The soybean experiment ‘1000 gardens’: a case study of citizen science for research, education, and beyond. Theor Appl Genet 132:617–626.  https://doi.org/10.1007/s00122-018-3134-2 CrossRefGoogle Scholar
  69. Zeileis A (2004) Econometric computing with HC and HAC covariance matrix estimators. J Stat Softw 11:1–17.  https://doi.org/10.18637/jss.v011.i10
  70. Zollitsch W, Baumung R (2004) Protein supply for organic poultry: options and shortcomings, 2nd SAFO workshop - organic livestock farming: potential and limitations of husbandary practice to secure animal health and welfare and food quality, Hovi M, Sundrum A, Padel S, Witzenhausen (DE), pp 153-160Google Scholar

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© Springer Nature B.V. 2019

Authors and Affiliations

  • Stephanie Witten
    • 1
    Email author
  • Herwart Böhm
    • 1
  • Karen Aulrich
    • 1
  1. 1.Johann Heinrich von Thünen Institute, Institute of Organic FarmingWesterauGermany

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