{"title":"Effect of pattern of water supply on Vicia faba L. 4. Simulation studies on yield variability.","authors":"C. Grashoff, R. Stokkers","doi":"10.18174/njas.v40i4.16504","DOIUrl":null,"url":null,"abstract":"The effects of water supply patterns on yield variability of Vicia faba L. were studied by means of a crop growth model. The model simulates crop dry matter production and soil water availability in dependence on plant characteristics and weather and soil data. Conse quences of various weather conditions on growth were evaluated, using 4 data sets from various soils and sites in Western Europe. In set 1 (14 years; heavy clay soil; Netherlands) and set 3 (2 years; 9 locations in Western Europe), linear regressions of measured versus simulat ed seed yields, fitted through the origin, had slopes of almost 1 and accounted for 68 % (set 1) and 12 % (set 3) of the yield variation. In both sets, these regressions accounted for about 80 % of the variation, if deviations, due to damage effects of hail, lodging, and diseases were excluded (these damage effects are not calculated in the model). In set 1, the average seed yield was 5.3 t ha\"1 (measured and simulated) and the standard deviation (s.d.) was 1.3 (measured) and 1.5 t ha ' (simulated). Simulated irrigation after the end of flowering (i.e. from grain filling onwards) stabilized yield (s.d. = 0.4 t ha\"1) on a high level (6.2 t ha\"1). Simulated irrigation during the whole season had almost no additional effect. The results for set 3 were similar to set 1. Simulations for set 1 showed that the 'target' soil water contents during flowering for optimum final seed yields varied from 0.27-0.32 cm3 cm\"3 for this soil type (pF-values of respectively 3 and 2.3), depending on temperature and air humidity. After flowering a water content higher than 0.32 cm3 cm\"3 was required. Two strategies for breeding ideotypes were evaluated; doubling the rooted depth and root growth rate stabilized seed yields (the s.d. was reduced by 30 % in set 1), but doubling the water extraction capacity of the crop had almost no effect. The model accounted for less than 1 % of the variation in set 2 (14 years; light silty loam; Netherlands) and 4 (3 years; 5 regional experimental farms; Netherlands). This was different from set 1 and 3 and probably due to effects of capillary rise (in set 2) and diseases (in set 4), which are not included in the model. In set 4, the yield gap between simulated and measured yields increased with observed disease attack in the field, from less than 1 t ha\"' with 'absent or low' attack to more than 3.5 with 'severe' attack. The simulation studies show how control of water availability stabilizes faba bean yields in many environments. They also indicate the importance of disease control and of breeding ideotypes with deeper rooting capacity.","PeriodicalId":324908,"journal":{"name":"Netherlands Journal of Agricultural Science","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Netherlands Journal of Agricultural Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18174/njas.v40i4.16504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The effects of water supply patterns on yield variability of Vicia faba L. were studied by means of a crop growth model. The model simulates crop dry matter production and soil water availability in dependence on plant characteristics and weather and soil data. Conse quences of various weather conditions on growth were evaluated, using 4 data sets from various soils and sites in Western Europe. In set 1 (14 years; heavy clay soil; Netherlands) and set 3 (2 years; 9 locations in Western Europe), linear regressions of measured versus simulat ed seed yields, fitted through the origin, had slopes of almost 1 and accounted for 68 % (set 1) and 12 % (set 3) of the yield variation. In both sets, these regressions accounted for about 80 % of the variation, if deviations, due to damage effects of hail, lodging, and diseases were excluded (these damage effects are not calculated in the model). In set 1, the average seed yield was 5.3 t ha"1 (measured and simulated) and the standard deviation (s.d.) was 1.3 (measured) and 1.5 t ha ' (simulated). Simulated irrigation after the end of flowering (i.e. from grain filling onwards) stabilized yield (s.d. = 0.4 t ha"1) on a high level (6.2 t ha"1). Simulated irrigation during the whole season had almost no additional effect. The results for set 3 were similar to set 1. Simulations for set 1 showed that the 'target' soil water contents during flowering for optimum final seed yields varied from 0.27-0.32 cm3 cm"3 for this soil type (pF-values of respectively 3 and 2.3), depending on temperature and air humidity. After flowering a water content higher than 0.32 cm3 cm"3 was required. Two strategies for breeding ideotypes were evaluated; doubling the rooted depth and root growth rate stabilized seed yields (the s.d. was reduced by 30 % in set 1), but doubling the water extraction capacity of the crop had almost no effect. The model accounted for less than 1 % of the variation in set 2 (14 years; light silty loam; Netherlands) and 4 (3 years; 5 regional experimental farms; Netherlands). This was different from set 1 and 3 and probably due to effects of capillary rise (in set 2) and diseases (in set 4), which are not included in the model. In set 4, the yield gap between simulated and measured yields increased with observed disease attack in the field, from less than 1 t ha"' with 'absent or low' attack to more than 3.5 with 'severe' attack. The simulation studies show how control of water availability stabilizes faba bean yields in many environments. They also indicate the importance of disease control and of breeding ideotypes with deeper rooting capacity.
利用作物生长模型研究了不同供水方式对蚕豆产量变异的影响。该模型根据植物特性、天气和土壤数据模拟作物干物质生产和土壤水分有效性。利用来自西欧不同土壤和地点的4个数据集,评估了各种天气条件对生长的影响。在第1组(14岁;重粘土;荷兰)和设置3(2年;在西欧的9个地点),测量和模拟种子产量的线性回归,通过原点拟合,斜率几乎为1,占产量变化的68%(集1)和12%(集3)。在这两组中,如果排除冰雹、倒伏和疾病造成的损害影响的偏差(这些损害影响不在模型中计算),这些回归约占变异的80%。在第1组中,平均种子产量为5.3 t ha ' 1(实测和模拟),标准差(s.d)为1.3 t ha ' 1(实测)和1.5 t ha ' 1(模拟)。开花结束后(即从灌浆开始)的模拟灌溉在较高水平上稳定了产量(s.d = 0.4 t / hm2) (6.2 t / hm2)。整个季节的模拟灌溉几乎没有额外的效果。第3组的结果与第1组相似。对第1组的模拟表明,开花期间最佳最终种子产量的“目标”土壤含水量在这种土壤类型的0.27-0.32 cm3 cm”3之间变化(pf值分别为3和2.3),取决于温度和空气湿度。开花后水分要求高于0.32 cm3 cm”3。评估了两种理想型育种策略;根深和根生长速率加倍可以稳定种子产量(在第1组中s.d.减少了30%),但作物的抽水量加倍几乎没有影响。该模型在集合2(14年;轻粉质壤土;荷兰)和4(3年;5个区域实验农场;荷兰)。这与第1组和第3组不同,可能是由于毛细血管上升(第2组)和疾病(第4组)的影响,这些因素没有包括在模型中。在第4组中,模拟产量与实测值之间的产量差距随着田间观察到的病害程度而增加,从“无病或低病”的小于1 / 1英寸到“严重病”的大于3.5英寸。模拟研究显示了在许多环境下控制水分的有效性如何稳定蚕豆的产量。它们还表明了疾病控制和培育具有更深生根能力的理想型的重要性。