Effect of pattern of water supply on Vicia faba L. 4. Simulation studies on yield variability.

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 cm 3 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 cm 3 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.

Adapting the CROPGRO Legume Model to Simulate Growth of Faba Bean

“…Except for one spring type, the slope of days to flower vs. daylength was the same for all types, but the types differed in the apparent intercept to the longest daylength at which rate of development was most rapid (range was 12 h for spring type to more than 24 h for the slowest winter type). We concluded that there is a wide array of faba bean types such that degree‐day–oriented coefficients without daylength sensitivity may work for spring types in Germany (Stutzel, 1995a, 1995b) and the Netherlands (Grashoff and Stokkers, 1992) but not for winter types grown in France, Spain, and the Mediterranean. Evans (1957) found evidence of vernalization in the winter types; however, this was the only reference in the literature.…”