Use of crop growth models to evaluate physiological traits in genotypes of horticultural crops

Abstract

Quantifying the relevance of different plant traits for yield and quality under different growth conditions can improve the efficiency of a breeding programme. Crop models are powerful tools to give guidance to breeding, because model calculations enable the analysis of many different situations (sensitivity analysis and scenario studies). Three case studies of using crop growth models to evaluate physiological traits potentially used in breeding programmes are presented. The models used are explanatory models, with several submodels; e.g., for light interception, leaf photosynthesis, organ formation and biomass partitioning. Case study 1: It is hypothesized that yield improvement of cut chrysanthemum can be obtained by a higher specific leaf area (SLA) or a higher light-saturated leaf photosynthetic rate (Pg,max). Model calculations showed that for a winter planting, a higher SLA has more impact on yield than improving Pg,max, whereas for a summer-grown crop Pg,max and SLA are of equal importance for yield. Case study 2: Regarding the yield of tomato, it is hypothesized that new genotypes, with two leaves in between trusses, may improve yield. In tomato cultivars generally there are three leaves in between two trusses. The formation of fewer leaves favours dry-matter partitioning towards the fruits, but it also decreases leaf area index (LAI), resulting in less light interception. Model calculations showed that a genotype with two instead of three leaves between trusses indeed will improve yield. To maximize the benefit of this trait it is important to keep the LAI sufficiently high. Case study 3: It is hypothesized that modified tomato genotypes that show a shade avoidance response will result in higher yields as they can be grown at higher planting densities. Model calculations for tomato showed that this modification would hardly influence total yield. Standard conditions already result in a high light interception, which can hardly be improved by a higher planting density. Hence, it may be questioned whether for tomato developing genotypes with suppressed shade avoidance response for yield improvement is worthwhile. In conclusion, crop growth models are powerful tools to evaluate the impact of differences in crop characteristics under different growth conditions. Such quantitative evaluations are important to focus breeding programmes and to ideotype genotypes for different environments