Spike number (SN) per unit area is one of the major determinants of grain yield in wheat. Development of high-throughput techniques to count SN from large populations enables rapid and cost-effective selection and facilitates genetic studies. In the present study, we used a deep-learning algorithm, i.e., Faster Region-based Convolutional Neural Networks (Faster R-CNN) on Red-Green-Blue (RGB) images to explore the possibility of image-based detection of SN and its application to identify the loci underlying SN. A doubled haploid population of 101 lines derived from the Yangmai 16/Zhongmai 895 cross was grown at two sites for SN phenotyping and genotyped using the high-density wheat 660K SNP array. Analysis of manual spike number (MSN) in the field, image-based spike number (ISN), and verification of spike number (VSN) by Faster R-CNN revealed significant variation (P < 0.001) among genotypes, with high heritability ranged from 0.71 to 0.96. The coefficients of determination (R²) between ISN and VSN was 0.83, which was higher than that between ISN and MSN (R² = 0.51), and between VSN and MSN (R² = 0.50). Results showed that VSN data can effectively predict wheat spikes with an average accuracy of 86.7% when validated using MSN data. Three QTL Qsnyz.caas-4DS, Qsnyz.caas-7DS, and QSnyz.caas-7DL were identified based on MSN, ISN and VSN data, while QSnyz.caas-7DS was detected in all the three data sets. These results indicate that using Faster R-CNN model for image-based identification of SN per unit area is a precise and rapid phenotyping method, which can be used for genetic studies of SN in wheat.

Powdery mildew caused by Blumeria graminis f. sp. tritici is one of the major wheat diseases worldwide. The Chinese wheat landrace Pingyuan 50 has shown adult-plant resistance (APR) to powdery mildew in the field for over 60 years. To dissect the genetic basis of APR to powdery mildew in this cultivar, a mapping population of 137 double haploid (DH) lines derived from Pingyuan 50/Mingxian 169 was evaluated in replicated field trials for two years in Beijing (2009–2010 and 2010–2011) and one year in Anyang (2009–2010). A total of 540 polymorphic SSR markers were genotyped on the entire population for construction of a linkage map and QTL analysis. Three QTL were mapped on chromosomes 2BS (QPm.caas-2BS.2), 3BS (QPm.caas-3BS), and 5AL (QPm.caas-5AL) with the resistance alleles contributed by Pingyuan 50 explaining 5.3%, 10.2%, and 9.1% of the phenotypic variances, respectively, and one QTL on chromosome 3BL (QPm.caas-3BL) derived from Mingxian 169 accounting for 18.1% of the phenotypic variance. QPm.caas-3BS, QPm.caas-3BL, and QPm.caas-5AL appear to be new powdery mildew APR loci. QPm.caas-2BS.2 and QPm.caas-5AL are possibly pleiotropic or closely linked resistance loci to stripe rust resistance QTL. Pingyuan 50 could be a potential genetic resource to facilitate breeding for improved APR to both powdery mildew and stripe rust.