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    徐磊, 赵萌生, 陈伟志, 巴永, 张亚, 侯青叶, 陆芳芳, 钱坤. 西南红层山间盆地典型农耕区土壤-作物系统锌铜有益元素生物有效性及影响因素[J]. 中国地质. DOI: 10.12029/gc20230216002
    引用本文: 徐磊, 赵萌生, 陈伟志, 巴永, 张亚, 侯青叶, 陆芳芳, 钱坤. 西南红层山间盆地典型农耕区土壤-作物系统锌铜有益元素生物有效性及影响因素[J]. 中国地质. DOI: 10.12029/gc20230216002
    XU Lei, ZHAO Mengsheng, CHEN Weizhi, BA Yong, ZHANG Ya, HOU Qingye, LU Fangfang, QIAN Kun. Bioavailability and influencing factors of Zn and Cu beneficial elements in soil-crop system in typical farming areas of red layer intermountain basin in the southwest China[J]. GEOLOGY IN CHINA. DOI: 10.12029/gc20230216002
    Citation: XU Lei, ZHAO Mengsheng, CHEN Weizhi, BA Yong, ZHANG Ya, HOU Qingye, LU Fangfang, QIAN Kun. Bioavailability and influencing factors of Zn and Cu beneficial elements in soil-crop system in typical farming areas of red layer intermountain basin in the southwest China[J]. GEOLOGY IN CHINA. DOI: 10.12029/gc20230216002

    西南红层山间盆地典型农耕区土壤-作物系统锌铜有益元素生物有效性及影响因素

    Bioavailability and influencing factors of Zn and Cu beneficial elements in soil-crop system in typical farming areas of red layer intermountain basin in the southwest China

    • 摘要:研究目的】在滇中楚雄地区开展的土地质量地球化学调查发现了大面积富锌富铜土壤,为研究西南地区红层山间盆地富锌富铜土壤农耕区土壤—作物系统Zn、Cu等有益元素的迁移转化机制,【研究方法】本文选取滇中姚安典型农耕区为研究区,依据所获得的表层土壤、农作物籽实-根系土地球化学数据,通过分析表层土壤、作物籽实及根系土中Zn、Cu含量特征,探讨影响水稻和玉米吸收富集Zn、Cu的主控因素,建立作物Zn、Cu生物富集系数预测模型。【研究结果】结果表明:姚安平坝区表层土壤Zn、Cu含量均值为105.40mg/kg和42.67mg/kg,富锌和富铜土地(一等)面积占比分别为84.86%和90.59%,水稻籽实Zn、Cu含量均值为19.28mg/kg和2.92mg/kg,富集率为100%和70%,生物富集系数为0.20和0.07,玉米籽实Zn、Cu含量均值为21.42mg/kg和2.06mg/kg,富集率为80.00%和6.70%,生物富集系数为0.20和0.07。【结论】影响水稻和玉米籽实Zn、Cu富集的因素存在差异,主控水稻Zn、Cu生物富集系数的因素分别为Soil–Zn、N、TFe2O3和Soil-Cu、OM、S,主控玉米Zn生物富集系数的因素为Soil-Zn、SiO2/Al2O3、TFe2O3。建立滇中红层山间盆地典型农耕区水稻和玉米籽实Zn、Cu生物富集系数的多元线性回归方程,最优模型决定系数均大于0.495,水稻的预测效果优于玉米,Zn的预测效果优于Cu。预测出姚安县典型农耕区富Zn水稻、富铜水稻、富锌玉米种植面积分别为72.87km2、70.47km2和69.71km2,可优化研究区水稻和玉米种植结构规划,服务高原特色农业发展与乡村振兴战略实施。

       

      Abstract: This paper is the result of agricultural geological survey engineering. Objective A land quality geochemical survey carried out in Chuxiong area of central Yunnan Province had found a large area of zinc and copper-rich soil. The purpose of this study is to study the migration and transformation mechanism of Zn, Cu and other beneficial elements in the soil-crop system in the farming area of zinc and copper-rich red bed mountain basin in southwest China. Methods In this paper, the typical farming area of Yao'an in central Yunnan is selected as the research area. Based on the geochemical data of surface soil and crop seed-root soil, the main control factors affecting the absorption and enrichment of Zn and Cu in rice and corn are discussed by analyzing the content characteristics of Zn and Cu in surface soil, crop seed and root soil, and the prediction model of crop Zn and Cu bioconcentration coefficient is established. Results The results showed that the average Zn and Cu contents in the surface soil of Yao 'an alluvial basin are 105.40 mg/kg and 42.67 mg/kg, the proportion of zinc-rich and copper-rich land (first-class) area are 84.86% and 90.59%, the average Zn and Cu contents in rice seeds are 19.28 mg/kg and 2.92 mg/kg, the enrichment rates are 100% and 70%, and the bioconcentration coefficients are 0.20 and 0.07, the average Zn and Cu contents in corn seeds are 21.42 mg/kg and 2.06 mg/kg, the enrichment rates are 80.00% and 6.70%, and the bioconcentration coefficients are 0.20 and 0.07. Conclusions There are differences in factors affecting Zn and Cu enrichment in rice and corn seeds. The main factors controlling Zn bioconcentration coefficients in rice are Soil-Zn, N, TFe2O3, and the main factors controlling Cu bioconcentration coefficients in rice are Soil-Cu, OM and S. The main factors controlling Zn bioconcentration coefficients in corn are Soil-Zn, SiO2/Al2O3 and TFe2O3. The multi-linear regression equation of Zn and Cu bioconcentration coefficients of rice and corn seeds in the typical farming area of the red layer mountain basin in Yunnan was established, and the optimal model decision coefficient was greater than 0.495, the prediction effect of rice is better than corn, and the prediction effect of Zn is better than Cu. The optimal model predicted that the planting area of Zn-rich rice, copper-rich rice and zn-rich corn in Yao'an County are 72.87 km2, 70.47 km2 and 69.71 km2. Therefore, the planting structure planning of rice and corn in the study area can be optimized to serve the development of plateau characteristic agriculture and the implementation of rural revitalization strategy.

       

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