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Simulation of leaf area development based on dry matter partitioning and specific leaf area for cut chrysanthemum.

ABSTRACT: This work aims to predict time courses of leaf area index (LAI) based on dry matter partitioning into the leaves and on specific leaf area of newly formed leaf biomass (SLA(n)) for year-round cut chrysanthemum crops. In five glasshouse experiments, each consisting of several plant densities and planted throughout the year, periodic destructive measurements were conducted to develop empirical models for partitioning and for SLA(n). Dry matter partitioning into leaves, calculated as incremental leaf dry mass divided by incremental shoot dry mass between two destructive harvests, could be described accurately (R(2 )= 0.93) by a Gompertz function of relative time, R(t). R(t) is 0 at planting date, 1 at the start of short-days, and 2 at final harvest. SLA(n), calculated as the slope of a linear regression between periodic measurements of leaf dry mass (LDM) and LAI, showed a significant linear increase with the inverse of the daily incident photosynthetically active radiation (incident PAR, MJ m(-2 )d(-1)), averaged over the whole growing period, the average glasshouse temperature and plant density (R(2 )= 0.74). The models were validated by two independent experiments and with data from three commercial growers, each with four planting dates. Measured shoot dry mass increase, initial LAI and LDM, plant density, daily temperature and incident PAR were input into the model. Dynamics of LDM and LAI were predicted accurately by the model, although in the last part of the cultivation LAI was often overestimated. The slope of the linear regression of simulated against measured LDM varied between 0.95 and 1.09. For LAI this slope varied between 1.01 and 1.12. The models presented in this study are important for the development of a photosynthesis-driven crop growth model for cut chrysanthemum crops.

SUBMITTER: Lee JH

PROVIDER: S-EPMC4244956 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Chrysanthemums (Chrysanthemum morifolium Ramat.) are famous ornamental crops with high medicinal and industrial values. The inflorescence and leaf traits are key factors that affect the yield and quality of chrysanthemum. However, the genetic improvement of those traits is slow within chrysanthemum because of its hexaploidy, high heterozygosity and enormous genome. To study the genetic control of the important traits and facilitate marker-assisted selection (MAS) in chrysanthemum, it is desirable to populate the genetic maps with an abundance of transferrable markers such as microsatellites (SSRs). A genetic map was constructed with expressed sequence tag-simple sequence repeat (EST-SSR) markers in an F1 progeny of 192 offspring. A total of 1000 alleles were generated from 223 EST-SSR primer pairs. The preliminary maternal and paternal maps consisted of 265 marker alleles arranged into 49 and 53 linkage groups (LGs), respectively. The recombined parental maps covered 906.3 and 970.1 cM of the genome, respectively. Finally, 264 polymorphic loci were allocated to nine LGs. The integrated map spanned 954.5 cM in length with an average genetic distance of 3.6 cM between two neighbouring loci. Quantitative trait loci (QTLs) analysis was performed using the integrated map for inflorescence diameter (ID), central disc flower diameter (CDFD), number of whorls of ray florets (NWRF), number of ray florets (NRF), number of disc florets (NDF), number of florets (NF), ray floret length (RFL), ray floret width (RFW), ray floret length/width (RFL/W), leaf length (LL), leaf width (LW) and leaf length/width (LL/W). Overall, 36 (21 major) QTLs were identified. The successful mapping of inflorescence and leaf traits QTL demonstrated the utility of the new integrated linkage map. This study is the first report of a genetic map based on EST-SSR markers in chrysanthemum. The EST-SSR markers, genetic map and QTLs reported here could be valuable resources in implementing MAS for chrysanthemums in breeding programs.

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Simulation of leaf area development based on dry matter partitioning and specific leaf area for cut chrysanthemum.

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