Genetic mechanism deciphering on nitrogen-use efficiency in maize and innovative research on germplasm resources using modern molecular biology and artificial intelligence (AI) technology, including high-throughput genome sequencing data analysis, crutial genes identification for efficient nitrogen utilization, heterosis utilization and its genetic basis dissection, whole genome selection, development of noval molecular markers, and molecular breeding

Collection and identification of excellent wheat germplasm resources; Mining of new genes controlling important traits; Germplasm innovation; Location and genetic analyses of new genes controlling important target traits of wheat such as high quality and disease (stress) resistance by modern molecular genetics combined with precise identification of phenotypes; Breeding and utilization of new excellent wheat germplasm with molecular marker-assisted selection (MAS) and gene editing

Collection, precise identification and innovative utilization of rice germplasm resources; Exploring superior haplotypes with high quality, broad-spectrum blast resistance genes using omics big data analysis and classical and molecular genetics for rice breeding; Developing efficient molecular marker systems and create elite introgression lines (ILs) with rice modern varieties as the genetic background

Ensuring germplasm safety and facilitating resource sharing; Focusing on the requirements of food safety and development of the seed industry; Preservation of crop germplasm resources and protection of genetic diversity; Undertaking public welfare and basic work such as the investigation and collection of crop germplasm resources in Jiangsu Province, safe preservation, breeding identification, cataloging management, sharing and distribution to drive the innovation of agricultural science and technology

Testing the distinctness, uniformity, and stability (referred to as DUS test for short) of agricultural plant varieties; Research and identification of new technologies for protecting and testing various plant varieties based on the quality policy of “scientific, rigorous, objective, and fair”

 Study of the characteristics and their relationships of the genome, transcriptome, metabolome and phenotype of major crops with latory networks while building machine learning models and applying them to crop progeny genome prediction and germplasm creation

Crop improvement, molecular design breeding, herbicide resistance and disease resistance