Bench and simulation study demonstrates a centrifugal breakage index predicts harvest damage in ten rice varieties, supporting low-damage harvesting and bioprocessing quality control.
Rice ( Oryza sativa L.) produces abundant starch-rich grain biomass that can enter post-harvest industrial processing chains, such as industrial starch recovery, bioethanol production, enzymatic hydrolysis, and starch-derived bio-based materials. However, harvest-induced mechanical degradation alters the integrity and particle-size distribution of grain biomass, which can reduce raw-material uniformity and complicate downstream fractionation and conversion processes. In this study, a centrifugal impact-based method was developed to quantify the impact-induced damage response of rice grain biomass and to predict threshing-induced breakage under high-moisture harvesting conditions. A discrete element method-bonded particle model was established to analyse grain migration, impact loading, and fracture behaviour in the impact device. Simulation and bench tests showed that a guide-plate installation angle of 30° and a centrifugal disc speed of 1800 rpm provided the optimal impact condition, characterised by a stable impact environment and effective damage identification, with coefficients of variation of 10.89%, 13.24%, and 7.08% for mean velocity, maximum impact force, and maximum kinetic energy, respectively. A breakage ratio index ( BRI ) was proposed by combining the mass fractions of two distinct post-impact damage categories: completely fractured and separated grains, and damaged grains whose fractured portions remained connected by the seed coat. Higher BRI values indicated more severe impact-induced degradation. Across ten rice varieties with different moisture contents, the BRI showed good repeatability, with a maximum deviation of 4.6%. A moisture-segmented linear model was then developed to predict the mechanical threshing breakage rate from BRI , with prediction errors ranging from 3.95% to 8.41%. The proposed method provides a rapid tool for assessing harvest-induced mechanical degradation of rice grain biomass and supports low-damage harvesting, raw-material grading, and quality control for rice-based industrial processing chains.
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Xu et al. (2026) studied this question.
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