Elucidating The Multifunctional Role of The Cell Wall Components in The Maize Exploitation

doi:10.21203/rs.3.rs-50191/v1

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Elucidating The Multifunctional Role of The Cell Wall Components in The Maize Exploitation

https://doi.org/10.21203/rs.3.rs-50191/v1

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published 02 Jun, 2021

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Background: Besides the use of maize grain as food and feed, maize stover can be a profitable by-product for cellulosic ethanol production, whereas the whole plant can be used in silage production. However, yield is reduced by pest damages, where stem corn borers are one of the most important factors limiting yield. Overall, cell wall composition is key in determining the quality of maize biomass, as well as pest resistance. This study aims to address the interrelations between cell wall components in diverse maize genotypes, and pest resistance, ethanolic production and forage digestibility.

Results: We can highlight the following results: (i) pests resistant inbred lines may show cell walls with low p-coumaric acid and hemicellulose content; (ii) inbred lines showing cell walls with high cellulose content and diferulate cross-linking may present higher performance in ethanol production; (iii) and inbred lines with enhanced digestibility may have cell walls poor in neutral detergent fibre and diferulates, combined with a lignin polymer composition richer in G subunits.

Conclusions: Our results evidence that there is no maize cell wall ideotype among the tested for optimal performance in the three areas evaluated, and maize plants should be specifically bred for each particular application.

Plant Physiology and Morphology

maize

saccharification

digestibility

pest resistance

cell wall

Accessibility, extensibility, and digestibility of tissues would determine important characteristics of maize, such as resistance to stem borers, stem diseases, feedstuff quality and saccharification for ethanol production. These characteristics depend on the cell wall composition and structure (1). Genetic variation for resistance to corn borers (2), for cell wall composition and degradability (3), and for ethanol production (4) has been identified in maize.

Maize inbred lines have different mechanisms of defence that determine the level of corn borer resistance in a particular inbred line (5). Similarly, saccharification yields or cell wall degradability depend on the cell wall composition and properties of the inbred line, and their response to pre-treatment and hydrolysis (6). Therefore, it seems that different genotypes may have different defence mechanisms, react differently to pre-treatment, and have different cell wall properties that facilitate saccharification or digestibility.

Maize breeding strategies are normally focused on a particular trait (pest resistance, digestibility or ethanol production) that produce indirect effects on cell wall components. For example, recurrent selection to improve resistance to corn borer attack increases cell wall bound hydroxycinnamates concentration in the pith tissues of the improved maize cycles (7). Buendgen et al. (8) recorded increases in neutral and acid detergent fibres values (NDF, ADF) and lignin content in the leaf sheath and stalks of maize after five cycles of selection for first and second generation European Corn Borer resistance. Similarly, Bergvinson et al. (9) found increases in diferulic acid concentration over diverse cycles of selection to increase corn borer resistance.

In switchgrass, Sarath et al. (10) studied divergent breeding generations for high or low in vitro dry matter digestibility (IVDMD). This selection resulted in populations differing in lignin concentration and acid detergent fibre. Plants from these two populations also displayed different cell wall composition and accessibility to hydrolytic enzymes (11), which led to an increase in the net mean ethanol yields in plants selected for increased IVDMD. Also, selection for improved saccharification efficiency in alfalfa stems produced increases in glucose release and a reduced lignin content in the lines selected (12). Similarly, after six generations of divergent breeding for forage IVDMD on switchgrass, Vogel et al. (13) observed differences between populations cell wall fibres, lignin content matrix polysaccharides and esterified ferulates.

On the other hand, direct changes towards cell wall structure can also influence the final uses of maize. Successful divergent selection for diferulate ester content in the maize pith resulted in changes in cell wall composition, such as decreases in glucose concentration, lower total cell walls contents and thereby thinner cell walls (14). These changes led to cell wall stiffening, which is the main deterrent of corn borer attack and development (15). Furthermore, the increase in diferulate content impact negatively in cell wall degradability properties. Jung et al. (16) studied the effect of ferulate crosslinking on dry matter intake, milk production potential and in vivo digestibility for silage maize using the low ferulate sfe mutant. Lines presenting the mutation showed reduced ether ferulate crosslinking of lignin to arabinoxylans. Cattle fed with this mutant showed greater dry matter intake and milk production.

Brown midrib mutants (bmr 1–4) have been an excellent material to study digestibility and lignification (17). These mutants have favourable phenotypic traits such as decreased lignin concentration, shift in lignin composition and modified ratio of esterified phenolics. This change in cell wall composition produces higher digestibility and a higher rate of ingestion when fed to cattle (18). In the same way, modifications of the phenylpropanoid pathway, through up and downregulation of enzymes directly influencing lignin content and monolignol composition, have been associated with increases in saccharification efficiency in several crops. For example, transgenic switchgrass lines with reduced Cinnamyl Alcohol Dehydrogenase (CAD) levels and consequently reduced lignin content and altered lignin composition, showed improved sugar release and forage digestibility (19).

Considering that usually different cell wall components affect economically important traits and have been tested in diverse studies, the aim of the current study is to extensively characterize the relationship between cell wall composition and the performance for different applications of maize genotypes using the same experimental trials for the whole research. The present work has the advantage of including an extensive and representative selection of 20 inbred lines characterized in depth. The composition of the cell wall (cellulose, hemicellulose, lignin and hydroxycinnamates) was determined in all inbred lines, and different uses (forage digestibility, ethanol production, digestibility and saccharification) were evaluated not only in internodes, but also in whole plant, in order to investigate correlations between them.

Thereby, the specific objectives of this research were: (i) to study the relationships between different cell wall components in diverse maize genotypes, and (ii) to determine the degree to which each component have a role in pest resistance (R), ethanolic production (E) and forage digestibility (D). Those last three aspects will be further on denoted as R.E.D.

Plant Material

In order to study the correlation between cell wall components and its influence in the final use of the maize plant or stover, a set of 20 inbred lines was evaluated (Table 1). These inbreds were divided into groups according to the reason they were included in the panel set:

The first subset of inbred lines includes maize inbreed lines that have been characterised in relation to resistance to corn borer attack. (2) Among these inbred lines there are susceptible (EP42, EP47) and resistant (EP17, EP53, EP105, EP125, EP86, F473, PB130, A509) lines. The resistant group (with the exception of EP105) was composed by seven of the eight founders of a Multi-Parent Advanced Generation Inter-Cross (MAGIC) population (20–22). EP105 derived from the cross A671 x A295 to obtain reduced tunnel length (23). All are resistant to corn borer attack, but show particular defence mechanisms (24). This subset of inbred lines was obtained and ceded by Mision Biologica de Galicia’s germplasm bank.
The second subset includes five inbred lines from the Agriculture and Agri-Food Canada (AAFC): C103, CO384, CO348, CO442 and CO444. Inbred C103 is well known by presenting a high concentration of sucrose in the stalk. Reid et al. (25) developed hybrids combinations using C103 as male with CO348, CO384, CO442 and CO444. Authors proposed the usage of these hybrids for ethanol production and biomass for silage, and they are known as “Sugarcorn Hybrids”. This subset of inbred lines was obtained and ceded by Dr. Lana Reid from the Eastern Cereal and Oilseed Research Centre in Canada.
The last group was formed by inbred lines with good performance in hybrid combination. Inbred EC212 has very good general and specific combinatorial aptitude for high animal digestibility (26). This group was completed with inbreds A654 and W182B, both belonging to the Reid germplasm group. The hybrid combination attending to heterotic patterns is well stablished in maize; in this case, we would expect good hybrid combinations with the MAGIC inbred parents, these not belonging to Reid germplasm. The inbred EC212 was ceded by CIAM’s germplasm bank in Mabegondo and A654 and W182 by Mision Biologica de Galicia’s germplasm bank.

Field Experimental Design

The inbred panel was evaluated in 2016 and 2017 in Pontevedra, in North Western Spain (42°25′ N, 8°38′ W and 20 m above sea level). A random block design with three repetitions was used in the two trials. The second year, the subset of inbred lines was reduced to nineteen due to the lack of seed for the inbred PB130. Each experimental plot consisted of three rows, each row with 15 double-kernel hills planted manually, spacing between consecutive hills in a row being 0.18 m and 0.8 m between rows, obtaining a final density of ~ 70,000 plants ha^-1 after thinning. Local agronomical practices were fulfilled.

Agronomic Traits

Agronomic traits were recorded at the time of harvest (approx. 70 days after silking) except for diameter, rind puncture resistance, number of internodes and forage yield that were recorded 55 days after silking. Days to silking/anthesis were recorded periodically by the time each plot started to show pollen and silks.

Days to silking/anthesis. Considered as the time passed from the day of sowing until approximately 50% of the plants showed either pollen (male anthesis) or silks (female silking).

Stem descriptions traits. Plant and ear height: mean of plant height or ear height (in cm) of five plants per plot. Plant height was measured from the base of the plant until the flag leaf, while ear height was taken from the base of the plant until the insertion point of the main ear; Total number of internodes in the plant and below the ear: the total number of visible internodes in the plant and below the main ear was taken from five plants of each plot 55 days after silking; Lodging: lodging was calculated as the sum of broken and leaning plants divided by the total number of plants in the plot, expressed in percentage. A plant was considered broken when it was split underneath the main ear, and leaned when the stem formed an angle with the ground at less than 45°; Diameter and rind puncture resistance: rind puncture was the measured of the maximum force required to puncture the rind (in kg/section) on one side of the stalk. The second internode under the main ear was punctured at 55 days after silking using an Accuforce Cadet Force Gauge (Ametek, Mansﬁeld and Green Division, Largo, FL). The needle was inserted perpendicular to the internode in five plants. At the same time, the diameter of the same five internodes was recorded, in millimetres, using an electronic calliper.

Grain yield. Grain yield was calculated as the weight of grain in megagrams ha^-1 at 14% humidity. It was determined by the following equation:

Where humidity, expressed as a percentage, was recorded using a moisture meter Kett (model PM-400) in a sample of 240 cm³. Surface was calculated as the number of plants per plot multiplied by the space between rows (0.80 m) and the space between plants (0.18 m). The value 86 on the equation corresponds to a constant to adjust the yield at 14% humidity. Yields were calculated per plant and then transformed to Mg ha^-1; thus, it refers to a maximum yield and not to the yield in a plot.

Stover and forage yield. Plots were harvested approximately 70 days after silking (days from planting until half of the plants in the plot showed visible silks). In each plot, the weight of 2-10 plants without ears (weight of fresh stover) was recorded, and a stover sample was collected for estimating the percentage of stover dry matter and saccharification efficiency analyses. The stover sample was composed of tissue from 2-10 plants, the fresh stover was weighed (sample fresh weight), chopped, pre-dried at 35 °C in a forced air camera, dried at 60 °C in a stove and again weighed after seven days (sample dry weight). Dry stove samples from each plot were grounded in a Wiley mill with a 0.75 mm screen for saccharification assays.

Forage yield was calculated as stover yield with the difference that plant samples included the ear and were collected 55 days after silking.

Stover yield and forage in Mg ha^-1 was determined by the following equation:

Surface was calculated as the number of plants per plot multiplied by the space between rows (0.80 m) and the space between plants (0.18 m). As above, yields were calculated per plant and then transformed to Mg / ha; thus, it refers to a maximum yield and not to the yield in a plot.

Biochemical Analysis

The second internode below the main ear were collected from five plants in each plot. Samples were collected 55 days after silking. Each harvested internode was frozen at −20 °C until analytical determinations. Then, samples were dried at 60 °Cnd ground in a Wiley (Arthur H. Thomas, Philadelphia, PA) mill with a 0.75 mm screen before being analysed.

Determinations were based in whole dry tissues unless mentioned otherwise. Some other biochemical traits (cellulose, total and neutral sugars, uronic acids, and lignin monomeric composition) were determined in isolated cell walls from those internodes following the cell wall isolation protocol modified by Melida et al. (27).

Cellulose quantification. Cellulose was quantified by the Updegraff method (28). The concentration of cellulosic sugars was assessed by the method of the anthrone (29) using glucose as standard.

Hemicellulose. For total, and neutral sugars and uronic acids, 5 mg of tissue were weighed and hydrolysed at 212 °C by adding 2 ml of 2M trifluoroacetic acid (TFA) for 1 hour. Total sugar content was determined by the phenol-sulphuric method using glucose as standard (30). Uronic acid contents were determined by the m-hydroxybiphenyl method (31), with glucuronic acid as a standard. Monosaccharide composition of the matrix polysaccharides was performed in whole dry tissues samples using high performance anion exchange chromatography (HPAEC) (Carbopac PA-10; Dionex, Camberley, Surrey, UK) as described previously by Jones et al. (32).

Lignin content and lignin monomeric composition. Total lignin content was determined by Klason Lignin protocol (33). Monomer composition was determined by thioacidolysis followed by Gas chromatography–mass spectrometry (GC–MS)(34). The thioacidolysis procedure estimates the proportion of lignin subunits linked by the major β-O-4 linkages.

Cell wall bound hydroxycinnamates. A recently optimized protocol by Santiago and col. (35)was used for cell wall bound hydroxycinnamates quantification (35). Phenolic standards ferulic acid (FA) and p-coumaric acid (PCA) were purchased from Sigma-Aldrich Quimica SL, Madrid, Spain Sigma. The identities of FA dimers were confirmed by a comparison with 5−5 standard or published retention times and UV spectra (36). The total diferulate content (DFAT) was calculated as the sum of the following three identified and quantified DFA isomers: DFA 8–O–4, DFA 5–5-, and DFA 8–5. The DFA 8–5 concentrations were calculated as the sum of 8−5-cyclic (or benzofuran)-DFA and 8–5-noncyclic (or open).

Fibres composition. Neutral Detergent Fibre (NDF) and Acid Detergent Fibre (ADF) were determined by Near-Infrared Spectroscopy (NIRs). We included a new variation in the hemicellulose estimation using the hemicellulose content in the fibres, as the difference between ADF and NDF. We will refer to this determination in the text as hemicellulose quantified as percentage (%). The spectral information of the dried and grounded (1mm) samples was obtained using a Foss NIRSystem 6500 monochromator spectrophotometer (Foss NIRSystem, Silver Spring, Washington, USA), located in an isothermal chamber (24 ± 1 ° C), provided with a rotation module that performs reflectance measurements in the spectral region between 400 and 2500 nm, at 2 nm intervals. The collection of the spectral data and the chemometric analysis of the data was carried out using the WinISI II v program. 1.5 (Infrasoft International, Port Matilda, PA, USA). In order to detect the presence of extrapolations of the prediction model, the identification of “outliers” samples (spectra not represented within the available NIRS calibration group) was performed using the Mahalanobis (GH). Those samples that presented GH values greater than 3, were selected indicating that the sample did not belong to the calibration group (37). In this case, the samples recognized as outliers were analysed by reference methods in the LIGAL laboratory. Subsequently, the reference values were integrated into the corresponding spectral library of the calibration group, expanding and updating the NIRS prediction equations. The outlier samples were analysed in duplicated by wet determinations using reference methods. NDF and ADF were carried out following the procedures proposed by Van Soest and Robertson (38) for NDF, and by Goering and Van Soest (39) for ADF, adapted to the Fibretec System model 1020 digester (Foss Tecator AB, Höganäs, Sweden).

Saccharification efficiency. Saccharification assays were performed as described in Gomez et al. (40). Samples were pre‐treated with 0.5M NaOH at 90°C for 30 min, washed four times with 500 μl sodium acetate buffer and subjected to enzymatic digestion (Celluclast CTec2, 7FPU/g) at 50°C for 8 hours. The amount of released sugars (nmol mg^-1 material^-1 hour^-1) was assessed against a glucose standard curve using the 3-methyl-2-benzothiazolinone hydrozone method.

Saccharification efficiency was obtained for the internode samples and the stover yield samples, that include whole plants “without” ears. On this last case plants were crushed and a representative sample was taken; those samples were pre-dried at 35Cº in a forced air camera and finally dried at 60Cº in a stove. Dried samples were ground in a Wiley (Arthur H. Thomas, Philadelphia, PA) mill with a 0.75 mm screen before being analysed.

Digestibility of the organic matter. Digestibility of the Organic Matter (DOM) of the internode was also determined by Near-infrared spectroscopy (NIRs) at LIGAL. The spectral information of the dried and grounded (1mm) samples was obtained in the same way that for fibres estimations. The samples recognized as outliers were analysed by the in vitro digestibility procedure described by Tilley and Terry, (41) modified by Alexander and McGowan (42).

DOM was obtained in the internode and in the forage yield samples, that include whole plants “including” the ears. Samples preparation in this last case follows the same procedures previously described for saccharification efficiency.

Statistical Analysis

Analysis of variance. An individual and combined analyses of variance was done for each trait according to the SAS mixed model procedure (PROC MIXED) of the SAS program (version 9.4)(43). The best linear unbiased estimators (BLUES) for each inbred line was calculated based on the combined data for the 2-year analysis. Inbred lines were considered as the fixed effects, while years, replication within years, and lines × year were considered random effects. The comparison of means among inbred lines was carried out using the Fisher's protected least significant difference (LSD). Variance analyses for fibres and DOM were included because only ve enough sample to carried out one analysis per genotype, instead of three reps per sample trial.

Contrast analysis. After the variance analysis, the inbred lines were classified according to saccharification efficiency. For digestibility of organic matter, lines were classified qualitatively. The 6 inbred lines presenting the highest values for each corresponding trait were assigned value 1, and the 6 inbred lines presenting the lowest values for each corresponding trait the value -1, whereas for the lines that presented intermediate values, the value 0 was assigned. The inbred lines were also classified by its resistance or susceptibility to corn borer attack based on previous evaluations of these materials(2). Resistance to corn borer has been associated to lower tunnel length of galleries. In this case, the groups were only formed by 5 inbred lines in accordance to the results obtained in previous evaluations (2). With this new dataset, means comparison were performed in order to determine the existence of significant differences in cell wall composition between high and low groups.

Multiple linear regression analysis. In order to understand the relationship between cell wall components and the economically important uses of maize (R.E.D), a multiple linear regression model with BLUES estimate was performed. The stepwise method following the PROC REG procedure in SAS was used (43). In this method, by steps, each explanatory variable is considered for addition or subtraction from the model. Only the variables with a significance value more than 0.15 are selected to take part of the regression model. We have considered as dependent variables the traits involved in resistance to corn borer (tunnel length), forage digestibility (DOM), and ethanolic production traits (saccharification efficiency). On the other side, cell wall traits were considered as independent variables.

Multivariate analysis: Principal Component Analysis and Cluster Analysis.In order to group the inbred lines by its cell wall composition, a principal components analysis was performed. With this analysis we aim to create a new set of variables which are the result of a linear combination of the originals, but not correlated between themselves. The first new variable is the one that explains most of the variability and so on. Once we standardized the database to avoid scale errors, a principal components analysis for all cell wall related traits was performed following the PRIMCOMP procedure in SAS. We chose 8 components that presented an eigen value >1 and that covered 90% of the variability. Next, with the principal components previously obtained we performed a cluster analysis, following a CLUSTER procedure in SAS using the Euclidean distance and the UPGMA (unweighted pair group method with arithmetic mean)(43).

Correlation analysis. Correlation coefficients between cell wall components in the second internode samples were calculated using REML estimates according to a published SAS mixed model procedure (43). In parallel, correlations between the saccharification potential and DOM of the internode and the whole plant were performed, as well as correlations between those traits, tunnel length and yield (grain, biomass, and forage yields). In the case of traits with only one data point, the Pearson correlation was tested.

Table 1

Description (grain type and colour, pedigree, research interest) of the inbred lines included in the experimental set.
Inbred Line	Germplasm Group	Grain Colour and Type	Pedigree	Research Interest
EP17	European	- Yellow - Flint	J.L. Blanco (A1267)	- Parent MAGIC population - Corn borer resistant
EP42	European	- Yellow - Flint	Tomiño. Spanish Landrace	- Corn borer susceptible
EP47	Longfellow	- Yellow - Flint	(EP4 × A239) EP4	- Corn borer susceptible
EP53	European	- Yellow - Flint	Laro. Spanish Landrace	- Parent MAGIC population - Corn borer resistant
EP105	Lancaster	- Yellow - Dent	A671xA295	- Corn borer resistant
EP125	Corn Belt	- Yellow - Dent	Seleccion of CO125. Wisc. exp. single cross	- Parent MAGIC population - Corn borer resistant
EP86	European	- Yellow - Flint	Nostrano dell'Isola. Italian Landrace	- Parent MAGIC population - Corn borer resistant
F473	European	- White - Flint	Doré de Gomer. French Landrace	- Parent MAGIC population - Corn borer resistant
PB130	European	- Yellow - Flint	Rojo vinoso de Aragón. Spanish Landrace	- Parent MAGIC population - Corn borer resistant
A509	Corn Belt	- Yellow - Dent	A78 × A109	- Parent MAGIC population - Corn borer resistant
CO348	Tropical	- Yellow - Flint	CIMMYT-NTR-2	- Sugar corn ethanol hybrids - Moderate Fusarium stalk rot resistance
C103	Lancaster	- Yellow - Dent	Lancaster	- High stalk sucrose inbred
CO384	Reid	- Yellow - Flint	A632 x CO255	- Parent of sugar corn ethanol hybrids
CO442	Iodent	- Flint-Dent	Iodent/NSS	- Parent of sugar corn ethanol hybrids
CO444	Lancanster-European	- Yellow - Flint-Dent	S1381 × CO382	- Parent of sugar corn ethanol hybrids - Lodging resistance
EC212	European	- Yellow - Flint	European Germplasm	- High degradability - Good general combining ability (GCA)
A654	Reid	- Yellow - Dent	A116 × WF9	- Good GCA
W182B	Reid	- Yellow - Dent	WD × W22	- Good GCA
A632	Reid	- Yellow - Dent	(Mt42 × B14) B143	- Reid Germplasm Group
W64A	Reid	- Yellow - Dent	WF9 × C.I.187-2	- Corn Borer resistant

Analysis of Variance and Means Comparisons

For agronomic traits, inbred lines differed significantly for all traits, except for plant lodging (Supplementary Table 1). The combined analysis of variance of the two year trials showed a significant year × inbreds interaction for the trait number of plant internodes (data not shown). With regard to yield, there was significant differences among inbred lines for grain, biomass and forage yields, and only grain yield showed a significant genotype × environment interaction.

There was large variability for all traits of economic importance. Within trials involving the final use of maize, inbred lines differed significantly for saccharification efficiency ranging from 85.98 nmol mg^-1 lassification of the inbred linematerial^-1 hour^-1 in the inbred CO384 to 107.72 nmol mg^-1 material^-1 hour^-1 in the line F473 (Supplementary Table 2). For the DOM we have just one value by genotype, not allowing the analysis of variance for this trait. However, CO348 and A509 are the inbred lines that presented the highest and the lowest DOM values respectively (Supplementary Table 2).

Attending to the cell wall polysaccharides composition of the inbred lines, we observed differences in cellulose and in the neutral sugars of the hemicellulose fraction (Supplementary Table 3). Even though the inbred lines did not differ in the total hemicellulosic fraction, we observed genotype × environment interactions for uronic acids, total sugars and arabinose:xylose ratio. For lignin related traits, inbred lines showed significant differences for Klason lignin and lignin composition (subunits H, G, S and ratio SG). Cell wall bound hydroxycinnamates showed significant differences among inbreds, with the exception of FA which p-value was 0.06 (Supplementary Table 4).

We can summarize the results highlighting the following inbred lines by its cell wall composition: inbreds CO442, EP105 and EP86 exhibit cell walls with high concentration of cell wall bound hydroxycinnamates, and thereby cross-linking. Conversely, inbreds C103, CO384 and CO384, show cell walls with a low concentration of cell wall bound hydroxycinnamates and lignin. EP53 was the inbred line that showed the greatest concentration for lignin, but displayed low concentrations of cell wall bound hydroxycinnamates and saccharification potential. The inbred line F437 stands out for having high values of cellulose, total diferulates, and saccharification efficiency, but low lignin concentration. Similarly, inbred A654 presented high saccharification efficiency and p-coumaric acid concentration.

Contrast Analysis

With the data from the analysis of variance, and the previous data for tunnel length, the groups that would be further used for contrast analysis are shown in Table 2. A high saccharification group was formed by the inbreds A654, EP42, F437, CO442, EC212 and EP17; while the low saccharification group was formed by the inbred EP53, W182B, CO384, EP125, C103 and CO444. With regard to digestibility, CO348, C103, CO384, PB130, EC212 and EP42 were grouped as the inbred lines showing high DOM. The contrasting inbred lines A509, EP125, F473, EP86, W182B and EP53 were included in the low digestibility group. Finally, the group of inbred lines considered susceptible to corn borer attack (longer tunnel length) comprised CO444, EP42, EP47, W182B and EP86; whereas inbred lines PB130, A654, CO348, EP125 and A632 were classified as borer resistant.

Table 2: Classification of the inbred lines according to the mean values they presented for R.E.D traits evaluated in two years.

Inbred line	Saccharification efficiency	Digestibility of organic matter	Tunnel Length
A509	0	-1	0
A632	0	0	-1
A654	1	0	-1
C103	-1	1	0
CO348	0	1	-1
CO384	-1	1	0
CO442	1	0	0
CO444	-1	0	1
EC212	1	1	0
EP105	0	0	0
EP125	-1	-1	-1
EP17	1	0	0
EP42	1	1	1
EP47	0	0	1
EP53	-1	-1	0
EP86	0	-1	1
F473	1	-1	0
PB130	0	1	-1
W182B	-1	-1	1
W64A	0	0	0
The inbred lines presenting the higher values for each trait are represented with a 1, the ones presenting the lower values with a -1 and the intermediates with a 0.

Significant differences between high and low groups of inbred lines according to R.E.D related traits are shown in Table 3. Inbred lines classified as resistant to corn borer attack presented cell walls with lower concentration of p-coumaric acid and lower hemicellulose percentages in the fibres. Conversely, groups with higher saccharification efficiency showed higher concentrations for diferulates: DFA 8-O-4, DFA 8-5-b, DFA 8-5 and DFAT. Finally, in the case of DOM the group that presented the higher digestibility showed lower concentrations in glucuronic acid and p-coumaric, DFA 8-5-b, DFA 8-5-l and DFAT. Inbred lines included in the high digestibility group showed greater proportion of G subunit in their cell walls.

Table 3: Contrast analysis for the high and low groups of inbred lines classified attending to R.E.D traits. Means for cell wall components with significant differences among groups are included.

	Classification Group
CW Component	High	Low	LSD
Tunnel Length (cm)
PCA (mg/g)	13.10	12.27	0.777
Hemicellulose (%)	30.2	29.5	0.5
Saccharification Efficiency (nmol mg material^-1 hour^-1)
DFA 8-O-4 (mg/g)	0.088	0.065	0.015
DFA 8-5-b (mg/g)	0.116	0.089	0.015
DFA 8-5 (mg/g)	0.017	0.014	0.017
DFAT (mg/g)	0.350	0.274	0.041
Digestibility of the Organic Matter (%)
PCA (mg/g)	10.72	13.94	0.991
DFA 8-5-l (mg/g)	0.042	0.060	0.010
DFA 8-5 (mg/g)	0.125	0.164	0.013
DFAT (mg/g)	0.255	0.320	0.017
G (%)	40.42	39.27	0.852
GLUA (mg/g)	2.46	3.43	0.55
LSD: Least Square Distance PCA: p-coumaric acid; DFA85l: Diferulic acid 8-5-Linear; DFA8O4: Diferulic acid 8-O-4; DFAT: Total diferulic acids; DFA85: Diferulic acid 8-5; G:Subunit; GLUA: Glucuronic Acid

Multiple Linear Regression Analysis

For the multiple linear regression model we analysed saccharification efficiency and DOM as dependent variables. Results of the model explaining each trait, the percentage of total and partial variance of each trait, as well as the equation obtained from the model and the regression coefficients are shown in Table 4.

Sixty-one percent of the variance for saccharification efficiency of the internode was explained by the cell wall composition. The cell wall traits that better explain this percentage of the variation were cellulose (45%) and DFA 8-5-b (16%). On the other hand, the variation in DOM of the internode was mainly determined by NDF (83%), ferulic acid (6%) and G subunit (2%), explaining a total of 90 % of the variation.

Table 4: Multiple linear regression step wise model selection and equation for saccharification efficiency and digestibility of organic matter according to the cell wall composition in the internode of 20 inbred lines evaluated during two years.

Step Wise Selection
Saccharification Efficiency (nmol mg material^-1 hour^-1)
Step	Variable introduced in the Model	R² Partial	R²
1	Cellulose (CEL mg/g)	0.45	0.45
2	Diferulic 8-5-b	0.16	0.61
Model	SACCHARIFICATION=53.24+14.47DFA 8-5-b+0.07CEL
Digestibility of the Organic Matter (%)
Step	Variable introduced in the Model	R² Partial	R²
1	Neutral Detergent Fibre (NDF)	0.83	0.83
2	Ferulic Acid (FA)	0.06	0.89
3	Lignin G Subunit (G)	0.02	0.90
Model	DOM=67.78+0.24FA+0.30G-0.47*NDF
R² partial: Percentage of the variance explained by each trait; R2: Total percentage of the variance explained by the model.

Principal Components Analysis

In order to group the inbred lines by its cell wall composition, principal components analysis was performed. Details of the analysis and the graphic representation obtained are shown in Table 5 and Figure 1 respectively. The three first principal components were represented, explaining a total variation of 60% (Figure 1). Principal component 1 (PRIN1) explained 30% of the variance and was mainly represented by total diferulates, individual dimers and fibres (ADF, NDF and Hemicellulose (%)), indicating that inbred lines presenting high values for this component have highly cross-linked cell wall fibres. Principal component 2 (PRIN2), high hemicellulose and glucuronic acid concentrations and lower lignin content, explained 17 % of the variance. Finally, 13% of the variance is explained by principal component 3 (PRIN3), which is associated with high proportions of G subunit, low proportions of S subunit, and thereby, also low S:G ratios.

The inbred lines EP105, F473 and CO442 present high values for PRIN1 (Figure 1), the last two with high saccharification efficiency; whereas the inbred lines CO348 and CO384, with the lowest value for PRIN1, presented high DOM.

For PRIN2, EP53 has the lower value and shows both, low saccharification and low DOM. The highest value for PRIN2 is for CO348, that presents high digestibility.

For PRIN3, the greatest value was EP86, that showed larger tunnel length and low DOM. The lowest values for PRIN3 were presented by inbred CO348, with high digestibility and shorter tunnel length, and the inbred line EP42, with large tunnel length and high digestibility. We can highlight CO348 as presenting highest values for PRIN2 and lowest values for PRIN1 and PRIN3.

Table 5: Three Principal Component obtained from cell wall composition traits of the 20 inbred lines evaluated during two years.

Trait^a	PRIN^b1	PRIN2	PRIN3
CEL	0.05	0.09	-0.12
UAHEMICEL (mg/g)	0.08	0.04	0.02
GALA (mg/g)	0.15	0.04	0.00
GLUA (mg/g)	0.20	0.08	0.17
NSHEMICEL (mg/g)	0.08	-0.26	-0.20
TSHEMICEL (mg/g)	0.08	-0.26	-0.20
FUC (mg/g)	0.21	0.12	0.04
ARA (mg/g)	0.16	0.11	0.31
RHA (mg/g)	-0.18	0.24	0.04
GAL (mg/g)	0.13	0.09	0.32
GLU(mg/g)	-0.17	0.33	0.05
XYL (mg/g)	0.16	0.21	0.08
MAN (mg/g)	0.15	0.06	0.18
ARAXYL (mg/g)	0.01	0.01	0.33
HEMTOT (mg/g)	0.08	0.35	0.06
LK (%)	0.07	-0.36	0.17
H (%)	0.00	0.03	0.18
G (%)	-0.03	0.01	0.30
S (%)	0.03	-0.02	-0.33
SG	0.04	-0.03	-0.32
PCA (mg/g)	0.21	-0.17	0.08
FA (mg/g)	0.17	0.19	-0.11
DFA 5-5 (mg/g)	0.27	0.04	-0.08
DFA 8-O- 4 (mg/g)	0.21	0.17	-0.11
DFA 8-5-l (mg/g)	0.28	0.05	-0.05
DFA 8-5-b (mg/g)	0.25	0.14	-0.17
DFA 8-5 (mg/g)	0.28	0.11	-0.14
DFAT (mg/g)	0.28	0.12	-0.12
ADF %	0.23	-0.17	0.07
NDF%	0.27	-0.16	0.07
Hemicellulose (%)	0.28	-0.12	0.06
^aCEL: Celullose; UAHEMICEL: Uronic Acids from hemicellulose; GALA: Galacturonic acid; GLUA: Glucuronic acid; NSHEMICEL: Neutral sugars from hemicellulose; TSHEMICEL: Total sugar from hemicellulose; FUC: Fucose; ARA: Arabinose; RHA: Rhammanose; GAL: galactose; GLU:glucose; XYL: Xylose; MAN: Mannose; ARAXYL: Ratio arabinose/xylose; HEMTOT: Total hemicellulose; ; LK: Klason lignin; H: Subunit H; G: Subunit G; S: Subunit S ; SG: S:G ratio; PCA: p-coumaric acid; FA: Ferulic acid; DFA 5-5: Diferulic acid 5-5; DFA 8-O-4: Diferulic acid 8-O-4; DFA 8-5-l: Diferulic acid 8-5-Linear; DFA 8-5-b: Diferulic acid 8-5-BenzofuranDFA85: Diferulic acid 8-5; DFAT: Total diferulic acids; ADF: Acid Detergent Fibre; NDF: Neutral Detergent Fibre, Hemicellulose(%): Fibre Hemicellulose ^bPRIN: Principal Component

Cluster Analysis

Taking into account the cluster analysis for cell wall composition, we can classify the inbred lines in four groups (Figure 2). The first group includes EP53 and the second EP86. This two inbred lines are the most distanced from the other 18 inbred lines; inbred EP53 presents a cell wall with both, low digestibility and saccharification efficiency, while line EP86 presents cell walls with low digestibility and susceptibility to corn borer attack. The third cluster is formed by the inbred lines PB130, CO384, EC212, CO348, EP42 and C103. This group contained all inbred lines presenting high DOM. The fourth cluster incorporates the inbred lines EP105, EP47, F473, CO442, W182B, W64A, EP17, A632, CO444 and A509. This last group includes four of the six inbred lines that present low values for DOM.

Correlation Analysis

Three groups of correlations were determined: (i) the complete set of cell wall components (Table 6, 7); (ii) R.E.D. and yield traits (Table 8); and (iii) R.E.D. traits determined using a particular internode and the whole plant material (Table 8). Phenotypic correlation coefficients were not computed for trait pairs including a trait with un-replicated genotype data (cell wall fibres and DOM). In this case, the Pearson correlation coefficients were used. Only significant correlations above 0.50 in absolute values are described, but the complete set of correlations in Tables 6-8.

In the first type of correlation analysis, the only significant correlations between cell wall components were among diferulates, and among lignin subunits (Table 6). All individual dimers were strong and positively correlated among them and with total diferulates (r_p<0.61). S subunit and ratio S:G were strong and positively correlated (r_p = 0.98), and have a strong, negative correlation with G subunit (-0.94 and -0.99, respectively).

Table 6: Phenotypic (below diagonal) correlation coefficient estimates for each pair of cell wall components traits evaluated in 20 inbred lines during two years. Only significant correlations higher than 0.50 are included.

	CEL	GLUA	XYL	MAN	LK	H	G	S	SG	PCA	FA	DFA 5-5	DFA 8-O-4	DFA 8-5-b	DFA 8-5-l	DFA 8-5	DFAT
CEL
GLUA	0.07
XYL	NE	NE
MAN	-0.1	0.18	NE
LK	-0.11	-0.20	NE	0.11
H	-0.32	-0.33	NE	-0.01	0.00
G	0.12	0.06	NE	0.02	0.15	0.13
S	0.00	-0.19	NE	-0.02	-0.13	-0.45	-0.94
S:G	NE	-0.18	NE	-0.02	0.00	-0.27	-0.99	0.98
PCA	-0.02	NE	0.1	0.11	0.23	-0.10	-0.14	0.16	0.17
FA	0.25	-0.11	NE	0.08	-0.04	-0.09	-0.06	0.08	0.00	0.17
DFA 5-5	0.23	-0.03	0.09	0.25	0	-0.13	-0.07	0.11	0.08	0.4	0.01
DFA 8-O-4	0.20	0.00	0.16	0.23	-0.01	0.02	0.03	-0.04	-0.04	0.13	0.31	0.65
DFA 8-5-b	0.14	0.08	0.14	0.22	-0.1	-0.02	-0.18	0.17	0.18	0.24	0.24	0.78	0.68
DFA 8-5-l	0.00	-0.20	0.29	NE	-0.02	0.06	-0.01	-0.01	0.02	0.22	0.4	0.68	0.62	0.61
DFA 8-5	0.11	-0.02	0.22	0.27	-0.08	0.01	-0.13	0.11	0.13	0.31	0.33	0.82	0.72	0.95	0.83
DFAT	0.18	-0.11	0.21	0.28	-0.07	-0.09	-0.06	0.08	0.00	0.29	0.33	0.89	0.88	0.9	0.8	0.95
CEL(mg/g): Celullose; UAHEMICEL: Uronic Acids from hemicellulose (mg/g); GALA: Galacturonic acid (mg/g); GLUA: Glucuronic acid (mg/g); NSHEMICEL: Neutral sugars from hemicellulose (mg/g); TSHEMICEL: Total sugar from hemicellulose (mg/g); FUC: Fucose (mg/g); ARA: Arabinose (mg/g); RHA: Rhammanose (mg/g); GAL: galactose (mg/g); GLU:glucose (mg/g); XYL: Xylose (mg/g); MAN: Mannose (mg/g); ARAXYL: Ratio arabinose/xylose; HEMTOT: Total hemicellulose (mg/g); LK: Klason lignin (%); H: Subunit H (%); G: Subunit G (%); S: Subunit S (%); SG: S/G ratio; PCA: p-coumaric acid (mg/g); FA: Ferulic acid (mg/g); DFA 5-5: Diferulic acid 5-5 (mg/g); DFA 8-O-4: Diferulic acid 8-O-4 (mg/g); DFA 8-5-l: Diferulic acid 8-5-Linear (mg/g); DFA 8-5-b: Diferulic acid 8-5-Benzofuran (mg/g); DFA85: Diferulic acid 8-5 (mg/g); DFAT: Total diferulic acids (mg/g);Fibre NE:Non-estimable. ^bPRIN: Principal Component

Correlations between cell wall fibres (ADF, NDF and Hemicellulose) and the rest of cell components are detailed in Table 7. ADF, NDF and hemicellulose (%) showed strong and positive correlation. ADF and NDF show a strong positive correlation with p-coumaric acid, DFA 8-5-l and DFA 8-5, and are negatively correlated with rhamnose. ADF positively correlated with arabinose and NDF correlated positively with fucose and total diferulates. Finally, hemicellulose positively correlated with fucose, p-coumaric acid, all the individual dimers and the total diferulates, and negatively correlated with rhamnose (Table 7).

Table 7: Pearson correlation r value between ADF, NDF, Hemicellulose (%) and cell wall components traits evaluated in 20 inbred lines during two years.

	ADF	NDF	Hemicellulose (%)
ADF (%)	NE	0.95	0.77
NDF (%)	0.95	NE	0.94
Hemicellulose (%)	0.77	0.94	NE
CEL (mg/g)	0.12	0.09	0.04
AUHEMICEL (mg/g)	0.02	0.17	0.30
GALA (mg/g)	0.08	0.15	0.21
GLUA (mg/g)	-0.38	-0.35	-0.26
NSHEMICEL (mg/g)	0.41	0.35	0.25
TSHEMICEL (mg/g)	0.43	0.38	0.29
FUC (mg/g)	0.42	0.52	0.57
ARA (mg/g)	0.52	0.49	0.40
RHA (mg/g)	-0 .54	-0.66	-0.72
XYL (mg/g)	0.29	0.37	0.41
MAN (mg/g)	0.17	0.28	0.37
ARAXYL (mg/g)	0.19	0.12	0.03
HEMTOT (mg/g)	0.00	0.03	0.05
LK (%)	0.44	0.45	0.42
H (%)	0.16	0.15	0.12
G (%)	-0.08	-0.03	0.02
S (%)	0.02	-0.02	-0.06
SG	0.07	0.03	-0.02
PCA (mg/g)	0.75	0.78	0.71
FA (mg/g)	0.38	0.34	0.25
DFA 5-5 (mg/g)	0.46	0.63	0.73
DFA 8-O-4 (mg/g)	0.29	0.41	0.50
DFA 8-5-l (mg/g)	0.59	0.72	0.77
DFA 8-5-b (mg/g)	0.35	0.48	0.57
DFA 8-5 (mg/g)	0.47	0.61	0.69
DFAT (mg/g)	0.44	0.59	0.69
ADF: Acid Detergent Fibre; NDF: Neutral Detergent Fibre; CEL: Celullose; UAHEMICEL: Uronic Acids from hemicellulose; GALA: Galacturonic acid; GLUA: Glucuronic acid; NSHEMICEL: Neutral sugars from hemicellulose; TSHEMICEL: Total sugar from hemicellulose; FUC: Fucose; ARA: Arabinose; RHA: Rhammanose; XYL: Xylose; MAN: Mannose; ARAXYL: Ratio arabinose/xylose; HEMTOT: Percentage of total hemicellulose; LK: Klason lignin; H: Subunit H; G: Subunit G, S:Subunit S ; SG: S/G ratio, PCA: p-coumaric acid; FA: Ferulic acid; DFA 5-5: Diferulic acid 5-5; DFA8-O-4: Diferulic acid 8-O-4, DFA 8-5-l: Diferulic acid 8-5-Linear;DFA 8-5-b: Diferulic acid 8-5-Benzofuran;DFA 8-5: Diferulic acid 8-5;DFAT: Total diferulic acids; NE: Non-estimable

The second and third group of correlations are detailed in Table 8. For the second type of correlations among R.E.D. and yield traits the only strong correlation was observed among stover and forage yield (r_p=0.66); whereas no correlation between saccharification efficiency in the whole plant without the ear and the internode were observed. There was no correlation between DOM in the internode and the whole plant with the ear (Table 8).

Table 8: Phenotypic correlation r values using a particular internode or the whole plant material for R.E.D and yield traits evaluated in 20 inbred lines during two years.

	Sacc internode	Sacc plant	Dom internode	Dom plant	Tunnel length	Grain Yield	Forage Yield
Sacc internode
Sacc plant	-0.1
Dom internode	0.001	-0.29
Dom plant	-0.02	0.00	0.24
tunnel length	0.02	0.06	-0.09	0.14
Grain Yield	0.16	-0.12	0.07	0.22	0.30
Forage Yield	0.00	-0.18	0.32	0.22	0.25	0.34
Stover Yield	-0.01	0.00	0.42	0.23	0.39	0.15	0.66
Sacc internode: Saccharification efficiency obtained in the second internode below the main ear (nmol mg material^-1 hour^-1); Sacc plant: Saccharification efficiency obtained in samples of crushed plant without the ears (nmol mg material^-1 hour^-1); Dom internode: digestibility of the organic matter obtained in the second internode below the main ear (%); Dom plant: digestibility of the organic matter obtained in samples of crushed plant including the ears (%); Tunnel Length (cm); Grain, Forage and stover yield (Mg/h)

Agronomic Characterization of the 20 Inbred Line Panel

The subset of inbred lines evaluated showed variation in the agronomic traits tested. The range obtained for days to silking and anthesis indicates that all inbred lines included in the panel develop appropriately and were well adapted to the growing conditions at the Pontevedra location (42°25′ N, 8°38′ W and 20 m above sea level). Inbred lines also differed for grain, forage and stover yield, the last two being positively correlated. In this sense, it is important to highlight two facts from the yield evaluations: (i) the value obtained for each inbred refers to the maximum-potential yield, not to the yield in a plot; and (ii) these values are for inbred lines, not being the standard material to be tested for yield, as it would be hybrid combinations.

Studying the Variability in the Cell Wall Composition

The relative quantities of secondary cell wall components in model grasses are: 35-45% cellulose, 40-50% hemicellulose and ~20% lignin(44). We studied the composition of the second internode below the main ear in a panel of 20 inbred lines of maize. We observed variation for cellulose, ranging from 29 to 51%; hemicellulose 19-28%, and lignin ranging from 19 to 33%. The internode represents a more uniform tissue than the whole plant or stover, allowing to obtain more accurate determination of the stalk composition.

As previously noted, the inbred lines included in this study show differences in cellulose, lignin, and hydroxycinnamates, but not in hemicellulose. The only hemicellulose related trait that showed significant differences in the set of inbred lines was the neutral sugars concentration.

We do not find variation in the monosaccharide composition among the 20 genotypes evaluated despite the germplasm variability. This may be because either, they are not diverse enough, or because there is no variability for those traits in maize, or at least not in the types of maize represented in this set. Besides, we are working with secondary cell wall, which is less variable than primary cell walls. (45)However, the lack of differences for monosaccharide composition in the second internode does not exclude variation between the tissues that constitute the internode (pith and rind). (46) Barros-Rios et al. (46) previously showed differences in polysaccharides in the pith (791 mg/g of cell wall) and the rind (772 mg/g of cell wall) of maize internodes..

Regarding lignin polymer, we found variation not only for lignin content, but also for lignin monomeric composition. In concordance with previous studies, S subunit represented the largest proportion, and H subunits the lowest proportion (47). Variation for hydroxicinnmamic acids among the inbred lines was also found in accordance with other studies.(3,15) For cell wall bound hydroxycinnamates we found that p-coumaric acid was the most abundant, which is also consistent with previous studies (5,15). The cell wall composition of some particular inbred lines in the current panel set has been previously established. In this sense, Santiago et al. (5) studied the relationship between the concentration of cell wall phenylpropanoids in the pith tissues (PCA, FA, DFA 8-O-4, DFA 8-5-b, DFA 8-5-l) and the level of resistance to corn borers in a set of 8 inbred lines (A509, EP42, EP47, F437 and PB130 were included). Some of the amounts described in the study from Santiago et al. (5) are kept in the present study. Inbred line A509 in both studies was the inbred that showed greater concentration in PCA content, not differing from F473 in this study; EP47 shows in both studies the greater concentration for DFA 8-5-l, and PB130 and EP42 show the lowest concentration of DFA 8-O-4 in both studies. Similarly, Barros-Rios et al. (46) determined the lignin and hydroxycinnamates (PCA, FA, and DFAT) concentrations in four inbred lines of maize (A509, EP39, EP42 and EP47) in the pith and rind tissues separately. The results showed larger concentration of cell wall components in the rind. In our case, analysing the complete internode, we also found higher concentrations of lignin and hydroxycinnamates than in core pith tissues for A509, EP42 and EP47.

In relation to the correlation analysis between cell wall components, ferulic acid dimers were positively and strongly correlated, and showed covariation in agreement with previous research (46,48). However, unlike in previous studies, individual and total diferulates did not show covariation with FA monomers (46,48). These discrepancies may be due to the type of tissue analysed. Barros-Rios et al. (46) studied the correlation between cell wall components independently in pith and rind tissues, and found that in pith tissues total diferulates and ferulic acid co-variate, although this covariation was not significant in rind tissues. In the same study, Barros-Rios et al. found greater concentration of both ferulic acid and total diferulates in the pith than in the rind. Similarly, positive correlations among ferulic acid, and individual and total dimers are described by López-Malvar et al. (48), where determinations were made in pith tissue. This reinforces the importance of the tissue selected for analysis, since it seems demonstrated that both the hydroxycinnmamic acid content and the relationship between hydroxycinnamates is different within the tissue.

Cell wall fibres were strongly correlated indicating that main cell wall polymers (cellulose, hemicellulose and lignin) covariate together (49). Cell wall fibres were strongly and positive correlated with PCA monomer which is in accordance with previous studies, as PCA is considered an indicator of lignification and secondary cell wall deposition (50,51). The strong positive correlations observed between individual and total diferulates and fibres are explained by the linkages between cell wall polymers and diferulates. Ferulic acid dimers crosslink hemicellulose chains binding specifically to arabinose. (52) Thus, this positive correlation may be caused by the linkage of diferulates and arabinoxylans, as the strongest correlations are among diferulates and hemicellulose. Moreover, ferulic acid and diferulic esters form cross-links through the etherification of the phenolic hydroxyl group to lignin polymers. Finally, the increasing amount of cell wall fibres is indicative of secondary cell wall deposition that is also correlated with an increasing cross-linkage. We found significant correlations among cell wall fibres and monosaccharides, both positive (arabinose, fucose) and negative (rhamnose) in agreement with previous studies. (53) The opposite correlations may be explained by dilution of primary cell wall material by the accumulation of secondary wall material. Furthermore, maize present type II cell walls characterized by a low rhamnose content (45).

In the cluster analysis, where it is reported the classification of inbred lines according to their variability in cell wall composition, 2 of the 4 groups were represented by just one inbred line: EP53 and EP86. EP53 was the most distinctive line due to deeper differences in cell wall composition from the other 19, including the highest value for lignin content. Lignification has been shown as the most detrimental component for both cell wall digestibility and biofuel production (4,47). Indeed, inbred line EP53 was included in the low digestibility and saccharification groups obtained after the variance analysis, even presenting the lowest saccharification value. Furthermore, in the multivariate analysis using the principal components approach it stands out for presenting low value for the PRIN2 (PRIN2 was mainly determined by low lignin concentration). Thus confirming the detrimental role that lignin plays on biomass quality, making less accessible cell wall polysaccharides to hydrolytic enzymes.

Inbred EP86, like EP53, was clustered alone in one group. For this inbred line we can highlight the high concentration of PCA and low concentration of individual and total dimers of FA. As previously mentioned, the structural reinforcement (lignin and cross-link) of the secondary cell walls is directly linked with low degradability values (54). Moreover, in the principal component analysis inbred line EP86 presented high values for PRIN2 and 3, and a low value for PRIN1. PRIN1 was mainly represented by individual and total dimers, indicating their influence in EP86 cell wall organization. This low concentration of total dimers and high concentration of PCA may also contribute in the susceptibility of this inbred line to corn borer attack (5). In accordance with its cell wall composition, this inbred line was classified in the analysis of variance in the low digestibility and borer susceptible group. Cell walls richer in crosslinking mediated by diferulates have been suggested to be a deterrent to borer attack and larvae development, presenting limited digestibility (55).

From e breeder point of view, EP86 and EP53 come from European Landraces, representing a reservoir for variability. These inbred lines present characteristics that make them different from the other eighteen inbred lines (Figure 2) and may be valuable for breeding purposes.

Another group that deserves attention is the group composed by inbred lines EC212, EP42, C103, CO348 and PB130. All the inbred lines included in this group were characterized by lower amounts of diferulates and lignin, and presented a highly degradable cell wall; in opposition to the two inbred lines previously mentioned (46,47,56).

Finally, in the correlation analysis we observed that the determinations of digestibility and saccharification of the cell walls in the internode and the whole plant did not show any significant correlation, indicating that results obtained for the internode cannot be extrapolated in or correlated to the whole plant. From a breeding standpoint, the aforementioned results indicate that to improve stover quality it seems more appropriate to evaluate stover. However, if the goal is to perform genetic analyses to find candidate genes that alter cell wall composition and digestibility of specific plant components, focusing on specific tissues would be more appropriate; as determinations performed in specific and more homogeneous tissues are more accurate. In addition, the sample uniformity in this last tissue makes this material more suitable for high-throughput robotic evaluations, which are generally based on replications of a few milligrams of biomass.

Relationship among Cell Wall Components and R.E.D. Traits

Resistance to corn borer (R.) has been associated to shorter tunnel length of galleries in the stalks (2). Taking into account this previous classification, groups of inbred lines classified as resistant or susceptible to corn borer showed differences in the percentage of hemicellulose content, being larger in inbred lines susceptible to borers attack, as well as in p-coumaric acid concentration, also in higher amounts in the cell walls of susceptible inbred lines.

Krakowsky et al. (57) suggested a positive correlation between European corn borer stalk tunnelling and stalk and sheath NDF adjusted for ADF. NDF adjusted represents the relatively digestible hemicellulosic fraction. Additionally, Terra et al. (58) found that hemicellulose is partly digested by the larvae of Erinnyis ello feeding on Euphorbia pulcherrima leaves, as opposed to other cell wall components. A larger proportion of hemicellulose could favour the attack of the insect, while other structural components involved in tissue strengthening, such as lignin, or cellulose, deter the larvae advance (59).

Susceptible and resistant inbred lines differed in PCA amounts; and susceptible lines have a higher concentration of p-coumaric acid. This result appears contradictory with previous results, as an increasing concentration of p-coumaric acid has been related to resistance to corn borer attack (5). Most p-coumarate accretion occurs in tandem with lignification and its accumulation can be considered a relevant indicator of lignin deposition. In maize, lignins are acylated (primarily syringyl units) at the γ-position by p-coumarates (60). Acylation has a marked influence on the bonding mode of S lignin units, on the spatial organization of lignins and consequently on their capacity to interact with polysaccharides. It is known that syringyl type lignin forms a more linear structure, (61) with little or no branching and with a lesser degree of polymerization. Although S lignin has been involved in defence against biotic stresses (62,63), in the case of corn borer resistance S-type lignin, indirectly associated to more PCA acetylation, may favours borer susceptibility, at least in the materials evaluated in the current study. In this sense, the type of tissues analysed has to be further considered in the establishment of clear relationships.

Differences in high and low saccharification efficiency (E.) obtained in the contrasts analysis were mainly determined by the ferulic acid dimers concentrations, showing larger values in the high saccharification efficiency group. Supporting these results, in the multiple linear regression analysis we identified cellulose and DFA 8-5-b as significantly involved in the variability for saccharification. Lignocellulosic polysaccharides, mainly cellulose (40%), serve as main substrate for fermentation of cell wall sugars in ethanol (40), Thereby, cell walls richer in cellulose have more sugars to potentially be fermented. Improving the relative content of cellulose was already one of the main strategies towards the development of advanced lignocellulosic feedstocks (64).

The rigid structure of the cell wall makes cellulosic materials inaccessible to hydrolytic enzymes, making a pre-treatment essential before the saccharification in order to enhance the effectivity of those enzymes. Among the several types of pre-treatments that could be used, alkaline pre-treatment is appropriate for corn stover and other monocots due to its particular cell wall composition (65). The cell walls of graminaceous monocots are known to contain alkali-labile ferulate ester cross-links within the hemicellulose (66), as well as high phenolic hydroxyl contents in their lignins, resulting in increased alkali solubility (67), rendering the cell wall highly susceptible to delignification by alkaline pretreatments (6). As a consequence, mild alkali pre-treatment of grasses such as maize has shown substantial advantages, as these can be employed for both fractionating biomass and generating a pre-treated biomass that is highly amenable to enzymatic hydrolysis (66).

Our findings indicate that a greater concentration of ester diferulates can be associated with an enhanced saccharification efficiency of the maize stalk. This was unexpected since a more cross-linked cell wall has been suggested to be more recalcitrant to enzyme deconstruction (68). This may involve cell wall plasticity, so a greater amount of crosslinking elements in the cell wall may replace the deposition of other structural elements, such as lignin, finally favouring deconstruction (69). A cell wall where the structural reinforcement is mainly due to a greater crosslinking effect mediated by dimers could represent an improvement in the process of obtaining ethanol, considering that among the pre-treatments of the samples for saccharification the saponification is usually included and would eliminate these compounds (70). Li et al. (6) found in a study of a subset of 26 inbred lines of maize that the pre-treated cell-wall hydrolysis yields were positively correlated with the ferulate released by alkali pre-treatment, indicating that breaking of ferulate cross-links between cell- wall polymers is an important outcome of pre-treatment. This result reinforces the hypothesis that cell walls where the structural support is based in a higher cross-linkage by diferulates could be more favourable to sugar release, but only after the corresponding alkaline pre-treatment. The role of crosslink is still negative for saccharification if not pre-treated. On the other hand, a greater proportion of ester-link diferulates may indicate a lesser proportion of ether-linked diferulates bound to lignin, and therefore less recalcitrant cell walls. However, ether-linked diferulates cannot be precisely determined under the current wet chemistry procedures.

Regarding to forage feedstocks (D.), highly degradable lines presented lower concentration of PCA, DFA 5-5, DFA 8-5-l and DFAT, lower proportion of glucuronic acid, and greater proportions of G subunits. In addition, we obtained that DOM was negatively affected by the content in NDF, whereas positively affected by FA and G subunits.

High concentration of fibres directly affects digestibility by the limitation of the energy intake by the animals (71). In agreement with our results, Wolf et al. (71) analysed two maize populations (with high and low concentrations of NDF, ADF, lignin, and silica) and foundthat the population exhibiting low range of NDF also showed greater digestibility.

During lignification the ferulic acid and diferulic esters form cross-links through the etherification of the phenolic hydroxyl group to lignin polymers, (72) forming a polysaccharide-lignin matrix that renders cell wall more recalcitrant to enzymatic hydrolysis (72). The results obtained in the contrast analysis are consistent with this statement, however, in the multiple linear regression analysis, we observed that 6% of the variation for DOM was positively explained by FA concentration. As this was unexpected, we next performed a simple regression analysis between DOM and FA in order to test if the positive effect was repeated, and it was not (data not shown). Overall, we suggest that this could be an effect of the multiple linear regression model. When constructing a multiple regression, the coefficient for the first independent traits coincides with that of the multiple regression for that trait. For the rest of the traits included in the analysis the regression is done with the residuals for each genotype, unless traits are totally independent. This may cause a change in the effect as in the case of FA.

In relation to the role of the p-coumaric acid in the DOM, cell walls presenting lower PCA content were more digestible. p-coumaric acid is mainly esterified to the y-position of the side chains of S units in lignin (60). The role of p-coumarate-monolignol conjugates, is to help control the three-dimensional organization of grass lignin. As previously mentioned Syringyl-type lignin is more linear in structure and extends further into the secondary wall, protecting a larger proportion of the polysaccharides in the wall from digestion; thus reducing cell wall digestibility (61). In our study, lines included in the high digestibility group also showed greater proportion of G subunits. Mechin et al. (3) observed a reduced proportion of subunits S in bm3 mutants, characterized by its improved stover digestibility. They also observed that the decrease in the proportion of S subunit was balanced by an increase in proportion of G. A greater proportion of subunit G implies a decrease of resistant C-C interbonds, explaining the increase in degradability in bm3 mutants.

Finally, a greater concentration of glucuronic acid was detrimental for DOM. Hemicellulose could be a potential repository of fermentable sugars (73), but unlike cellulose, hemicelluloses are not chemically homogeneous. Corn ﬁbre xylan is one of the complex heteroxylans containing β-(1,4)-linked xylose residues. (74) About 80% of the xylan backbone is highly substituted with monomeric side-chains of arabinose or glucuronic acid linked to O-2 and/or O-3 of xylose residues. The effect of hydrolytic enzymes used in processes such as DOM are influenced by the variation of the primary structure of the arabinoxylans (75). Based on the works of Van Eylen et al. (76) and Appeldoorn et al.(77) reductions in the frequency of acetic acid, uronic acid and arabinose side groups in glucuronoarabinoxylans would concurrently lead to a reduction in the cell wall recalcitrance. The presence of more substitutions in the arabinoxylan chain, particularly glucuronic acids, could interfere the specific mode of action of hydrolytic enzymes, limiting this way the DOM.

Promising Genotypes to be Used in R.E.D Improvement

Regarding saccharification efficiency, the 20 inbred lines showed significant differences and could be divided into three groups: high (101.58-108.96 nmol mg material^-1 hour^-1), intermediate (101.42-94.72 nmol mg material^-1 hour^-1) and low (93.67-80.18 nmol mgmaterial^-1 hour^-1) saccharification. Other researchers have studied the saccharification efficiency of several crops species following the same method and pre-treatment as in this study: Acevedo et al. (78) studied the cell wall composition and saccharification efficiency of internodes of seven Sorghum sudanense accessions; they obtained significant differences across the accessions and an average level of 53.63 nmol mg^-1 hour^-1 of reducing sugars. Similarly, Whitehead et al. (79) tested Miscanthus sinensis and Arabidopsis thaliana obtaining average values of reducing sugars of 60 nmol mg^-1hour^-1and 80 nmol mg^-1 hour^-1 for Arabidopsis and Miscanthus respectively. In a study using Brachypodium stem material Whitehead et al. (80) obtained variability in the saccharification efficiency ranging from 28.83 nmol mg^-1hour^-1to 46.67 nmol mg^-1hour^-1. Finally, Liu et al. (81) studied the genetic variability of saccharification efficiency in straw samples from a rice RIL population and they observed a wide range of saccharification values, ranging from 59 nmol mg^-1hour^-1to 116 nmol mg^-1hour^-1, with the highest saccharification plant stems producing 97% more reducing sugar than the lowest saccharification line in this population. Species like Miscanthus, switchgrass or sugarcane, are promising candidates for the industrial production of biofuel as they present high biomass yields (15-25 Mg/ha), broad geographic adaptation, superior carbon sequestration and efficient nutrient utilization.(82) However, these species cannot be readily implemented on a wide-commercial scale. In contrast, maize is the most important crop in terms of production, 1300 million tons of dry maize stover are produced worldwide ;(83) and can potentially supply vast amounts of lignocellulose in the form of agricultural residues (5 Mg/ha) (82). In view of the results obtained for saccharification efficiency in contrast to other crops, maize arises as an outstanding model able to contribute significantly to the energy industry’s feedstock both in quality and quantity.

Among the set of inbreds, the sugar corn lines C103, CO348, CO384, CO444 and CO442 were included because of their promising performance to be used in hybrid combination for ethanol production (25). However, this consideration was noted according to the soluble sugar content in the stalk of their hybrids, but without considering the sugars coming from the cell wall polysaccharides. In this study, we just can highlight the inbred line CO442 (Iodent) as the only one included in the high saccharification efficiency group. The high saccharification efficiency of this inbred line may be due to a cell wall rich in diferulate crosslinking that responds better to alkaline pre-treatment. Conversely, some other inbred lines identified as potential candidates as base material in breeding programs could be A654, EC212, EP17, EP42 and F473. Four of these inbred lines are included in the European Flint Heterotic Group (EC212, EP17, EP42 and F473) and the last one in the Reid Group (A654), so that it is possible to obtain good heterosis for grain production, while getting high saccharification efficiency.

The results from DOM were not included on the variance analysis by the reasons previously mentioned, but we can revise the rank obtained for this trait. DOM values in this research varied from 53.4% to 63.8%. This rank is in agreement with the previous values published for maize in vitro digestibility (84). Compared with other crops, digestibility of the organic matter was lower in sorghum than in maize, with values ranging between 40% and 45%; for rice straw differences in in vitro digestibility of the organic matter have been reported and ranged from 23.6% to 36.9%;(85) similarly Capper et al. (86) reported means of 32 to 35% in Barley stems. In search for a forage ideotype in cereals, it is necessary to improve the enzymatic digestibility and intake of the forage. DOM and cell wall digestibility are one of the major target for the improvement of feeding value in cereal plants. This subset of inbred lines represents a rich genetic background for improving R.E.D traits, since itincluded variation for cell wall composition and the well adapted genoytypes (87).

To respond to the question Is it Possible to Identify a Particular Ideotype Useful in the R.E.D.?, our results show that it is very difficult to find a maize ideotype presenting a cell wall composition that fits the three requirements of the R.E.D, as one combination of components would favour one use and negatively affect the other. For example, that is the case of the diferulic acid content, that affects cell wall digestibility and saccharification efficiency, or borer resistance and saccharification, both in opposite ways. Therefore, we could aim to obtain a putative genotype from this subset of lines with the best combination of cell wall compositional traits to be used in a particular usage. Despite this, among this subset of inbred lines, we found inbred lines that present high saccharification efficiency and high digestibility of the organic matter: EP42 and EC212; however, we must note that both are susceptible to corn borer attack.

According to these results, we can propose a maize cell wall ideotype to each specific area to be improved: (i) borers resistance in the internode may involve cell walls with low p-coumaric acid concentration and hemicellulose content; (ii) saccharification efficiency must be improved by increasing the presence of cellulose and diferulates; (iii) and to improve digestibility cell wall must have poor neutral detergent fiber and diferulate cross-links, combined with a lignin polymer richer in G subunits.

Genotypic variation has been observed for agronomic, cell wall composition and saccharification efficiency in the set of 20 inbred lines analysed. The germplasm represented by these inbred lines is a potential source of variation that can be exploited in the improvement of biofuel production using maize as a resource.

Depending on the final use of maize we must focus on the characterization of the indicated tissue. From a breeding standpoint, if the goal is to improve stover or forage quality, it seems more appropriate to evaluate stover or forage samples. The internode characterization leads us to a deep and more precise knowledge of the behaviour of the cell wall. Whereas for improving corn borer resistance the study has to focus on the feeding tissue of the larvae, in this case the pith.

It is not possible to define a cell wall ideotype that simultaneously fits the requirements for the three uses proposed. We have to settle for identifying the inbred lines with the better combination of cell wall traits for each final use of maize, to be used in future and specific breeding programs.

In theory, a resistant inbred line in the internode would present cell walls with low p-coumaric acid concentration and low hemicellulose content.

Inbred lines showing cell walls with high cellulose content, and high diferulate cross-linking as opposed to cell wall reinforced by lignin may present high saccharification efficiency

By last, inbred lines with enhanced digestibility must have a cell wall poor in neutral detergent fibre and diferulic acid cross-links, combined with a lignin polymer richer in G subunits

AAFC: Agriculture and Agri-Food Canada

ADF: Acid Detergent Fibre

ARA: Arabinose

ARAXYL: Ratio Arabinose/Xylose

AX: Arabinoxylan

BLUEs: Best Linear Unbiased estimators

bmr: Briwn midrib

CAD: Cinnamyl Alcohol Dehydrogenase

CEL: Celullose

DFA55: Diferulic Acid 5-5

DFA85: Diferulic Acid 8-5

DFA85b: Diferulic Acid 8-5-Benzofuran

DFA85l: Diferulic Acid 8-5-Linear

DFA8o4: Diferulic Acid 8-O-4,

DFAT: Total Diferulic Acids.

DOM: Digestibility of Organic Matter

FA: Ferulic Acid

FUC: Fucose

G: Subunit G

GAL: Galactose

GALA: Galacturonic acid

GCA: Good general combining ability

GLU: Glucose

GLUA: Glucuronic Acid

H: Subunit H

HEMTOT: Percentage of Total Hemicellulose

IVDMD: In vitro Dry Matter Digestibility

IVNDFD: In vitro Neutal Detergent Fibre Digestibility

KL: Klason Lignin

LSD: Least Significance Difference

MAGIC: Multiparent-Advanced Generation Intercross

MAN: Mannose

NIRs: Near-Infrared Spectroscopy

NDF: Neutral Detergent Fibre.

NSHEMICEL: Neutral Sugars from Hemicellulose

PCA: p-Coumaric Acid

PRIN: Principal Component

R.E.D: pest Resistance. Ethanol production, forage Digestibility

RHA: Rhammanose

rp: Phenotypic Correlation

S: Subunit S

S:G: S:G ratio

SACC: Saccharification Efficiency

TL: Tunnel Length

TSHEMICEL: Total Sugar from Hemicellulose

UAHEMICEL: Uronic Acids from Hemicellulose

XYL: Xylose

Author information

¹Facultad de Biología, Departamento de Biología Vegetal y Ciencias del Suelo, Universidad de Vigo, As Lagoas Marcosende, Vigo 36310, Spain. Agrobiología Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC);

²Misión Biológica de Galicia (CSIC), Pazo de Salcedo, Carballeira 8, 36143, Spain

³E.E. Forestales, Dpto. Ingenieria Recursos Naturales y Medio Ambiente, Pontevedra 36005, Spain

⁴ CNAP, Department of Biology, University of York, Heslington, York YO10 5DD, UK

⁵Universidad de León, Dpto. Ingeniería y Ciencias Agrarias, Área de Fisiología Vegetal, Campus de Vegazana s/n, 24071 León, Spain

⁶BioDiscovery Institute and Department of Biological Sciences, University of North Texas, 1155 Union Circle, #311428, Denton, TX 76203-5017, USA

⁷Laboratorio Interprofesional Galego de Análise do Leite (LIGAL), Mabegondo, 15318 Abegondo, A Coruña, Spain.

Corresponding author

*Email: [email protected]

Funding

This research has been developed in the frame of the ‘Agri-Food Research and Transfer Centre of the Water Campus (CITACA) at the University of Vigo (Spain), which is economically supported by the Galician Government and in the MIsión Biológica de Galicia-CSIC. It was funded by the “Plan Estatal de Ciencia y Tecnología de España” (projects RTI2018–096776-B-C21, and RTI2018–096776-B-C22 co-financed with European Union funds under the FEDER program). A. López-Malvar’s scholarship for the PhD fulfilment has been granted by University of Vigo and by a contract charged to the project RTI2018–096776-B-C22. R. Santiago’s postdoctoral contract “Ramón y Cajal” has been financed by the Ministry of Economy and Competiveness (Spain), Vigo University, and the European Social Fund. The funding body played no role in study design, data analysis, and manuscript preparation.

Authors’ contributions

RAM, RS conceived and design the study. RAM, RS, AL, participated in its design and carried out the field trial and participated in sample collection; AL, RAM, RS performed data analysis; AL wrote the manuscript; LDG, RS, JBR and SP performed laboratory analysis and assisted in saccharification efficiency, lignin composition and NIRs determinations. AE and XCS, contributed significantly to the discussion of the manuscript. All authors read and approved the final manuscript.

Availability of data and materials

The data sets used and/or analysed during the current study will be available

upon reasonable request to the corresponding author.

Ethics approval and consent to participate

Not applicable in this study.

Consent for publication

Not applicable in this study.

Competing interests

The authors declare that they have no competing interests.

Acknowledgements

We are grateful to Prof. Simon J McQueen Mason for their support at the CNAP, University of York, UK. We thank Lana Reid for the transfer of the Canadian inbred lines, and the Dixon laboratory at University of North Texas for support with the lignin compositional analyses.

Fry SC. Cross-Linking of Matrix Polymers in the Growing Cell Walls of Angiosperms. Annu Rev Plant Physiol. 1986;37(1):165–86.
Butrón A, Malvar RA, Cartea ME, Ordás A, Velasco P. Resistance of maize inbreds to pink stem borer. Crop Sci. 1999;39(1):102–7.
Méchin V, Argillier O, Menanteau V, Barrière Y, Mila I, Rollet B, et al. Relationship of cell wall composition to in vitro cell wall digestibility of maize inbred line stems. J Sci Food Agric. 2000;80(5):574–80.
Barrière Y, Méchin V, Riboulet C, Guillaumie S, Thomas J, Bosio M, et al. Genetic and genomic approaches for improving biofuel production from maize. Euphytica. 2009;170(1):183–202.
Santiago R, Butrón A, Reid LM, Arnason JT, Sandoya G, Souto XC, et al. Diferulate content of maize sheaths is associated with resistance to the Mediterranean corn borer Sesamia nonagrioides (Lepidoptera: Noctuidae). J Agric Food Chem. 2006;54(24):9140–4.
Li M, Heckwolf M, Crowe JD, Williams DL, Magee TD, Kaeppler SM, et al. Cell-wall properties contributing to improved deconstruction by alkaline pre-treatment and enzymatic hydrolysis in diverse maize (Zea mays L.) lines. J Exp Bot. 2015;66(14):4305–15.
Santiago R, Sandoya G, Butrón A, Barros J, Malvar RA. Changes in phenolic concentrations during recurrent selection for resistance to the Mediterranean corn borer (Sesamia nonagrioides Lef.). J Agric Food Chem. 2008;56(17):8017–22.
Buendgen MR, Coors JG, Grombacher AW, Russell WA. European corn borer resistance and cell wall composition of tree maize populations. Crop Sci. 1990;30:505–10.
Bergvinson DJ, Arnason JT. Phytochemical changes during recurrent selection for resistance to the European corn borer. Crop Sci. 1997;3.
Sarath G, Dien B, Saathoff AJ, Vogel KP, Mitchell RB, Chen H. Ethanol yields and cell wall properties in divergently bred switchgrass genotypes. Bioresour Technol. 2011;102(20):9579–85.
Sarath G, Akin DE, Mitchell RB, Vogel KP. Cell-wall composition and accessibility to hydrolytic enzymes is differentially altered in divergently bred switchgrass (Panicum virgatum L.) genotypes. Appl Biochem Biotechnol. 2008;150(1):1–14.
Bertrand A, Castonguay Y, Duceppe M. Selection for improved saccharification efficiency in alfalfa stems assessed by enzyme-released glucose. 2013;325–6.
Vogel KP, Mitchell RB, Sarath G, Jung HG, Dien BS, Casler MD. Switchgrass biomass composition altered by six generations of divergent breeding for digestibility. Crop Sci. 2013;53(3):853–62.
Barros-Rios J, Malvar RA, Jung HJG, Bunzel M, Santiago R. Divergent selection for ester-linked diferulates in maize pith stalk tissues. Effects on cell wall composition and degradability. Phytochemistry . 2012;83:43–50.
Barros-Rios J, Malvar RA, Jung HJG, Santiago R. Cell wall composition as a maize defense mechanism against corn borers. Phytochemistry . 2011;72(4–5):365–71.
Jung HG, Mertens DR, Phillips RL. Effect of reduced ferulate-mediated lignin/arabinoxylan cross-linking in corn silage on feed intake, digestibility, and milk production. J Dairy Sci . 2011;94(10):5124–37.
Barrière Y, Argillier O, Barrière Y, Brown-midrib OA, Sciences EDP. Brown-midrib genes of maize : a review To cite this version : HAL Id : hal-00885517 Brown-midrib genes of maize : 1993;13(10):865–76.
Jung HJG, Samac DA, Sarath G. Modifying crops to increase cell wall digestibility. Plant Sci . 2012;185–186:65–77.
Fu C, Xiao X, Xi Y, Ge Y, Chen F, Bouton J, et al. Downregulation of Cinnamyl Alcohol Dehydrogenase (CAD) Leads to Improved Saccharification Efficiency in Switchgrass. Bioenergy Res. 2011;4(3):153–64.
Butrón A, Santiago R, Cao A, Samayoa L, Malvar R. QTLs for Resistance to Fusarium Ear Rot in a Multiparent Advanced Generation Intercross (MAGIC) Maize Population. Plant Dis. 2019;103(5):897–904.
Jiménez-Galindo JC, Malvar RA, Butrón A, Santiago R, Samayoa LF, Caicedo M, et al. Mapping of resistance to corn borers in a MAGIC population of maize. BMC Plant Biol. 2019;19(1):1–17.
Yi Q, Malvar RA, Álvarez-Iglesias L, Ordás B, Revilla P. Dissecting the genetics of cold tolerance in a multiparental maize population. Theor Appl Genet. 2020;133(2):503–16.
Butrón A, Samayoa F, Santiago R, Malvar RA. Selection efficiency of tunnel length and stalk breakage to obtain maize inbred lines resistant to stem borer attack. Euphytica. 2014;197(2):295–302.
Santiago R, Butron A, Arnason JT, Reid LM, Souto XC, Malvar RA. Putative role of pith cell wall phenylpropanoids in Sesamia nonagrioides (Lepidoptera: Noctuidae) resistance. J Agric Food Chem. 2006;54(6):2274–9.
Reid LM, Morrison MJ, Zhu X, Jindal KK, Ma BL. High stalk sugar corn: A potential biofuel crop for Canada. Agron J. 2015;107(2):475–85.
Martínez Fernández A. Los pastos: nuevos retos, nuevas oportunidades. Vol. 43, Pastos: Revista de la Sociedad Española para el Estudio de los Pastos. 2013. 47–48 p.
Mélida H, Encina A, Álvarez J, Acebes JL, Caparrós-Ruiz D. Unraveling the biochemical and molecular networks involved in maize cell habituation to the cellulose biosynthesis inhibitor dichlobenil. Mol Plant. 2010;3(5):842–53.
Updegraff DM. Semimicro determination of cellulose inbiological materials. Anal Biochem. 1969;32(3):420–4.
Dische Z. Color reactions of carbohydrates. In: Whistler, R.L. and Wolfrom MLE, editor. Methods in carbohydrate chemistry, Vol1. New York: Academic Press; 1962. p. 475–514.
Dubois M, Gilles K, Hamilton J, Rebers P, Smith F. Colorimetric method for determination of sugars and related substances. Anal Chem . 1956;28(3):350–6.
Blumenkrantz N, Asboe-Hansen G. New method for quantitative determination of uronic acids. Anal Biochem. 1973;54(2):484-489.
Jones L, Milne JL, Ashford D, McQueen-Mason SJ. Cell wall arabinan is essential for guard cell function. Proc Natl Acad Sci U S A. 2003;100(20):11783–8.
Dence CW. The Determination of Lignin. 1992;33–61.
Barros J, Escamilla-Trevino L, Song L, Rao X, Serrani-Yarce JC, Palacios MD, et al. 4-Coumarate 3-hydroxylase in the lignin biosynthesis pathway is a cytosolic ascorbate peroxidase. Nat Commun . 2019;10(1):1–11.
Santiago R, López-Malvar A, Souto C, Barros-Ríos J. Methods for Determining Cell Wall-Bound Phenolics in Maize Stem Tissues. J Agric Food Chem. 2018;66(5):1279–84.
Waldron KW, Parr AJ, Ng A, Ralph J. Cell wall esterified phenolic dimers: Identification and quantification by reverse phase high performance liquid chromatography and diode array detection. Phytochem Anal. 1996;7(6):305–12.
Shenk JS, Westerhaus MO. Routine operation, calibration, development and network system management manual. NIRSystems Inc., Silver Spring, MD, USA.; 1995.
Van Soest PJ, Robertson JB. Analysis of forages and fibrous foods. Cornell Un. 1985.
Goering HK, Van Soest PJ. Forage fiber analysis. In: Agricultural handbook no379. US Department of Agriculture, Washington, DC,; 1970. p. 1–20.
Gomez LD, Whitehead C, Barakate A, Halpin C, McQueen-Mason SJ. Automated saccharification assay for determination of digestibility in plant materials. Biotechnol Biofuels . 2010;3(1):23.
Tilley JMA, Terry RA. a Two‐Stage Technique for the in Vitro Digestion of Forage Crops. Grass Forage Sci. 1963;18(2):104–11.
Alexander RH, McGowan M. The routine determination of in vitro digestibility of organic matter in forages‐an investigation of the problems associated with continuous large‐scale operation. Grass Forage Sci. 1966;21(2):140–7.
SAS/STAT; SAS Institute Inc.: Cary, NC, 2007.
Marriott PE, Gómez LD, Mcqueen-Mason SJ. Unlocking the potential of lignocellulosic biomass through plant science. New Phytol. 2016;209(4):1366–81.
Carpita NC, Mccann MC. Biochemistry and molecular biology of plants. Buchanan. 2000;52–108.
Barros-Rios J, Santiago R, Malvar RA, Jung HJG. Chemical composition and cell wall polysaccharide degradability of pith and rind tissues from mature maize internodes. Anim Feed Sci Technol . 2012;172(3–4):226–36. Available from: http://dx.doi.org/10.1016/j.anifeedsci.2012.01.005
Grabber JH, Ralph J, Lapierre C, Barrière Y. Genetic and molecular basis of grass cell-wall degradability. I. Lignin-cell wall matrix interactions. Comptes Rendus - Biol. 2004;327(5):455–65.
López-Malvar A, Butrón A, Samayoa LF, Figueroa-Garrido DJ, Malvar RA, Santiago R. Genome-wide association analysis for maize stem Cell Wall-bound Hydroxycinnamates. BMC Plant Biol. 2019;19(1):1–12.
Krakowsky MD, Lee M, Coors JG. Quantitative trait loci for cell-wall components in recombinant inbred lines of maize (Zea mays L.) I: Stalk tissue. Theor Appl Genet. 2005;111(2):337–46.
Barrière Y, Méchin V, Lefevre B, Maltese S. QTLs for agronomic and cell wall traits in a maize RIL progeny derived from a cross between an old Minnesota13 line and a modern Iodent line. Theor Appl Genet. 2012;125(3):531–49.
Courtial A, Méchin V, Reymond M, Grima-Pettenati J, Barrière Y. Colocalizations Between Several QTLs for Cell Wall Degradability and Composition in the F288 × F271 Early Maize RIL Progeny Raise the Question of the Nature of the Possible Underlying Determinants and Breeding Targets for Biofuel Capacity. Bioenergy Res. 2014;7(1):142–56.
Bunzel M, Allerdings E, Ralph J, Steinhart H. Cross-linking of arabinoxylans via 8-8-coupled diferulates as demonstrated by isolation and identification of diarabinosyl 8-8(cyclic)-dehydrodiferulate from maize bran. J Cereal Sci. 2008;47(1):29–40.
De Ruiter JM, Burns JC. Characterization of Trifluoroacetic Acid Hydrolyzed Subtropical Forage Grass Cell Walls. J Agric Food Chem. 1987;35(3):308–16.
Ralph J, Bunzel M, Marita JM, Hatfield RD, Lu F, Schatz PF, et al. Peroxidase-dependent cross-linking reactions of p -hydroxycinnamates in plant cell walls. Phytochem Rev . 2004;3(1–2):79–96.
Grabber JH, Ralph J, Lapierre C, Barrière Y. Genetic and molecular basis of grass cell-wall degradability. I. Lignin-cell wall matrix interactions. Comptes Rendus - Biol. 2004;327(5):455–65.
Barrière Y, Ralph J, Méchin V, Guillaumie S, Grabber JH, Argillier O, et al. Genetic and molecular basis of grass cell wall biosynthesis and degradability. II. Lessons from brown-midrib mutants. Comptes Rendus - Biol. 2004;327(9–10):847–60.
Krakowsky MD, Lee M, Holland JB. Genotypic correlation and multivariate QTL analyses for cell wall components and resistance to stalk tunneling by the European corn borer in maize. Crop Sci. 2007;47(2):485–90.
Terra WR, Valentin A, Santos CD. Utilization of sugars, hemicellulose, starch, protein, fat and minerals by Erinnyis ello larvae and the digestive role of their midgut hydrolases. Insect Biochem. 1987;17(8):1143–7.
Barros-Rios J, Santiago R, Jung HJG, Malvar RA. Covalent cross-linking of cell-wall polysaccharides through esterified diferulates as a maize resistance mechanism against corn borers. J Agric Food Chem. 2015;63(8):2206–14.
Ralph J, Hatfield RD, Quideau S, Helm RF, Grabber JH, Jung HJG. Pathway of p-Coumaric Acid Incorporation into Maize Lignin As Revealed by NMR. J Am Chem Soc. 1994;116(21):9448–56.
Kishimoto T, Uraki Y, Ubukata M. Easy synthesis of β-O-4 type lignin related polymers. Org Biomol Chem. 2005;3(3):1067–73.
Zhao Q, Wang H, Yin Y, Xu Y, Chen F, Dixon RA. Syringyl lignin biosynthesis is directly regulated by a secondary cell wall master switch. Proc Natl Acad Sci U S A. 2010;107(32):14496–501.
Ma QH, Zhu HH, Qiao MY. Contribution of both lignin content and sinapyl monomer to disease resistance in tobacco. Plant Pathol. 2018;67(3):642–50.
Jung HJG, Samac DA, Sarath G. Modifying crops to increase cell wall digestibility. Plant Sci . 2012;185–186:65–77.
Silverstein RA, Chen Y, Sharma-Shivappa RR, Boyette MD, Osborne J. A comparison of chemical pretreatment methods for improving saccharification of cotton stalks. Bioresour Technol. 2007;98(16):3000–11.
Hatfield RD, Wilson JR, Mertens DR. Composition of cell walls isolated from cell types of grain sorghum stems. J Sci Food Agric. 1999;79(6):891–9.
Lapierre C, Jouin D, Monties B. On the molecular origin of the alkali solubility of Gramineae lignins. Phytochemistry. 1989;28(5):1401–3.
Ralph J, Guillaumie S, Grabber JH, Lapierre C, Barrière Y. Genetic and molecular basis of grass cell-wall biosynthesis and degradability. III. Towards a forage grass ideotype. Comptes Rendus - Biol. 2004;327(5):467–79.
Chabannes M, Barakate A, Lapierre C, Marita JM, Ralph J, Pean M, et al. Strong decrease in lignin content without significant alteration of plant development is induced by simultaneous down-regulation of cinnamoyl CoA reductase (CCR) and cinnamyl alcohol dehydrogenase (CAD) in tobacco plants. Plant J. 2001;28(3):257–70.
Liu T, Williams DL, Pattathil S, Li M, Hahn MG, Hodge DB. Coupling alkaline pre-extraction with alkaline-oxidative post-treatment of corn stover to enhance enzymatic hydrolysis and fermentability. Biotechnol Biofuels. 2014;7(1):1–12.
Wolf DP, Coors JG, Albrecht KA, Undersander DJ, Carter PR. Forage quality of maize genotypes selected for extreme fiber concentrations. Crop Sci. 1993;33(6):1353–9.
Scalbert A, Monties B, Lallemand JY, Guittet E, Rolando C. Ether linkage between phenolic acids and lignin fractions from wheat straw. Phytochemistry. 1985;26(6):1359–62.
Bera AK, Ho NWY, Khan A, Sedlak M. A genetic overhaul of Saccharomyces cerevisiae 424A(LNH-ST) to improve xylose fermentation. J Ind Microbiol Biotechnol. 2011;38(5):617–26.
Saha BC, Bothast RJ. Pretreatment and enzymatic saccharification of corn fiber. Appl Biochem Biotechnol - Part A Enzym Eng Biotechnol. 1999;76(2):65–77.
Berrin JG, Juge N. Factors affecting xylanase functionality in the degradation of arabinoxylans. Biotechnol Lett. 2008;30(7):1139–50.
Van Eylen D, van Dongen F, Kabel M, de Bont J. Corn fiber, cobs and stover: Enzyme-aided saccharification and co-fermentation after dilute acid pretreatment. Bioresour Technol . 2011;102(10):5995–6004.
Appeldoorn MM, Kabel MA, Van Eylen D, Gruppen H, Schols HA. Characterization of oligomeric xylan structures from corn fiber resistant to pretreatment and simultaneous saccharification and fermentation. J Agric Food Chem. 2010;58(21):11294–301.
Acevedo A, Simister R, McQueen-Mason SJ, Gómez LD. Sudangrass, an alternative lignocellulosic feedstock for bioenergy in Argentina. PLoS One. 2019;14(5):1–16.
Whitehead C, Gómez LD, McQueen-Mason SJ. The analysis of saccharification in biomass using an automated high-throughput method . 1st ed. Vol. 510, Methods in Enzymology. Elsevier Inc.; 2012. 37–50 p.
Whitehead C, Ostos Garrido FJ, Reymond M, Simister R, Distelfeld A, Atienza SG, et al. A glycosyl transferase family 43 protein involved in xylan biosynthesis is associated with straw digestibility in Brachypodium distachyon. New Phytol. 2018;218(3):974–85.
Liu J, Kim JI, Cusumano JC, Chapple C, Venugopalan N, Fischetti RF, et al. The impact of alterations in lignin deposition on cellulose organization of the plant cell wall. Biotechnol Biofuels. 2016;9(1).
Torres AF, Weijde T Van Der, Dolstra O, Visser RGF, Trindade LM. Effect of Maize Biomass Composition on the Optimization of Dilute-Acid Pretreatments and Enzymatic Saccharification. 2013;1038–51.
Youngs H, Somerville C. Development of feedstocks for cellulosic biofuels. F1000 Biol Rep. 2012;4.
Flores Calvete G, González-Arráez A, Castro González J, Castro García P, Fernández Lorenzo, B Valladares Alonso J, Cardelle Campos M. Prediction of herbage and maize silages in vivo organic matter digestibility by laboratory methods. Rev Pastos. 2003;
Vadivelooa J, Fadelb JG. Compositional analyses and rumen degradability of selected tropical feeds. 1992;37.
Capper BS. Genetic variation in the feeding value of cereal straw. Anim Feed Sci Technol. 1988;21(2–4):127–40.
Barrière Y, Méchin V, Lafarguette F, Manicacci D, Guillon F, Wang H, et al. Toward the discovery of maize cell wall genes involved in silage quality and capacity to biofuel production. Maydica. 2009;54(2–3):161–98.

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Elucidating The Multifunctional Role of The Cell Wall Components in The Maize Exploitation

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