Cellulose Crystallinity in Orange Biomass-Derived Cellulose: Comparative Assessment by FT-IR, Solid-State 13C NMR, and X-Ray Diffraction
Year: 2026
Type: article
Abstract: Reliable determination of cellulose crystallinity is essential for biomass valorization, yet commonly used analytical methods may respond differently to residual non-cellulosic components present in partially purified lignocellulosic materials. In this study, fourteen cellulose-rich samples were produced from depectinated orange biomass under controlled alkaline processing conditions and characterized by Fourier-transform infrared spectroscopy (FT-IR), solid-state 13C nuclear magnetic resonance (CP/MAS 13C NMR), and X-ray diffraction (XRD). Crystallinity indices (CIs) were calculated using the lateral order index (FT-IR), C4 peak deconvolution (ssNMR), and the Segal method (XRD), while principal component analysis was employed to support multivariate interpretation of the FT-IR and NMR datasets. FT-IR-derived CIs ranged from approximately 65 to 91%, with the starting biomass exhibiting the highest value despite its substantial residual pectin content. In contrast, ssNMR-derived CIs were consistently lower (approximately 27–49%) and showed limited sensitivity to residual pectin, indicating greater selectivity toward cellulose crystalline organization. XRD produced intermediate CI values and displayed a moderate positive correlation with ssNMR (r = 0.5) but a moderate negative correlation with FT-IR (r = −0.5). PCA further revealed that pectin-associated FT-IR bands (~1737 and ~1635 cm−1) were the primary drivers separating the starting biomass from the purified cellulose samples. The study establishes a practical framework for selecting crystallinity evaluation methods during the sustainable valorization of citrus biomass into cellulose-based materials.
Source: Molecules
Language: English
Subfield: Biomaterials
Field: Materials Science
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W7223676869
