Multifactor breakage behavior and probabilistic prediction model of maize kernel breakage under quasi-static compression

Mechanical damage to maize kernels during harvesting, transportation, and processing reduces quality and increases postharvest losses. However, the coupled effects of moisture content, kernel size, and kernel shape on breakage behavior remain insufficiently quantified, which limits damage control and process optimization. In this study, quasi-static compression tests were conducted on 3000 kernels of cultivar MY73 to identify breakage modes and to evaluate the influences of moisture content, equivalent diameter, and shape. The results indicate that maize kernel breakage occurs primarily in three modes. Bursting exhibits the highest breakage strength and energy demand, followed by split fracture and edge breakage. Moisture content is the dominant factor governing compressive failure; increasing moisture markedly reduces breakage resistance and progressively weakens the effects of size and shape. Across the classified combinations of moisture content, size, and shape, breakage probability is well described by a Weibull distribution, and the fitted parameters enable mode-specific probability prediction under arbitrary loading conditions. These findings clarify multi-factor-coupled breakage behavior of maize kernels and provide a Weibull-based probabilistic approach for predicting breakage modes, offering a methodological reference for rapid screening of crack-resistant maize varieties and for optimizing equipment and process parameters in harvesting and postharvest operations to reduce mechanical damage and improve energy efficiency in grain processing. • Identify three distinct maize kernel breakage modes with clearly different strength and energy signatures. • Reveal coupled effects of moisture, size, and shape on strength, with moisture as dominant driver. • Develop a Weibull-based model to predict kernel breakage probability under varied loading conditions. • Although strengths across breakage modes are similar, maize kernel mass-normalized energies differ significantly.

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Publication Details

Journal
Industrial Crops and Products
Published
2026-05-01
DOI
https://doi.org/10.1016/j.indcrop.2026.123374
Primary Topic
Agricultural Engineering and Mechanization
Type
article
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article

Multifactor breakage behavior and probabilistic prediction model of maize kernel breakage under quasi-static compression

Zheng Zhou, J X Zhang, Xiguang Liu, Hongmei Zhang et al.
Industrial Crops and Products
Agricultural Engineering and Mechanization
article

Multifactor breakage behavior and probabilistic prediction model of maize kernel breakage under quasi-static compression

Zheng Zhou, J X Zhang, Xiguang Liu, Hongmei Zhang, Zhe Qu, Rongbin Zhang
article en

Abstract

Mechanical damage to maize kernels during harvesting, transportation, and processing reduces quality and increases postharvest losses. However, the coupled effects of moisture content, kernel size, and kernel shape on breakage behavior remain insufficiently quantified, which limits damage control and process optimization. In this study, quasi-static compression tests were conducted on 3000 kernels of cultivar MY73 to identify breakage modes and to evaluate the influences of moisture content, equivalent diameter, and shape. The results indicate that maize kernel breakage occurs primarily in three modes. Bursting exhibits the highest breakage strength and energy demand, followed by split fracture and edge breakage. Moisture content is the dominant factor governing compressive failure; increasing moisture markedly reduces breakage resistance and progressively weakens the effects of size and shape. Across the classified combinations of moisture content, size, and shape, breakage probability is well described by a Weibull distribution, and the fitted parameters enable mode-specific probability prediction under arbitrary loading conditions. These findings clarify multi-factor-coupled breakage behavior of maize kernels and provide a Weibull-based probabilistic approach for predicting breakage modes, offering a methodological reference for rapid screening of crack-resistant maize varieties and for optimizing equipment and process parameters in harvesting and postharvest operations to reduce mechanical damage and improve energy efficiency in grain processing. • Identify three distinct maize kernel breakage modes with clearly different strength and energy signatures. • Reveal coupled effects of moisture, size, and shape on strength, with moisture as dominant driver. • Develop a Weibull-based model to predict kernel breakage probability under varied loading conditions. • Although strengths across breakage modes are similar, maize kernel mass-normalized energies differ significantly.

Industrial Crops and ProductsVol. 246
Henan Agricultural University (CN)
Affordable and clean energy
Openalex Percentile: Top 11%
Agricultural Engineering and Mechanization
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