ArticleFrontiers in plant science2025
Leaf physiological characteristics and grain quality analysis of different types of quinoa-a case study of Shanxi Province, China.
Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Integrating electrical parameters with agronomic, yield, and quality traits for screening superiorPlant signaling & behavior · 2026Article
- Functional study of the AfRAP2 gene in Amorpha fruticosa L. tolerance to saline-alkali and drought stress.BMC plant biology · 2026Article
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Abstract
This study used Q77 as a control to measure the proline content, CAT activity, soluble sugar content and MDA content of three drought-resistant and four non-drought-resistant quinoa varieties at different growth stages, to screen quinoa varieties suitable for planting in alpine regions and for the development of functional foods. Yield and quality were determined after harvesting the grain. The results showed that the yields of Qing1 and Long4 were 27.25% and 21.42% higher than the control, respectively. Both varieties had higher average proline, CAT and soluble sugar contents than the control. Qing1 showed increases of 33.56%, 38.95% and 25.06% respectively, while Long4 showed increases of 29.01%, 40.05% and 22.35%. Their MDA content was 20.6% and 9.41% lower than the control, respectively. Gong8 ranked third in terms of yield (+6.14%), demonstrating strong physiological activity and good quality. B-16 had the best quality: its starch content was approximately 20 percentage points lower than that of corn; its fat content was 10.47 percentage points lower than that of wheat; its protein content was 69.47% higher than that of rice; its dietary fibre content was 48.67 times higher than that of rice; and its essential amino acid content was 1.86 g/100 g higher than that of rice. Correlation analysis revealed that yield was extremely significantly positively correlated with the number of effective branches, main panicle length and 1000-grain weight, with the number of effective branches showing the strongest correlation. Path analysis indicated that MDA content, proline content, CAT activity and soluble sugar content positively affected yield, with proline content contributing the most based on direct path coefficients. In conclusion, Qing1 and Long4 are suitable for large-scale planting in alpine regions, B-16 is primarily suitable for functional food research and development, and Gong8 is suitable for both large-scale planting and functional food development.
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