Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (14): 2859-2871.doi: 10.3864/j.issn.0578-1752.2020.14.010

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

The Methodology and Application of Agricultural Monitoring and Early Warning Model Cluster

XU ShiWei(),DI JiaYing,LI GanQiong,ZHUANG JiaYu   

  1. Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Agri-Informatics, Ministry of Agriculture and Rural Affairs/Beijing Engineering Research Center of Agricultural Monitoring and Early Warning, Beijing 100081
  • Received:2020-06-03 Accepted:2020-07-14 Online:2020-07-16 Published:2020-08-10

Abstract:

【Objective】The accurate prediction and evaluation of agricultural product supply and demand is an important manifestation for the improvement of agricultural monitoring and early warning capabilities. A multi-variety multi-link model cluster to construct that can efficiently solve analytical technical problems which are difficult to solve with single links or single models.【Method】 The methodology characterized by "factor classification decoupling, parameter conversion adaptation" for multi-variety agricultural products was proposed to build a multi-temporal dimension monitoring and early warning model cluster, which took into account the important factors of agricultural products supply and demand, namely production, consumption, trade volume, price, etc., the strong linkage among commodities, the entangled complex natural, social and economic factors, and the multivariate strong coupling, non-linear, time-varying characteristics of parameters in the model development.【Result】 The model clusters were developed covering production, consumption, trade and price for different agricultural products, based on the "factor classification decoupling, parameter conversion adaptation" methodology. These model clusters could be used to analyze and project the supply and demand situation of major agricultural products including rice, corn, wheat and meat in different spatial and temporal dimensions, and to support the generation of major agricultural products balance sheets in the China Agricultural Outlook Report. The 6-year average forecast accuracy was higher than 97%.【Conclusion】The methodology of agricultural monitoring and early warning model cluster proposed in the paper has effectively improved the solution efficiency and accuracy of agricultural product multi-variety model clusters, enhanced the systematic and intelligent analysis and projection of agricultural supply and demand. The research provided a new technical method for systematically revealing the complex characteristics of supply and demand of agricultural products in time and space, and promoting the scientific and predictable regulation of agricultural products market.

Key words: agricultural products, multi varieties, supply and demand forecast, factor classification decoupling, parameter conversion and adaptation, model cluster

Table 1

Main influencing factors to be considered in the construction of agricultural product monitoring and early warning model cluster"

模型变量 Model variable f(x) 影响因素Influence factor(xi)
生产量
Production quantity
(QP)
作物单产
Yield
气象单产
Meteorological yield
温度、日照时数、降水量等
Temperature, sunshine duration, precipitation, etc.
投入单产
Input yield
成本收益情况、费用和用工情况、化肥种子投入、科技等
Cost-benefit situation, expenses and employment situation, fertilizer and seed input, technology, etc.
管理单产
Management yield
投入政策、支持政策、保护政策、科技政策等
Input policy, support policy, protection policy, science and technology policy, etc.
收获面积
Harvested area
价格竞争面积
Price competition area
上一期投入产出效益、其他竞争农产品上一期投入产出效益、上一期种植面积等
Input-output benefits of the previous period, input-output benefits of the previous period of other competitive agricultural products, planting area of the previous period, etc.
调查面积
Survey area
调查问卷等
Questionnaire, etc.
遥感面积
Remote sensing area
NVDI植被指数、物候期等
NVDI vegetation index, phenology, etc.
畜禽产量
Livestock production
生育期因素、效益成本、管理因素、调查因素等
Fertility factors, benefit costs, management factors, survey factors, etc.
消费量
Consumption quantity (QC)
食用(口粮)消费
Food use consumption
人口数、人均收入、均衡价格等
Population, per capita income, equilibrium price, etc.
工业消费
Industrial consumption
生产价格、人均国民生产总值和工业增长率等
Production prices, GDP per capita, industrial growth rate, etc.
饲用消费
Feed consumption
畜产品产量、料肉比、饲料价格、投入品和产出品的价格
Production of livestock products, feed-to-meat ratio, feed prices, prices of inputs and outputs
种用消费
Seed consumption
播种面积、每亩种子用量
Seeded area, seed per mu
损耗
Wastage
产量、损耗系数
Production, wastage factor
贸易量
Trade (T)
进出口量
Import and export
国内外价差、关税、进出口配额、产需缺口和汇率等
Domestic and foreign price differences, tariffs, import and export quotas, production and demand gaps, exchange rates, etc.
价格
Price (P)
均衡价格指数
Equilibrium price index
生产因素、消费因素、政策因素、偶发因素等
Production factors, consumption factors, policy factors, incidental factors, etc.

Table 2

Cluster model production, consumption, price and trade general model form and variable description"

模型形式
Model form
主要变量
Main variable
主要参数
Main parameter
生产量
Production quantity (QP)
QPcrop = f (Ym, Yi, Yma, HA) QPcrop:作物产量;Ym:气象单产;Yi:投入单产;Yma:管理单产;As:收获面积
QPcrop: Production quantity of crop; Ym: Meteorological yield; Yi: Input yield; Yma: Management yield; HA: Harvested area
Ym=δ(T, S, P) T:温度;S:日照时间;P:降水量
T: Temperature; S: Sunshine duration; P: Precipitation.
δ:气象因子系数
δ: Meteorological factor coefficient
Yi=θ(CE, FE, FI) CE:成本收益因子;FE:费用和用工因素;FI:肥料投入因素
CE: Cost-benefit factors; FE: Cost and employment factors; FI: Fertilizer input factors
θ:投入因子弹性系数
θ: Input factor elastic coefficient
Yma =μ(Pol, Man) Pol:政策指数;Man:政策因素
Pol: Policy indexs; Man: Policy factors
μ:政策系数
μ: Policy coefficient
HA=ε(P, Psubs) P:作物价格指数;Psubs:竞争作物价格指数
P: Crop price index; Psubs: Competitive crop price index
ε:竞品价格指数系数
ε: Competitive price index coefficient
QPanimal = f(YLD × SL × CR) YLD:单只动物出栏活重;SL:动物出栏数量;CR:动物出栏率
YLD: Single animal slaughter live weight; SL: Number of animals slaughtered; CR: Animal slaughter rate
畜禽产量系数
Livestock production coefficient
消费量Consumption quantity (QC) QC = g(FC, IC, FEC, SEC, W) FC:食用(口粮)消费;IC:工业消费;FEC:饲用消费;SEC:种用消费;W:损耗
FC: Food use consumption; IC: Industrial consumption; FEC: Feed use consumption; SEC: Seed use consumption; W: Wastage
各消费细项系数
Coefficients of various consumption items
贸易量
Trade (T)
IM = h(QP, QC)
EX = f( QP, QC)
QP:产量;QC:消费量
QP: Production quantity; QC: Consumption quantity
产量、消费量、价格影响系数
Coefficient of influence of production, consumption, prices
价格
Price (P)
$\left\{ \overrightarrow{P}\left| \forall {{S}_{i}}(\overrightarrow{P}) \right.-{{D}_{i}}(\overrightarrow{P})=0 \right\}$ $\overrightarrow{P}$:均衡价格向量;Si:供给端价格向量;Di:需求端价格向量
$\overrightarrow{P}$: Equilibrium price vector; Si: Supply price vector; Di: Demand price vector
多产品均衡价格指数
Multi-product equilibrium price Index

Table 3

Cluster equation form of wheat monitoring and early warning model constructed by multi-factor classification decoupling technology"

预测变量
Predicted variable
模型方程形式
Model equation form
变量说明
Variable description
供需平衡
Supply- demand balance
SWT,t = DWT,t SWT:小麦总供给量 The total supply of wheat in the current period
DWT:小麦总需求量 The total demand of wheat in the current period
总供给
Supply (S)
SWT,t = QPWT,t + IMWT,t + OSWT,t QPWT:小麦生产量 Current production of wheat
IMWT:小麦进口量 Current import of wheat
OSWT:小麦期初库存 Opening stock of wheat
生产量
Production quantity
(QP)
QPWT,t = YLDWT,t × HAWT,t YLDWT:小麦单产 Wheat yield
HAWT:小麦收获面积 Wheat harvested area
单产
Yield (YLD)
YLDWT, t = w1Ym, WT, t +w2Yi, WT, t + w3Yma, WT, t Ym, WT、Yi, WT、Yma, WT:小麦气象单产、投入单产和管理单产
Current wheat meteorological yield, input yield and management yield
w1w2w3:小麦Ym、Yi、Yma单产对应的赋值系数
Corresponding value coefficients of Ym、Yi、Yma of wheat
气象单产
Meteorological yield
(Ym)
Ym, WT, t = w1YTm, WT, t + w2YSm, WT, t+ w3YPm, WT, t YTm, WTw2YSm, WTw3YPm, WT:小麦温度单因素气象单产、日照单因素气象单产以及降水量单因素气象单产
Current wheat temperature single factor meteorological yield, sunshine single factor meteorological yield and precipitation single factor meteorological yield
w1w2w3:小麦3个气象单因素模型对应的赋值系数
Corresponding value coefficients of each meteorological yield model
投入单产
Input yield
(Yi)
${{Y}_{i,WT,t}}=\log ({{\alpha }^{Yi}}+\beta _{1}^{{{Y}_{i}}}\ln {{P}_{t-1}}+\beta _{2}^{{{Y}_{i}}}\times $
$\ln CE_{t}^{\varepsilon }+\beta _{3}^{{{Y}_{i}}}\ln FE_{t}^{\varepsilon }+\beta _{4}^{{{Y}_{i}}}\ln FI_{t}^{\varepsilon })$
Pt-1:小麦上一期价格 Wheat price in the previous year
CEεt:成本收益情况因素向量 Cost-benefit factor vector
FEεt:费用和用工情况因素向量 Cost and employment factor vector
FIεt:肥料投入因素向量 Fertilizer input factor vector
管理单产
Management yield (Yma)
Yma,WT,t=(1+γtYLDWT,t
YLDWT:小麦基础单产 Wheat basic yield
γ:管理因子赋值系数 Management factor assignment coefficient
面积
Harvested area
(HA)
HAWT,t=(w1HAcompetition,t+w2HAsurvey,t+ w3HArs,t)-kADt HAcompetition:小麦价格竞争面积 Price competition area of wheat
HAsurvey:小麦调查面积 Survey area of wheat
HArs:小麦遥感面积 Remote sensing area of wheat
w1w2w3:小麦三种预测面积对应的权重系数
Corresponding value coefficients of each harvested area model
AD:小麦的成灾面积 Disaster area of current wheat
k:灾情指数,在0—1之间的一个数值,越大表示灾情越严
Disaster index, a value between 0—1, the greater the severity of the disaster
价格竞争面积
Price competition area(HAcompetition)
lnHA competition, t= α+β1lnHAcompetition,t-1+ β2lnPt-1+β3lnPsubs,t-1 HAcompetition,t-1:小麦上一期播种面积 Wheat harvested area in the previous year
Pt-1:小麦上一期价格 Wheat price in the previous year
Psubs,t-1:竞争相关性作物的上一期价格
Price of competitively related crops in the previous year
调查面积
Survey area
(HAsurvey)
$H{{A}_{survey,t}}=(\sum\limits_{i=1}^{n}{{{w}_{i}}\times H{{A}_{i,survey,t}}})\times k\times \frac{1}{r}$ HAsurvey:调查得出的某地区小麦面积 Surveyed area of wheat in a certain area
HAi,survey:某地区第i个村的小麦调查面积
Surveyed area of wheat in the i-th village in a certain area
wi:第i个村的权重 Weight of the i-th village
k:某地区调查县所有村数量与抽样框包含的所有村数量的比值
The ratio of the number of all villages in a survey county to the number of all villages included in the sampling frame in a certain area
r:国家调查县小麦面积占全省所有县小麦面积的比率
The ratio of the area of counties under national survey to the area of all counties in the province
预测变量
Predicted variable
模型方程形式
Model equation form
变量说明
Variable description
进口量
Import
(IM)
lnIMWT,t=αWT,IM+β1WT,IMlnQPWT,t+
β2WT,IMlnPWT,IM,t+β3WT,IMlnXRt
IMWT:小麦进口量 Wheat import
QPWT:小麦生产总量 Total wheat production
PWT,IM :以当地货币计价的小麦进口价格 Import prices of wheat in local currency
XR:人民币对美元汇率 RMB against the U.S. dollar
αWT,IM:小麦进口量误差项 Errors of wheat import
期初库存
Opening stock (OS)
OSWT,t= ESWT,t-1
ESWT,t-1:上一期小麦期末库存 The ending stock of wheat in the previous period
总需求
Demand (D)
DWT, t = QCWT, t + EXWT, t + ESWT, t QCWT:小麦消费量 Wheat consumption
EXWT:小麦出口量 Wheat export
ESWT:小麦期末库存 Ending stock of wheat
消费量Consumption quantity(QC)
QCWT, t = FCWT, t + ICWT, t + FECWT, t + SECWT, t + WWT, t FCWT:小麦口量消费量 Food use consumption of wheat
ICWT:小麦工业消费量 Industrial consumption of wheat
FECWT:小麦饲用消费量 Feed use consumption of wheat
SECWT:小麦种用消费量 Seed use consumption of wheat
WWT:小麦损耗 Wastage of wheat
口粮消费量
Food use consumption
(FC)
FCWT, t = PCWT, rural, t × POPWT ,rural, t + PCWT, urban, t × POPWT, urban, t PCWT, rural :农村人均小麦口量消费量 Rural per capita FC of wheat
POPWT, rural:农村总人口数 Total rural population
PCWT, urban:城镇人均口量消费量 Urban per capita FC of wheat
POPWT, urban:城镇总人口数 Total urban population
农村人均口粮消费量
Rural per capita consumption (PCrural)
PCWT,rural,t=exp(α1lnDPIWT,rural,t+
α2lnPRT, t+α3lnPWT, t+α4lnPMA,t+ α5lnPSB, t+b)
DPIWT, rural:农村人均可支配收入 Rural per capita disposable income
PRI:稻米均衡价格 Rice equilibrium price
PWT:小麦均衡价格 Wheat equilibrium price
PMA:玉米均衡价格 Corn equilibrium price
PSB:大豆均衡价格 Soybean equilibrium price
城市人均口粮消费量Urban per capita consumption (PCurban) PCWT, urban,t=exp(α1lnDPIWT,urban,t+ α2lnPRT, t+α3lnPWT, t+α4lnPMA,t+ α5lnPSB, t+b) DPIWT, urban:城镇人均可支配收入 Urban disposable income per capita
饲用消费量
Feed use consumption
(FEC)
FECWT, t = FERWT, 1×(QPPK, t + QPBV, t + QPMU, t) +FERWT, 2×QPPT, t + b QPPK:猪肉产量 Pork production
QPBV:牛肉产量 Beef production
QPMU:羊肉产量 Mutton production
QPPC:禽肉产量 Poultry production
工业消费量
Industrial consumption
(IC)
ICWT,t = exp (alnGDP + b) GDP:国内生产总值 Gross Domestic Product
种用消费量
Seed use consumption
(SEC)
SECWT, t = SPMWT, t × HAWT, t SPMWT:每亩小麦种子用量 Wheat seed dosage per acre
损耗
Wastage (W)
WWT, t = KLWWT, t ×QPWT, t KLWWT:小麦损耗率 Wheat loss rate
出口量
Export (EX)
lnEXCHN,WT,t=α1WT,EX+β1WT,EX× lnEXCHN,WT,t-1 +β2WT,EX×
ln FOBCHN,WT,t
EXCHN,WT,t:全国小麦出口量 National wheat export
EXCHN,WT,t-1:上一期全国小麦出口量 National wheat exports in the previous period
FOBCHN,WT,t:以当地货币计价的小麦离岸价格 FOB price of wheat in local currency

Table 4

Main variable parameters of model cluster and its solution"

模型主要变量
Model variable f(x)
模型方程变量系数的求解方法
Method for solving variable coefficients of model equation
产量
Production quantity
(QP)
作物单产
Yield
气象单产
Meteorological yield
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
投入单产
Input yield
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
管理单产
Management yield
历史数据、专家经验确定各系数
Historical data and expert experience determine the coefficients
综合单产
Comprehensive yield
专家人工设置和智能训练赋值各单产权重
Expert manual setting and intelligent training assign the weight of each yield
收获面积
Harvested area
价格竞争面积
Price competition area
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
调查面积
Survey area
调查数据
survey data
遥感面积
Remote sensing area
监测数据
Monitoring data
综合面积
Comprehensive area
专家人工设置和智能训练赋值各面积权重
Expert manual setting and intelligent training assign the weight of each area
畜禽产量
Livestock production
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
消费量
Consumption quantity
(QC)
食用(口粮)消费
Food use consumption
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
工业消费
Industrial consumption
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
饲用消费
Feed use consumption
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
种用消费
Seed use consumption
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
损耗
Loss
历史数据建立回归方程求解各系数
Use historical data to establish regression equations to solve coefficients
贸易量
Trade( T )
进出口量
Import and export
历史数据及专家预测
Historical data and expert forecasts
价格
Price( P )
均衡价格指数
Equilibrium price index
局部均衡模型求解
Local equilibrium model solution
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