Model for prediction of pesticide residues in soybean oil using partial least squares regression with molecular descriptors Article Swipe
Yonghong Shi
,
Fengzhong Wang
,
Hong Xie
,
Bei Fan
,
Long Li
,
Zhiqiang Kong
,
Yatao Huang
,
Zhipeng Wang
,
Daoyong Lei
,
Minmin Li
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.agrcom.2024.100053
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.agrcom.2024.100053
We developed a partial least squares regression (PLSR) model based on competitive adaptive reweighted sampling (CARS) to predict the processing factors of 54 pesticides during soybean oil processing. Characteristic variables were selected to improve the performance of the model. Four calculators were used to compute the molecular descriptors used in the model, and the model based on values computed with ChemoPy produced the best results: Rc = 0.94, RMSEc = 0.67, Rp = 0.91, and RMSEp = 0.54 for hot-pressed oil and Rc = 0.93, RMSEc = 0.73, Rp = 0.93, and RMSEp = 0.59 for cold-pressed oil. A rapid and quantitative model of processing factors was established to predict the behaviour and distribution of pesticide residues during food processing. The model was further validated using data from field-grown soybeans; it demonstrated a high correlation coefficient between predicted and measured residue concentrations (Rp > 0.93, RMSEp < 0.72) and successfully predicted the distribution and behaviour of pesticide residues. Our model provides a reference for assessing safety risk and determining the maximum residue limits for pesticides in processed products.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.agrcom.2024.100053
- OA Status
- diamond
- Cited By
- 4
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401529439
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Raw OpenAlex JSON
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https://openalex.org/W4401529439Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.agrcom.2024.100053Digital Object Identifier
- Title
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Model for prediction of pesticide residues in soybean oil using partial least squares regression with molecular descriptorsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-13Full publication date if available
- Authors
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Yonghong Shi, Fengzhong Wang, Hong Xie, Bei Fan, Long Li, Zhiqiang Kong, Yatao Huang, Zhipeng Wang, Daoyong Lei, Minmin LiList of authors in order
- Landing page
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https://doi.org/10.1016/j.agrcom.2024.100053Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.agrcom.2024.100053Direct OA link when available
- Concepts
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Partial least squares regression, Iteratively reweighted least squares, Regression, Sampling (signal processing), Regression analysis, Algorithm, Mathematics, Statistics, Computer science, Total least squares, Computer vision, Filter (signal processing)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
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2025: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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