Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (21): 4158-4174.doi: 10.3864/j.issn.0578-1752.2022.21.006

• TILLAGE ＆ CULTIVATION·PHYSIOLOGY ＆ BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Development and Application of Rapid Investigation and Analysis Platform for Agricultural and Rural Information Based on Fission Model

ZHANG Jie1(),WANG Chuan1,DONG XiaoXia1,ZHU WenQi1,YUE HuiLi1,2,LIU ShengPing1,2(),ZHOU QingBo1,2()   

  1. 1Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081
    2Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs, Beijing 100081
  • Received:2022-01-03 Accepted:2022-04-01 Online:2022-11-01 Published:2022-11-09
  • Contact: ShengPing LIU,QingBo ZHOU E-mail:zhangjie10@caas.cn;liushengping@caas.cn;zhouqingbo@caas.cn

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Abstract:

【Objective】In order to effectively solve the problems existing in the process of collecting basic information of traditional agriculture and rural areas, such as long collection period, small sample size, inaccurate delivery, low data quality and difficulty in auditing, and to achieve rapid acquisition and visual analysis of massive data under the background of emergencies, a rapid survey platform for agricultural and rural information was designed and developed, which integrated accurate questionnaire delivery, rapid data collection and automatic analysis of results, so as to provide a convenient tool for agricultural management departments at all levels to make efficient decisions. 【Method】 (1) Overall design: The platform was designed based on the 5-layer architecture technology and the concept of “Mid-Plane”, and the new media, GIS and social network analysis (SNA) were used to build a questionnaire accurate delivery model, multi-level fission model, rapid review, and automatic analysis strategies. In order to deeply mine and present the value of platform data in multiple dimensions, this research used methods such as point centrality, betweenness centrality and spatial clustering to analyze the fission relationship, diffusion capacity, and community characteristics of the questionnaire dissemination network. (2) System realization: two subsystems were developed by adopting the front-end and back-end separation mode, namely, the rapid investigation collection system for survey users, and the rapid investigation management and analysis system for the information investigators. (3) Application: VMware vSphere integrated container and cluster server were used to deploy system and Nginx load balancing to improve system response speed. 【Result】 After six months of continuous operation, the system had strong universality. It has provided 12 large-scale agricultural and rural information survey services in 8 fields and collected a total of 76 953 questionnaires; In the agricultural and rural economic information survey cases 12 243 questionnaires have been collected within 5 hours, with a fission ratio of 88.23%, of which 20.24% formed diffusion and fission. The community effect was obvious, with high degree of fission, fast speed and wide range. The platform had strong comprehensive functions, covering the functions of questionnaire design, placement control, fission sharing, intelligent judgment of papers, reward distribution, statistical analysis, user classification, etc., which could provide one-stop service for rapid investigation of agricultural and rural information.【Conclusion】The rapid investigation and analysis platform of agricultural and rural information based on fission mode had the characteristics of fast data collection, true information acquisition, more sample collection, and strong functionality. It realized the function of obtaining basic information urgently and visualizing investigation results quickly under the background of emergencies, and formed a poll mode based on huge data and different from official investigation. It could provide strong technical support for efficient decision-making of agricultural management departments, and had reference significance for the information investigation of other industries.

Key words: agricultural and rural information, quick investigation, fission mode, social network analysis, precise placement model, system design

Fig. 1

The overall structure diagram of the platform"

Fig. 2

The business process diagram of the platform"

Fig. 3

The fission flow chart"

Fig. 4

The diagram of accurate delivery model"

Fig. 5

Outdegree distribution of network points"

Table 1

The outdegree analysis of investigate network"

点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)		 点出度
OD		 占比
P(%)
0 79.76 10 0.13 19 0.04 28 0.02 62 0.02 63 0.01 167 0.01
1 11.61 12 0.12 22 0.04 34 0.02 111 0.02 66 0.01 172 0.01
2 2.99 15 0.09 35 0.04 37 0.02 24 0.01 74 0.01 175 0.01
3 1.45 14 0.06 13 0.03 40 0.02 31 0.01 84 0.01 182 0.01
4 1 17 0.06 21 0.03 41 0.02 32 0.01 97 0.01 193 0.01
5 0.60 16 0.05 23 0.03 42 0.02 43 0.01 106 0.01 209 0.01
6 0.35 18 0.05 26 0.03 45 0.02 49 0.01 107 0.01 280 0.01
8 0.19 20 0.04 27 0.03 46 0.02 50 0.01 108 0.01
7 0.18 25 0.04 33 0.03 51 0.02 55 0.01 121 0.01
9 0.18 29 0.04 36 0.03 53 0.02 58 0.01 142 0.01
11 0.15 39 0.04 44 0.03 59 0.02 61 0.01 145 0.01

Fig. 6

The ratio of betweenness centrality"

Fig. 7

The diagram of network modular distribution"

Fig. 8

The main function interface of the platform"

Fig. 9

The thematic analysis chart of autumn harvest investigation of silage corn"

Table 2

Time-consuming comparison of common methods of information survey"

阶段划分
Stage division		 传统走访式
Traditional visiting survey		 逐层上报式
Step by step escalation survey		 线上随机式
Online random survey		 裂变式
Fission survey
找到受访者
Find the interviewees		 11人各分担一省，到目的地半天，找到受访者1天
11 people each went to a province, arrived at the destination for half a day, and found the interviewees for 1 day		 群聊方式，半小时传递给11省，再2小时由省传递给访问者
Through group chat, it would be delivered to 11 provinces in half an hour, and then delivered to interviewees by the provincial administrator in 2 hours		 多人反复转发，常规2人×3天
Repeatedly forwarded by multiple people, usually 2 people×3 days		 自行传播，常规2天
Self-transmitted, routinely 2 days
问卷填写（每份问卷）
Fill out the questionnaire
(per questionnaire)		 6分钟填写，3分钟沟通，基本不可并行
6 minutes to fill out, 3 minutes to communicate, basically not parallel		 3分钟填写，可并行，但及时性很低
3 minutes to fill out, can be parallelized, but the timeliness is very low		 3分钟填写，可并行
3 minutes to fill out, can
be parallelized		 3分钟填写，可并行
3 minutes to fill out, can be parallelized
问卷审阅
Audit questionnaire		 2分钟/份
2 minutes/questionnaire		 2分钟/份，国家、省、市各审核一次，
人多时间不可控，需反复催促
2 minutes/questionnaire, the national, provincial and municipal managers would review it once, the time was uncontrollable due to the large number of people, and it needed to be repeatedly urged		 2分钟/份
2 minutes/questionnaire		 提前设置阈值，自动审核，10秒/份
Set thresholds in advance, automatic review, 10 seconds/ questionnaire
预估总耗时
Estimated total time		 11人×2.5天=27.5人天
11 people×2.5 days = 27.5 people days		 11人×1天=11人天
11 people×1 day = 11 people days		 2人×4天=8人天
2 people×4 days = 8 people days		 1人×2天=2人天
1 person×2 days = 2 people days

Table 3

Function comparison of common methods of information survey"

功能描述
Feature description		 传统走访式Traditional walk-in style 逐层上报式
Cascade reporting style		 线上随机式
Online random		 裂变式
Fissionable
电子问卷E-questionnaire √ √ √
问卷数量控制Control of the number of questionnaires √ √ √
投放地控制Placement control √ √
裂变式扩散Fissionable diffusion √
数据导出Data export √ √ √
问卷审阅Questionnaire review √ √ √ √
智能审核Smart audit √
酬劳发放Remuneration √ √
推广效果分析Promotion effect analysis √
答题统计Answer statistics √ √
问卷空间分布Spatial distribution of questionnaires √
专题分析Thematic analysis √ √
用户画像User profiling √
用户分级User classification √
用户沉淀User sedimentation √

Table 4

Platform historical survey results"

问卷名称
Questionnaire name		 指标数量
Number of indicators		 发布时间
Release
date
(Y-M-D)		 采集时长
Duration of collection		 采集数量
Number of collections		有效问卷数量
Number of valid questionnaires		问卷有效率
Questionnaire efficiency(%)		有效覆盖省数
Number of provinces effectively covered
7月农业农村经济信息调查
Agricultural and rural economic information survey in july		 21 2021-7-8 5 d 541 506 93.53 29
农业农村信息速调系统水稻调查（7月）
Agricultural and rural information rapid response system rice survey (July)		 16 2021-7-15 6 d 17794 1554 8.73 17
居民乳制品消费调查
Residential dairy consumption survey		 23 2021-9-3 5 d 7101 1056 14.87 12
农业农村信息速调系统水稻调查（9月）
Agricultural and rural information rapid response system rice survey (September)		 30 2021-9-22 8 d 3396 967 28.47 12
粮食作物秋收秋播调查
Autumn harvest and sowing survey for food crops		 20 2021-10-18 5 d 1721 452 26.26 12
2021年青贮秋收调查
Silage autumn harvest survey in 2021		 19 2021-10-23 3 d 3905 533 13.65 9
京津冀地区婴幼儿乳粉品牌选择调研
Research on brand choice of infant milk powder in Beijing, Tianjin and Hebei		 31 2021-11-9 6 d 2698 327 12.12 8
种植业产销经营中电子商务应用情况调查
Survey on the use of e-commerce in plantation production and marketing operations		 24 2021-11-29 2 d 7809 1054 13.50 31
区域蜂产业发展调查
Regional bee industry development survey		 30 2021-12-9 9 h 4001 1489 37.22 17
农业农村信息速调系统小麦调查
Survey of wheat for the agricultural rural information rapid response system		 13 2021-12-7 2.5 d 6675 721 10.80 31
水果线上线下购买习惯和价格感知调研
Research on online and offline fruit buying habits and price perceptions		 19 2021-12-17 2 h 9096 2972 32.77 31
农业农村经济信息调查
Agricultural and rural economic information survey		 29 2021-12-22 5 h 12243 2228 18.20 31
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