Biomass recalcitrance in barley, wheat and triticale straw : Correlation of biomass quality with classic agronomical traits

The global production of cereal straw as an agricultural by-product presents a significant source of biomass, which could be used as feedstock for the production of second generation biofuels by fermentation. The production of sugars for fermentation is an important measure of straw quality and in its suitability for biofuel production. In this paper, we present a characterization of straw digestibility from a wide range of cereal. Our main objective is to evaluate the variability of fermentable sugars released from different species including wheat (Triticum durum L., Triticum aestivum L.), barley (Hordeum vulgare L.) and triticale (X Triticosecale Wittmack). To this end, we adapted a saccharification method (IAS Method) capable of detecting significant differences of released sugars between cultivars and species, while using separately another method that would serve as a control and with which we could contrast our results (CNAP method). ANOVA analyses revealed that barley has a higher saccharification potential than wheat and triticale and shows more variation between genotypes. Thus, populations derived from crosses among them such as Steptoe × Morex and OWB Dominant × OWB Recessive hold potential for the identification of genetic basis for saccharification-related traits. The correlation of glucose released between the two methods was moderate (R2 = 0.57). An evaluation of the inter- and intra- specific correlation between a number of chemical and agronomical parameters and saccharification suggests that the cell wall thickness and lignin content in straw could be used in breeding programs for the improvement of the saccharification potential. Finally, the lack of correlation between grain yield and saccharification suggests that it would be possible to make a selection of genotypes for dual purpose, low recalcitrance and grain yield

High-Throughput Phenotyping of Bioethanol Potential in Cereals Using UAV-Based Multi-Spectral Imagery

Bioethanol production obtained from cereal straw has aroused great interest in recent years, which has led to the development of breeding programs to improve the quality of lignocellulosic material in terms of the biomass and sugar content. This process requires the analysis of genotype–phenotype relationships, and although genotyping tools are very advanced, phenotypic tools are not usually capable of satisfying the massive evaluation that is required to identify potential characters for bioethanol production in field trials. However, unmanned aerial vehicle (UAV) platforms have demonstrated their capacity for efficient and non-destructive acquisition of crop data with an application in high-throughput phenotyping. This work shows the first evaluation of UAV-based multi-spectral images for estimating bioethanol-related variables (total biomass dry weight, sugar release, and theoretical ethanol yield) of several accessions of wheat, barley, and triticale (234 cereal plots). The full procedure involved several stages: (1) the acquisition of multi-temporal UAV images by a six-band camera along different crop phenology stages (94, 104, 119, 130, 143, 161, and 175 days after sowing), (2) the generation of ortho-mosaicked images of the full field experiment, (3) the image analysis with an object-based (OBIA) algorithm and the calculation of vegetation indices (VIs), (4) the statistical analysis of spectral data and bioethanol-related variables to predict a UAV-based ranking of cereal accessions in terms of theoretical ethanol yield. The UAV-based system captured the high variability observed in the field trials over time. Three VIs created with visible wavebands and four VIs that incorporated the near-infrared (NIR) waveband were studied, obtaining that the NIR-based VIs were the best at estimating the crop biomass, while the visible-based VIs were suitable for estimating crop sugar release. The temporal factor was very helpful in achieving better estimations. The results that were obtained from single dates [i.e., temporal scenario 1 (TS-1)] were always less accurate for estimating the sugar release than those obtained in TS-2 (i.e., averaging the values of each VI obtained during plant anthesis) and less accurate for estimating the crop biomass and theoretical ethanol yield than those obtained in TS-3 (i.e., averaging the values of each VI obtained during full crop development). The highest correlation to theoretical ethanol yield was obtained with the normalized difference vegetation index (R2 = 0.66), which allowed to rank the cereal accessions in terms of potential for bioethanol production.This research was partly financed by the AGL2017-83325-C4 and the AGL2011-22596 Projects (Spanish Ministry of Economy, Industry and Competitiveness – MINECO, and FEDER funds). Research of FO-G and AdC was supported by the FPI (grant BES-2012-052455) and the Juan de la Cierva Programs of the Spanish MINECO funds, respectively.Peer reviewe