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Correlation between NIRS generated and chemically measured feed quality data in barley (Hordeum vulgare), and potential use in QTL analysis identification

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Abstract

A study was performed to investigate the value of near infrared reflectance spectroscopy (NIRS) as an alternate method to analytical techniques for identifying QTL associated with feed quality traits. Milled samples from an F6—derived recombinant inbred Tallon/Scarlett population were incubated in the rumen of fistulated cattle, recovered, washed and dried to determine the in-situ dry matter digestibility (DMD). Both pre- and post-digestion samples were analysed using NIRS to quantify key quality components relating to acid detergent fibre, starch and protein. This phenotypic data was used to identify trait associated QTL and compare them to previously identified QTL. Though a number of genetic correlations were identified between the phenotypic data sets, the only correlation of most interest was between DMD and starch digested (r = −0.382). The significance of this genetic correlation was that the NIRS data set identified a putative QTL on chromosomes 7H (LOD = 3.3) associated with starch digested. A QTL for DMD occurred in the same region of chromosome 7H, with flanking markers fAG/CAT63 and bPb-0758. The significant correlation and identification of this putative QTL, highlights the potential of technologies like NIRS in QTL analysis.

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References

  • Abdel-Haleem H, Bowman JGP, Kanazin V, Surber L, Talbert H, Hayes PM, Blake T (2010) Quantitative trait loci for dry matter digestibility and particle size traits in two-rowed 3 six-rowed barley population. Euphytica 172(3):419–433

    Article  Google Scholar 

  • Anderson MK, Reinbergs E (1985) Barley breeding. In: Rasmusson DC (ed) Barley agronomy monograph 26. American Society for Agronomy, Madison

    Google Scholar 

  • Antal I, Dávid ÁZ (2007) Fundamentals and pharmaceutical applications of near-infrared spectroscopy. GLATT Int Times. 23:1–3

    Google Scholar 

  • Black JL, Tredrea AM, Nielsen SG, Flinn PC, Kaiser AG, Barneveld RJV (2005) Feed uses for barley. In: Proceedings 12th Australian barley technical symposium

  • Boever JLD, Cottyn BG, Vanacker JM, Boucque CV (1994) An improved enzymatic method by adding gammanase to determine digestibility and predict energy value of compound feeds and raw materials for cattle. Anim Feed Sci Technol 47:1–18

    Article  CAS  Google Scholar 

  • Bowman J, Sowell B (2002) Feeding the beef cow herd. Livestock Feeds and Feeding, Prentice Hall

    Google Scholar 

  • Bowman JGP, Blake TK, Surber LMM, Habernicht DK, Bockelman H (2001) Feed quality variation in the barley core collection of the USDA national small grains collection. Crop Sci 41:863–870

    Article  Google Scholar 

  • Butler DG, Cullis BR, Gilmour AR, Gogel BJ (2009) ASReml-R reference manual release (3 edn). Queensland Department of Primary Industries, Technical report

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138(3): 963–971

    Google Scholar 

  • Coombes NE (ed) (2002) The reactive tabu search for efficient correlated experimental designs. Liverpool John Moores University, Liverpool

    Google Scholar 

  • Fox GP, Panozzo JF, Li CD, Lance RCM, Inkerman PA, Henry RJ (2003) Molecular basis of barley quality. Aust J Agric Res 54:1081–1101

    Article  CAS  Google Scholar 

  • Fox G, Bowman J, Kelly A, Inkerman A, Poulsen D, Henry R (2008) Assessing for genetic and environmental effects on ruminant feed quality in barley (Hordeum vulgare). Euphytica 163:249–257

    Article  Google Scholar 

  • Fox G, Kelly A, Bowman J, Inkerman A, Poulsen D, Henry R (2009) Is malting barley better feed for cattle than feed barley? J Inst Brewing 115(2):95–104

    Article  CAS  Google Scholar 

  • Givens DI, Deaville ER (1999) The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review. Aust J Agric Res 50:1131–1145

    Article  Google Scholar 

  • Gous PW, Martin A, Lawson W, Kelly A, Fox GP, Sutherland M (2012) QTL associated with barley (Hordeum vulgare) feed quality traits measured through in situ digestion. Euphytica. doi:10.1007/s10681-011-0608-6

  • Lawson W, Mace E, Collard BCY, Fox G, Kelly A, Sutherland M, Franckowiak J, Bowman J (2009) Investigating the molecular dynamics of feed quality traits in two barley F6-derived RIL populations. Paper presented at the Australian plant breeders Conference, Cairns

  • Norris KH, Barnes RF, Moore JE, Shenk JS (1976) Predicting forage quality by infrared reflectance spectroscopy. J Anim Sci 43:889–897

    CAS  Google Scholar 

  • Osborne BG (2006) Application of near infrared spectroscopy in quality screening of early-generation material in cereal breeding programmes. J Near Infrared Spectrosc 14:93–101

    Article  CAS  Google Scholar 

  • Osborne BG, Fearn T, Hindle PH (1993) Practical NIR Spectroscopy with applications in food and beverage analysis, 2nd edn. Longmans Scientific and Technical, Harlow

    Google Scholar 

  • Patterson HD, Thompson R (1971) Recovery of inter-block information when block sizes are unequal. Biometrika 58:545–554

    Article  Google Scholar 

  • Surber LMM, Bowman JGP, Blake TK, Hinman DD, Boss DL, Blackhurst TC (2000) Prediction of barley feed quality for beef cattle from laboratory analyses. Proc West Sec Am Soc Anim Sci 51:454–457

    Google Scholar 

  • Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Heredity 93:77–78

    Google Scholar 

  • Wang S, Basten CJ, Zeng Z-B (2002) Windows QTL Cartographer: WinQtlCart V2.0

  • Wrigley CW (1999) Potential methodologies and strategies for the rapid assessment of feed-grain quality. Aust J Agric Res 50:789–805

    Article  Google Scholar 

Download references

Acknowledgment

The authors thank the Grain Research and Development Corporation (GRDC) and the Department of Employment, Economic Development and Innovation (DEEDI) for funding the project. Donna Hocroft (DEEDI) and Jim Kidd (CAAS) for all their time and aid in sample preparation for the phenotypic trial and for maintaining the cattle herd.

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Correspondence to Peter W. Gous.

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Gous, P.W., Martin, A., Lawson, W. et al. Correlation between NIRS generated and chemically measured feed quality data in barley (Hordeum vulgare), and potential use in QTL analysis identification. Euphytica 188, 325–332 (2012). https://doi.org/10.1007/s10681-012-0644-x

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  • DOI: https://doi.org/10.1007/s10681-012-0644-x

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