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.
{"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":"https://doi.org/10.1051/AGRO:2004032","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":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79658570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Noblet-Ducoudré, S. Gervois, P. Ciais, N. Viovy, N. Brisson, B. Séguin, A. Perrier
Agriculture is still accounted for in a very simplistic way in the land-surface models which are coupled to climate models, while the area it occupies will significantly increase in the next century according to future scenarios. In order to improve the representation of croplands in a Dynamic Global Vegetation Model named ORCHIDEE (which can be coupled to the IPSL 1 climate model), we have (1) developed a procedure which assimilates some of the variables simulated by a detailed crop model, STICS, and (2) modified some parameterisations to avoid inconsistencies between assimilated and computed variables in ORCHIDEE. Site simulations show that the seasonality of the cropland-atmosphere fluxes of water, energy and CO 2 is strongly modified when more realistic crop parameterisations are introduced in ORCHIDEE. A more realistic representation of wheat and corn croplands over Western Europe leads to a drying out of the atmosphere at the end of summer and during autumn, while the soils remain wetter, specially at the time when winter crops are sowed. The seasonality of net CO 2 uptake fluxes is also enhanced and shortened.
{"title":"Coupling the Soil-Vegetation-Atmosphere-Transfer Scheme ORCHIDEE to the agronomy model STICS to study the influence of croplands on the European carbon and water budgets","authors":"N. Noblet-Ducoudré, S. Gervois, P. Ciais, N. Viovy, N. Brisson, B. Séguin, A. Perrier","doi":"10.1051/AGRO:2004038","DOIUrl":"https://doi.org/10.1051/AGRO:2004038","url":null,"abstract":"Agriculture is still accounted for in a very simplistic way in the land-surface models which are coupled to climate models, while the area it occupies will significantly increase in the next century according to future scenarios. In order to improve the representation of croplands in a Dynamic Global Vegetation Model named ORCHIDEE (which can be coupled to the IPSL 1 climate model), we have (1) developed a procedure which assimilates some of the variables simulated by a detailed crop model, STICS, and (2) modified some parameterisations to avoid inconsistencies between assimilated and computed variables in ORCHIDEE. Site simulations show that the seasonality of the cropland-atmosphere fluxes of water, energy and CO 2 is strongly modified when more realistic crop parameterisations are introduced in ORCHIDEE. A more realistic representation of wheat and corn croplands over Western Europe leads to a drying out of the atmosphere at the end of summer and during autumn, while the soils remain wetter, specially at the time when winter crops are sowed. The seasonality of net CO 2 uptake fluxes is also enhanced and shortened.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"1 1","pages":"397-407"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76773368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Julio C. Rodríguez, B. Duchemin, R. Hadria, C. Watts, J. Garatuza, A. Chehbouni, S. Khabba, G. Boulet, E. Palacios, A. Lahrouni
During the 1999/2000 agricultural seasons, an experiment was carried out on winter wheat fields in the semiarid Yaqui Valley (Northwest Mexico). This data set was used to calibrate the evolution of the leaf area index (LAI) simulated by STICS, which was found to be in excellent agreement with estimates obtained from field reflectance measurements. After calibration, STICS was able to simulate satisfactorily the seasonal levels and trends observed in net radiation, soil moisture and evapotranspiration, but the crop temperature was overestimated by about 2.5 °C. On a larger scale, STICS was run on 16 fields with contrasting management practices. The simulations indicate that yield predictability is significantly lower for later sowing dates, consistent with observations. The seasonal variations of field and satellite data (Landsat-ETM+, Terra-MODIS and VEGETATION) NDVI were very close. However, some difficulties were noted: saturation of NDVI at high LAI values and smoothed variability on a 1-km spatial scale, as well as the need for a sound methodology for processing satellite data.
{"title":"Wheat yield estimation using remote sensing and the STICS model in the semiarid Yaqui valley, Mexico","authors":"Julio C. Rodríguez, B. Duchemin, R. Hadria, C. Watts, J. Garatuza, A. Chehbouni, S. Khabba, G. Boulet, E. Palacios, A. Lahrouni","doi":"10.1051/AGRO:2004037","DOIUrl":"https://doi.org/10.1051/AGRO:2004037","url":null,"abstract":"During the 1999/2000 agricultural seasons, an experiment was carried out on winter wheat fields in the semiarid Yaqui Valley (Northwest Mexico). This data set was used to calibrate the evolution of the leaf area index (LAI) simulated by STICS, which was found to be in excellent agreement with estimates obtained from field reflectance measurements. After calibration, STICS was able to simulate satisfactorily the seasonal levels and trends observed in net radiation, soil moisture and evapotranspiration, but the crop temperature was overestimated by about 2.5 °C. On a larger scale, STICS was run on 16 fields with contrasting management practices. The simulations indicate that yield predictability is significantly lower for later sowing dates, consistent with observations. The seasonal variations of field and satellite data (Landsat-ETM+, Terra-MODIS and VEGETATION) NDVI were very close. However, some difficulties were noted: saturation of NDVI at high LAI values and smoothed variability on a 1-km spatial scale, as well as the need for a sound methodology for processing satellite data.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"34 1","pages":"295-304"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80272272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Scopel, Fernando-Antonio Macena Da Silva, M. Corbeels, F. Affholder, F. Maraux
A key principle of direct seeding mulch-based cropping systems is the retention of crop residues on the soil surface to preserve soil water for crop growth. In this study the impact of surface crop residue on water use and production risk associated with rainfall variability is analysed for two contrasting tropical sites. The two sites are La Tinaja in semi-arid Mexico and Planaltina in humid Brazil. The crop growth model STICS, version 3.0 was updated with a simple empirical module, incorporating the following effects of surface residue on soil water balance: (1) rainfall interception and subsequent mulch evaporation; (2) radiation interception with associated reduction of soil evaporation and (3) reduction of surface water runoff. The results of the model simulations showed that the effect of radiation interception at both sites was much more important than the effect of intercepting rain.[...]
{"title":"Modelling crop residue mulching effects on water use and production of maize under semi-arid and humid tropical conditions","authors":"E. Scopel, Fernando-Antonio Macena Da Silva, M. Corbeels, F. Affholder, F. Maraux","doi":"10.1051/AGRO:2004029","DOIUrl":"https://doi.org/10.1051/AGRO:2004029","url":null,"abstract":"A key principle of direct seeding mulch-based cropping systems is the retention of crop residues on the soil surface to preserve soil water for crop growth. In this study the impact of surface crop residue on water use and production risk associated with rainfall variability is analysed for two contrasting tropical sites. The two sites are La Tinaja in semi-arid Mexico and Planaltina in humid Brazil. The crop growth model STICS, version 3.0 was updated with a simple empirical module, incorporating the following effects of surface residue on soil water balance: (1) rainfall interception and subsequent mulch evaporation; (2) radiation interception with associated reduction of soil evaporation and (3) reduction of surface water runoff. The results of the model simulations showed that the effect of radiation interception at both sites was much more important than the effect of intercepting rain.[...]","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"3 1","pages":"383-395"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81519096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. D. Bella, R. Faivre, F. Ruget, B. Séguin, M. Guérif, B. Combal, M. Weiss, C. Rebella
In France, pastures represent a significant land-cover type, which mainly sustains husbandry production. For this reason, it is of great benefit to develop real-time monitoring of pasture biomass production, taking into account its spatial and temporal variability. The absence of low-cost methods applicable to large regions has oriented French stakeholders to the use of growth simulation models adequately informed through spatialised databases (such as the ISOP system). Remote-sensing data may be considered a potential tool to improve simulations by objective observations in a real-time framework and the aim of this work was to evaluate this potential role of remote sensing. Thirteen forage regions (administrative partitioning of the French territory for pastures and grasslands) were selected in France, differing by their soil, climatic and land-cover characteristics. SPOT 4 -VEGETATION satellite images (1 km 2 resolution) were used to provide the spectral signature corresponding to pure pasture, using subpixel estimation methods. This information was then related to growth variables calculated by the STICS-pasture model (included in the ISOP system). We found that the best relations were obtained between a middle infrared-based vegetation index (SWVI) calculated from the elementary reflectance bands of the satellite, and the leaf area index (LAI) calculated from STICS. The use of these relations first showed the ability of satellite data to provide real-time estimations of growth status variables. Second, the comparison between both types of data showed that spatial and temporal differences existed between satellite and model information, mainly during the harvesting periods. This result could contribute to improving the model evaluations on a regional scale.
{"title":"Use of SPOT4-VEGETATION satellite data to improve pasture production simulated by STICS included in the ISOP French system","authors":"C. D. Bella, R. Faivre, F. Ruget, B. Séguin, M. Guérif, B. Combal, M. Weiss, C. Rebella","doi":"10.1051/AGRO:2004034","DOIUrl":"https://doi.org/10.1051/AGRO:2004034","url":null,"abstract":"In France, pastures represent a significant land-cover type, which mainly sustains husbandry production. For this reason, it is of great benefit to develop real-time monitoring of pasture biomass production, taking into account its spatial and temporal variability. The absence of low-cost methods applicable to large regions has oriented French stakeholders to the use of growth simulation models adequately informed through spatialised databases (such as the ISOP system). Remote-sensing data may be considered a potential tool to improve simulations by objective observations in a real-time framework and the aim of this work was to evaluate this potential role of remote sensing. Thirteen forage regions (administrative partitioning of the French territory for pastures and grasslands) were selected in France, differing by their soil, climatic and land-cover characteristics. SPOT 4 -VEGETATION satellite images (1 km 2 resolution) were used to provide the spectral signature corresponding to pure pasture, using subpixel estimation methods. This information was then related to growth variables calculated by the STICS-pasture model (included in the ISOP system). We found that the best relations were obtained between a middle infrared-based vegetation index (SWVI) calculated from the elementary reflectance bands of the satellite, and the leaf area index (LAI) calculated from STICS. The use of these relations first showed the ability of satellite data to provide real-time estimations of growth status variables. Second, the comparison between both types of data showed that spatial and temporal differences existed between satellite and model information, mainly during the harvesting periods. This result could contribute to improving the model evaluations on a regional scale.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"215 1","pages":"437-444"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85883861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Houlès, B. Mary, M. Guérif, D. Makowski, E. Justes
The use of crop models for nitrogen fertiliser management raises several issues. A first problem is to define suitable criteria for optimising nitrogen fertilisation in function of economic, quality and environmental objectives. A second issue is to assess the capacity of the crop model to predict the variables involved in the calculation of the criteria such as grain yield, grain protein content, residual soil mineral nitrogen or nitrogen balance. A third issue is to evaluate the results obtained by applying the decision rules selected by the crop model. The three problems are considered in this paper in the case of winter wheat and the STICS model. Fourteen field experiments with various N fertilisation strategies were used for evaluating the model. STICS predicted grain yield and nitrogen balance more accurately than protein content and soil mineral N at harvest. Among the eight criteria tested for optimising N fertilisation, those using a maximal threshold on nitrogen balance seem to be the most valuable for satisfying agricultural and environmental objectives. Under conditions of environmental constraint, STICS was more efficient than the reference method (AZOBIL) at selecting the optimal nitrogen fertilisation scenario.
{"title":"Evaluation of the ability of the crop model STICS to recommend nitrogen fertilisation rates according to agro-environmental criteria","authors":"V. Houlès, B. Mary, M. Guérif, D. Makowski, E. Justes","doi":"10.1051/AGRO:2004036","DOIUrl":"https://doi.org/10.1051/AGRO:2004036","url":null,"abstract":"The use of crop models for nitrogen fertiliser management raises several issues. A first problem is to define suitable criteria for optimising nitrogen fertilisation in function of economic, quality and environmental objectives. A second issue is to assess the capacity of the crop model to predict the variables involved in the calculation of the criteria such as grain yield, grain protein content, residual soil mineral nitrogen or nitrogen balance. A third issue is to evaluate the results obtained by applying the decision rules selected by the crop model. The three problems are considered in this paper in the case of winter wheat and the STICS model. Fourteen field experiments with various N fertilisation strategies were used for evaluating the model. STICS predicted grain yield and nitrogen balance more accurately than protein content and soil mineral N at harvest. Among the eight criteria tested for optimising N fertilisation, those using a maximal threshold on nitrogen balance seem to be the most valuable for satisfying agricultural and environmental objectives. Under conditions of environmental constraint, STICS was more efficient than the reference method (AZOBIL) at selecting the optimal nitrogen fertilisation scenario.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"10 1","pages":"339-349"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86121551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The simulations supplied by a combination of a global climate model and a weather generator allowed the creation of two climate scenarios including an increase and/or monthly variations in temperature for the 2070-2100 horizon, which were compared with two currently available series (1961-1990 and 1990-2000). Three forage systems applied in upland areas of southern France were simulated using the STICS model (silage maize, perennial alfalfa and grasses) and the outputs were introduced into a digital elevation model. We noted changes in precocity which allowed the sowing of silage maize varieties with longer crop cycles at lower altitudes and an enlargement of the crop zone above 700-800 m. When introducing monthly temperature variations, we observed major frost damage which decreased maize yields. As for gramineous and alfalfa grasslands, we obtained a lengthening in the growing period with earlier first cut dates and sometimes the possibility of a supplementary cut.
{"title":"Impact of global warming on the growing cycles of three forage systems in upland areas of southeastern France","authors":"Stéphanie Juin, N. Brisson, P. Clastre, P. Grand","doi":"10.1051/AGRO:2004028","DOIUrl":"https://doi.org/10.1051/AGRO:2004028","url":null,"abstract":"The simulations supplied by a combination of a global climate model and a weather generator allowed the creation of two climate scenarios including an increase and/or monthly variations in temperature for the 2070-2100 horizon, which were compared with two currently available series (1961-1990 and 1990-2000). Three forage systems applied in upland areas of southern France were simulated using the STICS model (silage maize, perennial alfalfa and grasses) and the outputs were introduced into a digital elevation model. We noted changes in precocity which allowed the sowing of silage maize varieties with longer crop cycles at lower altitudes and an enlargement of the crop zone above 700-800 m. When introducing monthly temperature variations, we observed major frost damage which decreased maize yields. As for gramineous and alfalfa grasslands, we obtained a lengthening in the growing period with earlier first cut dates and sometimes the possibility of a supplementary cut.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"139 8 1","pages":"327-337"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85433758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Crop models are important tools in agronomic research, a major use being to make predictions. A proper parameter estimation method is necessary to ensure accurate predictions. Until now studies have focused on the application of a particular estimation method and few comparisons of different methods are available. In this paper, we compare several parameter estimation methods, related, on the one hand, to model selection, and on the other, to ridge regression based on an analogy to a Bayesian approach. The different methods are applied to a simplified crop model derived from the STICS model, using simulated data. The criteria for comparison are prediction error and errors in the parameter estimates. Among the methods of model comparison a version of the Schwarz criterion, corrected for small samples and with maximum and minimum bounds for each parameter, is the preferred method. Ridge regression is found to be superior to this best method of model selection.
{"title":"Comparison of parameter estimation methods for crop models","authors":"Marie Tremblay, D. Wallach","doi":"10.1051/AGRO:2004033","DOIUrl":"https://doi.org/10.1051/AGRO:2004033","url":null,"abstract":"Crop models are important tools in agronomic research, a major use being to make predictions. A proper parameter estimation method is necessary to ensure accurate predictions. Until now studies have focused on the application of a particular estimation method and few comparisons of different methods are available. In this paper, we compare several parameter estimation methods, related, on the one hand, to model selection, and on the other, to ridge regression based on an analogy to a Bayesian approach. The different methods are applied to a simplified crop model derived from the STICS model, using simulated data. The criteria for comparison are prediction error and errors in the parameter estimates. Among the methods of model comparison a version of the Schwarz criterion, corrected for small samples and with maximum and minimum bounds for each parameter, is the preferred method. Ridge regression is found to be superior to this best method of model selection.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"8 1","pages":"351-365"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88610729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pea seed protein content (SPC) and seed dry weight (SDW) are both influenced by genetic and environmental factors. To assess the variations of these within-plant traits between seeds, six genotypes were field tested. The sequential seed development at nodes along the main stem was determined. Nitrogen fixation was measured by the acetylene reduction assay (ARA). At maturity, protein content and dry weight were measured according to seed position on the plant. Individual protein content was determined by near-infrared transmission spectroscopy. The results show a significant difference in protein content between nodes of the genotypes Solara, L765 and L833. Protein content tended to decrease from the bottom to the top of the plant for these genotypes. The difference in protein content between the lowest and the uppermost node was about 26 g kg -1 for Solara, 40 g kg -1 for L765 and 49 g kg -1 for L833. There were also significant differences in dry weight between plant nodes for all genotypes, except Finale. In addition, the range of difference in dry weight between plant nodes was higher than that for protein content. Further, to determine the influence of morphological position on individual protein content and dry weight, multiple linear regression was established on node position, pod position on the node, and seed position within pods. The results showed that protein content and dry weight were not influenced either by within-pod seed position or pod position on the raceme. Moreover, protein content and dry weight were mainly influenced by node position on the main stem. However, for protein content, the effect of node position varied with genotype, indicating a genetic variability for this character. This genetic variability could be attributed to the difference between genotypes in the ability to maintain nitrogen fixation during the onset of seed filling. For dry weight, the decrease in seed weight for upper nodes of the plant also varied with genotype in relation to the duration of seed filling and the seed growth rate.
豌豆种子蛋白质含量(SPC)和干重(SDW)均受遗传和环境因素的影响。为了评估这些植物内性状在种子间的变化，对6个基因型进行了田间试验。测定了沿主茎各节的种子发育顺序。采用乙炔还原法(ARA)测定固氮作用。成熟时，根据种子在植株上的位置测定蛋白质含量和干重。用近红外透射光谱法测定个体蛋白质含量。结果表明，索拉、L765和L833基因型结间蛋白质含量差异显著。这些基因型的蛋白质含量从植株底部到顶部呈下降趋势。最低节与最高节之间的蛋白质含量差异为Solara 26 g kg -1, L765 40 g kg -1, L833 49 g kg -1。除终曲外，各基因型植株节间干重也存在显著差异。植株节段间干重差异幅度大于蛋白质含量差异幅度。此外，为了确定形态位置对单株蛋白质含量和干重的影响，建立了节点位置、节点上荚果位置和荚果内种子位置的多元线性回归。结果表明，籽粒内籽粒位置和总状花序上籽粒位置对蛋白质含量和干重均无显著影响。蛋白质含量和干重主要受主茎节位的影响。然而，对于蛋白质含量，节点位置的影响因基因型而异，表明该性状具有遗传变异性。这种遗传变异可归因于不同基因型在种子灌浆开始时维持固氮能力的差异。干重方面，不同基因型植株上节种子重的下降也与种子灌浆时间和种子生长速率有关。
{"title":"Protein content and dry weight of seeds from various pea genotypes","authors":"S. Atta, S. Maltese, R. Cousin","doi":"10.1051/AGRO:2004025","DOIUrl":"https://doi.org/10.1051/AGRO:2004025","url":null,"abstract":"Pea seed protein content (SPC) and seed dry weight (SDW) are both influenced by genetic and environmental factors. To assess the variations of these within-plant traits between seeds, six genotypes were field tested. The sequential seed development at nodes along the main stem was determined. Nitrogen fixation was measured by the acetylene reduction assay (ARA). At maturity, protein content and dry weight were measured according to seed position on the plant. Individual protein content was determined by near-infrared transmission spectroscopy. The results show a significant difference in protein content between nodes of the genotypes Solara, L765 and L833. Protein content tended to decrease from the bottom to the top of the plant for these genotypes. The difference in protein content between the lowest and the uppermost node was about 26 g kg -1 for Solara, 40 g kg -1 for L765 and 49 g kg -1 for L833. There were also significant differences in dry weight between plant nodes for all genotypes, except Finale. In addition, the range of difference in dry weight between plant nodes was higher than that for protein content. Further, to determine the influence of morphological position on individual protein content and dry weight, multiple linear regression was established on node position, pod position on the node, and seed position within pods. The results showed that protein content and dry weight were not influenced either by within-pod seed position or pod position on the raceme. Moreover, protein content and dry weight were mainly influenced by node position on the main stem. However, for protein content, the effect of node position varied with genotype, indicating a genetic variability for this character. This genetic variability could be attributed to the difference between genotypes in the ability to maintain nitrogen fixation during the onset of seed filling. For dry weight, the decrease in seed weight for upper nodes of the plant also varied with genotype in relation to the duration of seed filling and the seed growth rate.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"17 1","pages":"257-266"},"PeriodicalIF":0.0,"publicationDate":"2004-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72833304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a dominant component crop in intercropping systems, common bean is exposed to radiation deficit during various phases. An indeterminate cultivar was examined from twenty-seven treatments consisting of all possible combinations of three levels of photosynthetic irradiance, 100, 250 and 400 μmol m -2 s -1 , applied during three phenological phases. Acclimation characteristics to reduced irradiance included lower chlorophyll a/b ratio, reduced stomatal density, increased specific leaf area and leaf area ratio and increased shoot-root ratio. Susceptibility of the phases varied when comparisons were made based on entire phases and a magnitude that considered timing and light interception. Number of pods per plant, the predominant yield component, responded to irradiance level during all phases but most during flowering. For number of seeds per pod the only relevant phase was seed filling while seed weight responded during flowering and seed filling. A significant interaction between the irradiance levels of phases was observed for pod number.
普通豆作为间作系统的主要组成作物，在不同阶段都面临辐射亏缺。在三个物候期施用100、250和400 μmol m -2 s -1 3个光合辐照水平的所有可能组合的27个处理中，检测了一个不确定的品种。辐照减弱后的驯化表现为叶绿素a/b比降低、气孔密度降低、比叶面积和比叶面积增大、茎根比增大。当基于整个相位和考虑时间和光拦截的幅度进行比较时，相位的敏感性有所不同。单株荚果数是产量的主要组成部分，在所有阶段均对光照水平有响应，但在开花期响应最大。单荚种子数与种子灌浆期有关，而种子重与开花和灌浆期有关。各相辐照水平对荚果数有显著的交互作用。
{"title":"Responses of common bean (Phaseolus vulgaris L.) to photosynthetic irradiance levels during three phenological phases","authors":"W. Worku, A. Skjelvåg, H. Gislerød","doi":"10.1051/AGRO:2004024","DOIUrl":"https://doi.org/10.1051/AGRO:2004024","url":null,"abstract":"As a dominant component crop in intercropping systems, common bean is exposed to radiation deficit during various phases. An indeterminate cultivar was examined from twenty-seven treatments consisting of all possible combinations of three levels of photosynthetic irradiance, 100, 250 and 400 μmol m -2 s -1 , applied during three phenological phases. Acclimation characteristics to reduced irradiance included lower chlorophyll a/b ratio, reduced stomatal density, increased specific leaf area and leaf area ratio and increased shoot-root ratio. Susceptibility of the phases varied when comparisons were made based on entire phases and a magnitude that considered timing and light interception. Number of pods per plant, the predominant yield component, responded to irradiance level during all phases but most during flowering. For number of seeds per pod the only relevant phase was seed filling while seed weight responded during flowering and seed filling. A significant interaction between the irradiance levels of phases was observed for pod number.","PeriodicalId":7644,"journal":{"name":"Agronomie","volume":"14 1","pages":"267-274"},"PeriodicalIF":0.0,"publicationDate":"2004-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75105734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：