PDF(Pubmed)
Abstract：
Climate change has brought an alarming situation in the scarcity of fresh water for irrigation due to the present global water crisis, climate variability, drought, increasing demands of water from the industrial sectors, and contamination of water resources. Accurately evaluating the potential of future rice genotypes in large-scale, multi-environment experiments may be challenging. A key component of the accurate assessment is the examination of stability in growth contexts and genotype-environment interaction. Using a split-plot design with three replications, the study was carried out in nine locations with five genotypes under continuous flooding (CF) and alternate wet and dry (AWD) conditions. Utilizing the web-based warehouse inventory search tool (WIST), the water status was determined. To evaluate yield performance for stability and adaptability, AMMI and GGE biplots were used. The genotypes clearly reacted inversely to the various environments, and substantial interactions were identified. Out of all the environments, G3 (BRRI dhan29) had the greatest grain production, whereas G2 (Binadhan-8) had the lowest. The range between the greatest and lowest mean values of rice grain output (4.95 to 4.62 t ha-1) was consistent across five distinct rice genotypes. The genotype means varied from 5.03 to 4.73 t ha-1 depending on the environment. In AWD, all genotypes out performed in the CF system. With just a little interaction effect, the score was almost zero for several genotypes (E1, E2, E6, and E7 for the AWD technique, and E5, E6, E8, and E9 for the CF method) because they performed better in particular settings. The GGE biplot provided more evidence in support of the AMMI study results. The study\'s findings made it clear that the AMMI model provides a substantial amount of information when evaluating varietal performance across many environments. Out of the five accessions that were analyzed, one was found to be top-ranking by the multi-trait genotype ideotype distance index, meaning that it may be investigated for validation stability measures. The study\'s findings provide helpful information on the variety selection for the settings in which BRRI dhan47 and BRRI dhan29, respectively, performed effectively in AWD and CF systems. Plant breeders might use this knowledge to choose newer kinds and to design breeding initiatives. In conclusion, intermittent irrigation could be an effective adaptation technique for simultaneously saving water and mitigating GHG while maintaining high rice grain yields in rice cultivation systems.
摘要：
由于当前的全球水危机，气候变化带来了灌溉淡水短缺的令人震惊的情况，气候变异,干旱,工业部门对水的需求不断增加，和水资源的污染。准确评估未来水稻基因型的潜力，多环境实验可能具有挑战性。准确评估的关键组成部分是检查生长环境和基因型-环境相互作用的稳定性。使用具有三个复制的分割图设计，该研究是在连续洪水（CF）和干湿交替（AWD）条件下在9个地点进行的，具有5种基因型。利用基于网络的仓库库存搜索工具(WIST)，水的状况已经确定。为了评估产量性能的稳定性和适应性，使用AMMI和GGE双曲线。基因型显然与各种环境相反，并确定了实质性的相互作用。在所有的环境中，G3(BRRIdhan29)的粮食产量最高，而G2（Binadhan-8）最低。在五种不同的水稻基因型中，稻米产量的最大和最低平均值（4.95至4.62tha-1）之间的范围是一致的。根据环境的不同，基因型均值从5.03到4.73tha-1不等。在AWD中,所有基因型都在CF系统中表现出来。只有一点互动效应，对于几种基因型（AWD技术的E1，E2，E6和E7，和CF方法的E5，E6，E8和E9），因为它们在特定设置中表现更好。GGE双plot提供了更多证据支持AMMI研究结果。该研究的发现清楚地表明，AMMI模型在评估许多环境中的品种表现时提供了大量信息。在所分析的五个种质中，其中一个被多性状基因型理想型距离指数排名第一，这意味着它可以进行调查，以验证稳定性措施。这项研究的发现为BRRIdhan47和BRRIdhan29的品种选择提供了有用的信息，在AWD和CF系统中有效执行。植物育种者可能会利用这些知识来选择较新的品种并设计育种计划。总之,间歇灌溉可能是一种有效的适应技术，可以同时节水和减少温室气体排放，同时在水稻种植系统中保持水稻的高产量。
