Leaf area estimation: a first step towards virtual rose breeding
Year: 2010
Type: conference-paper
Abstract: Introduction New genotypes (varieties) of hybrid tea roses are introduced at a high rate. At the same time growing conditions like greenhouse climate and cropping systems are also rapidly changing and diversifying, and, varieties may be grown all over the world. For a breeder, the challenge is to efficiently breed the best variety for specific environments. However, at present, breeders and growers lack appropriate tools to find the most suitable combination of greenhouse technology, plant management and genotype other than their own experience and trial and error. A model that integrates all relevant information and that can predict performance of genotypes under a variety of combinations, can serve as an important decision support system for plant breeding. A crop growth model is an excellent means to predict plant performance under a wide range of conditions, based on a limited number of plant characteristics. However, in order to predict stem production and quality of cut rose, we have to take into account the 3D architecture of the plant. The aim of this study is to develop a functional-structural model for rose and to parameterize it for a large number of genotypes (150). We also want to find genetic markers that are associated with genotype-specific model parameters. The hypothesis for the latter is that model parameters are more directly linked to genetic information than direct plant measurements of yield as the latter are the final result of complex interactions between different physiological processes, including sink-source. Hence Quantitative Trait Loci (QTL) for these model parameters are expected to be more specific and stable over environments than QTL for those directly measured traits (Van Eeuwijk et al., 2010). The potential of this “gene-to-phenotype” modeling approach was illustrated in a simulation study by Chenu et al. (2009). In this presentation, different aspects of the virtual rose breeding project will be shown, (1) the currently available functional structural plant model for a single variety; (2) a description of the experiments; (3) the measurements carried out on the genotypes; (4) the genetic markers; (5) the integrative approach, estimating the model parameters from the measurements and finding genetic markers for the model parameters. To reach the final aim of virtual rose breeding, a huge number of measurements need to be made during growth and development of the genotypes at all locations; such a data collection effort is often referred to as ‘large scale phenotyping’. One of the most important measurements to parameterize a crop growth model is leaf area. Hence we need a cheap, fast, unbiased and non-destructive method to measure/estimate leaf area of all the genotypes. In this presentation emphasis will be given on the development of such a method for roses. A common approach for leaf area estimation is to develop ratios and regression estimators by using easily measurable leaf parameters such as leaf length and leaf width (Schwarz and Klaring, 2001). Various combinations of measurements and various models relating length and width to area have been developed for several crops, such as sunflower (Chanda and Singh, 1997; Bange et al., 2000), avocado (Uzun and Celik, 1999), grape (Montero et al., 2000; Williams and Martinson, 2003), and hazelnut (Cristofori et al., 2007). Since leaf shape (length/width ratio) may vary among different genotypes (Stoppani et al., 2003), most statistical models demonstrated a relationship between leaf area and length and width or the product of length and width. For rose, no such length/width model has been reported. A rose leaf has a pinnate shape with a laminar structure as a central rib with leaflets on each side and one terminal leaflet. A leaf usually consists of one to eleven leaflets. Some rose leaves have ovate leaflets, other rose leaves have lanceolate leaflets, and this may differ between genotype. The number of leaflets per leaf depends on the leaf rank along the stem.
Authors: G.W.A.M. van der Heijden, M. Gao, J. Vos, Gerhard Buck-Sorlin, L.F.M. Marcelis
Institution: Wageningen University & Research
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W1604530411