Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Quantitation of relationship and development of nutrient prediction with vibrational molecular structure spectral profiles of feedstocks and co-products from canola bio-oil processing

  • Alessandra M.R.C.B. de Oliveira (Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan) ;
  • Peiqiang Yu (Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan)
  • Received : 2022.03.01
  • Accepted : 2022.06.17
  • Published : 2023.03.01
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Abstract

Objective: This program aimed to reveal the association of feed intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The special objective of this study was to quantify the relationship between molecular spectral feature and nutrient availability and develop nutrient prediction equation with vibrational molecular structure spectral profiles. Methods: The samples of feedstock (canola oil seeds) and co-products (meals and pellets) from different bio-oil processing plants in Canada (CA) and China (CH) were submitted to this molecular spectroscopic technique and their protein and carbohydrate related molecular spectral features were associated with the nutritional results obtained through the conventional methods of analyses for chemical and nutrient profiles, rumen degradable and intestinal digestible parameters. Results: The results showed that the spectral structural carbohydrates spectral peak area (ca. 1,487.8 to 1,190.8 cm-1) was the carbohydrate structure that was most significant when related to various carbohydrate parameters of canola meals (p<0.05, r>0.50). And spectral total carbohydrate area (ca. 1,198.5 to 934.3 cm-1) was most significant when studying the various carbohydrate parameters of canola seeds (p<0.05, r>0.50). The spectral amide structures (ca. 1,721.2 to 1,480.1 cm-1) were related to a few chemical and nutrient profiles, Cornell Net Carbohydrate and Protein System (CNCPS) fractions, truly absorbable nutrient supply based on the Dutch protein system (DVE/OEB), and NRC systems, and intestinal in vitro protein-related parameters in co-products (canola meals). Besides the spectral amide structures, α-helix height (ca. 1,650.8 to 1,643.1 cm-1) and β-sheet height (ca. 1,633.4 to 1,625.7 cm-1), and the ratio between them have shown to be related to many protein-related parameters in feedstock (canola oil seeds). Multi-regression analysis resulted in moderate to high R2 values for some protein related equations for feedstock (canola seeds). Protein related equations for canola meals and carbohydrate related equations for canola meals and seeds resulted in weak R2 and low p values (p<0.05). Conclusion: In conclusion, the attenuated total reflectance Fourier transform infrared spectroscopy vibrational molecular spectroscopy can be a useful resource to predict carbohydrate and protein-relates nutritional aspects of canola seeds and meals.

Keywords

Acknowledgement

This work is part of the first author's Thesis and modified and edited for the journal [12]. The authors would like to thank B. Dyck and Q. Qin (Canola Council of Canada) and X. Zhang (Tianjin Agricultural University) for help sampling canola seed and canola meal in various crushers in Canada and China, D. Beaulieu and R. Newkirk for being in advisory committee, and Z. Niu (Department of Animal and Poultry Science, University of Saskatchewan) for technical assistance. The authors would like to acknowledge the University of Saskatchewan, the Rainer Dairy Research Facility, and Alexander Malcolm Shaw Memorial Graduate Scholarship (to AO).

References

  1. Newkirk R. Meal nutrients composition. In: Daun JK, Eskin NAM, Hickling D, editors. Canola: Chemistry, production, processing, and utilization. AOCS Press; 2011. pp. 229-44. https://doi.org/10.1016/b978-0-9818936-5-5.50012-7 
  2. Ban Y, Prates LL, Yu P. Investigating molecular structures of bio-fuel and bio-oil seeds predictors to estimate protein bioavailability for ruminants by advanced nondestructive vibrational molecular spectroscopy. J Agric Food Chem 2017;65: 9147-57. https://doi.org/10.1021/acs.jafc.7b02239 
  3. Chen L, Zhang X, Yu P. Correlating molecular spectroscopy and molecular chemometrics to explore carbohydrate functional groups and utilization of coproducts from biofuel and biobrewing processing. J Agric Food Chem 2014;62:5108-17. https://doi.org/10.1021/jf500711p 
  4. Theodoridou K, Yu P. Effect of processing conditions on the nutritive value of canola meal and presscake. Comparison of the yellow and brown-seeded canola meal with the brown-seeded canola presscake. J Sci Food Agric 2013;93:1986-95. https://doi.org/10.1002/jsfa.6004 
  5. Theodoridou K, Yu P. Application potential of ATR-FT/IR molecular spectroscopy in animal nutrition: revelation of protein molecular structures of canola meal and presscake, as affected by heat-processing methods, in relationship with their protein digestive behavior and utilization for dairy cattle. J Agric Food Chem 2013;61:5449-58. https://doi.org/10.1021/jf400301y 
  6. Theodoridou K, Yu P. Metabolic characteristics of the proteins in yellow-seeded and brown-seeded canola meal and presscake in dairy cattle: comparison of three systems (PDI, DVE, and NRC) in nutrient supply and feed milk value (FMV). J Agric Food Chem 2013;61:2820-30. https://doi.org/10.1021/jf305171z 
  7. Association of Official Analytical Chemists. Official methods of analysis (21st ed.). Arlington, VA, USA: AOAC International; 2019. http://www.eoma.aoac.org/ 
  8. National Research Council (NRC). Nutrient requirements of dairy cattle: Seventh Revised Edition. Washington, DC, USA: National Academies Press; 2001. Available from: http://nap.edu/9825 
  9. National Research Council (NRC). Nutrient requirements of beef cattle: Seventh Revised Edition. Washington, DC, USA: National Academies Press; 2000. Available from: http://nap.edu/9825 
  10. Van Amburgh ME, Foskolos A, Collao-Saenz EA, Higgs RJ, Ross DA. Updating the CNCPS feed library with new feed amino acid profiles and efficiencies of use: evaluation of model predictions - Version 6.5. 2013;2013:59. Available from: https://ecommons.cornell.edu/bitstream/handle/1813/36493/CNC2013_VanAmburgh_m.pdf 
  11. Van Amburgh ME, Collao-Saenz EA, Higgs RJ, et al. The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5. J Dairy Sci 2015;98:6361-80. https://doi.org/10.3168/jds.2015-9378 
  12. Calsamiglia S, Stern MD. A three-step in vitro procedure for estimating intestinal digestion of protein in ruminants. J Anim Sci 1995;73:1459-65. https://doi.org/10.2527/1995.7351459x 
  13. Tamminga S, Van Straalen WM, Subnel APJ, et al. The Dutch protein evaluation system: the DVE/OEB-system. Livest Prod Sci 1994;40:139-55. https://doi.org/10.1016/0301-6226(94)90043-4 
  14. Tamminga S, Brandsma GG, van Duinkerken G, van Vuuren AM, Blok MC. Protein evaluation for ruminants: the DVE/OEB 2007-system. Lelystad, the Netherlands: CVB; 2007. CVB documentation report nr. 53. Available from: https://edepot.wur.nl/336208 
  15. Frost J. Interpreting correlation coefficients. Statistics by Jim; 2018. Available from: https://statisticsbyjim.com/basics/correlations/ 
  16. Oconnor B. Yes. A p-value depends on the sample size, so a small sample can give this. Comment on the blog post "Example of strong correlation coefficient with a high p value". 2011. Available from: https://stats.stackexchange.com/questions/17371/example-of-strong-correlation-coefficient-with-a-high-p-value 
  17. Huang X. Improvements in nutritive value of canola meal with pelleting [Thesis]. Saskatoon, SK, Canada: University of Saskatchewan; 2015. UofS Campus Repository. https://sundog.usask.ca/record=b3851688 
  18. Petchko K. Data and methodology. In: Petchko K, editor. How to write about economics and public policy. Academic Press; 2018. 259 p. https://doi.org/10.1016/B978-0-12-813010-0.00013-2