Crop growth model‐enabled genetic mapping of biomass accumulation dynamics in photoperiod‐sensitive sorghum

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Abstract
Crop growth rate is a critical physiological trait for forage and bioenergy crops like sorghum [ Sorghum bicolor (L.) Moench], influencing overall crop productivity, particularly in photoperiod‐sensitive (PS) types. Crop growth rate studies focus on either a physiological approach utilizing a few genotypes to analyze biomass accumulation or a genetic approach characterizing easily scorable proxy traits in larger populations. Thus, the genetic control of crop growth rate in terms of biomass accumulation is poorly understood in PS sorghum. In this study, we monitored biomass accumulation in a diverse panel comprising 269 PS sorghum accessions in two growing seasons. We performed sequential samplings at 11 timepoints, separating leaves from stems. For the total biomass and each fraction, we applied the beta growth function to determine the maximum crop growth rate ( c m ), maximum biomass accumulation ( w max ), and time to c m ( t m ). Significant genetic variability was observed for all three parameters. Our analysis identified a practical window for c m assessment through accumulated biomass at 60–70 days after planting. Genome‐wide association analysis suggested distinct and independent genetic controls of leaf and stem biomass accumulation, both physically and temporally. Common genomic regions were discovered controlling w max and c m of stem and total biomass. These results provide new insights into the genetic control of crop growth rate, highlighting promising genomic regions for functional validation. This research also offers practical applications for plant breeding programs demonstrating the feasibility of selecting superior genotypes for both early and late biomass accumulation to enhance crop productivity.
Funding Information
  • National Institute of Food and Agriculture (Project #IOW05768, #IOW05730)

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