首页|期刊导航|中国科学数据(中英文网络版)|陕西关中平原典型县域耕地肥力演变数据集(2011和2023年)

陕西关中平原典型县域耕地肥力演变数据集(2011和2023年)OA

A dataset of soil fertility evolution in typical farmlands of counties in the Guanzhong Plain,Shaanxi Province(2011 and 2023)

中文摘要英文摘要

耕地质量是作物高产稳产的关键因子,了解区域耕地肥力现状及变化趋势,有助于掌握农田生产的障碍因子,指导农户进行合理的田间管理,以提升土壤肥力和农田生产力.关中平原 2023年粮食产量占全省粮食总产的一半以上,对于保障全省粮食安全具有至关重要的作用.该地区测土配方施肥 2011年进入规模化应用关键节点,2023年达深化应用期,土壤肥力累积效应显现,故本数据集主要汇集 2011年和 2023 年对关中地区农户调研和耕地土壤样品采集测定数据.其中,2011年调研地点涵盖 3 市 11区县,分别为宝鸡市(扶风县、陈仓区、岐山县、眉县)、渭南市(富平县、蒲城县、临渭区)、咸阳市(武功县、三原县、兴平县、泾阳县);2023年调研地点涵盖 1 市 4 区县,为宝鸡市(扶风县、陈仓区、岐山县、眉县).所得样品由不同时间的专业人员统一处理,并采用相同方法测定.2011年测定了耕层(0-20 cm)有机碳、全磷、土壤pH、速效磷和速效钾 5项土壤指标,共计 443条数据;2023年除了以上指标外,还增加测定了耕层厚度、土壤全氮、容重、紧实度、团聚体组成(>2000 μm、250-2000 μm、53-250 μm和<53 μm)、团聚体稳定性、微生物量碳、微生物量氮、有效钙、有效镁、有效微量元素(锌、铁、铜、锰)、碱性磷酸酶、亮氨酸氨基多肽酶、β-1,4-N-乙酰氨基葡萄糖苷酶、纤维素酶、β-1,4-葡萄糖苷酶 27 项土壤指标和产量,共计 130条数据.本数据集通过实验人员自查、质控人员复核的双层数据质量控制流程,同时对不同时间点和样点数据进行规范化处理,保障了数据的准确性与可比性,可为将来进一步研究关中典型区域土壤质量的演变趋势提供资料,同时也为该地区的科学管理提供可靠的数据支撑.

Soil quality is a key factor for achieving high and stable crop yields.Understanding the current status and evolutionary trends of regional land fertility is conducive to identifying the limiting factors that hinder farmland production,guiding farmers in implementing rational field managements,and thus improving soil fertility and farmland productivity.In 2023,the grain yield of the Guanzhong Plain accounted for more than half of the total grain yield of Shaanxi Province,which plays a crucial role in ensuring the food security.In this region,recommended fertilization based on soil testing entered the key stage of large-scale application in 2011,and reached the in-depth application stage in 2023,with the cumulative effects on soil fertility becoming apparent.Therefore,this dataset compiled the data obtained from farmers'surveys and measurements of representative soil samples collected from cultivated lands in the Guanzhong region in 2011 and 2023.In 2011,the surveyed sites covered 11 counties/districts across 3 prefecture-level cities:Baoji City(Fufeng County,Chencang County,Qishan County,Mei County),Weinan City(Fuping County,Pucheng County,Linwei District),and Xianyang City(Wugong County,Sanyuan County,Xingping County,Jingyang County);while in 2023,the surveyed sites included only one prefecture-level city with 4 representative counties,namely Baoji City(Fufeng County,Chencang County,Qishan County,and Mei County).All soil samples were uniformly processed by qualified personnels at sampling period and analyzed using consistent protocols.In 2011,five soil(0-20 cm)parameters were measured,including soil organic carbon,total phosphorus,soil pH,available phosphorus and available potassium,totaling 443 data entries.In 2023,in addition to the aforementioned parameters,measurements included topsoil thickness,total nitrogen,bulk density,soil compaction,soil aggregates'composition(>2,000 μm,250-2,000 μm,53-250 μm,and<53 μm),aggregate stability,microbial biomass carbon,microbial biomass nitrogen,available calcium,available magnesium,available microelements(zinc,iron,copper,manganese),alkaline phosphatase,leucine aminopeptidase,β-1,4-N-acetylglucosaminidase,cellulase,β-1,4-glucosidase were also measured,totaling 130 data entries.This dataset adopts a two-tier data quality control process involving self-checks by qualified experimental personnel and review by quality control staff,and standardizes data across different time points and sampling sites to ensure accuracy and comparability.The dataset can provide information on the evolution trend of soil quality in typical regions of Guanzhong Plain and support scientific management of farmland in the region.

牛金璨;林小丁;王林;徐佳星;秦贞涵;刘力;张树兰;杨学云

西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100西北农林科技大学资源环境学院,陕西 杨凌 712100

关中平原土壤物理性质土壤化学性质土壤生物性质产量

Guanzhong Plainsoil physical propertiessoil chemical propertiessoil biological propertiesyield

《中国科学数据(中英文网络版)》 2026 (2)

138-150,13

科技基础资源调查专项(2021FY100502)National Science&Technology Fundamental Resources Survey Project of China(2021FY100502)

10.11922/11-6035.csd.2025.0185.zh

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