{"type":"survey","doc_desc":{"title":"ESP_2014-2019_GGP-P_v01_M_v01_A_OCS","idno":"DDI_ESP_2014-2019_GGP-P_v01_M_v01_A_OCS","producers":[{"name":"Office of Chief Statistician","abbreviation":"OCS","affiliation":"Food and Agriculture Organization","role":"Metadata producer"},{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Metadata adapted for World Bank Microdata Library"}],"prod_date":"2023-01-03","version_statement":{"version":"Version 01 (January 2023): This metadata was downloaded from the FAO website (https:\/\/microdata.fao.org\/index.php\/catalog) and it is identical to FAO version (ESP_2014-2019_GGP-P_v01_EN_M_A_OCS). The following two metadata fields were edited - Document ID and Survey ID."}},"study_desc":{"title_statement":{"idno":"ESP_2014-2019_GGP-P_v01_M_v01_A_OCS","title":"Good Growth Plan 2014-2019","alt_title":"GGP-P 2014-2019"},"authoring_entity":[{"name":"Syngenta","affiliation":""}],"production_statement":{"producers":[{"name":"Kynetec","affiliation":"","role":"Technical assistance"}]},"distribution_statement":{"contact":[{"name":"The Good Growth Plan team","affiliation":"Syngenta","email":"goodgrowthplan.data@syngenta.com","uri":"https:\/\/www.syngenta.com\/en\/sustainability\/good-growth-plan"}]},"series_statement":{"series_name":"Agricultural Survey [ag\/oth]"},"study_info":{"keywords":[{"keyword":"Input efficiency","vocab":"","uri":""},{"keyword":"Crop productivity","vocab":"","uri":""},{"keyword":"Agriculture","vocab":"","uri":""},{"keyword":"The Good Growth Plan","vocab":"","uri":""}],"topics":[{"topic":"Agriculture & Rural Development","vocab":"FAO","uri":""},{"topic":"Environment","vocab":"FAO","uri":""},{"topic":"Agricultural input efficiency","vocab":"FAO","uri":""}],"abstract":"Syngenta is committed to increasing crop productivity and to using limited resources such as land, water and inputs more efficiently. Since 2014, Syngenta has been measuring trends in agricultural input efficiency on a global network of real farms. The Good Growth Plan dataset shows aggregated productivity and resource efficiency indicators by harvest year. The data has been collected from more than 4,000 farms and covers more than 20 different crops in 46 countries. The data (except USA data and for Barley in UK, Germany, Poland, Czech Republic, France and Spain) was collected, consolidated and reported by Kynetec (previously Market Probe), an independent market research agency. It can be used as benchmarks for crop yield and input efficiency.","coll_dates":[{"start":"2014","end":"2019","cycle":""}],"nation":[{"name":"Spain","abbreviation":"ESP"}],"geog_coverage":"National coverage","analysis_unit":"Agricultural holdings","data_kind":"Sample survey data [ssd]","notes":"Data was collected on the usage of inputs, such as crop protection products, chemical fertilizer, seeding rates, labor hours, machinery usage hours, and marketable crop yield on a per hectare basis."},"method":{"data_collection":{"sampling_procedure":"A. Sample design \nFarms are grouped in clusters, which represent a crop grown in an area with homogenous agro- ecological conditions and include comparable types of farms. The sample includes reference and benchmark farms. The reference farms were selected by Syngenta and the benchmark farms were randomly selected by Kynetec within the same cluster.\n\nB. Sample size\nSample sizes for each cluster are determined with the aim to measure statistically significant increases in crop efficiency over time. This is done by Kynetec based on target productivity increases and assumptions regarding the variability of farm metrics in each cluster. The smaller the expected increase, the larger the sample size needed to measure significant differences over time. Variability within clusters is assumed based on public research and expert opinion. In addition, growers are also grouped in clusters as a means of keeping variances under control, as well as distinguishing between growers in terms of crop size, region and technological level. A minimum sample size of 20 interviews per cluster is needed. The minimum number of reference farms is 5 of 20. The optimal number of reference farms is 10 of 20 (balanced sample).\n\nC. Selection procedure\nThe respondents were picked randomly using a \u201cquota based random sampling\u201d procedure. Growers were first randomly selected and then checked if they complied with the quotas for crops, region, farm size etc. To avoid clustering high number of interviews at one sampling point, interviewers were instructed to do a maximum of 5 interviews in one village.\n\nBF Screened from Spain were selected based on the following criterion:\n\n(a) Pepper growers (Province Almeria):\n- Passive greenhouse \t\n- Part of a integrated producer or cooperative\t\n- Exported orientated\t\n- RF producing variety 'Melchor'\t\n\n-> Integrated producers: those that integrate the production & exportation of crops. They own the land and buy production outside to fulfill market demands. This is different from cooperatives as this ones only buy production to small farmers associated to them, they don't own land, they are intermediates to sell farmer production. \n-> Professionals, marketing oriented, direct link to foodchain (It means that Cooperatives or Integrated Producers sell directly to supermarkets or traders in Europe) \n- innovators (early adopters)\t\n- Sell production to cooperatives and growers receive technical support, varieties, recommendations ( from cooperatives).\t\n\n(b) Tomato growers (Province Almeria):\n- Passive greenhouse \t\n- part of a integrated producer or cooperative\t\n- Exported orientated\t\n- RF producing variety 'Caniles'\t\n-> Integrated producers: those that integrate the production & exportation of crops. They own the land and buy production outside to fulfill market demands. This is different from cooperatives as this ones only buy production to small farmers associated to them, they don't own land, they are intermediates to sell farmer production. \n-> Professionals, marketing oriented, direct link to foodchain (It means that Cooperatives or Integrated Producers sell directly to supermarkets or traders in Europe) - innovators (early adopters)\t\nSell production to cooperatives and growers receive technical support, varieties, recommendations ( from cooperatives).\t\n\n(c) Medium\/Large growers (Province: Andaluc\u00eda (Cities: C\u00e1diz, Huelva, Sevilla, C\u00f3rdoba): \n- Full time farmers\t\n- Growing sunflowers and cereals as main income source\t\n- Open minded: they are open to introduce new varieties, they adopt new technologies in a fast way, but it's still a crop where there is a low input of technology available. \t\n- High input spending (background info: this crop is of low investment, they don't do irrigation, only a cheap herbicide and some fertilizers, so it's not a crop where nowadays they invest more, unless you give more productive seeds.)\t\n- Need to identify benchmark farms that have similar size but use local practices. (i.e. Planting date later )\t\n- Early adopters of new technologies\t\n- Benchmark grower can use HTC seeds. This is only 5% of the market, so only 5% use this and 95% use non HTC seeds, due to more productivity. Our variety will bring HTC tolerace + productivity, so farmer will get a reduction on costs + increase in yield, to increase gains.","coll_mode":["Face-to-face [f2f]"],"research_instrument":"Data collection tool for 2019 covered the following information:\n\n(A) PRE- HARVEST INFORMATION\n\nPART I: Screening \nPART II: Contact Information\nPART III: Farm Characteristics \n a. Biodiversity conservation\n b. Soil conservation\n c. Soil erosion\n d. Description of growing area\n e. Training on crop cultivation and safety measures\nPART IV: Farming Practices - Before Harvest \n a. Planting and fruit development - Field crops \n b. Planting and fruit development - Tree crops\n c. Planting and fruit development - Sugarcane\n d. Planting and fruit development - Cauliflower \n e. Seed treatment \n\n(B) HARVEST INFORMATION\n\nPART V: Farming Practices - After Harvest \n a. Fertilizer usage\n b. Crop protection products\n c. Harvest timing & quality per crop - Field crops\n d. Harvest timing & quality per crop - Tree crops\n e. Harvest timing & quality per crop - Sugarcane \n f. Harvest timing & quality per crop - Banana\n g. After harvest\nPART VI - Other inputs - After Harvest \n a. Input costs\n b. Abiotic stress\n c. Irrigation\n\nSee all questionnaires in external materials tab","cleaning_operations":"Data processing:\nKynetec uses SPSS (Statistical Package for the Social Sciences) for data entry, cleaning, analysis, and reporting. After collection, the farm data is entered into a local database, reviewed, and quality-checked by the local Kynetec agency. In the case of missing values or inconsistencies, farmers are re-contacted. In some cases, grower data is verified with local experts (e.g. retailers) to ensure data accuracy and validity. After country-level cleaning, the farm-level data is submitted to the global Kynetec headquarters for processing. In the case of missing values or inconsistences, the local Kynetec office was re-contacted to clarify and solve issues. \n\nQuality assurance \nVarious consistency checks and internal controls are implemented throughout the entire data collection and reporting process in order to ensure unbiased, high quality data. \n\n\u2022 Screening: Each grower is screened and selected by Kynetec based on cluster-specific criteria to ensure a comparable group of growers within each cluster. This helps keeping variability low. \n\n\u2022 Evaluation of the questionnaire: The questionnaire aligns with the global objective of the project and is adapted to the local context (e.g. interviewers and growers should understand what is asked). Each year the questionnaire is evaluated based on several criteria, and updated where needed. \n\n\u2022 Briefing of interviewers: Each year, local interviewers - familiar with the local context of farming -are thoroughly briefed to fully comprehend the questionnaire to obtain unbiased, accurate answers from respondents. \n\n\u2022 Cross-validation of the answers: \n o Kynetec captures all growers' responses through a digital data-entry tool. Various logical and consistency checks are automated in this tool (e.g. total crop size in hectares cannot be larger than farm size) \n o Kynetec cross validates the answers of the growers in three different ways: \n 1. Within the grower (check if growers respond consistently during the interview) \n 2. Across years (check if growers respond consistently throughout the years) \n 3. Within cluster (compare a grower's responses with those of others in the group) \n o All the above mentioned inconsistencies are followed up by contacting the growers and asking them to verify their answers. The data is updated after verification. All updates are tracked. \n\n\u2022 Check and discuss evolutions and patterns: Global evolutions are calculated, discussed and reviewed on a monthly basis jointly by Kynetec and Syngenta. \n\n\u2022 Sensitivity analysis: sensitivity analysis is conducted to evaluate the global results in terms of outliers, retention rates and overall statistical robustness. The results of the sensitivity analysis are discussed jointly by Kynetec and Syngenta.\n\n\u2022 It is recommended that users interested in using the administrative level 1 variable in the location dataset use this variable with care and crosscheck it with the postal code variable."},"analysis_info":{"data_appraisal":"Due to the above mentioned checks, irregularities in fertilizer usage data were discovered which had to be corrected: \n\nFor data collection wave 2014, respondents were asked to give a total estimate of the fertilizer NPK-rates that were applied in the fields. From 2015 onwards, the questionnaire was redesigned to be more precise and obtain data by individual fertilizer products. The new method of measuring fertilizer inputs leads to more accurate results, but also makes a year-on-year comparison difficult. After evaluating several solutions to this problems, 2014 fertilizer usage (NPK input) was re-estimated by calculating a weighted average of fertilizer usage in the following years."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO","required":"yes","form_no":"","uri":""}],"cit_req":"The Good Growth Plan Progress Data - Productivity 2019","conditions":"Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. 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