Development of a Multi-Criteria Decision-Making Approach for Evaluating the Comprehensive Application of Herbaceous Peony at Low Latitudes

Int J Mol Sci. 2022 Nov 18;23(22):14342. doi: 10.3390/ijms232214342.

Abstract

The growing region of herbaceous peony (Paeonia lactiflora) has been severely constrained due to the intensification of global warming and extreme weather events, especially at low latitudes. Assessing and selecting stress-tolerant and high-quality peony germplasm is essential for maintaining the normal growth and application of peonies under adverse conditions. This study proposed a modified multi-criteria decision-making (MCDM) model for assessing peonies adapted to low-latitude climates based on our previous study. This model is low-cost, timesaving and suitable for screening the adapted peony germplasm under hot and humid climates. The evaluation was conducted through the analytic hierarchy process (AHP), three major criteria, including adaptability-related, ornamental feature-related and growth habits-related criteria, and eighteen sub-criteria were proposed and constructed in this study. The model was validated on fifteen herbaceous peonies cultivars from different latitudes. The results showed that 'Meiju', 'Hang Baishao', 'Hongpan Tuojin' and 'Bo Baishao' were assessed as Level I, which have strong growth adaptability and high ornamental values, and were recommended for promotion and application at low latitudes. The reliability and stability of the MCDM model were further confirmed by measuring the chlorophyll fluorescence of the selected adaptive cultivars 'Meiju' and 'Hang Baishao' and one maladaptive cultivar 'Zhuguang'. This study could provide a reference for the introduction, breeding and application of perennials under everchanging unfavorable climatic conditions.

Keywords: analytic hierarchy process (AHP); breeding; germplasm resources; global warming; herbaceous peony; low latitudes; multi-criteria decision-making (MCDM).

MeSH terms

  • Paeonia*
  • Plant Breeding
  • Plants
  • Reproducibility of Results