■枯萎病是水稻的主要病害之一,造成广泛的作物损失。在正在进行的营养密集型水稻种植系统中使用半矮秆水稻品种进一步加剧了该病的发病率。该问题的理想解决方案是确定稳定的耐鞘枯病基因型。
■在两个地点(农业研究农场,农业科学研究所,Banaras印度教大学(28.18°N,38.03°E,和75.5masl),在2015年至2018年的雨季(Kharif)和国家水稻研究所的两个季节(20°27\'09\“N,东经85°55\'57\",26masl),Cuttack,奥里萨邦,在2019年的旱季(rabi)和2019年的kharif,包括易感和抗性检查。在4周内收集疾病指数百分比数据(7日,14日,21日,感染后第28天),以及其他形态和生理特征的数据。
■与敏感检查Tapaswini(G32)(半纤维素12.96,氮1.38)相比,跨季节的抗性基因型是半纤维素含量较高(13.93-14.64)和氮含量较低(1.10-1.31)的基因型,这也许可以解释耐药反应。三种不同的稳定性模型-加性主效应和乘法相互作用(AMMI),基因型+基因型x环境(GGE)双plot,然后使用多性状稳定性指数(MTSI)来鉴定六个季节的稳定抗性基因型。所有三个模型获得的结果都具有共同的基因型,突出显示为稳定且疾病进展曲线(AUDPC)值下面积低。具有低发病率的理想稳定基因型是IC283139(G19),泰特普(G28),IC260917(G4),和IC277274(G10),AUDPC值分别为658.91、607.46、479.69和547.94。天气参数,如温度,降雨,日照时数,和相对湿度也每天记录。相对湿度与疾病百分比指数呈正相关。
UNASSIGNED: Sheath blight caused by Rhizoctonia solani is one of the major diseases of rice, causing widespread crop losses. The use of semi-dwarf rice varieties in the ongoing nutrient-intensive rice cultivation system has further accentuated the incidence of the disease. An ideal solution to this problem would be identifying a stable sheath blight-tolerant genotype.
UNASSIGNED: A multi-environment evaluation of 32 rice genotypes against sheath blight infection was conducted over six seasons across two locations (Agricultural Research Farm, Institute of Agricultural Sciences, Banaras Hindu University (28.18° N, 38.03° E, and 75.5 masl), for four years during the wet seasons (kharif) from 2015 to 2018 and two seasons at the National Rice Research Institute (20°27\'09\" N, 85°55\'57\" E, 26 masl), Cuttack, Odisha, during the dry season (rabi) of 2019 and the kharif of 2019, including susceptible and resistant check. Percent disease index data were collected over 4 weeks (on the 7th, 14th, 21st, and 28th day after infection), along with data on other morphological and physiological traits.
UNASSIGNED: The resistant genotypes across seasons were the ones with a higher hemicellulose content (13.93-14.64) and lower nitrogen content (1.10- 1.31) compared with the susceptible check Tapaswini (G32) (hemicellulose 12.96, nitrogen 1.38), which might explain the resistant reaction. Three different stability models-additive main effect and multiplicative interaction (AMMI), genotype + genotype x environment (GGE) biplot, and multi-trait stability index (MTSI)-were then used to identify the stable resistant genotypes across six seasons. The results obtained with all three models had common genotypes highlighted as stable and having a low area under the disease progress curve (AUDPC) values. The ideal stable genotypes with low disease incidence were IC 283139 (G19), Tetep (G28), IC 260917 (G4), and IC 277274 (G10), with AUDPC values of 658.91, 607.46, 479.69, and 547.94, respectively. Weather parameters such as temperature, rainfall, sunshine hours, and relative humidity were also noted daily. Relative humidity was positively correlated with the percent disease index.