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Nutrients 2018, 10(4), 519; https://doi.org/10.3390/nu10040519

Article
On a Molecular Basis, Investigate Association of Molecular Structure with Bioactive Compounds, Anti-Nutritional Factors and Chemical and Nutrient Profiles of Canola Seeds and Co-Products from Canola Processing: Comparison Crusher Plants within Canada and within China as well as between Canada and China
1
Ministry of Strategic Research Chair Program, Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
2
Department of Animal Nutrition and Clinical Nutrition, Faculty of Veterinary Medicine, Assiut University, Assiut 71515, Egypt
*
Author to whom correspondence should be addressed.
Received: 7 February 2018 / Accepted: 16 April 2018 / Published: 21 April 2018

Abstract

:
The objectives of this study were to: (1) Use molecular spectroscopy as a novel technique to quantify protein molecular structures in relation to its chemical profiles and bioenergy values in oil-seeds and co-products from bio-oil processing. (2) Determine and compare: (a) protein molecular structure using Fourier transform infrared (FT/IR-ATR) molecular spectroscopy technique; (b) bioactive compounds, anti-nutritional factors, and chemical composition; and (c) bioenergy values in oil seeds (canola seeds), co-products (meal or pellets) from bio-oil processing plants in Canada in comparison with China. (3) Determine the relationship between protein molecular structural features and nutrient profiles in oil-seeds and co-products from bio-oil processing. Our results showed the possibility to characterize protein molecular structure using FT/IR molecular spectroscopy. Processing induced changes between oil seeds and co-products were found in the chemical, bioenergy profiles and protein molecular structure. However, no strong correlation was found between the chemical and nutrient profiles of oil seeds (canola seeds) and their protein molecular structure. On the other hand, co-products were strongly correlated with protein molecular structure in the chemical profile and bioenergy values. Generally, comparisons of oil seeds (canola seeds) and co-products (meal or pellets) in Canada, in China, and between Canada and China indicated the presence of variations among different crusher plants and bio-oil processing products.
Keywords:
bioactive compounds; anti-nutritional factors; protein molecular structure; oil seeds; co-products from bio-oil processing; canola; crusher plants; Canada and China

1. Introduction

In the international economy, canola has become a central issue as the second most abundant oil source [1] with the valuable co-product of oil extraction: high quality protein rich meal [2]. Canola was modified from rapeseed [3] by Canadian plant breeders [4] to obtain plant with low levels of “erucic acid” in the oil (<2% of total fatty acids in the oil) and low levels of glucosinolates in the non-oil part (<30 μmol in its defatted meal) [5,6,7]. Therefore, rapeseeds that contain low levels of erucic acid in oil and glucosinolates in meal are called canola in North America and “double-zero” rapeseeds in Europe [6,8,9]. About 13% of the total oilseed and protein meals production in the world comes from canola seeds and rapeseeds [10] and the biggest producers of them in the world are China and Canada [11].
Although canola has been extensively studied [4,12], the relation between its protein molecular structure and the chemical and nutrient profiles remains unclear. In addition, little information is present about canola variations among the different crusher plants, the bio-oil processing products, and the different producers’ countries as Canada and China. These variations affect the molecular structure, chemical composition, and concentration of protein and carbohydrates in canola seeds and meal [13,14] and availability of nutrients in the meal [5].
Thus, the main purposes of the present study were to use molecular spectroscopy as a novel technique to quantify protein molecular structure of canola in relation to its chemical and energy profiles and to compare the protein molecular structure, chemical profile and energy values in canola seeds, meal and pellets from different crushing plants in the main two producer countries: Canada and China.
The hypothesis of this study was that the protein molecular structure changes induced by processing had close relationship to the chemical and bioenergy profiles in canola seeds, meal and pellets and the chemical and bioenergy profiles could be predicted using the parameters of protein molecular structure.

2. Materials and Methods

2.1. Sample Preparation

Systematic sampling process was arranged by Canada Council of Canola (CCC, Winnipeg, Manitoba, Canada). Oil seeds (canola seeds) and co-products from bio-oil processing (canola meal or meal pellets) were obtained from five different bio-oil processing plants in Canada as well as from five different bio-oil processing plants in China (three different batches of seeds, meal or meal pellet produced at different times were obtained from each plant). Total samples: Canadian seed: 5 × 3 = 15; Canadian meal: 3 × 2 = 6; Canadian meal pellet: 3 × 3 = 9; Chinese seed: 5 × 3 = 15; and Chinese meal: 5 × 3 = 15.

2.2. Chemical Analysis

Canola seeds were ground by a coffee grinder (PC770, Loblaws Inc., Toronto, ON, Canada) for 20 s while canola meal and pellets were ground via a 1 mm screen using Retsch ZM 200 rotor mill (Rose Scientific Ltd., Edmonton, AB, Canada) and analyzed for dry matter (DM) (AOAC official method 930.15), ash (AOAC official method 942.05), crude protein (CP) (AOAC official method 984.13), crude fat (EE) (AOAC official method 920.39), neutral detergent fiber (NDF) (AOAC official method 2002.04), acid detergent fiber (ADF) (AOAC official method 973.18) and acid detergent lignin (ADL) (AOAC official method 973.18) according to AOAC [15]. Neutral detergent-insoluble crude protein (NDICP), acid detergent-insoluble crude protein (ADICP) and non-protein nitrogen (NPN) were analyzed according to Licitra et al. [16]. Soluble crude protein (SCP) was analyzed in accordance with Roe et al. [17]. Structural and non-structural carbohydrates were determined using Van Soest et al. [18] and NRC [19]. Total carbohydrate (CHO), non-fiber CHO (NFC), hemicellulose, and cellulose were calculated as follows: CHO = 100 − EE − CP − ash; NFC = 100 − (NDF − NDICP) − EE − CP − ash; hemicellulose = NDF − ADF; and cellulose = ADF − ADL according to NRC [19]. All samples were analyzed in duplicate and repeated if error exceeded 5%.

2.3. BioEnergy Values

The available bioenergy is very important in ration formulation [5] and it can be estimated by using total digestible nutrient (TDN), as well as digestible energy, metabolizable energy, and net energy [20]. The truly digestible non-fiber carbohydrate (td NFC), total digestible crude protein (td CP), total digestible neutral detergent fiber (td NDF), and total digestible fatty acid (td FA) were calculated according to NRC [19] based on canola chemical composition.
Total digestible nutrient at maintenance (TDN1x), digestible energy at a production level (DE3x), metabolizable energy at a production level (ME3x), and net energy at a production level (NE3x) were estimated using NRC [19]. Metabolizable energy, net energy for maintenance (NEm), net energy for gain (NEg) were predicted using NRC [21].

2.4. Protein Molecular Structure

Attenuated Total Reflectance (ATR)—Fourier transform infrared (FT/IR) molecular spectroscopy can be used as a rapid tool to detect protein molecular structures [22,23]. The protein molecular spectrum data of canola seeds, meal and pellets were collected using ATR-FT/IR vibrational spectroscopy 4200 (JASCO Corporation, Tokyo, Japan), at the Feed/Food Molecular Structure Analysis Lab, University of Saskatchewan (Saskatchewan, SK, Canada). The samples were ground through a 1 mm screen using a coffee grinder (PC770, Loblaws Inc., Toronto, ON, Canada) before spectral analysis. The IR spectrum of each sample was obtained within the mid-IR range (ca. 4000–800 cm−1) with 32 scans at a resolution of 4 cm−1. Five replicates were randomly carried out for each sample. The spectral data were analyzed by OMNIC 7.3 software (Spectra Tech., Madison, WI, USA). Amide I (ca. 1650) and amide II (ca. 1550) were detected. For protein 2nd structure of α-helix (ca. 1657) and β-sheet (ca. 1630) in the IR regions of approximately 1715 to 1480 cm−1, two steps were applied as described by Yu [24]. The ratios of amide I and II and α-helix and β-sheet spectral intensities were calculated. The ratio was obtained by the height or area under one functional group band (e.g., amide I) divided by the height or area under another functional group band (amide II) at each pixel, which represents the biological component ratio intensity and distribution in the tissue.

2.5. Statistical Analysis

Effect of plant crusher on chemical and nutrient profile data of canola seeds, meal and pellets in both Canada and China were analyzed using the mixed model procedure of SAS 9.1.4 (SAS Institute, Cary, NC, USA).The model used for the analysis is as follows:
Yij = μ + Pi + eij
where Yij is an observation of the dependent variable ij, μ is the population mean for the variable, and Pi is the effect of plant crushers within Canada (i = 1, 2, 3, 4, 5, total five crushers) or within China (i = A, B, C, D, E, total five crushers). Three batches from three different processing times in each crusher were replicates. eij is the random error associated with observation ij.
The residual analysis was carried out to check the model assumptions. Normality check was carried out using Proc Univariate with Normal and Plot options in SAS. For all statistical analyses, significance was declared at p < 0.05. Treatment means were compared using Tukey method. Contrast was carried out between meal and pellets.
Correlation Analysis between the protein molecular structure and chemical profile and bioenergy values was analyzed using the CORR procedure of SAS (Version 9.4, SAS Institute, Cary, NC, USA). The normality checking for correlation analysis was done using Univariate Procedure with Plot and Normal option. Multiple regression analysis of protein molecular structure spectral profile with chemical and nutrient profile were performed using PROC REG procedure of SAS 9.4 (SAS Institute, Cary, NC, USA). The model variables selection for regression was carried out using Stepwise Option.

3. Results and Discussion

3.1. Effect of Different Bio-Oil Processing Plants on Chemical Analysis within Canada and China: Comparison between Canada and China

The chemical composition of canola seeds: comparisons of crusher plants within Canada and within China as well as between Canada and China are presented in Table 1. Canola seeds in Canada had significantly higher dry matter, non-protein nitrogen, neutral detergent-insoluble crude protein, acid detergent fiber, and cellulose and significantly lower contents of soluble crude protein, sugar, and non-structural carbohydrates than canola seeds in China. There were significant differences in dry matter, ash, soluble crude protein, non-protein nitrogen, neutral detergent-insoluble crude protein, acid detergent-insoluble crude protein, sugar, and acid detergent lignin among the five different crusher plants within Canada. The Chinese crusher plants showed significant differences only in dry matter, crude protein, and acid detergent-insoluble crude protein. The variations in chemical profiles among crusher plants and between canola in Canada and China may be related to inherent variations in the type of seeds.
Total carbohydrate, neutral detergent fiber, acid detergent fiber, non-fiber carbohydrates, non-structural carbohydrates and ether extract of canola seeds were not significantly affected by the different crushing plants within Canada or China. Results for dry matter, ash, and CHO were similar to those reported by Samadi et al. [25] while the values of crude protein, soluble crude protein, neutral detergent-insoluble crude protein, acid detergent-insoluble crude protein, neutral detergent fiber, and acid detergent fiber were different than their results.
Table 2 shows the chemical composition of canola meals: canola meal in Canada had significantly higher dry matter, ash, neutral detergent-insoluble crude protein, neutral detergent fiber, acid detergent lignin, hemicellulose and non-fiber carbohydrates and significantly lower crude protein, soluble crude protein, non-protein nitrogen, sugar, and cellulose compared with those in China. We found that ash, crude protein, CHO, and cellulose contents of canola meal in our study are consistent with the finding of Xin and Yu [20]. Brito and Broderick [26] reported lower values for neutral detergent fiber (23.7%), acid detergent fiber (15.8%), and hemicellulose (7.87%) than our study. Maison [10] analyzed canola meal and his results for dry matter, crude protein and ash agree with our findings.
Moreover, the same table indicated that, ash, soluble crude protein, non-protein nitrogen, neutral detergent-insoluble crude protein, acid detergent-insoluble crude protein, sugar, neutral detergent fiber, hemicellulose, cellulose, non-fiber carbohydrates and non-structural carbohydrates had significant differences among crusher plants within Canada and China. Based on contrast P value between meal and pellets in Canada, we found significant differences in ash, soluble crude protein, non-protein nitrogen (%SCP), neutral detergent-insoluble crude protein, acid detergent-insoluble crude protein, neutral detergent fiber, acid detergent fiber, acid detergent lignin, hemicellulose and cellulose contents.
Our results in Table 1 and Table 2 reflect that the processing induced variations in the chemical profile between seeds and meal and among bio-oil processing products in the different crushing plants within Canada and within China and between Canada and China.

3.2. Effect of Different Bio-Oil Processing Plants on BioEnergy Values within Canada and China: Comparison between Canada and China

As shown in Table 3, no significant differences were detected in digestible nutrients or energy values between canola seeds in Canada and China. The same for crushing plants within Canada and China which did not show any significant differences in digestible nutrients or energy values except for td CP, which was significantly different among the different crusher plants within China. Our results were parallel with the published data of Samadi et al. [25].
Results for the energy values of canola meal are presented in Table 4. Canola meal in China had significantly higher td NDF, td CP, TDN 1x, TDN p 3x, TDN p 4x, DE 1x, DE p 3x, ME p 3x, NEL p 3x, ME 3x, NE m 3x, and NE g 3x. This may indicate that Chinese canola might be better than Canadian canola as the energy source. Our results are in the range of those reported by Theodoridou and Yu [27] and Xin and Yu [20]. Regarding crusher plants within Canada, a significant difference was found in all digestible nutrients and all energy values, while no significant difference was detected among crusher plants within China. Based on contrast P-values, td NDF, TDN 1x, TDN p 3x, TDN p 4x, DE 1x, DE p 3x, ME p 3x, NEL p 3x, ME 3x, NE m3x, and NE g 3x showed significant differences between meal and pellets. Bell [5] indicated that the variation in energy values in canola meal may be related to several factors as variety and quality of seeds, methods of processing, and the content of fiber in addition to the environmental factors. There were differences between the energy values of seeds and meal that might indicate the effect of oil extraction during canola meal processing. After pressing and solvent extraction during canola meal processing, it has less than 1% oil (CCC, Canada), which affects the energy values of meal.
Moreover, Toghyani et al. [28] indicated that Variations in oil, protein and fiber contents of canola may affect its energy content.

3.3. Effect of Different Crusher Plants on Protein Molecular Structure within Canada and China: Comparison between Canada and China

Variations between seeds and bio-oil processing product (meal) in the protein molecular structure indicated processing induced changes during canola meal manufacture. The cause of these changes in protein structure between meal and seeds may be the denaturation or disorganization that occurs to protein molecules during processing [29]. Table 5 shows the protein molecular structure characteristics of canola seeds detected by FT/IR molecular spectroscopy. Canola seeds in Canada and China, and crusher plants within Canada aand within China showed no significant differences in protein molecular structure except the ratio of α-helix/β-sheet which showed significant differences among crusher plants within Canada. Samadi and Yu [30] reported that changes in α-helix/β-sheet ratio can occur as a result of denaturation of α-helix and β-sheet from heat treatment during processing.
Amide I band is very sensitive to the protein secondary structure [20]. In our result, there were no variations in α-helix and β-sheet among the crusher plants within Canada and china, as no variations was found in amide I among the different crusher plants. Zhang and Yu [31] in their synchrotron-based study recorded these values for canola seeds: amide I: 16.77; amide II: 5.64; area ratios of amide I and II: 3.01; α-helix height: 0.25; β-sheet height: 0.22; and ratio α-helix/β-sheet: 1.15.
Protein molecular structure characteristics of canola meal are shown in Table 6. We found lower IR absorbance (p < 0.05) in amide I and II peak area, amide I peak area, area ratios of amide I and II, amide I height, height ratios of amide I and II, α-helix height, β-sheet height, and ratio α-helix to β-sheet for canola meal in Canada than canola meal in China. It might be suggested from these results that canola meal in Canada and China differ in their protein utilization related to the differences in their protein molecular structure. Yu [29] indicated that heat treatment during feed processing changes the protein secondary structure and these changes could affect the protein utilization and availability. Moreover, Xin and Yu [20] indicated presence of a close relationship between protein secondary structure (α-helix and β-sheet) and protein quality, availability and digestibility and protein utilization may be decreased due to increasing the percentage of β-sheet. No differences were found among crusher plants within Canada in the protein molecular structure except in area ratios of amide I and II. Crusher plants within China showed significant differences in amide I and II peak area, amide I peak area, amide II peak area, area ratios of amide I and II, amide I height, height ratios of amide I and II, alpha-helix height, beta-sheet height, and ratio a helix: b sheet. Amide I peak area, amide I height, α-helix height, and β-sheet height showed significant differences between meal and pellets. Area ratio amide I: amide II and ratio α-helix: β-sheet of canola meal are in the range of those reported by Theodoridou and Yu [4]. However, Xin and Yu [20] reported lower values for amide I area and height, amide II area and height, a helix and b sheet than our study and this might be due to the different sources, batches, storage condition or time of processing of canola in the two experiment.
Xin and Yu [20] said that “the amide I and II bands are the two primary features within the protein spectrum. The amide I band is particularly sensitive to changes in protein secondary structure, and α-helix and β-sheet are the two typical structures in protein secondary structure, which closely relates to nutritional quality, digestive behavior, and nutrient availability. In protein secondary structure, a higher percentage of β-sheet may cause lower protein degradability and utilization”.

3.4. Relationship Study between Protein Structure Spectral Characteristics and Chemical and Nutrient Profiles

3.4.1. Correlation Study between Protein Structure Spectral Characteristics and Chemical Profile

We performed correlation study to indicate that the nutritional values of canola seeds and meal may be related partially to the protein molecular structure characteristics. The correlation analysis between protein structure spectral characteristics and chemical profile of canola seeds (Table 7) indicated that no strong correlation was found between them.
Table 8 shows the correlation analysis between protein structure characteristics and chemical profile of canola meal. Regarding protein profile, CP had a positive correlation with α-helix height (r = 0.61, p < 0.001) while, SCP was positively correlated with amide I area (r = 0.67, p < 0.001), amide I height (r = 0.73, p < 0.001), α-helix height (r = 0.83, p < 0.001), and β-sheet height (r = 0.60, p < 0.001). NPN showed strong positive correlation with amide I area (r = 0.71, p < 0.001), amide I height (r = 0.75, p < 0.001), and α-helix height (r = 0.78, p < 0.001). However, only α-helix height (r = −0.67, p < 0.001) showed a negative correlation with NDICP. In carbohydrate profile, ADF (%NDF) was positively correlated with amide I height (r = 0.68, p < 0.001) and β-sheet height (r = 0.75, p < 0.001), while hemicellulose showed a negative correlation with them (r = −0.66, p < 0.001 and r = −0.74, p < 0.001, respectively).

3.4.2. Correlation Study between Protein Structure Spectral Characteristics and Energy Profile

We did not observe strong correlation between the protein structure characteristics and energy profile in canola seeds (Table 9) or canola meal (Table 10) except td CP of canola meal showed a positive correlation with α-helix height (r = −0.61, p < 0.001).

3.5. Regression Study between Protein Structure Spectral Characteristics and Chemical and Nutrient Profile in Canola Seed or Canola Meal

3.5.1. Regression Study between Protein Structure Spectral Characteristics and Chemical Profile

Multiple regression analyses were conducted to select variables to predict nutrient profiles. The tested multiple regression model was Y = Amide I and II peak area (AI_II_T) + amide I area (AI) + amide I height (AIH) + amide II area (AII) + amide II height (AIIH) + area ratio of amide I to amide II (R_AAI_II) + height ratio of amide I to amide II (R_H_AI_II) + α-helix height (Alpha) + β-sheet height (Beta) + height ratio of α-helix to β-sheet (R_Ha_b), with variables (p < 0.05) selected to leave in the prediction equation. Table 11 shows regression analyses for predicting chemical profile of canola seeds. Height ratio of amide I to amide II was left in the model as a predictor for DM and ADL, while amide I and II peak area and amide I area could be used as predictors for SCP, NPN (%SCP) and NDICP.
For predicting chemical profile of canola meal (Table 12), α-helix height could be used to predict DM and NDICP. Ash and NFC (%CHO) were predicted by amide II height and height ratio of α-helix to β-sheet while, the height ratio of α-helix to β-sheet was a single predictor for CP and sugar (%NFC). In addition, height ratio of amide I to amide II was left in the model as a single predictor for CHO and ADL (%DM). Amide II height, amide II area and β-sheet height could be left in the model as a single predictor for ADF (%DM), ADL (%NDF), ADF (%NDF), and Cellulose respectively. Height ratio of amide I to amide II and α-helix height were left in the model to detect SCP. Height ratio of amide I to amide II, α-helix height and amide I and II peak area could be used to detect NPN (%SCP). In summary, protein structure spectral features could be used as predictors for the chemical profile of canola meal.

3.5.2. Regression Study between Protein Structure Spectral Characteristics and Energy Profile

We found that no variables met the 0.05 significance level for entry into the model to detect energy values of canola seeds (Table 13). Multiple regression analyses for predicting energy values of canola meal are shown in Table 14. Height ratio of amide I to amide II could be used as a predictor for digestible energy at one times maintenance, digestible energy at a productive level of intake, metabolizable energy at production level of intake, net energy for lactation at productive level, metabolizable energy, net energy for maintenance, and net energy for gain. Truly digestible neutral detergent fiber and truly digestible crude protein could be predicted by height ratio of α-helix to β-sheet. However, amide II area and height ratio of α-helix to β-sheet could be variables to predict truly digestible non-fiber carbohydrate. Total digestible nutrients were predicted by the area ratio of amide I to amide II.

4. Conclusions

Based on the results mentioned above, it was indicated that protein molecular structure of canola could be characterized on a molecular basis using FT/IR molecular spectroscopy and chemical and nutrient profiles could be correlated to its protein molecular structure. In addition, the chemical profile, and inherent molecular structures of canola meal were affected by the bio-processing during its manufacture. Canola seeds in Canada had different chemical profile and protein molecular structure, when compared with canola seeds in China but we did not detect a difference between them in the bioenergy profile. On the other hand, canola meal in Canada and China were different in chemical profile, energy values, and protein molecular structures. Concerning comparison crusher plants within Canada, within China, and between meal and pellets within Canada, our result reflected variations among bio-oil processing products among the different crushing plants within Canada and within China. Generally, crusher plants within Canada showed variations in the chemical profile (seeds and meal) and bioenergy values (meal). The seeds from crusher plants within China showed variations in dry matter, crude protein, and acid detergent-insoluble crude protein from chemical profile, td CP from bioenergy values, and in protein molecular structures. However, the meal from the same crusher plants within China were different in the chemical profile, tdNDF, tdNFC, tdCP from energy profile, and protein molecular structures. Regarding the comparison of meal versus pellets in Canada, values were significantly different in the chemical profile, bioenergy profile, and protein molecular structures (amide I, amide I height, α-helix height, and β-sheet height). We only found a strong correlation between canola meal and protein molecular structures in some parameters in the chemical profile, and bioenergy profile. Further study should be done to study the relationship between their protein molecular structure and protein utilization and availability.

Acknowledgments

The authors would like to thank Brittany Dyck and Qin Guoqin (Canola Council of Canada) and Xuewei Zhang and Su Qian (Tianjin Agricultural University) for help sampling canola seed and canola meal and pellets in various crushers in Canada and China and Zhiyuan Niu (University of Saskatchewan) for the lab and technical assistance. The SRP Chair (PY) research programs have been supported by the Ministry of Agriculture Strategic Research Chair (PY) Program, SaskCanola, Natural Sciences and Engineering Research Council of Canada (NSERC-Individual Discovery grant and NSERC-CRD grant), the Saskatchewan Agriculture Development Fund (ADF), SaskMilk, Saskatchewan Forage Network (SNK), Saskatchewan Pulse Producers, Western Grain Research Foundation (WGRF), Prairie Oat Growers Association (POGA) etc.

Author Contributions

W.M.S.G is a PhD student under P.Y.’s supervision at the University of Saskatchewan, Canada, and performed the experiments and wrote the draft paper at the University of Saskatchewan; G.M.M. is a collaborator for W.M.S.G.’s project. P.Y. is the principle investigator and the mentor/supervisor and designed the project and revised the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Bioactive compounds, anti-nutritional factors, and chemical composition of oil-seeds from bio-oil processing (canola seeds): Comparison of crusher plants within Canada and within China as well as between Canada and China.
Table 1. Bioactive compounds, anti-nutritional factors, and chemical composition of oil-seeds from bio-oil processing (canola seeds): Comparison of crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within CanadaCrusher Plants within ChinaOverall
C1C2C3C4C5* SEMp-ValueABCDESEMp-ValueCanadaChinaSEMp-Value
Basic chemical
** DM (%)93.08 b94.70 a92.94 b91.91 c91.66 c0.181<0.00192.14 a91.96 a92.12 a92.22 a91.45 b0.087<0.00192.86 a91.98 b0.2170.008
Ash (%DM)3.98 a3.72 b4.00 a3.83 a,b3.73 b0.0520.0073.733.823.823.843.860.0420.2933.853.810.0300.393
EE (%DM)43.1942.5845.3245.2243.581.3150.51042.3346.2745.3243.6544.470.9690.11543.9844.410.5470.582
FA (%DM)42.1941.5844.3244.2242.581.3150.51041.3345.2744.3242.6543.470.9690.11542.9843.410.5470.582
Protein profile
CP (%DM)23.1721.9522.8321.9222.020.3250.06222.35 a21.48 b22.14 a,b22.16 a,b22.02 a,b0.1660.03522.3822.030.1490.110
SCP (%DM)11.27 a,b,c9.67 c10.81 b,c12.22 a,b12.81 a0.351<0.00113.5112.7213.4611.7912.980.8570.62811.36 b12.89 a0.3440.004
SCP (%CP)48.64 b44.06 b47.38 b55.71 a58.20 a1.261<0.00160.5059.2060.7853.0858.963.7600.61350.80 b58.50 a1.5520.002
NPN (%DM)8.688.308.248.106.620.8200.4825.345.322.703.182.950.9850.2067.99 a3.90 b0.430<0.001
NPN (%CP)37.4437.8436.1336.8930.103.6410.57223.8824.8712.1714.2913.404.5760.20735.68 a17.72 b1.951<0.001
NPN (%SCP)76.96 a,b85.87 a76.12 a,b66.15 a,b51.86 b6.0750.02440.1543.3320.1926.5522.918.7430.29471.39 a30.63 b4.002<0.001
NDICP (%DM)2.61 a2.65 a2.29 b2.27 b1.98 c0.060<0.0012.042.072.012.021.980.1110.9812.36 a2.03 b0.058<0.001
NDICP (%CP)11.26 a,b12.09 a10.04 b,c10.37 b,c9.00 c0.3050.0019.149.679.109.149.010.5230.90410.55 a9.21 b0.2610.001
ADICP (%DM)1.20 a1.10 a,b0.95 b1.18 a1.14 a0.0340.0031.04 b1.19 a1.17 a,b1.22 a1.17 a,b0.0320.0171.111.160.0240.207
ADICP (%CP)5.18 a5.04 a4.16 b5.41 a5.16 a0.1840.0064.64 b5.54 a5.29 a,b5.52 a5.34 a,b0.1590.0154.995.270.1210.121
Carbohydrate profile
CHO (%DM)29.6631.7627.8529.0430.671.4360.41331.5028.5228.7230.3429.660.9580.24029.7929.750.5660.956
Sugar (%DM)4.724.535.405.975.890.4760.1857.675.767.305.995.421.0200.4745.30 b6.43 a0.3620.037
Sugar (%NFC)30.96 a,b28.10 b38.73 a,b44.05 a36.44 a,b3.0610.02942.6242.6552.2639.7837.375.9790.50235.66 b42.94 a2.2970.033
NDF (%DM)16.9418.0716.1817.6816.460.5330.13715.9316.7116.6717.3417.040.7120.70317.0616.740.2880.428
ADF (%DM)12.4312.7712.1613.2012.160.3710.29511.7612.2611.3811.8512.090.3720.54212.54 a11.87 b0.1690.009
ADF (%NDF)73.3470.9075.2174.7073.892.0010.60774.0973.3268.2768.5771.021.8100.14873.6171.050.8960.053
ADL (%DM)5.48 b5.82 a,b4.99 b6.58 a5.80 a,b0.1930.0025.296.116.365.975.780.2580.116
ADL (%NDF)32.37 a,b32.31 a,b30.82 b37.22 a35.24 a,b1.2820.03233.2436.7238.1434.5933.921.6300.25433.6135.320.7870.136
Hemicellulose (%DM)4.515.304.014.484.310.4550.4034.174.455.295.494.950.4780.3174.524.870.2160.263
Cellulose (%DM)6.956.957.186.626.350.2720.2966.466.155.035.876.310.4380.2306.81 a5.96 b0.1770.002
NFC (%DM)15.3316.3413.9713.6316.181.2080.42317.6213.8914.0615.0314.600.8380.06015.0915.040.5140.943
NFC (%CHO)51.6950.9749.8946.9852.792.0030.36055.8448.5848.9149.6249.191.7640.07350.4650.430.9570.982
NSC (%DM)4.724.535.405.975.890.4760.1857.675.767.305.995.421.0200.4745.30 b6.43 a0.3620.037
Notes: * SEM, standard error of the mean. ** DM, dry matter; EE, ether extract; FA, fatty acid; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Hemicellulose = NDF − ADF; Cellulose =ADF − ADL; NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. Means in the same row with different letters (a,b,c) differ significantly (p < 0.05).
Table 2. Bioactive compounds, anti-nutritional factors and chemical composition of co-products from bio-oil processing (canola meal): Comparison of crusher plants within Canada and within China as well as between Canada and China.
Table 2. Bioactive compounds, anti-nutritional factors and chemical composition of co-products from bio-oil processing (canola meal): Comparison of crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within Canada Contrast p ValueCrusher Plants within China Overall (Meal Only)
C1 MealC2 MealC3 PelletC4 PelletC5 Pellet* SEMp ValueMeal vs. PelletABCDESEMp ValueCanadaChinaSEMp Value
Basic chemical
** DM (%)89.6989.0388.7289.8488.990.4320.3520.66488.2388.5288.5088.1688.780.2730.53289.36 a88.44 b0.1960.004
Ash (%DM)7.67 b,c8.29 a8.19 a,b7.46 c7.27 c0.1240.00060.0137.09 b7.12 b7.38 a7.14 a,b7.33 a,b0.0530.0097.98 a7.21 b0.0860.001
Protein profile
CP (%DM)42.42 a40.86 b41.62 a,b41.78 a,b41.77 a,b0.2770.0330.75242.4143.3143.0443.4241.910.3310.04141.64 b42.82 a0.2840.009
SCP (%DM)7.33 b7.40 b8.56 a,b9.34 a7.72 a,b0.3850.0180.00810.05 b9.81 b,c11.48 a10.12 a,b8.46 c0.3050.0017.37 b9.99 a0.356<0.001
SCP (%CP)17.28 b18.08 b20.57 a,b22.34 a18.49 a,b0.8380.0100.00523.73 a,b22.66 b26.67 a23.32 a,b20.19 b0.7730.00217.68 b23.31 a0.793<0.001
NPN (%DM)7.13 a,b6.90 a,b7.89 a,b8.33 a6.04 b0.4370.0310.3358.45 b8.93 b10.06 a8.69 b7.53 b0.2760.0017.02 b8.63 a0.330.003
NPN (%CP)16.79 a,b16.86 a,b18.96 a,b19.93 a14.45 b0.9730.0200.30819.95 b19.38 b23.38 a20.01 b17.97 b0.7180.00416.83 b20.14 a0.7410.005
NPN (%SCP)96.90 a93.07 a92.21 a89.23 a78.15 b1.8700.0010.00184.0085.5687.6985.8689.011.2330.10994.98 a86.43 b1.089<0.001
NDICP (%DM)7.78 a,b9.03 a5.93 b5.95 b7.99 a,b0.5580.0100.0064.13 c6.59 a4.08 c5.30 b5.83 b0.135<0.0018.40 a5.19 b0.381<0.001
NDICP (%CP)18.32 a,b22.14 a14.25 b14.24 b19.12 a,b1.4050.0110.0079.74 c15.21 a9.49 c12.20 b13.90 a0.288<0.00120.23 a12.11 b0.941<0.001
ADICP (%DM)2.35 a2.27 a,b1.90 c2.23 b2.19 b0.024<0.001<0.0012.08 b2.76 a2.08 b2.06 b2.30 a,b0.1000.0022.312.250.0920.659
ADICP (%CP)5.54 a5.56 a4.56 b5.34 a5.22 a0.082<0.001<0.0014.90 b6.37 a4.83 b4.75 b5.48 a,b0.2320.0035.555.270.2120.357
Carbohydrate profile
CHO (%DM)49.90 a50.84 a50.19 a50.76 a50.96 a,b,c0.2480.0520.27550.4949.5749.5849.4450.760.3300.05350.3749.970.2450.261
Sugar (%DM)7.62 a,b8.35 a,b8.61 a7.20 b8.30 a,b0.2630.0180.8328.33 b7.99 b8.22 b8.44 b10.62 a0.3220.0017.988.720.3350.137
Sugar (%NFC)28.75 b,c32.24 a,b31.01 a,b,c27.93 c33.03 a0.9190.0120.85332.41 b31.89 b34.26 b35.53 a,b41.07 a1.3460.00530.50 b35.03 a1.2240.017
NDF (%DM)31.18 b33.97 a28.35 c30.96 b33.82 a0.541<0.0010.01128.90 b31.11 a29.66 a,b31.20 a30.71 a0.3230.00332.58 a30.28 b0.4310.001
ADF (%DM)19.94 bc21.84 a19.32 c22.06 a20.94 a,b0.259<0.0010.62220.9821.4520.4620.6119.930.3700.12420.8920.690.2990.637
ADF (%NDF)63.94 b64.37 b68.17 a,b71.34 a61.92 b1.4880.0080.05272.59 a68.96 a,b69.00 a,b66.49 b,c64.88 c0.8020.00164.16 b68.39 a0.9350.005
ADL (%DM)9.41 b10.45 a7.78 c10.22 a9.20 b0.131<0.0010.00019.08 a,b10.01 a8.44 b8.85 b8.49 b0.2390.0069.93 a8.97 b0.2280.008
ADL (%NDF)30.19 b30.80 b27.47 c33.04 a27.21 c0.472<0.0010.01631.4 a,b32.18 a28.46 b,c28.55 b,c27.66 c0.7620.00630.4929.650.6520.373
Hemicellulose (%DM)11.24 a,b12.12 a9.04 b8.90 b12.88 a0.6070.0020.0297.91c9.66 a,b9.20 b10.39 a10.78 a0.2440.00111.68 a9.59 b0.3690.001
Cellulose (%DM)10.53b11.39 a,b11.53 a,b11.84 a11.73 a0.2310.0170.00611.9011.4412.0211.7611.440.3030.57110.96 b11.71 a0.1760.007
NFC (%DM)26.49 a,b25.90 b,c27.77 a25.75 b,c25.12 c0.2910.0010.94625.72 a25.05 a,b24.01 b23.74 b25.87 a0.3100.00226.20 a24.88 b0.310.008
NFC (%CHO)53.10 a,b50.94 b,c55.33 a50.72 b,c49.30 c0.521<0.0010.62650.94 a50.55 a,b48.43 a,b48.02 b50.97 a0.5530.00752.02 a49.78 b0.5280.007
NSC (%DM)8.62 a,b9.35 a,b9.61 a8.20 b9.30 a,b0.2630.0180.8329.33 b8.99 b9.22 b9.44 b11.62 a0.3220.0018.989.720.3350.137
Notes: * SEM, standard error of the mean. ** DM, dry matter; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Hemicellulose = NDF − ADF; Cellulose = ADF − ADL; NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. Means in the same row with different letters (a,b,c) differ significantly (p < 0.05).
Table 3. Digestible nutrients and bioenergy values of canola seeds: Comparison of crusher plants within Canada and within China as well as between Canada and China.
Table 3. Digestible nutrients and bioenergy values of canola seeds: Comparison of crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within CanadaCrusher Plants within ChinaOverall
C1C2C3C4C5* SEMp ValueABCDESEMp ValueCanadaChinaSEMp Value
Digestible nutrients % of DM
 ** td NDF3.143.453.302.872.990.2460.5003.062.842.663.293.290.2820.4643.153.030.1170.464
 td NFC15.0216.0213.6913.3515.861.1840.42217.2713.6213.7814.7314.310.8210.06014.7914.740.5040.947
 td CP22.6921.5122.4521.4421.570.3280.06021.93 a21.00 b21.67 a,b21.67 a,b21.55 a,b0.1700.03221.9321.570.1520.099
 td FA42.1941.5844.3244.2242.581.3150.51041.3345.2744.3242.6543.470.9690.11542.9843.410.5470.582
 TDN 1X128.79127.52132.17130.16129.231.8320.501128.25132.31130.82128.66129.941.4560.340129.57130.000.7450.689
 TDN p 3X118.28117.11121.38119.54118.681.6830.502117.78121.52120.15118.16119.341.3360.338119.00119.390.6840.688
 TDN p 4X113.02111.90115.98114.22113.401.6080.502112.55116.11114.81112.91114.031.2780.341113.71114.080.6540.687
Energy values (Mcal/kg DM)
 DE 1x5.705.635.845.745.700.0790.4905.675.825.775.685.730.0620.4185.725.740.0320.779
 DE p 3x5.235.175.365.275.240.0720.4645.205.355.305.225.260.0560.3955.265.270.0290.821
 ME p 3x5.024.955.165.075.030.0790.5004.995.155.105.005.060.0610.3775.055.060.0320.745
 NEL p 3x3.623.573.743.673.630.0680.5093.593.743.693.613.660.0520.3383.643.660.0270.744
 ME 3x4.674.614.794.714.670.0650.4744.654.774.734.664.700.0500.4024.694.700.0260.760
 NE m3x3.343.303.433.373.340.0490.5023.323.423.383.333.360.0380.3463.363.360.0200.831
 NE g 3x2.432.402.502.452.430.0380.4962.422.492.472.422.450.0290.4162.442.450.0150.735
 DE p 4x5.004.945.125.045.000.0680.4724.975.115.064.995.030.0530.4135.025.030.0270.784
 ME p 4x4.794.724.924.834.790.0760.4864.754.914.864.774.820.0590.4024.814.820.0300.782
 NEL p 4x3.453.403.563.493.450.0650.5143.413..563.513.443.480.0500.3093.473.480.0260.761
Notes: * SEM, standard error of the mean. ** td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; td FA, truly digestible fatty acid; TDN 1x, total digestible nutrients at one times maintenance; TDN p 3x, total digestible nutrients at productive level of intake at three times maintenance; TDN p 4x, total digestible nutrients at productive level at four times maintenance; DE 1x, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake (3x maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (3x maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain. Means in the same row with different letters (a,b) differ significantly (p < 0.05).
Table 4. Digestible nutrients and bioenergy values of co-products from bio-oil processing (canola meal): Comparison crusher plants within Canada and within China as well as between Canada and China.
Table 4. Digestible nutrients and bioenergy values of co-products from bio-oil processing (canola meal): Comparison crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within CanadaContrast p ValueCrusher Plants within ChinaOverall (Meal Only)
C1 MealC2 MealC3 PelletC4 PelletC5 Pellet* SEMp ValueMeal vs. PelletABCDESEMp ValueCanadaChinaSEMp Value
Digestible nutrients % of DM
 ** td NDF4.78 c4.787 c5.560 b4.987 b,c6.203 a0.132<0.001<0.0015.75 a,b4.91 b6.72 a6.43 a6.29 a0.2320.0024.78 b6.02 a0.2210.001
 td NFC25.97 a,b25.38 b,c27.22 a25.23 b,c24.62 c0.285<0.0010.96225.21 a24.55 a,b23.53 b23.27 b25.35 a0.3040.00225.68 a24.38 b0.3040.007
 td CP41.49 a39.95 b40.86 a,b40.88 a,b40.90 a,b0.2820.0400.54041.58 a,b42.20 a,b42.21 a,b42.59 a40.99 b0.3280.04240.72 b41.92 a0.2810.007
 TDN 1X65.23 b63.12 d66.64 a64.11 c,d64.73 b,c0.239<0.0010.00165.5564.6665.4665.2965.640.2880.19864.18 b65.32 a0.2700.007
 TDN p 3X59.90 b57.97 d61.20 a58.87 c,d59.45 b,c0.219<0.0010.00160.2059.3860.1259.9660.280.2630.19158.94 b59.99 a0.2480.008
 TDN p 4X57.24 b55.40 d58.48 a56.25 c,d56.81 b,c0.209<0.0010.00157.5256.7457.4457.3057.600.2530.19856.32 b57.32 a0.2370.008
Energy values (Mcal/kg DM)
 DE 1x3.31 a,b3.21 c3.36 a3.26 b,c3.29 b0.012<0.0010.0033.333.303.343.333.320.0160.5393.26 b3.33 a0.0130.003
 DE p 3x3.04 a,b2.94 c3.09 a3.00 b3.02 b0.011<0.0010.0023.063.033.063.063.050.0160.5632.99 b3.05 a0.0130.004
 ME p 3x2.62 a,b2.52 c2.67 a2.58 b2.60 b0.001<0.0010.0022.642.612.642.642.630.0160.5632.57 b2.63 a0.0130.004
 NEL p 3x1.65 a,b1.58 c1.69 a1.62 b1.64 b0.008<0.0010.0011.661.651.671.671.660.0100.5461.62 b1.66 a0.0090.002
 ME 3x2.72 a,b2.63 c2.76 a2.67 b2.69 b0.010<0.0010.0022.732.712.742.732.730.0140.5732.67 b2.73 a0.0110.003
 NE m3x1.80 a,b1.72 c1.83 a1.76 b,c1.77 b0.0100.0010.0091.811.791.811.811.800.0110.5411.76 b1.80 a0.0100.004
 NE g 3x1.17 a,b1.10 d1.20 a1.13 c1.15 b,c0.007<0.0010.0031.181.161.181.181.180.0100.6271.14 b1.18 a0.0090.005
 DE p 4x2.91 a,b2.81 d2.95 a2.86 c,d2.88 b,c0.011<0.0010.0032.922.902.932.922.920.0140.5772.86 b2.92 a0.0120.003
 ME p 4x2.49 a,b2.39 c2.53 a2.44 b,c2.46 b0.011<0.0010.0032.502.482.512.502.500.0140.5732.44 b2.50 a0.0120.003
 NEL p 4x1.56 a,b1.49 d1.59 a1.52 c,d1.54 b,c0.007<0.0010.0031.571.551.571.571.570.0100.6271.53 b1.57 a0.0090.005
Notes: * SEM, standard error of the mean. ** td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; td FA, truly digestible fatty acid; TDN 1x, total digestible nutrients at one times maintenance; TDN p 3x, total digestible nutrients at productive level of intake at three times maintenance; TDN p 4x, total digestible nutrients at productive level at four times maintenance; DE 1x, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake (3x maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (3x maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain. Means in the same row with different letters (a,b,c,d) differ significantly (p < 0.05).
Table 5. Protein molecular structure characteristics of oil-seeds from bio-oil processing (canola seeds): Comparison of crusher plants within Canada and within China as well as between Canada and China.
Table 5. Protein molecular structure characteristics of oil-seeds from bio-oil processing (canola seeds): Comparison of crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within CanadaCrusher Plants within ChinaOverall
C1C2C3C4C5* SEMp ValueABCDESEMp ValueCanadaChinaSEMp Value
Amide I and II peak area44.1641.4443.1945.9048.022.1970.32842.7645.1048.1344.1554.013.9410.33944.5446.831.4860.286
Amide I21.2420.2020.4822.5422.231.0020.42219.8020.4322.1720.5925.271.9040.32221.3421.650.7070.757
Amide II6.266.445.796.366.260.4640.8695.665.166.326.436.850.5710.3076.226.080.2310.679
Area ratios of amide I and II3.483.163.663.923.720.2970.4843.704.093.813.243.820.3980.6673.593.730.1510.508
Amide I Height0.3240.3100.3110.3430.3290.0150.5620.2900.2970.3210.3100.3540.0210.2960.320.310.0080.454
Amide II Height0.1380.1420.1320.1360.1290.0090.8450.1200.1110.1310.1330.1340.0100.4420.140.130.0040.099
Height ratios of amide I and II2.392.202.402.612.620.1070.0952.492.732.502.382.710.1650.5272.452.560.0660.223
α-helix height0.3040.2910.2770.3100.3040.0150.5750.2630.2670.2980.2810.3360.0230.2360.300.290.0090.526
β-sheet height0.2800.2610.2680.3060.2860.0130.2020.2440.2520.2720.2640.3040.0170.2140.280.270.0080.247
Ratio α-helix: β-sheet1.083 a,b1.121 a1.037 b1.013 b1.064 a,b0.0180.0141.0771.0581.0931.0631.1020.0250.6931.061.080.0110.355
Notes: * SEM, standard error of the mean. Means in the same row with different letters differ significantly (p < 0.05).
Table 6. Protein molecular structure characteristics of co-products from bio-oil processing (canola meal): Comparison of crusher plants within Canada and within China as well as between Canada and China.
Table 6. Protein molecular structure characteristics of co-products from bio-oil processing (canola meal): Comparison of crusher plants within Canada and within China as well as between Canada and China.
ItemsCrusher Plants within CanadaContrast p ValueCrusher Plants within ChinaOverall (Meal Only)
C1 MealC2 MealC3 PelletC4 PelletC5 Pellet* SEMp ValueMeal vs. PelletABCDESEMp ValueCanadaChinaSEMp Value
Amide I and II peak area52.9854.0657.2258.9154.252.1180.3120.12156.10 a,b58.78 a57.67 a,b59.81 a53.85 b1.0350.01653.52 b57.24 a1.1380.032
Amide I23.3524.2925.9826.7424.310.8520.0970.03825.49 a,b26.76 a,b26.54 a,b27.08 a24.30 b0.5480.02823.82 b26.04 a0.5180.007
Amide II7.527.597.758.348.020.3270.4250.1388.06 a8.04 a7.94 a8.00 a7.21 b0.1870.0417.567.850.1820.269
Area ratios of amide I and II3.12 b3.20 a,b3.36 a3.21 a,b3.04 b0.0450.0060.3693.17 b3.33 a,b3.35 a3.39 a3.38 a0.0380.0153.16 b3.32 a0.0330.003
Amide I Height0.3270.3450.3690.3750.3490.0130.1630.0440.370 a,b0.376 a,b0.377 a,b0.381 a0.344 b0.0070.0320.336 b0.370 a0.0080.006
Amide II Height0.1600.1660.1680.1770.1780.0090.5790.1930.1780.1750.1660.1700.1610.0040.0590.1630.1700.0040.258
Height ratios of amide I and II2.062.082.202.121.970.0550.1170.6262.07 b2.15 a,b2.28 a2.25 a,b2.14 a,b0.0420.0362.07 b2.18 a0.0330.028
α-helix height0.2890.3000.3280.3340.3150.0120.1030.0160.332 b0.346 a,b0.350 a,b0.362 a0.321 b0.0060.0080.295 b0.342 a0.007<0.001
β-sheet height0.2860.3050.3320.3330.3070.0120.0990.0300.331 a0.332 a0.325 a,b0.328 a,b0.302 b0.0060.0270.295 b0.324 a0.0070.008
Ratio α-helix: β-sheet1.0130.9840.9871.0071.0300.0180.3650.5671.005 b1.043 a,b1.077 a1.105 a1.063 a,b0.0140.0050.999 b1.058 a0.0130.005
Notes: * SEM, standard error of the mean. Means in the same row with different letters (a,b) differ significantly (p < 0.05).
Table 7. Correlation analyses between protein structure spectral characteristics and chemical profile of canola seeds.
Table 7. Correlation analyses between protein structure spectral characteristics and chemical profile of canola seeds.
Items** AI_II_TAIAIIR_AAI_IIAIHAIIHR_HAI_IIAlphaBetaR_Ha_b
*** r Valuep ValueR Valuep Valuer Valuep ValueR Valuep Valuer Valuep ValueR Valuep Valuer Valuep Valuer Valuep Valuer Valuep Valuer Valuep Value
 * DM (%)−0.450.012−0.330.072−0.070.704−0.280.133−0.220.2510.180.356−0.540.002−0.190.328−0.290.1160.220.235
 Ash (%DM)−0.100.614−0.030.8660.020.9130.000.9860.010.9730.040.8210.020.939−0.010.9650.090.621−0.170.368
 EE (%DM)0.220.2420.160.402−0.130.4960.290.1220.090.624−0.110.5610.260.1610.050.7860.060.748−0.110.578
 FA (%DM)0.220.2420.160.402−0.130.4960.290.1220.090.624−0.110.5610.260.1610.050.7860.060.748−0.110.578
Protein profile
 CP (%DM)0.080.6590.180.3370.120.5180.000.9850.250.1880.360.053−0.160.4020.230.2190.290.120−0.080.682
 SCP (%DM)0.520.0030.390.0330.200.2820.090.6420.270.1510.040.8400.230.2250.260.1600.200.2790.090.656
 SCP (%CP)0.520.0030.370.0420.180.3460.120.5390.230.215−0.030.8900.280.1300.240.2110.180.3470.070.716
 NPN (%DM)−0.300.106−0.150.433−0.210.2770.070.7220.000.9960.080.684−0.110.582−0.050.8030.030.867−0.260.173
 NPN (%CP)−0.320.081−0.180.347−0.230.2170.080.673−0.030.8600.020.914−0.090.646−0.090.657−0.010.954−0.240.202
 NPN (%SCP)−0.410.025−0.250.181−0.160.394−0.060.740−0.090.6370.130.502−0.280.140−0.110.572−0.070.723−0.110.549
 NDICP (%DM)−0.520.003−0.320.090−0.160.400−0.080.686−0.150.4250.070.722−0.260.170−0.160.413−0.090.634−0.120.528
 NDICP (%CP)−0.570.001−0.390.036−0.180.335−0.110.579−0.220.235−0.010.980−0.250.183−0.220.253−0.160.408−0.120.538
 ADICP (%DM)−0.000.9820.030.8750.100.601−0.110.5470.070.709−0.050.7920.120.5180.040.8350.110.573−0.100.608
 ADICP (%CP)0.001.0000.010.9710.070.705−0.080.6640.030.890−0.130.4890.190.326−0.010.9590.050.777−0.090.644
CHO profile
 CHO (%DM)−0.190.304−0.170.3630.100.596−0.240.201−0.150.432−0.030.866−0.140.475−0.120.535−0.140.4770.110.575
 Sugar (%DM)0.360.0540.280.1280.260.173−0.060.7510.190.3160.150.444−0.100.6130.160.3920.170.367−0.030.869
 Sugar (%NFC)0.450.0140.360.0490.230.2260.020.9230.270.1560.160.3940.010.9410.210.2550.260.164−0.170.365
 NDF (%DM)−0.340.068−0.180.3440.050.780−0.160.393−0.080.6920.000.984−0.110.572−0.090.6480.000.990−0.050.796
 ADF (%DM)−0.300.113−0.100.6000.020.900−0.080.6830.050.8140.080.672−0.130.486−0.010.9770.160.408−0.140.477
 ADF (%NDF)0.080.6780.110.5610.060.7380.020.9060.150.4430.170.367−0.120.5250.120.5380.210.276−0.060.771
 ADL (%DM)0.120.5140.130.484−0.080.6770.220.2330.050.801−0.240.2050.370.0470.030.8710.080.692−0.060.767
 ADL (%NDF)0.350.0600.280.137−0.070.7110.310.0930.130.510−0.210.2750.430.0190.150.4410.130.4900.050.799
 Hemi (%DM)−0.140.468−0.120.5290.010.973−0.100.593−0.130.506−0.120.5340.060.737−0.100.617−0.150.4240.040.816
 Cell (%DM)−0.330.074−0.170.3830.080.694−0.230.215−0.010.9680.240.209−0.380.037−0.050.8030.050.800−0.030.858
 NFC (%DM)−0.180.347−0.210.273−0.010.952−0.120.517−0.200.301−0.070.725−0.130.492−0.150.445−0.220.2330.260.162
 NFC (%CHO)−0.100.606−0.150.426−0.080.6670.000.994−0.170.372−0.070.713−0.120.533−0.100.608−0.220.2390.330.078
 NSC (%DM)0.360.0540.280.1280.260.173−0.060.7510.190.3160.150.444−0.100.6130.160.3920.170.367−0.030.869
Notes: * DM, dry matter; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Hemi, Hemicellulose (Hemicellulose = NDF − ADF); Cell, Cellulose (Cellulose = ADF − ADL); NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. ** AI_II_T, Amide I and II peak area; AI, Amide I area; AII, Amide II area; R_AAI_II, Area ratios of amide I and II; AIH, Amide I height; AIIH, Amide II height; R_HAI_II, Height ratios of amide I and II; alpha, α-helix height; beta, β-sheet height; R_Ha_b, Ratio α-helix:β-sheet. *** r: correlation coefficient calculated using Spearman method.
Table 8. Correlation analyses between protein structure spectral characteristics and chemical profile of canola meal.
Table 8. Correlation analyses between protein structure spectral characteristics and chemical profile of canola meal.
Items** AI_II_TAIAIIR_AAI_IIAIHAIIHR_HAI_IIAlphaBetaR_Ha_b
*** r Valuep ValueR Valuep Valuer Valuep ValueR Valuep Valuer Valuep Valuer Valuep Valuer valuep Valuer Valuep Valuer Valuep Valuer Valuep Value
 * DM (%)−0.270.155−0.190.319−0.070.707−0.270.142−0.340.066−0.220.237−0.070.718−0.380.038−0.330.079−0.180.345
 Ash (%DM)−0.250.177−0.260.163−0.340.070−0.050.797−0.390.035−0.330.0750.010.954−0.550.002−0.290.123−0.520.004
Protein profile
 CP (%DM)0.400.0280.420.0210.220.2510.320.0810.430.0170.050.7860.330.0750.61<0.0010.290.1190.580.001
 SCP (%DM)0.560.0010.67<0.00010.340.0630.490.0060.73<0.00010.080.6930.590.0010.83<0.00010.60<0.0010.460.010
 SCP (%CP)0.560.0010.67<0.00010.350.0580.470.0090.74<0.00010.100.5880.570.0010.82<0.00010.610.0010.440.014
 NPN (%DM)0.630.0000.71<0.00010.390.0330.450.0140.75<0.00010.100.5860.590.0010.78<0.00010.63<0.0010.360.050
 NPN (%CP)0.590.0010.68<0.00010.340.0660.450.0120.70<0.00010.050.8090.620.0000.73<0.00010.590.0010.330.078
 NPN (%SCP)−0.080.673−0.140.449−0.220.2330.030.873−0.220.243−0.240.1970.050.803−0.390.034−0.110.557−0.400.029
 NDICP (%DM)−0.420.021−0.450.012−0.210.264−0.420.021−0.570.001−0.090.635−0.470.009−0.67<0.0001−0.540.002−0.370.046
 NDICP (%CP)−0.430.018−0.470.009−0.220.236−0.430.019−0.580.001−0.080.656−0.480.008−0.68<0.0001−0.540.002−0.380.038
 ADICP (%DM)−0.130.501−0.130.4860.080.691−0.280.128−0.190.3110.110.549−0.410.025−0.320.087−0.270.155−0.180.345
 ADICP (%CP)−0.170.381−0.160.3970.040.851−0.260.160−0.210.2720.090.618−0.420.020−0.340.063−0.280.133−0.220.242
CHO profile
 CHO (%DM)−0.410.026−0.410.024−0.070.700−0.430.017−0.380.0390.120.519−0.540.002−0.500.005−0.310.090−0.370.045
 Sugar (%DM)−0.270.154−0.250.185−0.450.0120.250.182−0.150.418−0.310.0960.100.6000.030.855−0.200.2820.280.132
 Sugar (%NFC)−0.140.457−0.070.694−0.280.1290.360.049−0.020.930−0.330.0720.220.2430.290.122−0.180.3430.580.001
 NDF (%DM)−0.320.082−0.330.078−0.060.740−0.390.031−0.440.016−0.070.713−0.400.028−0.400.027−0.520.003−0.050.781
 ADF (%DM)0.150.4340.120.5200.410.026−0.380.0390.160.3970.410.026−0.420.022−0.040.8290.160.395−0.280.139
 ADF (%NDF)0.550.0020.540.0020.460.0110.130.5080.68<0.0010.450.0130.150.4190.510.0040.75<0.001−0.080.689
 ADL (%DM)0.010.9470.010.9780.300.112−0.490.006−0.010.9750.370.042−0.510.004−0.220.254−0.060.745−0.290.125
 ADL (%NDF)0.300.1050.280.1370.410.025−0.250.1810.330.0740.490.006−0.270.1560.090.6400.350.060−0.250.187
 Hemi (%DM)−0.510.004−0.520.003−0.380.038−0.200.278−0.66<0.001−0.370.043−0.250.184−0.510.004−0.74<0.0010.040.821
 Cell (%DM)0.300.1040.240.2110.310.0920.030.8880.330.0710.200.2900.080.6670.290.1260.380.040−0.010.953
 NFC (%DM)−0.330.072−0.390.032−0.290.121−0.230.221−0.370.045−0.030.880−0.280.130−0.580.001−0.170.376−0.560.001
 NFC (%CHO)−0.250.187−0.300.109−0.270.146−0.130.489−0.280.140−0.010.965−0.230.224−0.490.006−0.090.619−0.520.003
 NSC (%DM)−0.270.154−0.250.185−0.450.0120.250.182−0.150.418−0.310.0960.100.6000.030.855−0.200.2820.280.132
Notes: * DM, dry matter; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Hemi, Hemicellulose (Hemicellulose = NDF − ADF); Cell, Cellulose (Cellulose = ADF − ADL); NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. ** AI_II_T, Amide I and II peak area; AI, Amide I area; AII, Amide II area; R_AAI_II, Area ratios of amide I and II; AIH, Amide I height; AIIH, Amide II height; R_HAI_II, Height ratios of amide I and II; alpha, α-helix height; beta, β-sheet height; R_Ha_b, Ratio α-helix:β-sheet. *** r: correlation coefficient calculated using Spearman method.
Table 9. Correlation analyses between protein structure spectral characteristics and estimated energy values of canola seeds.
Table 9. Correlation analyses between protein structure spectral characteristics and estimated energy values of canola seeds.
Items** AI_II_TAIAIIR_AAI_IIAIHAIIHR_HAI_IIAlphaBetaR_Ha_b
*** r Valuep ValueR Valuep Valuer Valuep ValueR Valuep Valuer Valuep Valuer Valuep Valuer valuep Valuer Valuep Valuer Valuep Valuer Valuep Value
Digestible nutrients % of DM
* td NDF−0.330.072−0.250.1810.110.575−0.320.085−0.120.5130.110.547−0.290.120−0.140.453−0.100.616−0.070.724
td NFC−0.180.346−0.210.272−0.010.954−0.120.514−0.200.299−0.070.723−0.130.495−0.150.442−0.220.2340.260.165
td CP0.080.6800.160.3940.100.5860.000.9810.220.2410.340.063−0.180.3560.220.2550.250.183−0.060.771
td FA0.220.2420.160.402−0.130.4960.290.1220.090.624−0.110.5610.260.1610.050.7860.060.748−0.110.578
TDN 1X0.210.2700.120.525−0.130.4980.230.2190.070.712−0.050.7990.150.4420.060.7660.010.955−0.010.960
TDN p 3X0.210.2700.120.525−0.130.4980.230.2190.070.712−0.050.7990.150.4420.060.7660.010.955−0.010.960
TDN p 4X0.210.2700.120.525−0.130.4980.230.2190.070.712−0.050.7990.150.4420.060.7660.010.955−0.010.960
Energy values (Mcal/kg DM)
DE 1x0.240.2090.160.401−0.100.5930.220.2410.110.5780.000.9870.120.5230.100.6160.050.777−0.020.921
DE p 3x0.230.2290.140.461−0.130.4860.250.1930.080.66−0.030.8930.130.4810.070.7080.030.876−0.030.879
ME p 3x0.220.2440.130.488−0.120.5390.220.2350.080.679−0.030.8920.130.4900.070.7060.030.898−0.010.948
NEL p 3x0.220.2520.150.444−0.130.5090.250.1820.100.615−0.030.8580.150.4230.080.6850.050.783−0.050.806
ME 3x0.230.2310.150.430−0.120.5420.230.2190.100.609−0.010.9440.130.4950.090.6450.050.801−0.030.875
NE m3x0.240.2090.150.427−0.120.5290.240.2080.100.614−0.010.9450.130.4870.090.6560.040.818−0.020.904
NE g 3x0.220.240.150.440−0.110.5470.230.2270.100.604−0.010.9470.130.5040.090.6380.050.787−0.040.833
DE p 4x0.220.2380.150.436−0.110.5640.220.2420.100.611−0.010.9690.120.5270.090.6470.050.81−0.020.900
ME p 4x0.230.2230.160.412−0.100.5840.220.2480.100.591−0.010.9770.120.5180.090.6340.050.792−0.020.905
NEL p 4x0.230.230.150.429−0.110.5620.230.2310.100.605−0.030.8920.140.4470.080.6660.050.814−0.030.882
Notes: * td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; td FA, truly digestible fatty acid; TDN 1x, total digestible nutrients at one times maintenance; TDN p 3x, total digestible nutrients at productive level of intake at three times maintenance; TDN p 4x, total digestible nutrients at productive level at four times maintenance; DE 1x, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake ( three times maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (three times maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain. ** AI_II_T, Amide I and II peak area; AI, Amide I area; AII, Amide II area; R_AAI_II, Area ratios of amide I and II; AIH, Amide I height; AIIH, Amide II height; R_HAI_II, Height ratios of amide I and II; alpha, α-helix height; beta, β-sheet height; R_Ha_b, Ratio α-helix:β-sheet. *** r: correlation coefficient calculated using Spearman method.
Table 10. Correlation analyses between protein structure spectral characteristics and estimated energy values of canola meal.
Table 10. Correlation analyses between protein structure spectral characteristics and estimated energy values of canola meal.
Items** AI_II_TAIAIIR_AAI_IIAIHAIIHR_HAI_IIAlphaBetaR_Ha_b
*** r Valuep ValueR Valuep Valuer Valuep ValueR Valuep Valuer Valuep Valuer Valuep Valuer valuep Valuer Valuep Valuer Valuep Valuer Valuep Value
Digestible nutrients % of DM
* td NDF0.050.8030.090.623−0.040.8480.350.0600.090.621−0.240.1980.420.0190.420.0210.020.8960.550.002
td NFC−0.330.073−0.390.033−0.290.124−0.240.209−0.370.045−0.020.897−0.290.124−0.580.001−0.170.378−0.560.001
td CP0.410.0230.420.0200.210.2670.330.0760.430.0170.040.8420.370.0430.61<0.0010.310.1010.560.001
TDN 1X−0.020.928−0.010.966−0.310.0930.480.0070.040.848−0.300.1020.460.0110.210.2690.110.5810.250.179
TDN p 3X−0.020.921−0.010.957−0.310.0930.480.0080.040.849−0.300.1010.460.0110.210.2730.110.5790.250.184
TDN p 4X−0.020.915−0.010.950−0.310.0900.480.0080.030.858−0.310.0990.460.0110.200.2790.100.5880.250.182
Energy values (Mcal/kg DM)
DE 1x0.070.6980.090.652−0.240.2030.500.0050.140.454−0.260.1730.490.0060.300.1060.190.3220.290.124
DE p 3x0.080.6620.090.626−0.240.1950.510.0040.140.470−0.240.1930.480.0070.290.1240.200.3010.280.139
ME p 3x0.080.6620.090.626−0.240.1950.510.0040.140.470−0.240.1930.480.0070.290.1240.200.3010.280.139
NEL p 3x0.110.5520.130.488−0.220.2480.510.0040.170.359−0.230.2280.490.0060.320.0820.220.2480.270.143
ME 3x0.090.6270.090.621−0.250.1900.510.0040.150.441−0.260.1620.490.0060.300.1040.200.2850.290.126
NE m3x0.100.5920.110.580−0.240.2010.490.0060.160.401−0.240.2030.480.0070.310.0940.210.2720.290.123
NE g 3x0.040.8240.050.798−0.280.1370.500.0050.100.607−0.280.1390.480.0070.260.1590.150.4230.280.138
DE p 4x0.070.6990.090.650−0.260.1610.520.0040.130.494−0.270.1430.490.0060.300.1030.180.3370.300.113
ME p 4x0.090.6380.100.600−0.240.1960.520.0030.150.429−0.260.1610.510.0040.310.0940.200.2870.280.131
NEL p 4x0.050.8100.050.804−0.280.1360.500.0050.100.609−0.270.1440.480.0070.260.1620.150.4230.280.141
Notes: * td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; td FA, truly digestible fatty acid; TDN 1X, total digestible nutrients at one times maintenance; TDN p 3X, total digestible nutrients at productive level of intake at three times maintenance; TDN p 4X, total digestible nutrients at productive level at four times maintenance; DE 1X, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake (3x maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (3x maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain. ** AI_II_T, Amide I and II peak area; AI, Amide I area; AII, Amide II area; R_AAI_II, Area ratios of amide I and II; AIH, Amide I height; AIIH, Amide II height; R_HAI_II, Height ratios of amide I and II; alpha, α-helix height; beta, β-sheet height; R_Ha_b, Ratio α-helix:β-sheet. *** r: correlation coefficient calculated using Spearman method.
Table 11. Multiple regression analyses to find the important protein structural variables for predicting chemical profiles of canola seeds.
Table 11. Multiple regression analyses to find the important protein structural variables for predicting chemical profiles of canola seeds.
Predicted Variables (Y)Variable (s) Selection (Variables Left in the Model with p < 0.05)Prediction Equation Test Model: Y = a + b1 × x1 + b2 × x2…R2 Value* RSDp Value
** DM%*** Height left in the modelDM% = 97.44 − 2.01 × Height0.300.800.002
 Ash (%DM)No variable met the 0.05 significance level for entry into the model
 EE (%DM)No variable met the 0.05 significance level for entry into the model
 FA (%DM)No variable met the 0.05 significance level for entry into the model
Protein profile
 CP (%DM)No variable met the 0.05 significance level for entry into the model
 SCP (%DM)Peak area and AI left in the modelSCP (%DM) = 7.43 + 0.56 × Peak area − 0.97 × AI1.550.620.002
 SCP (%CP)Peak area and AI left in the modelSCP (%CP) = 33.81 + 2.69 × Peak area − 4.74 × AI0.385.760.001
 NPN (%DM)No variable met the 0.05 significance level for entry into the model
 NPN (%CP)No variable met the 0.05 significance level for entry into the model
 NPN (%SCP)Peak area and AI left in the modelNPN (%SCP) = 113.86 − 10.43 × Peak area + 19.24 × AI0.3920.860.001
 NDICP (%DM)Peak area and AI left in the modelNDICP (%DM) = 2.10 − 0.13 × Peak area +0.24 × AI0.510.20<0.001
 NDICP (%CP)Peak area and AI left in the modelNDICP (%CP) = 13.50 − 0.55 × Peak area +1.00 × AI0.510.87<0.001
 ADICP (%DM)No variable met the 0.05 significance level for entry into the model
 ADICP (%CP)No variable met the 0.05 significance level for entry into the model
CHO profile
 CHO (%DM)No variable met the 0.05 significance level for entry into the model
 Sugar (%DM)No variable met the 0.05 significance level for entry into the model
 Sugar (%NFC)No variable met the 0.05 significance level for entry into the model
 NDF (%DM)No variable met the 0.05 significance level for entry into the model
 ADF (%DM)No variable met the 0.05 significance level for entry into the model
 ADF (%NDF)No variable met the 0.05 significance level for entry into the model
 ADL (%DM)Height left in the modelADL (%DM) = 3.76 + 0.82 × Height0.140.540.042
 ADL (%NDF)Height left in the modelADL (%NDF) = 20.43 + 5.61 × Height0.212.820.010
 Cell (%DM)No variable met the 0.05 significance level for entry into the model
 NFC (%DM)No variable met the 0.05 significance level for entry into the model
 NFC (%CHO)No variable met the 0.05 significance level for entry into the model
 NSC (%DM)No variable met the 0.05 significance level for entry into the model
Notes: * RSD, residual standard deviation. ** DM, dry matter; EE, ether extract; FA, fatty acid; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Cell, cellulose; NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. *** Protein structural spectral parameters; Height, Height ratios of amide I and II; Peak area, Amide I and II peak area; AI, Amide I area.
Table 12. Multiple regression analyses to find the important protein structural variables for predicting chemical profiles of canola meal.
Table 12. Multiple regression analyses to find the important protein structural variables for predicting chemical profiles of canola meal.
Predicted Variables (Y)Variable (s) Selection (Variables Left in the Model with p < 0.05)Prediction Equation Test Model: Y = a + b1 × x1 + b2 × x2…R2 Value* RSDp Value
** DM%*** Alpha left in the modelDM% = 92.49 − 11.13 × Alpha0.140.710.039
 Ash (%DM)AIIH and Ratio left in the modelAsh (%DM) = 17.52 − 17.22 × AIIH − 6.89 × Ratio0.540.30<0.001
Protein profile
 CP (%DM)Ratio left in the modelCP (%DM) = 30.41 + 11.49 × Ratio0.320.760.001
 SCP (%DM)Height and Alpha left in the modelSCP (%DM) = −9.46 + 3.87 × Height +31.26 × Alpha0.590.93<0.001
 SCP (%CP)Height and Alpha left in the modelSCP (%CP) = −18.24 + 8.19 × Height + 67.45 × Alpha0.572.07<0.001
 NPN (%DM)AIIH and Height left in the modelNPN (%DM) = −17.41 + 38.07 × AIIH + 8.85 × Height0.550.84<0.001
 NPN (%CP)AIH and Height left in the modelNPN (%CP) = −21.87 + 38.58 × AIH + 12.52 × Height0.531.88<0.001
 NPN (%SCP)Peak area, Height and Alpha left in the modelNPN (%SCP) = 39.64 + 1.59 × Peak area + 31.76 × Height − 331.98 × Alpha0.544.04<0.001
 NDICP (%DM)Alpha left in the modelNDICP (%DM) = 20.99 − 44.95 × Alpha0.471.23<0.001
 NDICP (%CP)Alpha left in the modelNDICP (%CP) = 51.92 − 113.10 × Alpha0.483.05<0.001
 ADICP (%DM)No variable met the 0.05 significance level for entry into the model
 ADICP (%CP)No variable met the 0.05 significance level for entry into the model
CHO profile
 CHO (%DM)Height left in the modelCHO (%DM) = 56.83 − 3.08 × Height0.250.620.005
 Sugar (%DM)AII, AIIH and Alpha left in the modelSugar (%DM) = 13.27 − 3.02 × AII + 64.08 × AIIH + 24.02 × Alpha0.520.71<0.001
 Sugar (%NFC)Ratio left in the modelSugar (%NFC) = − 11.74 + 43.20 × Ratio0.243.480.006
 NDF (%DM)Height and Beta left in the modelNDF (%DM) = 52.87 − 5.79 × Height − 30.05 × Beta0.291.640.010
 ADF (%DM)AIIH left in the modelADF (%DM) = 14.16 + 38.79 × AIIH0.230.860.007
 ADF (%NDF)Beta left in the modelADF (%NDF) = 29.71 + 117.76 × Beta0.452.81<0.001
 ADL (%DM)Height left in the modelADL (%DM) = 16.28 − 3.32 × Height0.190.790.016
 ADL (%NDF)AII left in the modelADL (%NDF) = 16.59 + 1.67 × AII0.142.100.042
 Cell (%DM)Beta left in the modelCell (%DM) = 6.93 + 14.56 × Beta0.310.480.002
 NFC (%DM)AII and Ratio left in the modelNFC (%DM) = 49.56 − 0.85 × AII − 16.84 × Ratio0.470.91<0.001
 NFC (%CHO)AIIH and Ratio left in the modelNFC (%CHO) = 95.38 − 72.97 × AIIH − 31.17 × Ratio0.421.75<0.001
 NSC (%DM)AII, AIIH and Alpha left in the modelNSC (%DM) = 14.27 − 3.02 × AII + 64.08 × AIIH + 24.02 × Alpha0.520.71<0.001
Notes: * RSD, residual standard deviation. ** DM, dry matter; EE, ether extract; FA, fatty acid; CP, crude protein; SCP, soluble crude protein; NPN, non-protein nitrogen; NDICP, neutral detergent-insoluble crude protein; ADICP, acid detergent-insoluble crude protein; CHO, total carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; Cell, cellulose; NFC, non-fiber carbohydrate; NSC, non-structural carbohydrate. *** Protein structural spectral parameters; Height, Height ratios of amide I and II; Peak area, Amide I and II peak area; AII, Amide II area; AIH, Amide I height; AIIH, Amide II height; alpha, α- helix height; beta, β-sheet height; Ratio, Ratio α-helix: β-sheet.
Table 13. Multiple regression analyses to find the important protein structural variables for predicting energy values of canola seeds.
Table 13. Multiple regression analyses to find the important protein structural variables for predicting energy values of canola seeds.
Predicted Variables (Y)Variable (s) Selection (Variables Left in the Model with p < 0.05)Prediction Equation Test Model: Y = a + b1 × x1+ b2 × x2…R2 Value* RSDp Value
Digestible nutrients % of DM
** td NDFNo variable met the 0.05 significance level for entry into the model
td NFCNo variable met the 0.05 significance level for entry into the model
td CPNo variable met the 0.05 significance level for entry into the model
td FANo variable met the 0.05 significance level for entry into the model
TDN 1XNo variable met the 0.05 significance level for entry into the model
TDN p 3XNo variable met the 0.05 significance level for entry into the model
TDN p 4XNo variable met the 0.05 significance level for entry into the model
Energy values (Mcal/kg DM)
DE 1xNo variable met the 0.05 significance level for entry into the model
DE p 3xNo variable met the 0.05 significance level for entry into the model
ME p 3xNo variable met the 0.05 significance level for entry into the model
NEL p 3xNo variable met the 0.05 significance level for entry into the model
ME 3xNo variable met the 0.05 significance level for entry into the model
NE m3xNo variable met the 0.05 significance level for entry into the model
NE g 3xNo variable met the 0.05 significance level for entry into the model
DE p 4xNo variable met the 0.05 significance level for entry into the model
ME p 4xNo variable met the 0.05 significance level for entry into the model
NEL p 4xNo variable met the 0.05 significance level for entry into the model
Notes: * RSD, residual standard deviation. ** td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; td FA, truly digestible fatty acid; TDN 1X, total digestible nutrients at one times maintenance; TDN p 3X, total digestible nutrients at productive level of intake at three times maintenance; TDN p 4X, total digestible nutrients at productive level at four times maintenance; DE 1X, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake (3x maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (3x maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain.
Table 14. Multiple regression analyses to find the important protein structural variables for predicting energy values of canola meal
Table 14. Multiple regression analyses to find the important protein structural variables for predicting energy values of canola meal
Predicted Variables (Y)Variable (s) Selection (Variables Left in the Model with p < 0.05)Prediction Equation Test Model: Y = a + b1 × x1+ b2 × x2…R2 Value* RSDp Value
Digestible nutrients % of DM
** td NDF*** Ratio left in the modeltd NDF = −4.28 + 9.62 × Ratio0.310.650.001
td NFCAII and Ratio left in the modeltd NFC = 48.58 − 0.83 × AII − 16.50 × Ratio0.470.89<0.001
td CPRatio left in the modeltd CP = 29.40 + 11.60 × Ratio0.340.740.001
TDN 1XArea left in the modelTDN 1X = 55.82 + 2.83 × Area0.140.940.040
TDN p 3XArea left in the modelTDN p 3X = 51.27 + 2.60 × Area0.140.870.040
Energy values (Mcal/kg DM)
DE 1xHeight left in the modelDE 1x = 2.90 + 0.19 × Height0.200.050.014
DE p 3xHeight left in the modelDE p 3x = 2.67 + 0.17 × Height0.190.050.016
ME p 3xHeight left in the modelME p 3x = 2.25 + 0.17 × Height0.190.050.016
NEL p 3xHeight left in the modelNEL p 3x = 1.39 + 0.12 × Height0.190.030.017
ME 3xHeight left in the modelME 3x = 2.38 + 0.15 × Height0.190.030.017
NE m3xHeight left in the modelNE m3x = 1.51 + 0.13 × Height0.180.030.018
NE g 3xHeight left in the modelNE g 3x = 0.92 + 0.11 × Height0.190.030.017
DE p 4xHeight left in the modelDE p 4x = 2.55 + 0.16 × Height0.190.050.016
ME p 4xHeight left in the modelME p 4x = 2.12 + 0.17 × Height0.190.050.015
NEL p 4xHeight left in the modelNEL p 4x = 1.31 + 0.11 × Height0.180.030.020
Notes: * RSD, residual standard deviation. ** td NDF, truly digestible neutral detergent fiber; td NFC, truly digestible non-fiber carbohydrate; td CP, truly digestible crude protein; TDN 1x, total digestible nutrients at one times maintenance; TDN p 3x, total digestible nutrients at productive level of intake at three times maintenance; DE 1x, digestible energy at one times maintenance; DE p 3x, digestible energy at a productive level of intake (3x maintenance); ME p 3x, metabolizable energy at production level of intake (3x maintenance); NEL p 3x, net energy for lactation at productive level (3x maintenance); ME 3x, metabolizable energy; NE m 3x, net energy for maintenance; NE g 3x, net energy for gain. *** Protein structural spectral parameters; Height, Height ratios of amide I and II; AII, Amide II area; Ratio, Ratio α-helix: β-sheet; Area, Area ratios of amide I and II.

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