Review pubs.acs.org/JAFC
Interactive Association between Biopolymers and Biofunctions in Carinata Seeds as Energy Feedstock and Their Coproducts (Carinata Meal) from Biofuel and Bio-oil Processing before and after Biodegradation: Current Advanced Molecular Spectroscopic Investigations Peiqiang Yu,*,†,‡ Hangshu Xin,‡ Yajing Ban,‡ and Xuewei Zhang† †
Department of Animal Science, Tianjin Agricultural University, 22 Jinjin Road, Tianjin 300384, China Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan S7N 5A8, Canada
‡
ABSTRACT: Recent advances in biofuel and bio-oil processing technology require huge supplies of energy feedstocks for processing. Very recently, new carinata seeds have been developed as energy feedstocks for biofuel and bio-oil production. The processing results in a large amount of coproducts, which are carinata meal. To date, there is no systematic study on interactive association between biopolymers and biofunctions in carinata seed as energy feedstocks for biofuel and bioethanol processing and their processing coproducts (carinata meal). Molecular spectroscopy with synchrotron and globar sources is a rapid and noninvasive analytical technique and is able to investigate molecular structure conformation in relation to biopolymer functions and bioavailability. However, to date, these techniques are seldom used in biofuel and bioethanol processing in other research laboratories. This paper aims to provide research progress and updates with molecular spectroscopy on the energy feedstock (carinata seed) and coproducts (carinata meal) from biofuel and bioethanol processing and show how to use these molecular techniques to study the interactive association between biopolymers and biofunctions in the energy feedstocks and their coproducts (carinata meal) from biofuel and bio-oil processing before and after biodegradation. KEYWORDS: carinata, molecular structure, biopolymer functions, nutrient profiles, molecular spectroscopy application, nutrient utilization, coproducts, biofuel/bio-oil processing
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INTRODUCTION Carinata Seeds as Energy Feedstocks for Biofuel and Bio-oil Processing. With the development of environmentally friendly biofuel industry and bio-oil industry, vegetable oil is extracted from oilseed crops and widely utilized for biofuel and food oil production, because these oilseeds are renewable, nontoxic, nutritive sources and the biofuel made from them has lower emissions (e.g., particulates, carbon monoxide, hydrocarbons) than the normal fuel from petroleum.1 Brassica carinata (or Ethiopia mustard), which originates in Ethiopia, is an oilseed crop with development potential for the dry western Canadian prairie because of its good tolerance of heat and drought climate, high-salt2 or clay soil, and its more productive character, compared with canola, which prefers to grow in a cooler environment with good moisture.2−4 Recently, Ban and Yu3 summarized growth conditions of carinata in comparison with canola. Carinata seeds have a lower oil content (26−40%) compared with canola Brassica napus, and Brassica carinata has less oleic acid (28%) than B. napus (62%).4−6 In addition, the linoleic and linolenic acid contents of carinata seeds are higher than those of B. napus.4−7 With the development of the high oleic acid and low linolenic acid B. carinata germplasm,8 the oil extracted from those seeds could be utilized for the food-grade oil industry.3 Similar to canola seeds, carinata seed and carinata meal still contain some antinutrients, which may inhibit the bioactivities © 2014 American Chemical Society
of digestive enzymes and so decrease the digestibility and absorption of some important nutrients.5,6,9 These antinutrients include erucic acids, glucosinolates, and condensed tannins. The structures of these antinutrients could be found on the Web3 (http://en.wikipedia.org/wiki). The oil extracted from canola seeds has 95% of the variance, to reduce the amount of linear combinations (PCs) with the same information.37−39 Infrared Molecular Spectroscopy of ATR-FT/IR for Molecular Structure Studies on Biofuel and Bio-oil Coproducts (Carinata Meals). The carbohydrate, protein, and lipid molecular spectra of the carinata meal and canola meal can be studied by infrared molecular spectroscopy of ATR-FT/IR or DRIFT.5,11,40−46 Brief procedure is as follows: Sample spectral data are collected using the FT/IR with ATR (JASCO Corp., Tokyo, Japan). All of the samples are ground through a 0.25 mm screen two times. Then the IR spectra are obtained under the mid-IR region (ca. 4000−800 cm−1) with 64 or 128 co-added scans at a spectral resolution of 4 cm−1. For univariate molecular spectral analysis, the parameters shown on the spectrum can be analyzed for the band intensities, integrated intensities, band frequencies, and band intensity ratios.36 OMNIC 7.3 (Spectra Tech., Madison, WI, USA) is used to analyze the spectral data. Several parameters of carbohydrate and protein functional groups are detected as follows:5,11,41−43 structural carbohydrate peak height and area (SCHO with theoretical baseline of ca. 1487−1190 cm−1); cellulosic compound peak height and area (CELC with theoretical baseline of ca. 1306−1191 cm−1); total carbohydrate peak height and area (CHO with theoretical baseline of ca. 1198−896 cm−1); protein amide I and II height and area (theoretical baseline of ca. 1728− 1478 cm−1, peaks between ca. 1728−1576 and ca. 1576− 1478 cm−1); α-helix and β-sheet peak height and area (peaks within ca. 1662−1650 and ca. 1636−1620 cm−1, theoretically). For multivariate molecular spectral analysis, the multivariate data analysis creates spectral corrections and maps according to all of the spectral information. Statistica 8.0 software (StatSoft Inc.) is used to analyze the differences of carbohydrate-related and protein-related molecular conformation using the multivariate 4041
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(U), and potentially degradable fraction (D) and the degradation rate in % h−1 (Kd) and the lag time (T0) can be calculated on the basis of the first-order kinetic models to fit the fermentation or disappearance curves (goodness of fit) using the nonlinear and logarithmic-linear mathematical models.56,59,60 Gamage61 summarized the potential sources of variation associated with the in situ nylon bag technique as animal, bag, substrate, temporal, procedural aspects and mathematical component, bag pore size, sample to bag ratio, particle size, bag incubation sequence, relative location of nylon bags suspended in the rumen, feeding frequency, diet composition, type of animal used, washing after incubation, and selection of mathematical model. In our preliminary study, we reported detailed kinetics studies in carinata seed and meals and their rumen residues.5,11,41−46 Intestinal Digestion Estimation. Intestinal digestibility of rumen undegraded feed protein (% RUP) is estimated by a three-step in vitro procedure (using in situ 12 or 16 h rumen incubation residue).62 A brief procedure is as follows: (1) If using 16 h rumen incubation, nylon bags need to be filled with feed samples and then incubated in the rumen for 16 h. (2) After 16 h of rumen incubation, the residue is weighed to contain about 15 mg of N and put into a 50 mL centrifugation tube. Then 10 mL of 0.1 N HCl solution containing 1 g/L of pepsin is added into the tube, and the weighed residue is incubated for 1 h at 38 °C. (3) After incubation, the pH is neutralized by adding 0.5 mL of 1 N NaOH and 13.5 mL of pancreatin solution (pH 7.8, 0.5 M KH2PO4 buffer containing 50 ppm of thymol and 3 g/L pancreatin). The tube is vortexed and incubated at 38 °C in a shaker water bath for 24 h. All of the samples should be vortexed every 8 h. (4) Then 3 mL of a 100% (w/v) trichloroacetic acid solution is added to the tube immediately to stop the enzymatic action precipitating undigested protein. The tube is vortexed and kept for 15 min. (5) The samples are centrifuged at 10000g for 15 min and analyzed for soluble N in the supernatant. Pepsin−pancreatin digestion of protein is calculated as trichloroacetic acid-soluble N divided by sample nitrogen content (bag residues).62 This technique has been used to estimated intestinal digestion of protein in energy feedstock (carinata seed) and coproducts (carinata meals).5,11,41−46 Modeling Truly Absorbable Protein Supply to the Small Intestine. To model true protein digested and absorbed in the small intestine, three models are most widely used, TDN-based NRC-2001 model in North America and nonTDN-based model DVE/OEB model57,58,63 and PDI system in Europe. These models have been developed on the basis of the many previously developed nutritional models and incorporate some new approaches.54,64−66 There is an updated version of DVE/OEB protein evaluation system, which is DVE-2010. Based on truly absorbable protein supply or metabolizable protein value, the feed milk vaule (FMV) will be determined.15,49 Detailed comparisons among the three models have been reported.64,66−68 In our recent study,43 we used modeling approaches to determine metabolizable protein supply of carinata meal to dairy cattle in comparison with conventional canola meal and found that “the value of true protein digested in the intestine predicted by the DVE/OEB system was 153 g/kg DM in carinata meal, which was similar to that in canola meal. Carinata meal had a positive degraded protein balance (+248 g/kg DM)”, which has been reported.43
mammalian enzymes. The CHO fraction is partitioned based on CNCPS 6.1 into fraction CA1 (volatile fatty acids, VFA), fraction CA2 (lactic acid), fraction CA3 (other organic acids), fraction CA4 (sugars), fraction CB1 (starch), fraction CB2 (soluble fiber), fraction CB3 (available neutral detergent fiber, NDF), and fraction CC (unavailable NDF). In the CNCPS 6.1 model, rumen degraded and bypassed protein as well as bypassed CHO will be estimated on the basis of the contribution from each fraction. The following parameters will be determined: RDPA, RDPB1, RDPB2, RDPB3, total RDP = RDPB1 + RDPB2 + RDPB3, where RDPA is ruminally degraded protien A fraction, RDPB1 is ruminally degraded PB1, RDPB2 (g/day) is ruminally degraded PB2, RDPB3 is ruminally degraded PB3, and total RDP is ruminally degraded peptides/protein REPB1, REPB2, REPB3, and REPC, where REPB1 is ruminally escaped protein B1, REPB2 is ruminally escaped protein B2, REPB3 is ruminally escaped protein B3, and REPC is ruminally escaped protein C. RDCA is ruminally degraded CA, RDCB1 is ruminally degraded CB1, and RDCB2 is ruminally degraded CB2. RECA is ruminally escaped carbohydrate A, RECB1 is ruminally escaped carbohydrate B1, RECB2 is ruminally escaped carbohydrate B2, and RECC is ruminally escaped carbohydrate C. The fraction studies in carinata seed and carinata meals by CNCPS system have been reported recently from our laboratories.11,41 Energy Evaluation. In the NRC-2001 model, energy requirements for maintenance and milk production are described on the premise of metabolic body size (NEm), tissue (NEg), and milk (NEL) composition. The feed energy values are also expressed on the basis of feed NEm, NEg, and NEL values. In feeds, the total digestible nutrient (TDN) and digestible energy (DE), metabolizable energy (ME), and net energy (NE) are used to estimate available energy according to the NRC dairy 2001. Gross energy is measured using a Parr adiabatic bomb calorimeter (model 1200, Parr Instrument Co., Moline, IL, USA). Using the NRC 2001 system, tdNDF, tdNFC, tdCP, tdFA (% DM), TDN1×, ME3×, NEm, NEg, and NELp can be determined. Detailed energy studies in energy feedstock (carinata seeds) and coproducts (carinata meals) have been reported recently from our laboratories.5,11,41−43 In Situ Technique for Degradation Kinetic Study. In situ incubation is a widely used method of evaluating ruminant feed according to the rate and extent of degradation. This involves suspension of tested feed material in the rumen, allowing for contact between the tested feed and actual rumen environment.53 The rate and extent of rumen degradation of particular test feed are evaluated by the analysis of in situ residue samples after incubation. This fractionates nutrients into three fractions depending on their rumen availability. These fractions are soluble, potentially degradable, and undegradable fractions, named A, B, and C or S, D, and U, respectively.54,55 Brief Procedure. The samples are ground through 3 mm screens or using a roller (coarsely ground); then ca. 7 g of DM is placed into each nylon bag with the pore size of approximately 40 μm and subsequently put into the rumen. The rumen incubation is performed according to the schedule of “gradual addition − all out” for 48, 24, 12, 8, 4, 2, and 0 h. After that, all of the bags should be pulled out and washed in cool water without detergent and then dried at 55 °C for 48 h (including the 0 h bags). Later, the dried samples will be pooled and stored at 4 °C.54 The rumen degradation parameters can be estimated according to the modified first-order kinetics model56−58 and NRC model.49 The soluble fraction (S), undegradable fraction 4042
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CURRENT MOLECULAR STRUCTURE STUDIES ON CARINATA AS ENERGY FEEDSTOCKS AND THEIR COPRODUCTS FROM BIOFUEL AND BIO-OIL PROCESSING Study Interactive Association between Biopolymers and Biofunctions in Carinata Meal -Coproducts from Biofuel and Bio-oil Processing before and after Rumen Biodegradation. Application 1 of Molecular Spectroscopy To Study the Relationship between CHO Structure and CHO Availability in Carinata Meal (Coproducts). Molecular analyses with FTIR technique with attenuated total reflectance (ATR) and chemometrics may enable detection of structural features on a molecular basis. In this study,11 we used FTIRATR spectroscopy in our laboratory to “investigate spectral features of carbohydrate conformation in carinata meal and investigate differences in carbohydrate molecular functional group spectral intensities after in situ ruminal fermentation at 0, 12, 24, and 48 h compared to conventional canola meal as a reference”. Our measured parameters included11 SCHO (mainly associated with hemicellulosic and cellulosic compounds; region and baseline ca. 1483−1184 cm−1), cellulosic compounds (CELC, region and baseline ca. 1304−1184 cm−1), total carbohydrates (CHO, region and baseline ca. 1193− 889 cm−1) as well as the spectral ratios calculated on the basis of respective spectral intensity data of carbohydrates. In this study we also published a typical ATR-FTIR molecular spectrum of carinata meal in the mid-IR region ca. 4000−800 cm−1; please check our previous paper for the spectral graph.11 In this study, we reported that “the spectral profiles of carinata meal were different from that of canola meal in CHO 2nd peak area (center at ca. 1091 cm−1, region: 1102−1083 cm−1) and functional group peak intensity ratios such as SCHO 1st peak (ca. 1415 cm−1) to 2nd peak (ca. 1374 cm −1) height ratio, CHO 1st peak (ca. 1149 cm−1) to 3rd peak (ca. 1032 cm−1) height ratio, CELC to total CHO area ratio and STCHO to CELC area ratio. The results indicated that carinata meal may not in full accord with canola meal in carbohydrate utilization and availability in ruminants. Almost all the spectral parameters were decreased during 48 h ruminal degradation in both carinata meal and canola meal.”11 Application 2 of Molecular Spectroscopy To Study the Relationship between Protein Structure and Protein Availability in Carinata Meal (Coproducts). To date, no study in other laboratories was found on nutritive values and molecular structural characteristics associated with protein biopolymers of carinata meal from biofuel and bio-oil processing.41 In this project,41 we investigated the possible relationship between protein intrinsic structural features and nutrient profiles of carinata meal in comparison with conventional canola meal. We found that “carinata meal had 20−31% greater IR absorbance in protein amide I height and area as well as α-helix and β-sheet heights than canola meal. But agglomerative hierarchical cluster analysis and principal component analysis indicated these two types of the meals could not be distinguished completely within protein spectrum region (ca. 1728−1478 cm−1).41 We also observed some close correlations between protein structural parameters and protein nutrient profiles and subfractions” as reported in our individual project publication.41 Application 3 of Molecular Spectroscopy To Study Rumen Residue of Canola Meal (Coproducts). No study was found on whether protein structure changes during rumen fermentation from other research teams. In these studies,41,42 we
characterized protein structure spectral changes in carinata meal during ruminal fermentation using the FTIR technique. We wanted to find out “1) whether protein amide profile and protein 2nd structure profile changed after ruminal fermentation at 0, 12, 24, and 48 h in carinata meal and canola meal; 2) whether there were some correlation between protein spectral parameters and chemical profile in in situ rumen residue samples”.41,42 In the publications, we reported that “Protein structure spectral features in both carinata meal and canola meal were altered as incubation time increased and linear and curvilinear relationships on amide II height and area, height and area ratio of amide I and II as well as height ratio of α-helix and β-sheet were observed within 48 h ruminal fermentation. The amide I height and area as well as α-helix height and β-sheet height were in the highest level of IR absorbance at 0 h and then gradually declined linearly by 30−38% after 48 h incubation. We found that not only quantities decreased but also inherent structure changed in protein chemical make-up during ruminal fermentation. Strong correlations were found between protein spectral parameters and some basic nutrients profile such as CP (positively) and NDF (negatively). And multivariate spectral analysis showed that rumen residues from carinata meal (were) not distinguished from those from canola meal, suggesting some relationship in structural make-up exhibited between them within protein region during 48 h rumen fermentation”.41,42 Study Interactive Association between Biopolymers and Biofunctions in Carinata Seeds as Feedstock for Biofuel and Bio-oil Processing. Application 4 of Molecular Spectroscopy To Study the Relationship between CHO Structure and CHO Availability in Energy Feedstock (Carinata Seeds). In this study,41 we investigated the correlations between carbohydrate structural features and nutritional profiles in yellow and brown types of carinata seeds, with comparison to common canola seed as a reference. The key findings in this study were reported as follows: “carinata lines showed significantly different IR intensities in structural carbohydrate (SCHO), cellulosic compounds (CELC) and total CHO profiles from Canola seeds. The changes of CELC and CHO peak intensities were highly related with some changes in CHO chemical profile, energy values and NDF degradation kinetics in carinata and canola seeds.”41 Application 5 of Molecular Spectroscopy To Study the Relationship between Protein Structure and Protein Availability in Carinata Seeds (as Energy Feedstock). In this study,44 we detected “the correlations between protein intrinsic structural features and most important nutritional profiles of DVE, OEB and FMV values in three lines of carinata in yellow and brown seed coats, with comparison to canola seed as a control reference”.44 We found “significant differences in protein amide II peak height, amide I peak area and β-sheet height among the different carinata lines. However, multivariate spectral analyses indicated a similarity in protein structural make-up in these four kinds of oilseed. Not very strong correlations showed in our study implied that the limited sample size and narrow range in biological and spectral variation might be (a) response (to) the weak relationships between chemical profile and mid-IR spectral data.” Nutritive values of DVE, OEB, and FMV from carinata seed and canola seed and multivariates molecular spectral analysis among the carinata lines were graphically presented in this publication.44 Application 6 of Molecular Spectroscopy To Study the Lipid-Related Chemical Functional Spectral Profile in Carinata Seeds (as Energy Feedstock). To date, information 4043
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carbonyl region (ca. 1787−1706 cm−1). However, the oilseeds heated for 30, 60, and 90 min were not grouped into separate classes or ellipses in all the lipid-related regions, indicating that there still exhibited similarities in lipid biopolymer conformations among autoclaved carinata seeds. Moreover, strong relationships observed in our study implied that lipid-related spectral parameters might have a potential to predict some fatty acids content in oilseed samples like B. carinata. However, more data from (a) large sample size and diverse range would be necessary and helpful to draw up a final conclusion.” All of the above results are based on limited samples in our laboratory, an experiment with a large sample size with detailed and systematical studies is on the way to confirming our findings in our preliminary study and exploring new findings in our large-scale study. For example, carinata meals with a higher crude protein content but contained less metabolizable protein supply for dairy cattle and had lower feed milk values when compared with conventional canola meals. These results should be checked and confirmed again. The correlation between inherent structures and nutrient biofunctions and bioavailability are inconclusive and should be studied with a large range of sample sizes. To improve nutrient availability predictions in energy feedstock and coproducts, the new concept of digestion in various functional groups could be tested in the new studies. In summary, this paper reviewed (1) the carinata seeds as energy feedstocks, biofuel and bio-oil processing procedures, and their processing coproducts; (2) potential synchrotronbased, globar-based molecular sepctroscopy and conventional evaluation methods on energy feestock (new carinata seeds) and coproducts (carinata meal) from biofuel and bio-oil processing; and (3) interactive association between biopolymers and biofunctions in carinata seeds and carinata meal, coproducts from biofuel and bio-oil processing before and after rumen biodegradation, and how molecular structural changes affect nutrient bioavailability and biofunctions.
is lacking on the lipid molecular structural characteristics in relation to contents of oil, fatty acids, and antinutritional compounds in B. carinata.5 In this study,5 we investigated (1) oil content and fatty acid profile; glucosinolate profile, total polyphenols, and condensed tannins; and lipid-related inherent molecular structures in terms of CH stretching bands, unsaturated lipid bands (ULB) and lipid ester CO carbonyl (LECC) bands in seeds from yellow-seeded and brown-seeded carinata lines [for typical ATR-FTIR molecular spectrum of carinata seeds and canola seed as a reference control in the mid-IR region ca. 4000−800 cm−1, please see our publication5]; and (2) the relationship between the molecular spectral data and the contents of oil, fatty acids, and antinutritional compounds in the oilseeds.69−71 In this study, we reported that “brown-seeded carinata had lower contents of oil, C17:0, C18:0, C20:1, C20:2n-6, C24:1n9 and total saturated fatty acids, and higher contents of C22:0, C22:1n-9 and C24:0 than yellow-seeded carinata. However, the contents of glucosinolates, polyphenols and condensed tannins were not different between the yellow and brown seeds. There were marked differences between carinata and canola seeds in the contents of oil, fatty acids profile, glucosinolates profile and polyphenols. The yellow seeds had lower peak heights of asymmetric CH2 and symmetric CH2, however, no changes were found in other spectral parameters. The absorbed peak intensities of CH stretchings, ULB and LECC of both types of carinata seeds were markedly stronger than those of canola seeds. The multivariate, cluster and principal component analyses showed no significant differences in the lipids molecular structures between the yellow-seeded and brown-seed carinata seed; whereas, the molecular structures of canola seeds were fully distinguished from both types of carinata seeds in the regions of CH stretchings and ULB. The lipid-related spectral bands intensities were strongly correlated to oil content, fatty acids, glucosinolates and polyphenols. The regression equations gave relatively high predictive power for the estimation of oil (R2 = 0.99); all measured fatty acids (R2 > 0.80), except C14:0, C20:3n-3, C22:2n-9 and C22:2n-6; 3-butenyl, 2-OH-3-butenyl, 4-OH-3-CH3-indolyl and total glucosinolates (R2 > 0.686) and total polyphenols (R2 = 0.935).”5 (For a detailed typical ATRFTIR lipid molecular spectrum of carinata seeds and canola seed, please check our publication.)5 Application 7 of Molecular Spectroscopy To Study HeatInduced Molecular Structure Change in Lipid-Related Chemical Functional Spectral Profile in Carinata Seeds (as Energy Feedstock). In this study,46 we explored the effect of different autoclave heating times (30, 60, and 90 min) on fatty acid supply and molecular stability in carinata seed. In this work,42 heat-induced molecular structure changes in lipid-related chemical functional spectral profile in carinata seeds detected by FTIR-ATR were presented graphically.42 We reported that “autoclaving treatments decreased total fatty acids content in a linear fashion in carinata seed as heating time increased; and reduced concentrations were observed in C18:3n3, C20:1, C22:1n9, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), omega 3 (ω-3) and 9 (ω-9) fatty acids. Correspondingly, the heated seeds showed dramatic reductions in all the peak intensities within lipid-related spectral regions. Results from agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) indicated that the raw oilseed had different structural make-up from the autoclaved seeds in both CH3 and CH2 asymmetric and symmetric stretching region (ca. 2999−2800 cm−1) and lipid ester CO
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AUTHOR INFORMATION
Corresponding Author
*(P.Y.) Mail: Professor and Ministry of Agriculture Strategic Research Chair, College of Agriculture and Bioresources, University of Saskatchewan, 6D10 Agriculture Building, 51 Campus Drive, Saskatoon, SK, Canada S7N 5A8. Phone: (306) 966-4132. E-mail:
[email protected]. Funding
We acknowledge financial support from the Saskatchewan Ministry of Agriculture Strategic Feed Research Chair (P.Y.) Program, the Natural Sciences and Engineering Research Council of Canada (NSERC, both CRD and ID grants), SaskCanola (Saskatchewan Canola Development Commission), the Saskatchewan-ADF fund, and the Federal and Provincial Growing Forward 2 Program as well as the Thousand-TalentPeople Award Program in Tianjin. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank Agrisoma, Dr. Kevin Falk (AAFC, Saskatoon), and Colleen Christensen (University of Saskatchewan) for providing study samples. 4044
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ABBREVIATIONS USED
amide I intensity under amide I band (ca. 1718−1579 cm−1) in this study amide II intensity under amide II band (ca.1579−1488 cm−1) in this study ADF acid detergent fiber ADICP acid detergent insoluble crude protein ADIN acid detergent insoluble nitrogen ADL acid detergent lignin AHCA agglomerative hierarchical cluster analysis ATR-FT/IR attenuated total reflectance Fourier transform infrared spectroscopy CA1 volatile fatty acids CA2 lactic acid CA3 other organic acids CA4 sugars CA rapidly degradable soluble sugar fraction (Kd = 200− 350% per h) defined by CNCPS CB1 intermediately degradable carbohydrate subfraction (Kd = 20−50% per h) defined by CNCPS CB2 slowly degradable carbohydrate subfraction (Kd = 2−10% per h) defined by CNCPS CC unfermentable carbohydrate subfraction defined by CNCPS CELC cellulosic compounds CHO total carbohydrate CNCPS Cornell Net Carbohydrate and Protein System CP crude protein D potential degradable fraction in the in situ ruminal incubation DE digestible energy DE1× digestible energy at maintenance DE3× (DEp) digestible energy at three times maintenance (i.e., production level) DM dry matter DRIFT diffuse reflectance infrared Fourier transform spectroscopy dRUP estimated intestinal digestibility of RUP DVE truly absorbed protein in the small intestine defined by DVE/OEB system EE ether extract FA fatty acid FMV feed milk vaule FTIR Fourier transform infrared spectroscopy H_1630 β-sheet peak height (ca. 1630 cm−1) H_1655 α-helix peak height (ca. 1655 cm−1) IDP estimated intestinal digestibility of RUP IR infrared Kd degradation rate Kp passage rate LECC lipid ester CO carbonyl ME metabolizable energy ME3× (MEp) metabolizable energy at 3 times maintenance (i.e., production level) MP metabolizable protein MUFA monounsaturated fatty acids NDF neutral detergent fiber NDFn nitrogen-free neutral detergent fiber (NDFn = NDF − NDICP) NDICP neutral detergent insoluble crude protein NEg net energy for growth NEL3× (NELp) net energy for lactation at 3 times maintenance (i.e., production level)
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NEm net energy for maintenance in growing animals NFC nonfiber carbohydrate NPN nonprotein nitrogen NSC nonstructural carbohydrate OEB degraded protein balance OM organic matter PA nonprotein nitrogen defined by CNCPS (Kd is assumed to be infinity) PB1 rapidly degradable protein subfraction defined by CNCPS (Kd = 120−400% per h) PB2 intermediately degradable protein subfraction defined by CNCPS (Kd = 3−16% per h) PB3 slowly degradable protein subfraction defined by CNCPS (Kd = 0.06−0.55% per h PC undegradable protein subfraction defined by CNCPS PCA principal component analysis PUFA polyunsaturated fatty acids RDCA ruminally degraded carbohydrate A RDCB1 ruminally degraded carbohydrate B1 RDCB2 ruminally degraded carbohydrate B2 RDPA ruminally degraded protein A RDPB1 ruminally degraded protein/peptide B1 RDPB2 ruminally degraded protein/peptide B2 RDPB3 ruminally degraded protein/peptide B3 RDP ruminally degraded peptides RECA ruminally escaped carbohydrate A RECB1 ruminally escaped carbohydrate B1 RECB2 ruminally escaped carbohydrate B2 RECC ruminally escaped carbohydrate CC REPB1 ruminally escaped protein B1 REPB2 ruminally escaped protein B2 REPB3 ruminally escaped protein B3 S potential soluble fraction in the in situ ruminal incubation SCHO structural carbohydrates SCP soluble crude protein SR-IMS synchrotron-based Fourier transform infrared microspectroscopy T0 lag time TCA trichloroacetic acid tdCP truly digestible crude protein tdFA truly digestible fatty acid TDN total digestible nutrients TDN1× total digestible nutrients at maintenance TDN3× total digestible nutrients at 3 times maintenance (i.e., production level) tdNDF truly digestible neutral detergent fiber tdNFC truly digestible nonfiber carbohydrate U potential undegradable fraction in the in situ ruminal incubation ULB unsaturated lipid bands
REFERENCES
(1) Bouaid, A.; Martinez, M.; Aracil, J. Production of biodiesel from bioethanol and Brassica carinata oil: oxidation stability study. Bioresour. Technol. 2009, 100, 2234−2239. (2) Canam, T.; Li, X.; Holowachuk, J.; Yu, M.; Xia, J.; Mandal, R.; Krishnamurthy, R.; Bouatra, S.; Sinelnikov, I.; Yu, B.; Grenkow, L.; Wishart, D. S.; Steppuhn, H.; Falk, K. C.; Dumonceaux, T. J.; Gruber, M. Y. Differential metabolite profiles and salinity tolerance between two genetically related brown-seeded and yellow-seeded Brassica carinata lines. Plant Sci. 2013, 198, 17−26. (3) Ban, Y.; Yu, P. Structure, Physicochemical, Nutrition Characterization of Newly Developed Yellow- or Brown-Types of AAFC Carinata Lines/ Germplasms for Bio-Fuel/ Bio-Oil Production in Comparison with
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