Forecasting and Estimation of Rice Production in Japan. May 2016

Transcription

1 Forecasting and Estimation of Rice Production in Japan May 2016

2

3

4 Major Rice Producing Region 1

5 Weather Condition(Niigata Prefecture) (mm) Precipitation Average Temperature ( ) Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Rice Growing Period 2 0

6 Planted Area and Production of Rice (10 thousand t) Planted Area Production (thousand ha )

7 Change in Production of Main Crops (10 thousand t) Rice Wheat Soybean Sweet Potato

8 Outline of the Rice Production Survey 1 Purpose of the Survey The result of survey is used as reference materials in order to implement agricultural measures Main Use Set the guideline regarding stabilization of supply, demand and prices of staple food and forecast rice supply and demand, based on Act on Stabilization of Supply, Demand and Prices of Staple Food Set the target volume of rice production and evaluate its achievement Calculate grants for farmers whose income was reduced Calculate the standard yield of the mutual relief policy based on Act on Compensation for Agricultural Loss 5

9 Outline of Rice Production Survey 2 Organization HQ of MAFF Regional Agricultural Administration Office (9) Branch Office (51) 6

10 Outline of Rice Production Survey 3 Basic Idea for Calculating Production Value to be Surveyed :Rice Yield per 10 a Planted Area Yield per 10 a = Production Forecasting method of yield in each survey period (Before Harvest) Forecasted by Multiple Regression Model (Harvest Season) Estimated by Weight of Sample 7

11 Outline of Rice Production Survey 4 Rice Planted Area Survey Satellite Images Meshing of Images Select Samples Utilize web delivery service of private company All images was taken before 2 or 3 years and automatically updated Import satellite images into GIS Divide it into 4 ha meshes Add information such as strata to each mesh Total approx. 285 million mesh Select 40,000 sample mesh 8

12 Outline of Rice Production Survey 5 Rice Planted Area Survey Objective Survey Enumerators survey utilization of land based on satellite images and measure area by GIS Estimation of Results Estimate rice planted area by strata Survey Sheet xi A= Y r yi Estimated Area Estimated Area Surveyed Area of Sample 標本の現況見積り面積推定面積 = 全単位区の台帳面積 Area on 標 Land 本の Register 台帳面 of 積 Sample Area on Land Register of All Meshes 台帳補正率 9

13 Outline of Rice Production Survey 6 Main Points of the Survey 1 Random Sampling 2 Objective Survey corresponding to Rice Growth 3 Forecast and Estimation by use of Surveyed Data 8

14 Outline of Rice Production Survey 7 Survey Period and Publishing Items C ro p C o n d itio n s S u rv e y J u l. A u g. S e p t. F o re c a st S u rv e y ( O c t.) F in a l ( N o v.) G ro w in g C o n d itio n s P la n t L e n g th N u m b e r o f S te m s C ro p C o n d itio n s M a in P u b lish e d Ite m s N u m b e r o f E a rs N u m b e r o f G ra in s p e r a E a r N u m b e r o f G ra in s p e r 1 m2 R ip e n in g C o n d itio n Forecast P la n te d A re a Y ie ld p e r 1 0 a re (fo re c a st) P ro d u c tio n (fo re c a st) Y ie ld p e r 1 0 a re P ro d u c tio n :Southwestern Area :Early Region :Late Region :All Prefectures 9

15 Outline of Rice Production Survey 8 Growing Conditions and Crop Conditions Text information to evaluate growing conditions and crop conditions by 5 categories G row in g C on d ition s E valu ation S tan d ard C rop C on d ition s E valu ation S tan d ard Very Poor Poor Fair Good Excellent Evaluate growing conditions in early stage based on plant length, number of stems and so on Very Poor Poor Fair Good Excellent less than more than106 Evaluate crop conditions by ratio of forecasted yield to normal yield 10

16 Survey Method 1 Sampling Sample Unit Sample Field The total area of Japan is divided into a grid of 200m x 200m square, which is defined as a land unit. Of all units, those containing paddy fields are defined as population. Of the population, approx. 10,000 land units are randomly selected as sample units. In each selected sample unit, a paddy field is randomly selected as sample fields. Sample Area In each sample field, 3 areas are randomly selected as sample areas in diagonal line by using a table of random numbers. 11

17 Survey Method 2 Survey Items C ro p C o n d itio n S u rvey F o recast S u rvey F in al J u ly A u gu st S ep tem b er O cto b er N o vem b er S eed in g C o n d itio n P lan tin g C o n d itio n P lan t L en gth N u m b er o f P lan ts/s tem s H ead in g an d F lo w erin g C o n d itio n R ice C u ltivatio n T ech n o lo gy N u m b er o f E ars N u m b er o f G rain s R ip en in g C o n d itio n D am age C o n d itio n T ran sp lan tin g M eth o d C h an ge in V ariety F ertilizatio n C o n d itio n P est C o tro ls itu atio n H arvestin g M eth o d W eigh t o f S am p le O n ly m ain su rvey item s are m en tion ed b ecau se d ifferen t region s h ave d ifferen t grow in g stages. Forecast 12

18 Survey Method 3 Growing Stage and Survey Period Seeding Transplanting Tillering Heading Harvesting 30 days 60 days Tillering 30 days 55 ~ 60 days Panicle Formation Booting Ripening Apr. May June July Aug. Sept. Oct. Nov. Survey Period 13

19 Survey Method 4 Objective Survey Rows and Columns To measure distance across 11 rows and between 11 plants in each 3 sample areas To calculate number of plants per 1 m2 Plant Length To measure length of plant of 5 plants in each 3 sample areas To calculate average length Number of Ears or Stems To count number of ears or stems of 10 plants In each 3 sample areas To calculate average and ears (stems) per 1m2 14

20 Survey Method 5 Objective Survey Number of Grains To count number of grains of highest ear and 2nd lowest ear in each sample plants (Number of sample plants are 3 at 1st sample area, 4 at 2nd area and 3 at 3rd area (Total 10 stocks)) To calculate number of grains per a ear and per 1 m2 Crop Cutting To cut plants in area equal to 1 m2 in each of the 3 sample areas (Total approx. 60 stocks ) To measure weight of sample grains 15

21 Survey Method 6 Basic Idea for Forecasting To break down yield into its elements To use data to be measured in the objective survey or forecasted data as each elements then to calculate yield by the formula bellow Number of Number of Number of Plants per Ears per a Grains per a 1m2 (19.4) Plant (22.2) Ear(69.1) Weight of 1000 Grains (17.5g) = Forecasted Yield (522 kg ) Number of Grains per 1 m2 (298) As we cannot use measured weight of 1000 grains for forecasting, following formula is the most reliable one. Number of grains per 1 m2 (measured) Weight of 1000 grains (forecasted) 16

22 Survey Method 7 Modeling To forecast yield in each prefecture by using their own multiple regression model To use data on the following table as predictors Each prefecture decides period of each item to be used for forecasting according to changes in varieties or cultivation technologies. (They usually stock historical data on around 30 years.) D a ta fro m O b jectiv e S u rv ey W ea th er D a ta (D a ily d a ta ) D a ta S h o w in g A n n u a l C h a n g es in Y ield L ev el N u m b er o f G ra in s p er 1 m2,n u m b er o f E a rs p er 1 m2,n u m b er o f G ra in s p er a E a r,r ip en in g ra tio,h ea d in g d a te,etc. A v era g e T em p era tu re,m a x.t em p era tu re,m in.t em p era tu re, S u n sh in e d u ra tio n,e stim a ted S o la r R a d ia tio n,d a ily T em p era tu re R a n g e,in teg ra ted V a lu e o f L o w T em p ertu re P recip ita tio n,etc. V a riety R a tio,y ield o f N o rm a ly ea r,etc. Predictors x1:number of Grains per 1 m2 x2:yield of Normal Year x3:max. Temp.(30 days before heading date) x4:daily Temperature Range (20 days after heading date) 17

23 Survey Method 8 Forecasting Accuracy Adjusted R2 should be over 0.7 In the early cultivating region (Production of this area is about 70% of national total ), R2 is over 0.8 basically Ratio of Yield to Normal Yield in Each Survey (National Total) Year Sept. Oct. Final Factors Briny wind damage Impediment in ripening by high temperature

24 Survey Method 9 Precision Aimed Precision C.V Japan A B C D E F G H I J

25 Survey Method 10 Distribution of Sample Means(Yield per 10 a: 2015) (%) Average:531 kg Under ~ ~ ~ ~ ~ ~ ~800 Over 800 ( kg ) 22

26 Further Issues Drop in Staff Numbers 1983 approx. 8, approx. 1,500 Streamlining Survey To Select Conducting Surveys corresponding to Needs To Introduce enumerator, Outsourcing, new technology (Tablet, GIS) etc. Promotion of Statistical Data (Improvement of Database etc.) Regarding rice production survey, we need to keep quality and quantity of data with streamlined method in consideration of its importance Enumerators(Introducing in Stage) Possibility to examine introduction of Remote Sensing Data in order to streamline forecast in early stage (Jul., Aug.) It s important to use not only remote sensing data but also objective survey data if we introduce this new data. 23

27 Thank You