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首页> 外文期刊>International Journal of Plant & Soil Science >Performance of Stress Indices in Assessing High Yield Potential of Rice Genotypes in Sulfur Deficient Soil
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Performance of Stress Indices in Assessing High Yield Potential of Rice Genotypes in Sulfur Deficient Soil

机译:胁迫指数在缺硫土壤中水稻基因型高产潜力评估中的应用。

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Aim: To recognize the rice genotypes based on stress indices which would give higher yield both under sulfur stress and non-stress conditions. Design Factorial Randomized design with two factors Place and Duration of Study: It was conducted in the farmers field( Chidambaram and Kuthalam in Tamilnadu, India and during Kharif season ( June to September , 2009) Methodology: Field experiments were conducted in two soils Kondal series (Typic Haplusterts- Vertisol) and Padugai series (Typic Ustifluvents- Entisol). The treatment details are factor A–S levels ( 0 & 10 mg S kg-1) applied through gypsum and Factor B- Rice genotypes (ADT 43,CO 47,ADT 39,CO 43,ADT 42,ASD 19,ADT 36,ADT 37,ADT 38 and CO45). The yield data from two soils was used to calculate for each genotype 1) Stress tolerance (TOL) 2) Mean productivity (MP) 3) Geometric mean productivity (GMP) 4) Stress susceptibility index (SSI) and 5) Stress tolerance index (STI). Results: Grain yield varied significantly (P=0.05) among rice genotypes regardless of S treatments. Without added S treatment CO 43 (4865 kg ha-1) and CO 47 (5025 kg ha-1) produced highest grain yield and ADT 36 (3437,3775 kg ha-1) produced lowest yield in Kondal and Padugai series, respectively. Stress susceptibility index (SSI) and stress tolerance index (TOL) was associated with low yield under S sufficient condition. But stress tolerance index, mean productivity (MP) and geometric mean productivity (GMP) was able to identify top yielders both under S stress and non stress situations because of very strong correlation with yield. Accordingly best performers based on STI under both S stress and non- stress were ADT 43, CO 47, ADT 39 and CO 43.
机译:目的:根据胁迫指数识别水稻基因型,无论在硫胁迫还是在非胁迫条件下,水稻均能获得更高的产量。设计有两个因素的因子分解随机设计研究的地点和持续时间:在农民田间(印度Tamilnadu的Chidambaram和Kuthalam)和Kharif季节(2009年6月至9月)进行。方法:在两种土壤Kondal系列中进行了田间试验。 (典型的Haplusterts- Vertisol)和Padugai系列(典型的Ustifluvents- Entisol),治疗细节是通过石膏施用的A–S因子水平(0和10 mg S kg-1)和B基因型水稻(ADT 43,CO 47) (ADT 39,CO 43,ADT 42,ASD 19,ADT 36,ADT 37,ADT 38和CO45)。每种基因型使用两种土壤的产量数据来计算1)耐胁迫性(TOL)2)平均生产力( MP)3)几何平均生产率(GMP)4)应力敏感性指数(SSI)和5)应力耐受指数(STI)。结果:无论采用何种处理方式,不同基因型的水稻的籽粒产量差异均显着(P = 0.05)。在未添加S处理的情况下,在Kondal和Padugai系列中,CO 43(4865 kg ha-1)和CO 47(5025 kg ha-1)分别产生最高的谷物产量和ADT 36(3437,3775 kg ha-1)产生的最低谷物产量。在S充足条件下,胁迫敏感性指数(SSI)和胁迫耐受指数(TOL)与低产相关。但是,由于耐性指数,平均生产力(MP)和几何平均生产力(GMP)能够在S胁迫和非胁迫条件下识别出最高产量,因为它与产量的相关性非常强。因此,在S应力和非应力下基于STI的最佳性能是ADT 43,CO 47,ADT 39和CO 43。

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