Defining durum wheat ideotypes adapted to Mediterranean environments through remote sensing traits

Area of Science:

• Agricultural Science
• Plant Breeding
• Remote Sensing

Background:

• Durum wheat is a vital crop in the Mediterranean, but phenotyping limits breeding progress.
• Remote sensing offers a potential solution to overcome phenotyping bottlenecks in durum wheat breeding.

Purpose of the Study:

• To identify optimal remote sensing traits for predicting durum wheat grain yield under Mediterranean conditions.
• To define durum wheat ideotypes by selecting key phenotypic traits related to plant physiology and growth.

Main Methods:

• Assessed 24 durum wheat cultivars across 19 environments in Spain over 3 years.
• Utilized RGB and multispectral vegetation indices and canopy temperature at anthesis and grain filling.
• Employed random forest regression models to evaluate remote sensing parameters as grain yield predictors.

Main Results:

• Biomass and canopy greenness indicators consistently predicted grain yield across all environments and phenological stages.
• Water status measurements were more crucial during anthesis in low-yielding environments, while grain filling predictions were better in high-yielding ones.
• Remote sensing traits related to pigment content and photosynthetic capacity were important in warmer conditions, particularly during grain filling.

Conclusions:

• Canopy greenness indicators are highly correlated with durum wheat grain yield, regardless of phenological stage or environment.
• Remote sensing provides valuable data for selecting durum wheat ideotypes, improving breeding efficiency for Mediterranean agriculture.
• Canopy temperature effectively accounts for water status variations, reducing the need for additional measurements like carbon isotope composition.