“…Similarly, it has been suggested that plant element stoichiometry could reflect the environment more than genotype ( Ågren & Weih, 2012 ). A control experiment on peanuts also revealed that the effect of the subregion on elemental contents was larger than that of variety ( Zhao & Yang, 2022 ). Fig.…”
Section: Resultsmentioning
confidence: 92%
“…In addition, how the SIRs and elements in Chinese yams (Tiegun) react to different environmental factors has also been investigated. SIRs such as δ 13 C, δ 15 N, δ 2 H, and δ 18 O in plants are largely correlated with climate and soil factors at large geographical scales ( Xiong et al, 2022 , Yoneyama et al, 1998 ), while multielement fingerprints are more correlated with the soil background, which is thought to be heterogeneous ( Hao et al, 2021 , Zhao and Yang, 2022 ). Consequently, the cause of the variation in SIRs and elemental characteristics in Chinese yams (Tiegun) from different regions was investigated.…”
“…Similarly, it has been suggested that plant element stoichiometry could reflect the environment more than genotype ( Ågren & Weih, 2012 ). A control experiment on peanuts also revealed that the effect of the subregion on elemental contents was larger than that of variety ( Zhao & Yang, 2022 ). Fig.…”
Section: Resultsmentioning
confidence: 92%
“…In addition, how the SIRs and elements in Chinese yams (Tiegun) react to different environmental factors has also been investigated. SIRs such as δ 13 C, δ 15 N, δ 2 H, and δ 18 O in plants are largely correlated with climate and soil factors at large geographical scales ( Xiong et al, 2022 , Yoneyama et al, 1998 ), while multielement fingerprints are more correlated with the soil background, which is thought to be heterogeneous ( Hao et al, 2021 , Zhao and Yang, 2022 ). Consequently, the cause of the variation in SIRs and elemental characteristics in Chinese yams (Tiegun) from different regions was investigated.…”
“…The highest coefficient of variation was 55.55% in Mn, while the lowest was 10.98% in K. The average coefficient of variation for the remaining 11 elements was 35.67%. The wild Idesia polycarpa from different sub-regions owned unique mineral element content; it was also observed in peanuts (Zhao and Yang, 2022), soybeans (Enengl et al, 2022), and red pepper (Hur et al, 2023). The large variation in elemental content among individuals indicates that there are large differences in carbon skeleton formation, nutrient accumulation, and physiological metabolism (Martino et al, 2018;Rashid et al, 2021;Wu et al, 2023) of wild Idesia polycarpa plant cells, and this variation underlies the differences in protein, cellulose, fatty acids, tocopherols, sterols, flavonoids, and polyphenols contents among wild Idesia polycarpa species.…”
Section: Mineral Element Contents Of Idesia Polycarpamentioning
Idesia polycarpa is a good source of high-quality vegetable oil and can potentially alleviate pressure on the supply of edible oil. Exploring Idesia polycarpa could enrich the world’s food and oil resources and make up for the shortage of vegetable oil types and production. Here, 15 varieties of wild Idesia polycarpa from major wild Idesia polycarpa resource belts in the middle and upper reaches of the Yangtze River in China were investigated to elucidate the quality and antioxidant activity of wild Idesia polycarpa fruits to tap the potential exploitation capacity of Idesia polycarpa. In this study, wild Idesia polycarpa varieties with high oil quality and antioxidant activity were screened by the comprehensive evaluation of 42 indexes including oil content, dry basis white grain weight, fatty acids, tocopherols, total flavonoids, and minerals, as well as comparisons of free radical scavenging of 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS)) and 1,1-diphenyl-2-picrylhydrazyl (DPPH). The result showed the quality characteristics of 15 wild Idesia polycarpa: oil (MN:29.21/100 g), dry basis white grain weight (MN:17.32 g), total flavonoids (MN:27.27 RE/kg), total polyphenols (MN:159.63 GAE/kg), tocopherols [MN:356.10 mg/kg (α-tocopherol (MN:284.96 mg/kg), γ-tocopherol (MN:50. 20 mg/kg), β-tocopherol (MN:9.54 mg/kg), and δ-tocopherol (MN:11.40 mg/kg)], total mineral content (MN:25653.44 mg/kg), and fatty acids [MN:20.89/100 g (70.42% polyunsaturated fatty acids (MN:14.63/100 g), 20.29% saturated fatty acids (MN:4.25/100 g), and 9.29% monounsaturated fatty acids (MN:2.01/100 g)]. Correlation analysis revealed that flavonoids, C16:0, C18:1n9c, C18:2n6c, polyphenols, α-tocopherol, δ-tocopherol, and Ca were significantly correlated with DPPH and ABTS. Cluster analysis and principal component analysis classified the 15 wild samples into three clusters, with the first cluster represented by H8, H6, and H9 being the optimal sample as a woody oilseed crop, the second cluster represented by H10, H 12, and H11 being the optimal sample for functional oil development, and the rest could be selected with emphasis when conducting certain characteristic product development. The excellent lipids and rich nutritional and antioxidant properties suggest that Idesia polycarpa will be a new direction for the development of edible oil resources in the future.
“…Mineral elements play a crucial role in the metabolism of living organisms, and organisms cannot synthesize them on their own. Instead, they must absorb these elements from the external environment, such as soil and water [35,36]. The mineral element composition of the soil varies from region to region, leading to variations in the mineral element content of tea cultivated in different regions.…”
Section: Analysis Of the Correlation Of Soil Factors With Biochemical...mentioning
In order to find out the differences in tea quality characteristics from different regions and the reasons for their formation, 32 biochemical components, 22 mineral elements, and 3 stable isotope ratios were determined in 93 white leaf tea (WLT) samples. The findings revealed that significant differences in the content of free amino acids, catechins, caffeine, several mineral elements, and stable isotope ratios were observed among the WLT samples of different origins. Furthermore, a Pearson correlation analysis showed significant correlations of 15 chemical composition qualities and 14 mineral elements with soil factors. The δ13C and δ18O values were significantly correlated with meteorological factors. Classification models based on multiple chemical signatures facilitated successful differentiation of WLT of different origins, achieving a high prediction accuracy of over 90%. This study comprehensively identified distinct quality characteristics of WLT from different regions in China and proved an effective method in classifying WLT samples from the main production areas.
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