2022年内蒙古自治区鄂托克前旗种养生产调查数据集
收稿日期: 2023-09-02
录用日期: 2023-09-22
网络出版日期: 2024-01-05
基金资助
内蒙古自治区科技重大专项“玉米智慧生产模式创新与无人农场示范”(2021ZD0046);中央高校基本科研业务费专项资金资助项目(2662021JC002)
Dataset of Survey on Cultivation Production in Otog Front Banner, Inner Mongolia Autonomous Region, 2022
Received date: 2023-09-02
Accepted date: 2023-09-22
Online published: 2024-01-05
鄂托克前旗位于内蒙古自治区西部的鄂尔多斯市,由于其特殊的地理环境,形成了种植业与养殖业并存的农业生产模式。课题组对鄂托克前旗的4个镇30个村(嘎查)开展了问卷调查,收集了2022年当地农户个人及家庭的基本情况、农户的种养殖业生产经营状况、农业机械使用情况等方面的数据。形成了2022年内蒙古鄂托克前旗种养生产调查数据集,包含451个样本和163个变量。该数据集为研究种养循环情况、农业机械的投资和使用情况等提供了支撑。
数据摘要:
| 项目 | 描述 |
|---|---|
| 数据库(集)名称 | 2022年内蒙古自治区鄂托克前旗种养生产调查数据集 |
| 所属学科 | 农业经济管理 |
| 数据时间范围 | 2022年 |
| 数据地理空间覆盖 | 内蒙古自治区 |
| 数据类型与技术格式 | .dta |
| 数据库(集)组成 | 本数据集包含451条记录,共163个变量。 |
| 数据量 | 733.50 KB |
| 主要数据指标 | 样本农户个体基本特征、样本农户家庭基本特征、样本农户玉米种植情况、样本农户养殖情况、样本农户机械拥有情况、样本农户农机服务购买情况 |
| 数据可用性 | CSTR:17058.11.sciencedb.agriculture.00053 DOI:10.57760/sciencedb.agriculture.00053 |
| 经费支持 | 内蒙古自治区科技重大专项“玉米智慧生产模式创新与无人农场示范”(2021ZD0046);中央高校基本科研业务费专项资金资助项目(2662021JC002) |
赵雅琴, 沈思利, 张景, 陈琳 . 2022年内蒙古自治区鄂托克前旗种养生产调查数据集[J]. 农业大数据学报, 2023 , 5(4) : 144 -151 . DOI: 10.19788/j.issn.2096-6369.230419
Otog Banner is located in Ordos City in the western part of Inner Mongolia Autonomous Region, China. Due to its unique geographic environment, it has formed a mode of agricultural production in which planting and farming coexist, and is one of the important agricultural and animal husbandry production bases in China. The main agricultural activities in the area are focused on corn cultivation and sheep farming. In 2022, corn production accounted for nearly 90% of the total grain production in the flag, while sheep are the main breeding animals, accounting for nearly 90% of the total stock. In the process of agricultural production, the use of agricultural machinery improves efficiency and reduces the labor intensity of farmers. In order to better understand the local agricultural production situation and provide a strong basis for the formulation of agricultural policies, at the same time, analyzing these data can also reflect the problems in agricultural production, so as to propose effective solutions. The research group visited 30 villages (Gacha) in 4 towns of Otog Front Banner in 2022, collected the basic information of local farmers' individuals and families, the production and operation status of farmers' breeding industry, and the use of agricultural machinery. A dataset of the 2022 survey on seeding and breeding production in Otog Banner, Inner Mongolia was formed, totaling 451 samples and 163 variables. This dataset lays the foundation for studying the pathways and mechanisms that affect the farming cycle, and provides support for studying the investment and use of agricultural machinery. Moreover, these data can provide scientific basis for policy makers to formulate more scientific and reasonable agricultural policies, and promote the sustainable and healthy development of local agriculture.
Data summary:
| Item | Description |
|---|---|
| Dataset name | Dataset of Survey on Cultivation Production in Otog Front Banner, Inner Mongolia Autonomous Region, 2022 |
| Specific subject area | Agricultural economics and management |
| Time range | 2022 |
| Geographical scope | Inner Mongolia Autonomous Region |
| Data types and technical formats | .dta |
| Dataset structure | This dataset contains 451 records with 163 variables |
| Volume of data | 733.50 KB |
| Key index in dataset | Basic characteristics of individual sample farmers, basic characteristics of sample farmers' households, maize cultivation of sample farmers, breeding of sample farmers, ownership of machinery of sample farmers, purchase of agricultural machinery services of sample farmers |
| Data accessibility | CSTR:17058.11.sciencedb.agriculture.00053 DOI:10.57760/sciencedb.agriculture.00053 |
| Financial support | Inner Mongolia Autonomous Region Science and Technology Major Project "Corn Intelligent Production Mode Innovation and Demonstration of Unmanned Farms" (2021ZD0046); Fundamental Research Funds for the Central Universities (2662022JC007) |
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