Predicting effects of drainage water management in Iowa's subsurface drained landscapes

Long-term hydrologic simulations are presented predicting the effects of drainage water management on subsurface drainage, surface runoff and crop production in Iowa's subsurface drained landscapes. The deterministic hydrologic model, DRAINMOD was used to simulate Webster (fine-loamy, mixed, superactive, mesic) soil in a Continuous Corn rotation (WEBS_CC) with different drain depths from 0.75 to 1.20 m and drain spacing from 10 to 50 m in a combination of free and controlled drainage over a weather record of 60 (1945-2004) years. Shallow drainage is defined as drains installed at a drain depth of 0.75 m, and controlled drainage with a drain depth of 1.20 m restricts flow at the drain outlet to maintain a water table at 0.60 m below surface level during the winter (November-March) and summer (June-August) months. These drainage design and management modifications were evaluated against conventional drainage system installed at a drain depth of 1.20 m with free drainage at the drain outlet. The simulation results indicate the potential of a tradeoff between subsurface drainage and surface runoff as a pathway to remove excess water from the system. While a reduction of subsurface drainage may occur through the use of shallow and controlled drainage, these practices may increase surface runoff in Iowa's subsurface drained landscapes. The simulations also indicate that shallow and controlled drainage might increase the excess water stress on crop production, and thereby result in slightly lower relative yields. Field experiments are needed to examine the pathways of water movement, total water balance, and crop production under shallow and controlled drainage in Iowa's subsurface drained landscapes.     

High throughput phenotyping for aphid resistance in large plant collections

ABSTRACT: BACKGROUND: Phloem-feeding insects are among the most devastating pests worldwide. They not only cause damage by feeding from the phloem, thereby depleting the plant from photo-assimilates, but also by vectoring viruses. Until now, the main way to prevent such problems is the frequent use of insecticides. Applying resistant varieties would be a more environmental friendly and sustainable solution. For this, resistant sources need to be identified first. Up to now there were no methods suitable for high throughput phenotyping of plant germplasm to identify sources of resistance towards phloem-feeding insects. RESULTS: In this paper we present a high throughput screening system to identify plants with an increased resistance against aphids. Its versatility is demonstrated using an Arabidopsis thaliana activation tag mutant line collection. This system consists of the green peach aphid Myzus persicae (Sulzer) and the circulative virus Turnip yellows virus (TuYV). In an initial screening, with one plant representing one mutant line, 13 virus-free mutant lines were identified by ELISA. Using seeds produced from these lines, the putative candidates were re-evaluated and characterized, resulting in nine lines with increased resistance towards the aphid. CONCLUSIONS: This M. persicae-TuYV screening system is an efficient, reliable and quick procedure to identify among thousands of mutated lines those resistant to aphids. In our study, nine mutant lines with increased resistance against the aphid were selected among 5160 mutant lines in just 5 months by one person. The system can be extended to other phloem-feeding insects and circulative viruses to identify insect resistant sources from several collections, including for example genebanks and artificially prepared mutant collections.