1. Variability in quality of wheat straw in terms of bio-ethanol production Jane Lindedam¹, Jacob Wagner Jensen², Sander Bruun¹, Claus Felby² and Jakob Magid¹. ¹ Plant and Soil Science Laboratory, Department of Agricultural Sciences, ² Forest & Landscape, Faculty of Life Sciences, University of Copenhagen, Denmark. The objectives are therefore T o provide information on the magnitude and causes for the variability of bio-available carbon in wheat straw cultivars. T o test near infrared reflectance (NIR) spectroscopy as a cheap and quick method to assess the potential of wheat cultivars for bio-ethanol production. How: We have yet to develop a small scale bio-ethanol assay, which includes the pre-treatment. Instead the variability of enzymatic solubility of the wheat cultivars could give us an indication of the ethanol potential. The ESOM-assay (Enzymatic Solubility of Organic Matter) correlates with the in vitro digestibility in rumen and will give us an idea of the bio-availability of the carbon. Results -120-100-80-60-40-200 4060 - -40 -20 0 40 60 80 A103 A63 A76 A92 A50 A101 A96 A49 A99 A73 A19 A17 A57 A98 A35 A53 A89 A40 A91 A12 A67 A34 A75 S60 A97 A86 S88 A74 A11 A43 A105 A85 A58 A56 A33 A104 A18 A28 A15 A60 A68 S82 S101 A14 A66 S57 A83 A54 A2 S86 A37 A41 A59 A16 S109 A87A39 A36 A78 A20 A42 S47 A55 A31 A62 A88 S110 S99 S80 S72 A84 A65 A61 A71 A23 A9 S97 S68 A25 S45 A77 A106 S58 S70 A69 A24 A47 A1 S51 A70 S48 A21 S41 A29 A90 S85 A52 A27 A94 A3 S90 A38 A95 A26 A8 A22 A13 S35 S71 S56 A46 A80 A72 A102 S89 A45 S108 S67 S53 A100 S95 A48 S59 S100 A64 A82 A93 S78 S16 A10 S55 S87 S69 A79 S46 S83 S81 S93 S32 S102 S39 S43 S98 S76 S103 S84 S64 S28 S31 S63 S38 S61 S62 A6 S66 S107 S65 A30 A32 A51 S74 S27 S73 S77 S44 S94 S24 S75 A7 S34 S25 S52 A44 S42 S50 S96 S33S92 S49 A81 A5 S21 S23 S13 S91 A4 S15 Scores PC#1 (69.493%) PCA Scores of Sejet andAbedcultivars S18 S36 S106 S26 S22 S54 S29 S14 S37 S17 S20 S19 S11 S30 S9 S12 S8 S7 S3 S6 S4 S5 S10 S2 S1 Scores PC#2 (25.553%) 2530354045 ESOM -120-100-80-60-40-200 4060 - -40 -20 0 40 60 80 A103 A63 A76 A92 A50 A101 A96 A49 A99 A73 A19 A17 A57 A98 A35 A53 A89 A40 A91 A12 A67 A34 A75 S60 A97 A86 S88 A74 A11 A43 A105 A85 A58 A56 A33 A104 A18 A28 A15 A60 A68 S82 S101 A14 A66 S57 A83 A54 A2 S86 A37 A41 A59 A16 S109 A87A39 A36 A78 A20 A42 S47 A55 A31 A62 A88 S110 S99 S80 S72 A84 A65 A61 A71 A23 A9 S97 S68 A25 S45 A77 A106 S58 S70 A69 A24 A47 A1 S51 A70 S48 A21 S41 A29 A90 S85 A52 A27 A94 A3 S90 A38 A95 A26 A8 A22 A13 S35 S71 S56 A46 A80 A72 A102 S89 A45 S108 S67 S53 A100 S95 A48 S59 S100 A64 A82 A93 S78 S16 A10 S55 S87 S69 A79 S46 S83 S81 S93 S32 S102 S39 A101 A96 A49 A99 A73 A19 A17 A57 A98 A35 A53 A89 A40 A91 A12 A67 A34 A75 S60 A97 A86 S88 A74 A11 A43 A105 A85 A58 A56 A33 A104 A18 A28 A15 A60 A68 S82 S101 A14 A66 S57 A83 A54 A2 S86 A37 A41 A59 A16 S109 A87A39 A36 A78 A20 A42 S47 A55 A31 A62 A88 S110 S99 S80 S72 A84 A65 A61 A71 A23 A9 S97 S68 A25 S45 A77 A106 S58 S70 A69 A24 A47 A1 S51 A70 S48 A21 S41 A29 A90 S85 A52 A27 A94 A3 S90 A38 A95 A26 A8 A22 A13 S35 S71 S56 A46 A80 A72 A102 S89 A45 S108 S67 S53 A100 S95 A48 S59 S100 A64 A82 A93 S78 S16 A10 S55 S87 S69 A79 S46 S83 S81 S93 S32 S102 S39 S43 S98 S76 S103 S84 S64 S28 S31 S63 S38 S61 S62 A6 S66 S107 S65 A30 A32 A51 S74 S27 S73 S77 S44 S94 S24 S75 A7 S34 S25 S52 A44 S42 S50 S96 S33S92 S49 A81 A5 S21 S23 S13 S91 A4 S15 Scores PC#1 (69.493%) PCA Scores of Sejet andAbedcultivars S18 S36 S106 S26 S22 S54 S29 S14 S37 S17 S20 S19 S11 S30 S9 S12 S8 S7 S3 S6 S4 S5 S10 S2 S1 Scores PC#2 (25.553%) 2530354045 ESOM 2530354045 ESOM Figure 1: The variation in ESOM values from the two sites Figure 2: PCA score plot of 107 genotypes of wheat straw grown at two different sites, Sejet (S) and Abed (A). Figure 3: Correlation between measured ESOM values and predicted ESOM values for all genotypes at two different sites. The ESOM-values revealed up to 30% difference in wheat straw digestibility, affected by both the type of cultivar and location (fig. 1). There was a significant correlation between the digestibilities at the two sites indicating that there is a significant effect of the cultivar. One effect of the locations was a large variation in ash-content; straw from Sejet containing twice the ash of the coherent Abed cultivar. PCA score plot of the all the cultivars showed that straw from the two locations can be distinguished on the basis of their NIR spectrum and EFOS values. Generally, straw from Sejet has higher EFOS values then from Abed (fig. 2). The PLS model made on the NIR specters could predict over 75% of the variation in ESOM-values, indicating that NIR spectroscopy is a potential easy way to forecast the straw quality of cultivars (fig. 3). Method and material 107 wheat cultivars were sampled from two different sites in Denmark and measured with ESOM assays as follows: The straw material was milled and sieved (1 mm) before soaking in pepsin acid for 24h at 40°C to dissolve protein. Additional heating to 80°C hydrolyzed the starch and inactivated the pepsin acid, after which incubation in enzyme mixture (cellulase, hemicellulase, γ-amylase, cellobiase) for 24h at 40°C then 19h at 60°C dissolved the digestible cell wall carbohydrates and starch. Fat was extracted from the residue with boiling water and acetone before dry matter and ash content of the treated straw was related to the untreated material (g dissolved/100g dm). NIR spectra were measured on all genotypes in the spectral range from 1100 nm – 2500 nm and used to make a PCA and PLS calibration model predicting the ESOM values. Outlook We are working on producing bioethanol from small samples (5-10 g dw) of the cultivars, to correlate with the NIR spectres. When a wide variaty of cultivars from multiple locations and years have been measured, the model can potentially be used as a tool for differential pricing to the farmer and batch optimized pre-processing based on genotype and environmental conditions during growth. We include historic genotypes to establish if a high genetic component for “good quality straw” is shown and evaluate if the trait may be considered a selection criterion in future cereal breeding programs. Hypothesis Wheat is not just wheat when it comes to producing bio-ethanol! The variability of bio-available carbon in wheat straw cultivars is large and potentially exploitable. Introduction The European Union (EU) has set up the goal that by the year 2010, 5.75 % of the fuels used for transportation must be produced from biomass. Ethanol produced by fermentation of C5 and C6 sugars derived from lignocellulosic biomass has in many Europeans countries been recognized as one platform to fulfill the directive. Large effort has been put into optimization of pre-treatment, enzyme and fermentation technologies of lignocellulosic biomass conversion. However, little attention has been given to differences between cultivars of the feedstock. Since soil incubations and analyses of feedstuff value indicate that there is large variability in quality of straw, this is also likely to be the case in terms of bio-ethanol production. Conclusion A 30% variability in carbon bio-availability is large enough to be highly interesting and potentially exploitable in bio-fuel production. To screen the bio-availability of carbon in a very large range of straw materials, we propose using NIR to predict the digestibility of straw.