ABSTRACT
Introduction: 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. Material and methods: 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. Result and discussion: 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.
ABSTRACT
The present research focuses on the significance of thermophoretic particle deposition on a ZnO-SAE50 nanolubricant flow in a stretchable/shrinkable convergent/divergent channel in the presence of an applied magnetic field and nonlinear heat radiation. A parameter in the governing differential equations and wall boundary conditions defines the physical mechanism of the model. The Galerkin finite element method, combined with similarity transformation, is adopted to solve the governing equations. The Levenberg-Marquardt backpropagating algorithm of an artificial neural network model forecasts heat and mass transfer properties. The results reveal that by stretching/shrinking the walls enough, the classical flow and heat properties are significantly affected. The stretching of the convergent or divergent channel is observed to increase the velocity profiles, whilst shrinking results in backflow regions. In terms of the temperature field, stretching causes more heat to be produced in the flow; nevertheless, the thermal layer is decreased and cooling is attained by channel shrinkage, which may have important technical implications.
