Panda Siddharth, R Naveen Kumar, Pavani S Lalitha, Ganesan Sangeetha, Singh Pawan Kumar, Sah Rameswar Prasad, V Padmakumar, Subudhi Hatanath, Mahender Anumalla, Anandan Annamalai, Ali Jauhar
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Siksha 'O' Anushandhan (SOA) [Deemed to be University (DU)], Bhubaneswar, Odisha, India.
Division of Plant Pathology, School of Agricultural Sciences, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.
Front Plant Sci. 2023 Oct 30;14:1280321. doi: 10.3389/fpls.2023.1280321. eCollection 2023.
Sheath blight caused by 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.
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 () 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 () of 2019 and the 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.
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.
由[病原菌名称缺失]引起的纹枯病是水稻的主要病害之一,导致作物广泛减产。在当前的养分密集型水稻种植系统中,半矮秆水稻品种的使用进一步加剧了该病的发病率。解决这一问题的理想办法是鉴定出稳定的抗纹枯病基因型。
在两个地点对32个水稻基因型进行了六个季节的纹枯病感染多环境评价。其中,在贝拿勒斯印度教大学农业科学研究所农业研究农场(北纬28.18°,东经38.03°,海拔75.5米)进行了四年的雨季评价(2015年至2018年),在奥里萨邦科塔克的国家水稻研究所(北纬20°27′09″,东经85°55′57″,海拔26米)进行了两个季节的旱季评价(2019年旱季和2019年[此处季节信息缺失]),评价包括感病和抗病对照品种。在感染后的4周内(感染后第7天、14天、21天和28天)收集病情指数百分比数据,以及其他形态和生理性状的数据。
与感病对照品种塔帕什维尼(G32)(半纤维素含量12.96,氮含量1.38)相比,各季节抗性基因型的半纤维素含量较高(13.93 - 14.64),氮含量较低(1.10 - 1.31),这可能解释了其抗性反应。然后使用三种不同的稳定性模型——加性主效应和乘积互作(AMMI)、基因型 + 基因型×环境(GGE)双标图和多性状稳定性指数(MTSI)——来鉴定六个季节中稳定的抗性基因型。所有三种模型得到的结果都突出了一些共同的基因型,这些基因型稳定且病害进展曲线下面积(AUDPC)值较低。发病率低的理想稳定基因型为IC 283139(G19)、特特普(G28)、IC 260917(G4)和IC 277274(G10),其AUDPC值分别为658.91、607.46、479.69和547.94。每天还记录温度、降雨量、日照时数和相对湿度等气象参数。相对湿度与病情指数百分比呈正相关。