A dataset of observed phenology images of 11 crops including sorghum in China

The change of phenology of crops directly affects the accumulation, quality and yield of photosynthetic products. Based on the historical photos data of 642 national agrometeorological observation stations and 69 national agrometeorological experimental stations and the photos data taken by professional agrometeorological observers, 1376 high-quality photos that can objectively reflect the structure and morphological characteristics of crops were selected from tens of thousands of photos. Through historical photo data collection, missing photos supplement, screening and sorting, multiple rounds of expert identification, data quality control and quality evaluation and other links, and in strict accordance with the standard of crop phenology specified in the “specification for agrometeorological observation (Volume I)”, 179 photos were selected to build the dataset. It includes 11 sub folders, respectively storing 27 photos of sorghum, 17 photos of foxtail millet, 12 photos of sweet potato, 14 photos of potato, 24 photos of peanut, 13 photos of sesame, 17 photos of sunflower, 9 photos of sugarcane, 17 photos of flax, 9 photos of sugar beet and 20 photos of tobacco, a total of 179 photos of key development stages of crops, with a total size of 516.89 MB. The dataset is classified according to the characteristics of crops and their phenological phases, with their growth and development process as the main line, so as to directly reflect the morphological structure characteristics of crops at different growth stages. The photo dataset can comprehensively display the technical standards and methods of agrometeorological observation of crops in the phenological phase. It can help agrometeorological observers to grasp the manual observation technology quickly, accurately and systematically in a short time, and improve the operational ability of agrometeorological observation and the quality of observation data. It can provide reliable data support for the research of automatic identification algorithm of crop phenological phase, agricultural production strategies to deal with climate change, and has important reference value for the research and technical training of agrometeorological manual observation technology, cultivation and management of crops, related education and popular science curriculum development.