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https://doi.org/10.5713/ab.22.0076    [Accepted] Published online June 30, 2022.
Quantitation of relationship and development of nutrient prediction with vibrational molecular structure spectral profiles of feedstocks and co-products from canola bio-oil processing
Peiqiang Yu1,* 
Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
Correspondence:  Peiqiang Yu, Tel: +1-306-966-4132, Fax: +1-306-966-4132, Email: peiqiang.yu@usask.ca
Received: 1 March 2022   • Revised: 23 March 2022   • Accepted: 17 June 2022
Conventional methods for laboratory analysis are reliable but require excessive labor, time, chemicals, and amounts of samples. For these reasons, alternative methods have been explored. ATR/FTIR spectroscopy is technique that analyzes samples simply by shooting a bright light and measuring the absorbance at the mid-infrared range. 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.
The samples of feedstock (canola oil seeds) and co-products (meals and pellets) from different bio-oil processing plants in different countries: 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. The procedure CORR was used at SAS 9.4 to determine the strength of the relationships between the carbohydrate-related molecular spectral profiles to the carbohydrate-relate characteristics of canola meals and seeds, as well as the protein-related molecular spectral profiles were related to the protein parameters of canola meals and seeds. Later the procedure MULTI-REG at SAS 9.4 with best model variable selection was used to generate prediction equations based on the relationships observed on the samples.
The STCA (ca. 1487.8 – 1190.8 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 TCA (ca. 1198.5 – 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. 1721.2 – 1480.1 cm-1) were related to a few chemical and nutrient profiles, CNCPS fractions, truly absorbable nutrient supply based on 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. 1650.8 – 1643.1 cm-1) and β-sheet height (ca. 1633.4 – 1625.7 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).


The ATR/FTIR vibrational molecular spectroscopy can be a useful resource to predict carbohydrate and protein-relates nutritional aspects of canola seeds and meals based on certain carbohydrate and protein spectral features inherent to canola seeds and meals.
Keywords: Canola Bio-Oil Processing; Feedstock and Co-products; Interactive Relationship; Molecular Structures; Nutrient Utilization and Availability

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