关键词: 辣椒, 耐低氮, 筛选指标, 模糊隶属函数, 主成分分析

Abstract: To develop a rapid and effective method for screening low nitrogen resistant pepper cultivars at seedling stage，the tolerance of 25 different pepper genotypes under low nitrogen stress was evaluated by hydroponic investigations. It indicated that 18 morphological and physiological indexes of pepper at seedling stage were affected by low nitrogen treatment，however，the effect degrees among genotypes were significantly different. Based on their higher coefficients of variation，relative values of 8 indexes including leaf area，dry weight of shoot，dry weight of root，root-shoot ratio of dry weight，dry weight of plant，nitrogen accumulation of shoot，nitrogen accumulation of root and nitrogen accumulation of plant were selected as the key indexes for screening and evaluation of low nitrogen tolerance of pepper. The low nitrogen tolerance of pepper was evaluated by fuzzy membership function with the normalized coefficients of variation of the 8 key indexes and all of the 18 indexes as weight，and the evaluation results were compared with the results of principal component analysis. It was showed that the evaluation results of the two analysis method were largely identical，so were the 8 key indexes and the 18 indexes，the coincidences rates of low nitrogen tolerance and sensitivity of the first 5 materials were above 80%. The nitrogen tolerance of 3 pepper materials with different degree of nitrogen tolerance at seedling stage was evaluated at maturity stage and it was revealed that the results were largely identical to that of seedling stage. Excepted for root-shoot ration of dry weight，significant correlations between the other 7 of the 8 key screening indexes and the nitrogen tolerance of pepper at maturity stage were observed. It is suggested that we can effectively and in large quantities evaluated the nitrogen tolerance of pepper at seedling stage by the 8 key screening indexes and fuzzy membership function.

Key words: pepper, nitrogen tolerance, screening index, fuzzy membership function, principal component analysis