Multi-Beneficiary Statistical Co-operation Programme 2005 Transition Facility Multi-Beneficiary Statistical Co-operation Programme 2005 Lot 2: Pesticide Indicators Survey on Pesticide Use on Wheat Crops 2006 in Estonia Kaia Oras 16.11.2018

...history: Statistical Office of Estonia started the collection of data on the use of pesticides about a decade ago Survey was worked out as a response to the demand of Estonian Agricultural Ministry Plant Production Inspectorate and has been financed from the state budget Quantity of pesticide used - by the crop Area treated with pesticide by the crop 16.11.2018

Pesticide Usage in Estonia, 1997-2006 Kg of active substance per agricultural land hectare Statistics Estonia has carried out the pesticide use survey for a decade now but the quality of data is still a major problem. 16.11.2018

Herbicides use per hectar 16.11.2018

General data structure NUTS 4 16.11.2018

Are there a direct correlations from purely statistical viewpoint between the yield and the use of pesticides ? CEREALS Use of fungicides Production Use of herbicides Use of seed treatment preparations kg per ha, NUTS 4 16.11.2018

Extrapolation in annual survey Pesticide quantity in holding: Ph= St*Pr Extrapolated quantity: Pt = Ph *L Area sown: Sg Treated area: St Used pesticides: kg/ha Pr Extrapolated quantity: Pt Extrapolation factor: L 16.11.2018

Yearly publications on environmental indicators Dissemination of data Data on pesticides are available on Statistical Office website http://www.stat.ee/, database program PC-AXIS gives the user a possibility to download data in different formats Yearly publications on environmental indicators Environmental strategy review 16.11.2018

Use of pesticides in agriculture, 2006 kg 16.11.2018

Use of pesticides in agriculture, 2006 Kg/ha of cultivated area 16.11.2018

Transition Facility Multi-Beneficiary Statistical Co-operation Programme 2005 Lot 2: Pesticide Indicators Survey on Pesticide Use on Wheat Crops 2006 in Estonia We made the attempt to stratify on a crop type level (routine has been on a household group level) Aim to get for one crop total of active substances used with incorporated error estimations 16.11.2018

Project Time Scale April May June July Aug Sept Oct Nov Dec Sampling Questionnaire design Postal survey Telephone interviews Data entry Data analysis 16.11.2018

Sample characteristics Area group Frame Sample Routine survey Pilot study 0…1 ha 774 75 33 29 1…2 ha 543 66 26 30 2…5 ha 748 227 45 162 5…10 ha 470 238 53 165 10…20 ha 406 347 80 264 20…30 ha 191 49 142 30…50 ha 202 71 131 50…100 ha 228 107 121 > 100 ha 231 175 56 Total 3793 1805 639 1100 16.11.2018

Sampling method: simple random stratified Sampling unit is agricultural holding growing wheat. Sampling frame is the Estonian Agricultural Registers and Information Board database of agricultural supports. Frame is stratified according to area of wheat. Holdings with area greater or equal to 20 ha are surveyed completely. Holdings with wheat area less than 20 ha were divided into 5 strata as follows: Sample survey: 0-1, 1-2, 2-5, 5-10, 10-20 ha Simple random sample is drawn in each strata with different inclusion probabilities. Method of permanent random numbers is used for sample selection. Sample is designed using Neyman optimal allocation method according to variability of the area of wheat. 16.11.2018

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Reasons for non-response Not co-operative 23 Did not grow wheat 43 Incorrect contact details 70 Total number of non-response 136 16.11.2018

Sample characteristics Area group Frame Sample Responses % Imputation Weight 0…1 ha 774 75 74 98,7 12,6885 1…2 ha 543 66 62 93,9 10,4423 2…5 ha 748 227 207 91,2 4,0000 5…10 ha 470 238 217 2,3858 10…20 ha 406 347 314 90,5 1,3055 20…30 ha 191 176 92,1 1,0852 30…50 ha 202 186 1,0860 50…100 ha 228 213 93,4 15 1,0000 > 100 ha 231 220 95,2 11 Total 3793 1805 1669 92,5 16.11.2018

Compensating non-response Non-response was compensated by imputation – over 50 ha “Hot deck” imputation method Nearest neighbour as a donor Nearest neighbour is the one who has the most similar wheat area in respective geographical category (county) 16.11.2018

State of the Art Sown areas, treated areas, products used, units used, number of treatments – are checked for mistakes (more than six thousand lines in database to validate still) Checking of the databases consistency The analyses of grossed up results will start with help of ESO´s Methodological Service in Februaryr. 16.11.2018

Use of pesticides on wheat 16.11.2018

Volatility of the staff Specific problems: Volatility of the staff Quality of the data: mistakes, mistakes, mistakes 3. No proper software, 4. Difficulties in consistency of the two databases General problems: No proper vision from the policy demand side Difficult regarding motivation Expensive 16.11.2018

Some lessons learned Carry out the survey in winter Provide more channels for information delivery (e g internet) Do not correct all “mistakes”, for example over and under dose uses and the use of the several forbidden products are the case in real life 16.11.2018

Identification of the logic of the errors Results: Attempt to stratify on a crop type level (routine has been on a household group level) For one specific crop to get the total of active substances used with incorporated error estimations Identification of the logic of the errors Maping of the workload to be invested to get the similar results on all crops 16.11.2018

This study gives the possibility for production of more relevant statistics for the objective “to minimize hazards and risks to health and environment” The risk incorporation requires the binding of information what is existing on chemical compound level The bottleneck is the binding of information what is available on single compound level with the information on the use patterns. Our previously produced grossed up figures of pesticide use by pesticides types do not allow the measurement of risks. The reason is the low representation of single active substance in 16.11.2018

Treated wheat area by categories of danger 16.11.2018

Glyphosate counts for 15-50 % of herbicides used on wheat 16.11.2018

Next steps… Finalize the consistency check of the databases Reparing the mistakes Gross up analyses : error estimations for active substances Quality analyses Final report …April 30 16.11.2018

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Permanent Random Numbers (PRN) To each unit in the register we associate a random number generated from uniform distribution U(0,1) and it is not changed, it is the permanent random number (PRN). A new unit (a birth) is assigned a random number which is independent of the existing ones. Closed down unit (a death) is withdrawn from the register together with its random number. On each sampling occasion we take a new sample using PRN-s 16.11.2018

Permanent Random Numbers (PRN) Permanent random numbers allow at the same time to get samples from the up-to-date register to get a large amount of overlap with the latest sample since units have the same random numbers (PRN) on both occasions. 16.11.2018

Neyman allocation Nh – number of units in stratum h n – predetermined overall sample size nh – sample size of stratum h 16.11.2018

Comparison of sales and use The comparison of the sales and use figures. Use figures have the breakdown by plant or crop type used. The sales figures have the further breakdown by pesticides types. 16.11.2018

Reporting format categories Total area surveyed Basic area treated Average number of treatments Quantity of active substance applied Average quantity applied per treated area Average quantity applied per total cultivated area 16.11.2018

Open questions: definition of treated area Four categories listed in “Guidelines for the collection of pesticide usage statistics within agriculture & horticulture” by Miles R. Thomas: Basic area treated Application area treated Formulation area treated Active substance area treated Which of the definitions is applicable and most relevant? 16.11.2018

Use of Pesticides with Different Categories of Danger on Wheat Dangerous : * Carcinogenic, mutagenic, teratogenic, sensitising Irritant: ** Irritant, sensitising 16.11.2018