Developing green super rice varieties with high nutrient use efficiency by phenotypic selection under varied nutrient conditions
2019
Jewel, Zilhas Ahmed | Ali, Jauhar | Pang, Yunlong | Mahender, Anumalla | Acero, Bart | Hernandez, Jose | Xu, Jianlong | Li, Zhikang
The development of green super rice varieties with improved nutrient use efficiency (NuUE) is a vital target area to increase yield and make it more stable under rainfed conditions. In the present study, we followed an early backcross (BC) breeding approach by using a high-yielding and widely adapted Xian variety, Weed Tolerant Rice 1 (WTR-1), as a recipient and a Geng variety, Hao-An-Nong (HAN), as a donor. Starting from the BC1F2 generation, the BC population went through one generation of selection under irrigated, low-input, and rainfed conditions, followed by four consecutive generations of screening and selection for high grain yield (GY) under six different nutrient conditions (NPK, 75N, -N, -P, -NP, and -NPK), leading to the development of 230 BC1F6 introgression lines (ILs). These 230 ILs were evaluated under the same six nutrient conditions for 13 agro-morphological and grain yield component traits in comparison to four checks and parents. Significant trait variations were observed between the treatments and ILs. Positive correlations were identified for GY with biomass, panicle length, flag-leaf area, flag-leaf width, filled grain number per panicle, 1000-grain weight, and tiller number under -N, -P, -NP, and -NPK conditions. Out of 230 ILs, 12 were identified as promising under two or more nutrient deficiency conditions. The results demonstrated an efficient inter-subspecific BC breeding procedure with a first round of selection under rainfed-drought conditions, followed by four generations of progeny testing for yield performance under six nutrient conditions. The promising ILs can be useful resources for molecular genetic dissection and understanding the physiological mechanisms of NuUE. (C) 2019 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd
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