This study demonstrates a dose-dependent response of Trichoderma harzianum Th-56 in improving drought tolerance in rice by modulating proline, SOD, lipid peroxidation product and DHN / AQU transcript level, and the growth attributes. In the present study, the effect of colonization of different doses of T. harzianum Th-56 strain in rice genotypes were evaluated under drought stress. The rice genotypes treated with increasing dose of T. harzianum strain Th-56 showed better drought tolerance as compared with untreated control plant. There was significant change in malondialdehyde, proline, higher superoxide dismutase level, plant height, total dry matter, relative chlorophyll content, leaf rolling, leaf tip burn, and the number of scorched/senesced leaves in T. harzianum Th-56 treated rice genotypes under drought stress. This was corroborated with altered expression of aquaporin and dehydrin genes in T. harzianum Th-56 treated rice genotypes. The present findings suggest that a dose of 30 g/L was the most effective in improving drought tolerance in rice, and its potential exploitation will contribute to the advancement of rice genotypes to sustain crop productivity under drought stress. Interaction studies of T. harzianum with three aromatic rice genotypes suggested that PSD-17 was highly benefitted from T. harzianum colonization under drought stress.
Total Productive Maintenance (TPM) has attracted the attention of industries all over the world. The perceptible impact of TPM lies in attaining the far-reaching productivity and quality standards. Attempts have been made to examine TPM for the feasibility in Indian industries. The present work describes a multiattribute decision model using analytical hierarchy process for the justi cation of TPM for Indian industries.
Rust caused by
Uromyces viciae-fabae
is a major biotic constraint to field pea (
Pisum sativum
L.) cultivation worldwide. Deployment of host-pathogen interaction and resistant phenotype is a modest strategy for controlling this intricate disease. However, resistance against this pathogen is partial and influenced by environmental factors. Therefore, the magnitude of environmental and genotype-by-environment interaction was assessed to understand the dynamism of resistance and identification of durable resistant genotypes, as well as ideal testing locations for rust screening through multi-location and multi-year evaluation. Initial screening was conducted with 250 diverse genotypes at rust hot spots. A panel of 23 promising field pea genotypes extracted from initial evaluation was further assessed under inoculated conditions for rust disease for two consecutive years at six locations in India. Integration of GGE biplot analysis and multiple comparisons tests detected a higher proportion of variation in rust reaction due to environment (56.94%) as an interactive factor followed by genotype × environment interaction (35.02%), which justified the requisite of multi-year, and multi-location testing. Environmental component for disease reaction and dominance of cross over interaction (COI) were asserted by the inconsistent and non-repeatable genotypic response. The present study effectively allocated the testing locations into various categories considering their “repeatability” and “desirability index” over the years along with “discrimination power” and “representativeness.” “Mega environment” identification helped in restructuring the ecological zonation and location of specific breeding. Detection of non-redundant testing locations would expedite optimal resource utilization in future. The computation of the confidence limit (CL) at 95% level through bootstrapping strengthened the accuracy of the GGE biplot and legitimated the precision of genotypes recommendation. Genotype, IPF-2014-16, KPMR-936 and IPF-2014-13 identified as “ideal” genotypes, which can be recommended for release and exploited in a resistance breeding program for the region confronting field pea rust.
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