What question did this study set out to answer?

This research aims to evaluate RGB imaging for detecting phenotypic differences in wheat genotypes under varying watering regimes.

June 14, 2026Open Access

Machine vision RGB phenotyping reveals divergent and real‐time responses to different watering regimes in near‐isogenic wheat genotypes

Puntos clave

This research aims to evaluate RGB imaging for detecting phenotypic differences in wheat genotypes under varying watering regimes.
Used high-throughput RGB imaging to assess side-projected area in genetically uniform wheat under different watering conditions.
This included modeling SPA with logistic growth curves to extract dynamic canopy traits.
Correlated these traits with yield, straw biomass, harvest index, and spike traits at maturity.
Under well-watered conditions, area under the curve was strongly associated with grain weight (R2 = 0.76, 95% CI: 0.59–0.87).
Weakened associations were observed under reduced watering, particularly post-anthesis, indicating reduced canopy size effects on reproductive output.
Distinct phenotypes and stress responses among wheat lines were revealed, highlighting the value of non-destructive phenotyping.

Resumen

Abstract This study assesses high‐throughput red, green, and blue (RGB) imaging as an approach for detecting subtle phenotypic differences under well‐watered and reduced watering conditions in genetically uniform wheat ( Triticum aestivum L.) populations. It aims to support the design of breeding populations by identifying parents with complementary coping mechanisms that can be combined in crosses to produce superior progeny. We used RGB imaging to monitor side‐projected area (SPA) in BC 2 F 6 wheat progenies under well‐watered, pre‐anthesis, and post‐anthesis reduced watering conditions. SPA was modeled with logistic growth curves per genotype to extract dynamic canopy traits, which, together with the area under the SPA‐based growth curve, were then correlated with yield, straw biomass, harvest index, and spike traits measured at maturity. Despite genetic similarity, RGB‐based imaging revealed distinct phenotypes under normal conditions and stress response strategies among wheat lines, highlighting the value of dynamic, non‐destructive phenotyping for identifying complementary response patterns. Under well‐watered conditions ( n = 36), area under the curve was strongly associated with grain weight ( R 2 = 0.76, 95% confidence interval CI: 0.59–0.87), but relationships weakened under reduced watering, especially post‐anthesis, indicating a reduced association of canopy size with reproductive output. The data revealed contrasting response patterns among breeding lines based on characteristics of the logistic growth curve under normal conditions, their recovery slope after pre‐flowering reduced watering, or conversion of their straw biomass into harvestable grains. RGB imaging enables real‐time, non‐destructive detection of reduced watering responses in genetically similar wheat lines and provides complementary in‐season data to design next‐generation breeding populations for climate‐resilient cultivars.

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