From microstructure to multivariate prediction models: Decoding the biomechanical properties of tea stems via PLSR-Ridge regression and multifactorial orthogonal design

Efficient harvesting and field management of tea is closely related to the mechanical properties of tea stems; however, there have no research on variables and models that can be used to predict them. In this paper, the relationship between factors (number of segments, diameter, stem length, density, moisture content, moment of inertia, and fracture deflection) affecting the mechanical properties (tensile and bending strength) of tea stems was analysed using a combination of partial least squares regression and ridge regression analyses, using three tea varieties, namely, Jinxuan, Yinghong, and Liannan, as the research subjects. Ultra depth of field electron microscopy was used to aid in the interpretation of the mechanical properties. The regression fitting results showed that the R ² values of the prediction models for the tensile and flexural strengths of Jinxuan tea stems were 0.9361 and 0.9054, respectively, and the root mean square errors of prediction (RMSEP) were 0.7709 MPa and 1.9083 MPa, respectively. The R ² values of the tensile and bending strengths of Liannan tea stems were 0.9161 and 0.9240, respectively, and the RMSEP were 0.3948 MPa and 1.2973 MPa, respectively. The R ² values of Yinghong tea stems were 0.9292 and 0.9196, and the RMSEP values were 1.3207 MPa and 1.7489 MPa, respectively. The RPD of all the prediction models was greater than 3, indicating high prediction accuracy. The results of the comprehensive orthogonal test using four factors and three levels showed that the factors affecting the shear strength of tea stems were in the following order: stem segment, variety, moisture content, and shear speed. The results of the study will help to understand the biomechanical properties of tea stems, improve their resource utilisation and provide a reference for the optimal design of industrial cutting devices. • Tensile, bending, and shear tests were conducted and compared for the first time on three types of tea stems. • The microstructure of tea stems was examined to elucidate their mechanical properties. • Predictive models (PLSR and RRA) were developed to assess the mechanical properties of three types of tea stems. (Maximum R ² = 0.9361 and minimum RMSEP= 0.3948, RPD>3) • The sequence of factors influencing shear performance and the optimal combination of these factors have been identified.

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Publication Details

Journal
Industrial Crops and Products
Published
2025-05-09
DOI
https://doi.org/10.1016/j.indcrop.2025.121143
Citations
3
Primary Topic
Tree Root and Stability Studies
Type
article
Field-Weighted Citation Impact
2.14
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article

From microstructure to multivariate prediction models: Decoding the biomechanical properties of tea stems via PLSR-Ridge regression and multifactorial orthogonal design

Yingmei Chen, Jiehao Li, Yuanqiang Luo, Haoxin Li et al.
3 citations
Industrial Crops and Products
Tree Root and Stability Studies
2.14
article

From microstructure to multivariate prediction models: Decoding the biomechanical properties of tea stems via PLSR-Ridge regression and multifactorial orthogonal design

Yingmei Chen, Jiehao Li, Yuanqiang Luo, Haoxin Li, Chongyang Han, Weibin Wu, Chun Wan, Jinhong Lv
article en
3 citations

Abstract

Efficient harvesting and field management of tea is closely related to the mechanical properties of tea stems; however, there have no research on variables and models that can be used to predict them. In this paper, the relationship between factors (number of segments, diameter, stem length, density, moisture content, moment of inertia, and fracture deflection) affecting the mechanical properties (tensile and bending strength) of tea stems was analysed using a combination of partial least squares regression and ridge regression analyses, using three tea varieties, namely, Jinxuan, Yinghong, and Liannan, as the research subjects. Ultra depth of field electron microscopy was used to aid in the interpretation of the mechanical properties. The regression fitting results showed that the R ² values of the prediction models for the tensile and flexural strengths of Jinxuan tea stems were 0.9361 and 0.9054, respectively, and the root mean square errors of prediction (RMSEP) were 0.7709 MPa and 1.9083 MPa, respectively. The R ² values of the tensile and bending strengths of Liannan tea stems were 0.9161 and 0.9240, respectively, and the RMSEP were 0.3948 MPa and 1.2973 MPa, respectively. The R ² values of Yinghong tea stems were 0.9292 and 0.9196, and the RMSEP values were 1.3207 MPa and 1.7489 MPa, respectively. The RPD of all the prediction models was greater than 3, indicating high prediction accuracy. The results of the comprehensive orthogonal test using four factors and three levels showed that the factors affecting the shear strength of tea stems were in the following order: stem segment, variety, moisture content, and shear speed. The results of the study will help to understand the biomechanical properties of tea stems, improve their resource utilisation and provide a reference for the optimal design of industrial cutting devices. • Tensile, bending, and shear tests were conducted and compared for the first time on three types of tea stems. • The microstructure of tea stems was examined to elucidate their mechanical properties. • Predictive models (PLSR and RRA) were developed to assess the mechanical properties of three types of tea stems. (Maximum R ² = 0.9361 and minimum RMSEP= 0.3948, RPD>3) • The sequence of factors influencing shear performance and the optimal combination of these factors have been identified.

Industrial Crops and ProductsVol. 230
South China Agricultural University (CN), University of Hong Kong (HK)
Zero hunger
Openalex Percentile: Top 14%
Tree Root and Stability Studies
2.14
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