Improving Pesticide Statistics Collection in Lithuania
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Statistics Lithuania and State Plant Protection Service collaborating to enhance pesticide data collection methods for future regulatory compliance and accurate reporting to Eurostat.
Improving Pesticide Statistics Collection in Lithuania
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Presentation Transcript
2005 Transition Facility Programme PESTICIDES USE SURVEY IN LITHUANIA DanguolėKrepštulienė, Statistics Lithuania Darius Baškys, State Plant Protection Service
OBJECTIVEOF THE PROJECT • improvement of methodology for pesticide statistics collection in the perspective of the further practical implementation of the proposed Regulation on Pesticide Statistics • consolidation of administrative networks of SatisticsLithuania and State Plant Protection Service
INVOLVED PARTIES • Statistics Lithuania (SL) is the institution organising the survey in the country. • State Plant Protection Service (SPPS) participates in the project as a partner.
ACTIONS PLANNED • Establishment of a Working Group involving specialists of SL and SPPS in the field of pesticide statistics • Implementation of Countrywide Plant Protection Usage Data Collection Survey on Winter Wheat • Participation in the workshops organized within the framework of the project • Submitting the final report and results to Eurostat
WORK TO BE CARRIED OUT BY SL • Identification of farm population for the survey • Preparation of the sampling methodology and selection of farms for the sample survey • Statistical analysis of the collected data • Evaluation of accuracy of the obtained estimates • Preparation and submission of the final report to Eurostat
WORK TO BE CARRIED OUT BY SPPS • Preparation of the sampling methodology • Designing and testing of the questionnaire • Selection and training of interviewers • Sample survey on farms using an interview mode • Checking questionable data • Data processing and analysis • Preparation of the final report
FURURE PLANS (IF PESTICIDE STATISTICSREGULATION COMES INTO FORCE • SL and SPPS have already had a joint meeting and discussions at the Ministry of Agriculture • Meeting outcomes : - to continue institutional cooperation and information exchange; • to follow pesticide regulation developments and to start actions only when regulation comes into force; • first steps if regulation comes into force: to distribute responsibilities and to find funding at national level (Government Decree).
SAMPLING METHODOLOGY • Sampling frame – IACS, farms growing wheat • Population size: N=34 533 • Sample unit – farm • Sample size - 500 farms • Startified simple random sample • Survey crop season – 2005/6
SURVEY MODE: FACE -TO-FACEINTERVIEWS • 22 State plant protection inspectors (interviewers) were trained to collect data on farms by an interview mode. • The number of interviews for each inspector is different depending on his inspection zones
- 22 State Plant Protection Inspectors interview 500 farms- The control zone for one inspector is two district municipalities
PROGRESS TO DATE • Questionnaire prepared and tested • Interviewers selected and trained • National sampling methodology prepared and farms selected • Data collection by an interview mode is in progress and will be finished in the end of September
QUESTIONNAIRE FOR PLANT PROTECTION PRODUCTS USE ON WINTER WHEAT IN 2005/6 • (Data are totally confidential and shall be used for the survey puposes in summarized form only) • Municipality number,Interviewer code,Questionnaire code • Registration No _____ • (date and place) • Respondent farm • (enterprise name / farmer’s name and surname) • (enterprise/farm registration address)
I. GENERAL INFORMATION (QUESTIONNAIRE) 1. Total farm size _________ ha 2. Total winter wheat (wheat) grown area _________ ha 3. Address of the basic1 wheat grown area (indicate place and municipality) 4. Wheat kinds and total area of the basic (survey) wheat grown area (ha) ? 5. Meteorological conditions for growing of wheat were: favourable / unfavourable, why? 6. Use of plant protection products (products) on wheat comparing to annual average was: higher / as usual / lower; why?
I. GENERAL INFORMATION (QUESTIONNAIRE)cont. 7. Use of plant protection products on wheat: • Not used (then part II. Technical information does not have to be completed) • Registered ecological farm • Professional use products are used 8. General information on use of plant protection products: • Person responsible for products and spraying has agronomical degree or plant protection course graduation certificate • Good records keeping of the products used ( use records journal for the completion of part II “Technical information”) • Sprayer used on farm with tank capacity more then 30 litres • Sprayer has a valid inspection certificate
II. TECHNICAL INFORMATION(data of plant protection products use on basic1 wheat grown area) • Basic area (ha) • Application date • Application stage: pre-drilling soil (seed) preparation /phenological crop growth stage • Product name • Application: - Rate (kg,l/ha,t) - Quantity (kg, l)
II. TECHNICAL INFORMATION(data of plant protection products use on basic1 wheat grown area) • Application of product mix: yes / no • Application type (seed treatment, spraying, etc.) • Water volume used (l/ha - spraying; or l/t – seed treatment) • Demand for the product use comparing to annual average (higher, as usual, lower) • Application targets (name main pests, diseases or weeds)
II. TECHNICAL INFORMATION (data of plant protection products use on basic1 wheat grown area) • Respondent (name and surname, position, signature) • Interviewer (name and surname, signature) • Definition: - Basic1 - wheat grown area on farm (field or sum of fields) where the same plant protection products were used identically (the same application rate, quantity, etc.)
EXPERIENCE: PILOT SURVEY 2004/5PROBLEMS SPECIFIC TO DATA COLLECTION ON WHEAT FARMS • When farm records are poor, it is more difficult to get high quality data (interview). • The Lithuanian farm record form does not include the point on crop stage when PPP are used (more difficult to get accurate data). • Human factor (farmer’s or interviewer’s errors).