biostudies-literatureLu RBiological Breeding-National Science and Technology Major ProjectNational Key Research and Development Program of Chinakiaf666https://www.ebi.ac.uk/biostudies/studies/S-EPMC12854233biostudies-literatureUnknown200(1)The distribution of spikelets significantly affects wheat (Triticum aestivum L.) spike architecture. However, traditional methods lack the precision to study spikelet distribution effectively. We developed RachisSeg, a deep learning-based phenotyping pipeline that automatically measures traits from scanned rachis images. In addition to traditional spikelet number per spike (SNS), rachis length (RL), and spikelet density (SD, SNS/RL), we introduced spikelet distribution traits based on rachis internode lengths, providing quantitative insights into spike architecture. RachisSeg showed high consistency with manual measurements for SNS and RL, with the R2 values of 0.975 and 0.998, respectively. Using RachisSeg, we analyzed spikelet distribution patterns across wheat germplasm and found that tPlant physiologyImage-based rachis phenotyping facilitates genetic dissection of spikelet distribution in wheat.PMC128542332023YFF10001002023ZD04076Yan MLiu XLing HQLi ZYang LZheng SSi YJiang NLu RfalseImage-based rachis phenotyping facilitates genetic dissection of spikelet distribution in wheat.The distribution of spikelets significantly affects wheat (Triticum aestivum L.) spike architecture. However, traditional methods lack the precision to study spikelet distribution effectively. We developed RachisSeg, a deep learning-based phenotyping pipeline that automatically measures traits from scanned rachis images. In addition to traditional spikelet number per spike (SNS), rachis length (RL), and spikelet density (SD, SNS/RL), we introduced spikelet distribution traits based on rachis internode lengths, providing quantitative insights into spike architecture. RachisSeg showed high consistency with manual measurements for SNS and RL, with the R2 values of 0.975 and 0.998, respectively. Using RachisSeg, we analyzed spikelet distribution patterns across wheat germplasm and found that t2026-01-01T00:00:00Z2026 Jan2026-06-15T03:13:23.937Z2026-06-15T03:08:46.744ZS-EPMC128542334141921910.1093/plphys/kiaf666