Speaker
Description
Introduction
Wheat (Triticum aestivum) and barley (Hordeum vulgare) are cereal grain crops vital for global food security. Adapting crop life cycles and agronomic management to changing climates is critical to increase yields to meet anticipated global demand. The study of crop species development and phenology has thus never been more important or urgent. Such studies depend on the ability to reliably measure and communicate crop development with repeatable and reproducible protocols.
Methods
New scales for assessing the development of wheat and barley were created as part of a national Australian project (Hunt et al., 2020) to improve the accuracy of cereal phenology modelling in APSIM-NG (Holzworth et al., 2018). The scales were developed and tested on a panel of 64 wheat and 32 barley genotypes that were grown in controlled environments with limiting or saturating photoperiod and vernalisation conditions (Bloomfield et al., 2023), and in time-of-sowing field experiments across Australia at sites with diverse geography and climate (Celestina et al., 2023b).
Results
The two new scales of wheat and barley development are the Single Culm Development Scale (SCDS) and the Population of Culms Development Scale (PCDS) (Celestina et al., 2023a). The SCDS defines progression through the lifecycle of an individual plant, whereas the PCDS accommodates population variation in the timing and duration of lifecycle events in a crop canopy (Figure 1).
Figure 1. The Single Culm Development Scale (SCDS) and Population of Culms Development Scale (PCDS) applied to the life cycle of wheat and barley. Adapted from Celestina et al., (2023a).
The SCDS has twelve phases that are disaggregated into stages and is measured on the primary culm of a single plant. Phases in the SCDS may occur concurrently within a single culm. Using the SCDS, a user makes a single observation at one time point to obtain an instantaneous measure of development. For example, a grower or their agronomist might use the SCDS for a rapid assessment of development in the field for the purpose of aligning crop inputs with optimal development stage.
In comparison, the PCDS has ten phases that are delimited by stages and is measured on all culms in a population. Phases in the PCDS are discrete and sequential. Using the PCDS, a user makes multiple observations over time to retrospectively determine the timing of stages and duration of phases. For example, a plant breeder might use the PCDS to compare the time taken for different cultivars to reach 50% anthesis in field evaluation experiments.
Discussion
Compared to existing scales of development such as a the widely-used Zadoks decimal code (Zadoks et al., 1974), the SCDS and PCDS describe development in terms that are unambiguous, objective and quantitative, and they are presented with protocols that ensure repeatable and reproducible results. These new scales distinguish between plant- and crop-level development; they merge and fill gaps within existing published scales; and they are compatible with modern technologies such as simulation modelling and automated image analysis.
The SCDS and PCDS have been successfully used for the parameterisation and validation of the APSIM-NG cereal phenology model and the development of a scheme to classify wheat and barley cultivars based on relative lifecycle length (Celestina et al., 2023b). These applications of the new scales demonstrate their utility and highlights their potential to facilitate ongoing advances in agronomy.
References
Bloomfield, Celestina, Hunt, et al., 2023. Vernalisation and photoperiod responses of diverse wheat genotypes. Crop & Pasture Science 74, 405–422. https://doi.org/10.1071/CP22213
Celestina, Hunt, Brown, et al., 2023a. Scales of development for wheat and barley specific to either single culms or a population of culms. European Journal of Agronomy 147, 126824. https://doi.org/10.1016/j.eja.2023.126824
Celestina, Hunt, Kuchel, et al., 2023b. A cultivar phenology classification scheme for wheat and barley. European Journal of Agronomy 143, 126732. https://doi.org/10.1016/j.eja.2022.126732
Holzworth, Huth, Fainges, et al., 2018. APSIM Next Generation: Overcoming challenges in modernising a farming systems model. Environmental Modelling and Software 103, 43–51. https://doi.org/10.1016/j.envsoft.2018.02.002
Hunt, Celestina, Bloomfield, 2020. Optimal sowing times for wheat and barley cultivars may soon be at our fingertips. GRDC Groundcover Supplement: Enabling Technologies May-June 2020.
Zadoks, Chang, Konzak, 1974. A decimal code for the growth stages of cereals. Weed Research 14, 415–421. https://doi.org/10.1111/j.1365-3180.1974.tb01084.x
| Keywords | development; phenology; growth, cereal; decimal code |
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