Article Cite This: J. Agric. Food Chem. 2017, 65, 9147-9157
pubs.acs.org/JAFC
Investigating Molecular Structures of Bio-Fuel and Bio-Oil Seeds as Predictors To Estimate Protein Bioavailability for Ruminants by Advanced Nondestructive Vibrational Molecular Spectroscopy Yajing Ban,‡ Luciana L. Prates,‡ and Peiqiang Yu†,‡,* †
College of Life Science and Engineering, Foshan University, ‡Department of Animal and Poultry Science, College of Agricultural and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N5A8, Canada ABSTRACT: This study was conducted to (1) determine protein and carbohydrate molecular structure profiles and (2) quantify the relationship between structural features and protein bioavailability of newly developed carinata and canola seeds for dairy cows by using Fourier transform infrared molecular spectroscopy. Results showed similarity in protein structural makeup within the entire protein structural region between carinata and canola seeds. The highest area ratios related to structural CHO, total CHO, and cellulosic compounds were obtained for carinata seeds. Carinata and canola seeds showed similar carbohydrate and protein molecular structures by multivariate analyses. Carbohydrate molecular structure profiles were highly correlated to protein rumen degradation and intestinal digestion characteristics. In conclusion, the molecular spectroscopy can detect inherent structural characteristics in carinata and canola seeds in which carbohydrate-relative structural features are related to protein metabolism and utilization. Protein and carbohydrate spectral profiles could be used as predictors of rumen protein bioavailability in cows. KEYWORDS: Brassicaceae, feedstock, oilseeds, microspectroscopy, metabolic characteristics
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INTRODUCTION The global demand for renewable sources of fuel such as a vegetable-based oil and for alternative protein products has increased the development and improvement of oilseeds.1 Among the oilseed crops, rapeseed (Brassica napus) places as the third largest oil crop in the world, in which the major part of rapeseed currently cultivated is canola.2 Canola is a variety bred from Brassica rapa and B. napus, and it has been developed to contain double low erucic acid (less than 2% in the oil portion) and low antinutritional compounds such as glucosinolates (less than 30 μmol of glucosinolates/g in the meal portion).2,3 These advantages associated with the production growth have increased the use of canola seed in cow diets as a protein source. However, canola seeds are not well adapted to hot and dry regions, and other oilseed varieties have been developed to grow in these areas.2,4 Brassica carinata (Ethiopian mustard) is a member of Brassicaceae family with high oil content and antinutritional compounds. Primarily, carinata was developed for oil production as biofuel; however, the excellent agronomic traits (high yield in hot, dry, and semiarid climates), associated with a high oil protein content (20−30% of seed weight), has increased the use of this seed as feedstuff.2,5−8 Furthermore, the cultivated area of carinata has been expanded worldwide, and the breeding program has developed lines with low glucosinolate levels, increasing the commercial interest for this oilseed.5−7,9 Currently, the Agriculture and Agri-Food Canada (AAFC) has bred zero erucic acid and low-glucosinates lines, and the Canadian Food Inspection Agency (CFIA) approved the use of carinata meal in beef cattle ration.10 However, published research related to the nutritional and metabolic effects of carinata seeds in dairy cows and the relationships between the inherent molecular structure and nutrient bioavailability is still limited.7,11,12 © 2017 American Chemical Society
The attenuated total reflectance Fourier transform infrared vibrational spectroscopy (ATR-Ft/VMS) is a rapid and noninvasive technique applied to identify molecular constituents from their vibrational spectra in the mid-infrared region.13,14 The mid-infrared spectrum (ca. 4000 to 800 cm−1) is used to identify molecular-level information due to a strong absorbance of many molecules or functional groups observed in this region.11,15 The principle of ATR-Ft/VMS is based on the organic molecules contain specific bonds and functional groups that vibrates independently when submitted to the infrared (IR) light. When the energy or frequency of IR meets any vibrational frequency of molecules in the sample, absorption occurs. Afterward, a detector can record the absorption to determine the chemical functional groups and examine the chemical composition of the complex matrix.16−18 The use of a noninvasive tool to detect the molecular structural in feeds could lead to an understanding of the components that makeup a whole protein. Therefore, this information could be used to improve the utilization of the nutrients in ruminant nutrition. The objectives of this study were to (1) reveal structural features of newly developed carinata and canola seeds by using ATR-Ft/VMS and (2) examine the relationship between molecular structure spectral features and protein bioavailability in dairy cows in terms of protein and carbohydrate molecular structure profiles. Received: Revised: Accepted: Published: 9147
May 12, 2017 September 15, 2017 September 21, 2017 September 21, 2017 DOI: 10.1021/acs.jafc.7b02239 J. Agric. Food Chem. 2017, 65, 9147−9157
Article
Journal of Agricultural and Food Chemistry
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endogenous protein in the small intestine. The OEB was estimated as OEB = N_MCP − E_MCP, where N_MCP is microbial protein synthesized in the rumen based on available nitrogen and E_MCP is the microbial protein synthesized in the rumen based on the available energy. For the molecular analysis, the samples were used to collect the molecular spectral data by using JASCO FT/IR-4200 spectrometer (JASCO Corp., Tokyo, Japan). The JASCO FT/IR-4200 was equipped with a ceramic infrared light source and a deuterated L-alanine doped triglycine sulfate detector consisting of a MIRacle attenuated total reflectance (ATR) accessory module and a zinc selenium (ZnSe) crystal and pressure clamp (Pike Technologies, Madison, WI, USA). The spectra were collected at the mid-infrared region (ca. 4000 to 700 cm−1) with a spectral resolution of 4 cm−1 and 128 coadded scans using JASCO Spectra Manager II Software. In addition, background spectra were corrected with 256 coadded scans in individual samples. Five replicate spectra of each sample were collected and analyzed by OMNIC 7.3 Software (Thermo Electron Corp., Madison, WI, US). The structural spectra information on protein, structural CHO, cellulosic compounds, and total carbohydrate were identified by analyzing absorption peak parameters (baseline, region, peak height, and area) according to Theodoridou and Yu32 and Yu.33 Univariate Spectral Analyses of Protein and Carbohydrate Structure. The univariate spectral analyses of protein-relative functional groups included primary and secondary protein structures.33 The primary protein structure is composed of amide I and amide II. The amide I area is baseline at ca. 1726 to 1579 cm−1 and peak height centered at 1647 cm−1, while the amide II area is baseline at ca. 1579− 1481 cm−1 with a peak height centered at ca. 1537 cm−1. The secondary protein structure includes the α-helix peak height (ca. 1652 cm−1) and βsheet peak height (ca. 1629 cm−1) that were relied on the amide I baseline using either second derivative function or the Fourier selfdeconvolution (FSD) function in OMNIC 7.4 Software.16,32 Afterward, the height and area ratios of amide I to amide II and the height ratio of αhelix to β-sheet were calculated. The carbohydrate molecular structure of carinata and canola seeds is located at the region from 1479 to 881 cm−1 with specific bands that include: (1) structural carbohydrate (STCHO) area and baseline at ca. 1479 to 1182 cm−1 and three major components peaks heights centered at ca. 1415 cm−1, 1373 cm−1, and 1334 cm−1, respectively; (2) cellulosic compounds (CELC) was obtained in baseline at ca. 1307 to 1182 cm−1 and peak centered at 1234 cm−1; (3) total carbohydrates (CHO) were obtained in the region and baseline at ca. 1192 to 881 cm−1 with three major components peaks heights centered at ca. 1154 cm−1, 1105 cm−1, and 1050 cm−1, respectively.34,35 The area ratios of three major CHO were calculated. The area ratios of amide I to amide II and of three major CHO were calculated considering the IR absorbance intensity values of each parameters, in which one characteristic area observed in the spectrum was divided for another. The height ratio of amide I to amide II and height ratio of α-helix to β-sheet were also calculated considering the IR absorbance, in which one characteristic height in the spectrum was divided for another.7,36,37 Multivariate Spectral Analyses. The data of functional groups in the regions related to protein (ca. 1729 to 1479 cm−1), STCHO (ca. 1479 to 1182 cm−1), and total CHO (ca. 1192 to 881 cm−1) were also analyzed by multivariate spectral analyses using Statistica 8.0 Software (StatSoft Inc., Tulsa, OK, USA). The multivariate spectral analyses were performed to obtain the maximum of information from the whole spectra data reducing the number of variables and include agglomerative hierarchical cluster analysis (CLA) and principal component analysis (PCA).18,38 In the CLA, Ward’s algorithm method was used to cluster different infrared spectra based on their similarity, with results displayed as dendrograms.38 In the PCA, all of the original data set can be transformed into a new data set with smaller dimensions composed of uncorrelated variables called principal components (PCs).18 The first principal component (PC1) and second principal component (PC2) were generated in a scatter plot and used to describe all variables. Statistical Analyses. The statistical analyses of protein and carbohydrate structure spectral data were conducted using the
MATERIALS AND METHODS
Sample Preparation and Spectra Collection. The experiment was carried out at the Department of Animal and Poultry Science, University of Saskatchewan (Saskatoon, SK, Canada). The seeds evaluated were the newly developed yellow (AAC A110) and brown (110915EM) carinata seeds and the newly yellow (YN07 C1386) and brown (N07 1374) canola seeds. A commercial brown canola variety was used as reference samples (Table 1). The seeds were ground by
Table 1. Description of Newly Varieties of Carinata and Canola Seeds in Comparison to Commercial Canola Seed: Feed, Line Code, and Seed Coat Color feeda
line code
sample source
seed coat color
new carinata seed new carinata seed new canola seed new canola seed commercial canola seed
AAC-A110 110915EM YN07-C1386 N07-1374 Brassica napus
2012, 2013 2012 (1, 2) 2008, 2011 2010, 2011 2010, 2011
yellow brown yellow brown brown
a
The seed samples were provided by Agriculture and Agri-Food Canada (AAFC), Saskatoon, SK, Canada.
using a coffee grinder (PC770, Loblaws Inc., Toronto, ON) for 20 s for further chemical and molecular analyses and in situ trial. In this study, the chemical profile and energy values analyses,19−21 in situ rumen degradation characteristics,22,23 intestinal digestion characteristics, and predicted truly absorbed protein supply to dairy cattle using the DVE/ OEB system24−26 were performed to evaluate and quantify the correlation between either protein or carbohydrate molecular structures and protein bioavailability of carinata and canola seeds in dairy cows. For chemical profile, dry matter (DM, method 930.15), ash (method 942.05), crude protein (CP, method 984.13), and acid detergent fiber (ADF, method 973.18) were performed according to AOAC procedures.19 The neutral detergent fiber (NDF) with the addition of sodium sulfite and heat stable amylase27 and acid detergent lignin (ADL) were quantified according to Van Soest et al.28 The neutral detergent insoluble crude protein (NDICP) and acid detergent insoluble crude protein (ADICP) were determined according to Licitra et al.29 Soluble crude protein (SCP) was quantified according to Roe et al.30 The total carbohydrate (CHO) was calculated as CHO = 100 − EE − CP − ash. For energy values, the total digestible nutrients (TDN), digestible energy, metabolizable energy, and net energy were estimated considering equations described by NRC.21 Rumen degradation characteristics of CP were determined by in situ method. The results from this procedure were calculated using NLIN procedure of SAS using iterative least-squares regression (Gauss− Newton method) considering the following first-order equation:22 R(t) = U + D exp[−kd(t − T0)], in which R(t) is the residue after t h incubation (%), U is the undegradable fraction (%), D is the degradable fraction (%), Kd is the degradation rate (h−1), and T0 is lag time (h). The rumen undegraded protein (bypass; BCPDVE) was calculated using the following equation: BCPDVE = 1.11 × CP (g/kg DM) × %BCP, where BCP is undegradable rumen crude protein and 1.11 is the regression coefficient between in situ RUP and in vivo RUP.31 The effective degradability of crude protein (EDCP) was calculated as EDCP (g/kg DM) = S + D × Kd/(Kp + Kd), in which S and D fractions and Kd were described above, and Kp is the passage rate (h−1) in which 0.06 h−1 was adopted. The intestinal digested protein (IDP) and total digested protein (TDP) were estimated from the residues after incubation using equations described by Calsamiglia and Stern26 and Nuez-Ortiń and Yu.23 The DVE/OEB system is a model used to predicted protein supply to ruminants, in which DVE refers to truly digested protein in the small intestine and OEB refers to the balance between available N and energy in the rumen.24 The DVE was calculated considering: DVE (g/kg DM) = AMCPDVE + ABCPDVE − ENDP, where AMCPDVE is truly absorbed rumen-synthesized microbial protein in the small intestine, ABCPDVE is a truly absorbed bypass protein in the small intestine, and ENDP is an 9148
DOI: 10.1021/acs.jafc.7b02239 J. Agric. Food Chem. 2017, 65, 9147−9157
Article
Journal of Agricultural and Food Chemistry
Table 2. Protein Structure Spectral Characteristics of New Carinata Seeds (Yellow-AAC A110 vs Brown-110915EM) in Comparison with New Canola Seeds (Yellow-YN07 C1386 vs Brown-N07 1374) and a Commercial Canola Seed (Brown) Using FTIR Vibrational Spectroscopy new carinata seedsa (N_CN)
item amide I peak height amide II peak height amide I:II height ratio amide I area amide II area amide I:II area ratio α-helix peak height β-sheet peak height α-helix: β-sheet height ratio
new canola seedsa (N_CL)
brown (110915 EM)
SEM
∼1651
0.083a
Protein Primary Structure (Unit: Absorbance) 0.078a,b 0.071b 0.070b 0.072a,b
∼1541
0.047a
0.045a,b
0.041b
0.040b
1.76
1.76
1.74
1722−1577 1577−1483
5.73 2.55 2.25a,b
5.55 2.40 2.32a,b
5.09 2.17 2.35a
∼1653
0.082a
0.078a,b
∼1631
0.068
0.063
1.20
a,b
1.27
a
P value
N_CN vs N_CL
N_CN vs COMM
yellow vs brown
0.0028
0.01
0.001
0.02
0.39
0.042b
0.0017
0.03
0.003
0.047
0.52
1.72
1.73
0.013
0.11
0.02
0.04
0.39
4.99 2.25 2.22b
5.12 2.26 2.27a,b
0.216 0.103 0.029
0.08 0.09 0.02
0.01 0.01 0.97
0.06 0.09 0.67
0.51 0.70 0.34
Protein Secondary Structure 0.070a,b 0.066b 0.067b
0.0035
0.01
0.002
0.01
0.26
0.061
0.0030
0.47
0.20
0.61
0.43
0.042
0.004
0.01
0.002
0.85
1.15
a,b
brown (N07 1374)
contrast, P value
yellow (AAC A110)
peak region and center (cm−1)
yellow (YN07 C1386)
commercial canola seeda (COMM)
brown
0.062
0.064
b
b
1.07
1.06
b
a Means with different superscripts in the same row are significantly different according to the Tukey method (P < 0.05). bSEM: standard error of the mean.
Figure 1. Multivariate spectral analyses of new carinata seeds (yellow-AAC A110 and brown-110915EM) in comparison with new canola seeds (yellowYN07 C1386 and brown-N07 1374) and commercial canola seed (brown) using FTIR vibrational spectroscopy at the protein structure region (ca. 1722−1483 cm−1). CLA (cluster analysis): cluster method (Ward’s algorithm) and distance method (Euclidean). PCA (principal component analysis): Scatter plots of the first principal component (PC1) vs the second principal component (PC2). effect of different feedstocks as a fixed effect (different sources were treated as replication), and eij is the random error associated with the observation ij. Contrast statements were used to compare differences
MIXED procedure of SAS 9.4 (SAS Institute, Inc., Cary, NC, US) with the model of Yij = μ + Fi + eij, where Yij is the observation of the dependent variable ij, μ is the population mean of the variable, Fi is the 9149
DOI: 10.1021/acs.jafc.7b02239 J. Agric. Food Chem. 2017, 65, 9147−9157
Article
Journal of Agricultural and Food Chemistry
Table 3. Carbohydrate Structure Spectral Characteristics of New Carinata Seeds (Yellow-AAC A110 vs Brown-110915EM) in Comparison with New Canola Seeds (Yellow-YN07 C1386 vs Brown-N07 1374) and a Commercial Canola Seed (Brown) Using FTIR Vibrational Spectroscopy new carinata seedsb (N_CN)
item
a
peak region and center (cm−1)
yellow (AAC A110)
brown (110915 EM)
new canola seedsb (N_CL) yellow (YN07 C1386)
brown (N07 1374)
commercial canola seedb (COMM)
brown
contrast, P value
SEM
c
P value
N_CN vs N_CL
N_CN vs COMM
yellow vs brown
STCHO peak 1 height STCHO peak 2 height STCHO peak 3 height STCHO area
∼1415
0.019b
0.022a
Structural CHO (STCHO) 0.022a 0.021a,b 0.020a,b
∼1377
0.012c
0.014b
0.018a
0.015b
0.015b
0.0004
