Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6374968 | Field Crops Research | 2015 | 9 Pages |
Abstract
Understanding plant traits that are associated with high grain yield and high nitrogen use efficiency (NUE) is very important in breeding program to develop N-efficient varieties. However, such traits are yet to be identified in rice. We investigated this issue using rice varieties differing in response to N rates. Four japonica rice varieties, Huaidao 5 (HD-5), Lianjing 7 (LJ-7), Ninjing 1 (NJ-1) and Yangjing 4038 (YJ-4) were grown in the field, and four N rates, 0, 100, 200 and 300 kg haâ1, were applied during the growing season. Results show that both HD-5 and LJ-7 produced higher grain yield, took up higher amount of N from the soil, and exhibited higher NUE than NJ-7 or YJ-4 at lower N rates (0, 100 or 200 kg haâ1). Grain yield and NUE were comparable among the four varieties at the N rate of 300 kg haâ1. When compared with NJ-1 or YJ-4, both HD-5 and LJ-7 had greater root and shoot biomass, deeper root distribution, longer root length, greater root length density, root oxidation activity and crop growth rate, higher photosynthetic NUE, and more remobilization of nonstructural carbohydrate from stems during grain filling at lower N rates. Our results suggest that HD-5 and LJ-7 can maintain grain yield at lower N rates as N-efficient varieties. The shoot and root traits, especially the deeper roots, greater root oxidation activity and higher photosynthetic NUE at lower N rates, could be used in selection for N-efficient rice varieties.
Keywords
ROAN harvest indexHINAENpFPNRoot oxidation activityPNUEN physiological efficiencyinternal N use efficiencyIENRENCgrDATNUENitrogen use efficiency (NUE)NSCNitrogen use efficiencyPhotosynthetic nitrogen use efficiencyRice (Oryza sativa L.)root length densityPENdays after transplantingCrop growth ratedry weightNonstructural carbohydrate
Related Topics
Life Sciences
Agricultural and Biological Sciences
Agronomy and Crop Science
Authors
Chengxin Ju, Roland J. Buresh, Zhiqin Wang, Hao Zhang, Lijun Liu, Jianchang Yang, Jianhua Zhang,