Abstract
The drying process is a critical step in determining the quality of safflower (Carthamus tinctorius L.). This study aims to systematically evaluate the effects of different drying methods on the chemical composition, color, morphology, odor, and microstructure of safflower dried petals, and to establish a comprehensive quality evaluation model for safflower based on machine learning. The results showed that drying methods significantly altered the chemical composition of safflower. Freeze-dried samples exhibited significantly higher levels of the active components hydroxysafflower yellow pigment A and anhydrosafflower yellow pigment B compared to other methods (p < 0.05), presenting a bright orange color and a mild odor. Microscopic structure and morphological analysis indicate that freeze-dried safflower effectively preserves its morphological characteristics, with a clear arrangement of cells and lower overall shrinkage. Based on nineteen quality parameters, nine quality evaluation models for safflower were constructed. The multiclassification decision forest model achieved a prediction accuracy of 89.1%. The importance analysis of quality parameters revealed that the B, G, and R color features in the RGB color mode are the most critical indicators for evaluating safflower quality. This study provides key basis for optimizing the drying process of safflower. The comprehensive evaluation model established provides a technical foundation for intelligent evaluation and standardized control of safflower quality, which is of significant practical value for improving safflower quality and promoting the standardized development of the industry.
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Claims 6
Claim · model-written summary
Drying methods significantly altered the chemical composition of safflower.
- Taxon
- Carthamus tinctorius L.
Carthamus tinctoriuse1 - Treatment
- drying methodse0
- Outcome
- chemical compositione0
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“drying methods significantly altered the chemical composition of safflower”
e1“safflower (Carthamus tinctorius L.)”
Claim · model-written summary
Freeze-dried safflower had significantly higher hydroxysafflower yellow pigment A and anhydrosafflower yellow pigment B than other methods.
- Taxon
- Carthamus tinctorius L.Carthamus tinctoriuse1
- Treatment
- Freeze-driede0
- Compound
- hydroxysafflower yellow pigment Ae0
- Outcome
- hydroxysafflower yellow pigment A and anhydrosafflower yellow pigment Be0
- Direction
- highere0
- Comparator
- other methodse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Freeze-dried samples exhibited significantly higher levels of the active components hydroxysafflower yellow pigment A and anhydrosafflower yellow pigment B compared to other methods (p < 0.05)”
e1“safflower (Carthamus tinctorius L.)”
Claim · model-written summary
Freeze-dried safflower presented a bright orange color and a mild odor.
- Taxon
- Carthamus tinctorius L.Carthamus tinctoriuse1
- Outcome
- bright orange color and a mild odore0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“presenting a bright orange color and a mild odor”
e1“safflower (Carthamus tinctorius L.)”
Claim · model-written summary
Freeze-dried safflower preserved morphological characteristics, with clear cell arrangement and lower overall shrinkage.
- Taxon
- safflowerCarthamus tinctoriuse0
- Treatment
- freeze-driede0
- Outcome
- morphological characteristicse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“freeze-dried safflower effectively preserves its morphological characteristics, with a clear arrangement of cells and lower overall shrinkage”
Claim · model-written summary
The multiclassification decision forest model achieved 89.1% prediction accuracy for safflower quality.
Verbatim
e0“The multiclassification decision forest model achieved a prediction accuracy of 89.1%”
Claim · model-written summary
B, G and R color features in RGB mode were the most critical indicators for evaluating safflower quality.
- Taxon
- safflowerCarthamus tinctoriuse0
- Outcome
- most critical indicatorse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the B, G, and R color features in the RGB color mode are the most critical indicators for evaluating safflower quality”