The phenotype, as outcome of genotype that interplays with environmental factors, includes different traits such as architecture, growth stage, yield characters, quality, and resistance to biotic and abiotic stresses. After long-term natural variations in eco-system as well as domestication and cultivation in agricultural eco-system crop germplasm obtained rich genetic and phenotypic diversity, as the fundamental basis in breeding for new varieties. It is of interest to explore and understand the phenotypic diversity by scientific and systematical identification and evaluation. Identifying elite germplasm resources that showed drought and heat tolerant, disease and pest resistant, high efficient use of water and fertilizer is absolutely important to breed new varieties with environmental adaptability under global climate change. Testing for phenotypic variations under controlled environment at multiple locations for years is desirable and highly recommended. The methods for identifying phenotypic variations are conducted in the fields, facilities, instruments and with person sensory. The identification of crop germplasm traits, which were surveyed at one environment (locus) with expected low-throughput and low accuracy, has been popularly performed at multi-environments with high-throughput and precise characterization. By taking advantage of rapid development on technologies of multi-Omics, artificial intelligence, image recognition and analysis, researches on phenotypic traits of crop germplasm resource will step for a new stage, valuable for crop breeding in the future.