Abstract

Barley is an important economical crop for food and beer industry with abundant lignocellulose residues convertible for biofuels and biochemicals. Although lignocellulose recalcitrance provides mechanic strength to maintain plant lodging resistance for biomass production, it also leads to a costly process for biofuel production. By collecting total 94 barely samples with diverse genetic backgrounds, this study examined large variations of lignocellulose levels, sugars yields and lodging index values, and further identified that the cellulose level was a crucial factor either positively accounting for biomass enzymatic saccharification or negatively affecting plant lodging resistance. Despite lignin level showed slight impact on lodging resistance, it could negatively affect biomass saccharification in barley samples examined. Regarding normal distributions of barley samples, this study generated optimal near-infrared spectroscopy (NIRS) equations applicable for rapid assessment of lignocellulose levels, sugars yields and lodging-related parameters with high determination coefficients for external validation (0.71–0.97), cross-validation (0.89–0.95) and calibration (0.89–0.95), and acceptable ratio performance deviation (2.85–4.35). Notably, the established NIRS models could be employed for selection of the desirable barley samples that are simultaneously of better lodging resistance and higher biomass saccharification. Therefore, this study has established a powerful approach applicable for both rapidly screening lignocellulose-related traits in crop breeding and precisely selecting the ideal lignocellulose substrates for green-like biomass process into cost-effective biofuels and value-added bioproducts.

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