ArticleFoods (Basel, Switzerland)2023
Novel Grade Classification Tool with Lipidomics for Indica Rice Eating Quality Evaluation.
Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Evolution of Rice Storage Quality and Underlying Microstructural Mechanisms Under Varying Nitrogen Fertilization Application Levels.Foods (Basel, Switzerland) · 2026Article
- Lipidomic signatures reveal biomarkers of mild cognitive impairment.Translational psychiatry · 2026Article
- Impacts of Inherent Components and Nitrogen Fertilizer on Eating and Cooking Quality of Rice: A Review.Foods (Basel, Switzerland) · 2023Review
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Authors and funding
3 authors.
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Abstract
The eating quality evaluation of rice is raising further concerns among researchers and consumers. This research is aimed to apply lipidomics in determining the distinction between different grades of indica rice and establishing effective models for rice quality evaluation. Herein, a high-throughput ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight (UPLC-QTOF/MS) method for comprehensive lipidomics profiling of rice was developed. Then, a total of 42 significantly different lipids among 3 sensory levels were identified and quantified for indica rice. The orthogonal partial least-squares discriminant analysis (OPLS-DA) models with the two sets of differential lipids showed clear distinction among three grades of indica rice. A correlation coefficient of 0.917 was obtained between the practical and model-predicted tasting scores of indica rice. Random forest (RF) results further verified the OPLS-DA model, and the accuracy of this method for grade prediction was 90.20%. Thus, this established approach was an efficient method for the eating grade prediction of indica rice.
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