{"title":"新作物春亚麻(Linum usitatissimum, L.)的gis模型适应方法","authors":"F. Flénet, P. Villon, F. Ruget","doi":"10.1051/AGRO:2004032","DOIUrl":null,"url":null,"abstract":"The STICS simulation model was adapted for linseed. An original procedure was used. Firstly, options were selected from among the possibilities available in STICS to simulate the processes of crops. Secondly, the model was calibrated following six steps: 1. gathering of information, 2. the use of parameters from the literature or from other models, 3. the use of STICS parameters for other crops if there is an analogy with linseed, 4. the use of the experimental data to determine parameters which can be measured or calculated, 5. the use of the experimental data to determine parameters by testing a range of values, and 6. the checking of consistency between the parameters and their physical or biological meaning. After adaptation to linseed, the simulations of leaf area, biomass, water consumption, plant nitrogen content, seed number and seed yield were in good agreement with the measurements used for calibration. Thirdly, the results of calculations by STICS were compared with measurements not used for calibration. There was little difference between calculations and measurements of leaf area, biomass, plant nitrogen content and seed number, while seed yield was overestimated because of diseases and lodging, which are not taken into account by the model. However, the differences in seed yield between treatments were properly simulated. This work was a first step towards developing a model to improve linseed crop management. To this end, modifications are needed to account for all yield limitations.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"83 1 1","pages":"367-381"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Methodology of adaptation of the STICS model to a new crop: spring linseed (Linum usitatissimum, L.)\",\"authors\":\"F. Flénet, P. Villon, F. Ruget\",\"doi\":\"10.1051/AGRO:2004032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The STICS simulation model was adapted for linseed. An original procedure was used. Firstly, options were selected from among the possibilities available in STICS to simulate the processes of crops. Secondly, the model was calibrated following six steps: 1. gathering of information, 2. the use of parameters from the literature or from other models, 3. the use of STICS parameters for other crops if there is an analogy with linseed, 4. the use of the experimental data to determine parameters which can be measured or calculated, 5. the use of the experimental data to determine parameters by testing a range of values, and 6. the checking of consistency between the parameters and their physical or biological meaning. After adaptation to linseed, the simulations of leaf area, biomass, water consumption, plant nitrogen content, seed number and seed yield were in good agreement with the measurements used for calibration. Thirdly, the results of calculations by STICS were compared with measurements not used for calibration. There was little difference between calculations and measurements of leaf area, biomass, plant nitrogen content and seed number, while seed yield was overestimated because of diseases and lodging, which are not taken into account by the model. However, the differences in seed yield between treatments were properly simulated. This work was a first step towards developing a model to improve linseed crop management. To this end, modifications are needed to account for all yield limitations.\",\"PeriodicalId\":7644,\"journal\":{\"name\":\"Agronomie\",\"volume\":\"83 1 1\",\"pages\":\"367-381\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agronomie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1051/AGRO:2004032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agronomie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/AGRO:2004032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Methodology of adaptation of the STICS model to a new crop: spring linseed (Linum usitatissimum, L.)
The STICS simulation model was adapted for linseed. An original procedure was used. Firstly, options were selected from among the possibilities available in STICS to simulate the processes of crops. Secondly, the model was calibrated following six steps: 1. gathering of information, 2. the use of parameters from the literature or from other models, 3. the use of STICS parameters for other crops if there is an analogy with linseed, 4. the use of the experimental data to determine parameters which can be measured or calculated, 5. the use of the experimental data to determine parameters by testing a range of values, and 6. the checking of consistency between the parameters and their physical or biological meaning. After adaptation to linseed, the simulations of leaf area, biomass, water consumption, plant nitrogen content, seed number and seed yield were in good agreement with the measurements used for calibration. Thirdly, the results of calculations by STICS were compared with measurements not used for calibration. There was little difference between calculations and measurements of leaf area, biomass, plant nitrogen content and seed number, while seed yield was overestimated because of diseases and lodging, which are not taken into account by the model. However, the differences in seed yield between treatments were properly simulated. This work was a first step towards developing a model to improve linseed crop management. To this end, modifications are needed to account for all yield limitations.