Showing 7 results for Mishra
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
This study examines the differences between the social networks of farm women in tribal and coastal areas. Using a multistage sampling method, interviews were conducted with 240 farm women from Ganjam and Raigada districts in Odisha. Social network analysis (SNA) was employed to map the networks and identify key sources and patterns of information access utilized by farmers. The study identified which village nodes received agricultural information based on high degree, betweenness, and closeness centrality.
The findings indicate that farm women in tribal areas have relatively weaker information networks compared to those in coastal areas. While farm women from both areas consider the most educated family or village member and self-help groups (SHGs) as primary information sources, coastal farm women are more adept at networking with additional sources such as TV, training sessions, demonstrations, field days, other farmers, agriculture departments, and input dealers.
Furthermore, women farmers are less likely to receive information when betweenness centrality is used in targeting. This highlights significant gender differences: in tribal areas, men are more likely to interact with cosmopolitan information sources, whereas farm women are mainly engaged in farm activities. In contrast, coastal farm women are actively involved in both farm activities and information gathering from various sources. This study underscores the need to address gender disparities and strengthen information networks among farm women, particularly in tribal areas.
Volume 15, Issue 1 (1-2013)
Abstract
The diallel cross design is frequently utilized to obtain information on genetic effects, estimates of General and Specific Combining Ability (GCA and SCA) and to identify promising heterotic combinations as well as heterotic patterns. In the present study, heterotic crosses were identified for specific alkaloids in opium poppy (Papaver somniferum L.) following Yan’s GGE Biplot model by use of 5×5 full diallel data. The results obtained through biplot analysis were compared with those obtained through Griffing’s to check and confirm the accuracy of Yan’s GGE biplot model. Parents A (papline), B (NB5KR40-7/2-3), and E (58/1) were identified as good general combiners. The crosses B×C, B×E and E×B for morphine, C×D and C×E for narcotine, and A×B, A×C and A×E were identified as heterotic combinations. None of the crosses were found heterotic for codeine and thebaine.
Volume 16, Issue 6 (11-2014)
Abstract
The objectives of the present study were to evaluate spring wheat recombinant inbred lines (RILs) of diverse origin by estimating genetic parameters viz., variability, character association, cluster analysis, and principal component analysis (PCA) for spot blotch resistance and yield components at BHU Agricultural Research Farm during 2010-2011. Grain yield per plot was significantly and positively associated with biomass, 1,000-grain weight, harvest index, chlorophyll content, and grains per spike at genotypic level. The line 65 exhibited lowest mean of AUDPC value (632) indicating its potential as resistant parent. Cluster analysis grouped all the 324 spring wheat lines into 19 clusters using Ward’s method. Extreme divergence was observed among clusters. By using D2-statistics, the highest inter cluster distance (584.72) was found between Clusters VIII and XIX. Cluster VIII recorded highest mean values for chlorophyll content, peduncle length, bio-mass, grains per spike, 1000-grain weight and grain yield. The major contributing trait towards genetic divergence was found to be AUDPC (60.36%). First 5 principal components (PC1, PC2, PC3, PC4 and PC5) accounted for proportionate values of 20.66, 17.96, 15.07, 8.28, and 7.38%, respectively, contributing 69.35% of the total variability. The second PCs had high positive PC value for plant height, biomass, and 1,000-grain weight. The breeding objectives of the present experiment was to identify genetically diverse wheat spot blotch resistant RILs for developing high yielding spot blotch resistant cultivars especially adopted to south Asia in future breeding programs.
Volume 20, Issue 4 (10-2018)
Abstract
Horticulture sector plays a prominent role in economic growth for most of the developing countries. India is the largest producer of fruits and vegetables in the world next only to China. Among the horticultural crops, fruit crops are cultivated in majority of the area. Fruit crops play a significant role in the economic development, nutritional security, employment generation, and overall growth of a country. Among fruit crops, mango and banana are largest producing fruits of India. Generally, Karnataka is called as the horticultural state of India. In Karnataka, mango and banana are highest producing fruit crops. With these prospective, yield of mango and banana of Karnataka have been chosen as study variables. Forecasting is a primary aspect of developing economy so that proper planning can be undertaken for sustainable growth of the country. In this study, classes of linear and nonlinear, parametric and non-parametric statistical models have been employed to forecast yield of mango and banana of Karnataka. The major drawback of linear models is the presumed linear form of the model. In most of the cases, the time series are not purely linear or nonlinear as they contain both linear and nonlinear components. To overcome this problem a hybrid model has been proposed which consists of linear and nonlinear models. The hybrid model with the combination of Autoregressive Integrated Moving Average (ARIMA) and Support Vector Regression model performed better in both model building as well as in model validation as compared to other models.
Volume 21, Issue 2 (3-2019)
Abstract
Plant microRNAs (miRNAs) play important roles in plant development and responses to biotic and abiotic stress. Recently, there is clear evidence that miRNAs are involved in host-virus interactions. By using stem-loop RT-PCR, an expression levels change of thirteen miRNA belonging to six miRNA families targeting leaf development and morphogenesis were analyzed upon Tobacco Mosaic Virus (TMV)-tomato infection. Compared to mock plants, significant changes in relative expression levels of nine miRNAs were observed. The miR319c-5p showed the highest statistically significant increase in accumulation at 15 days post-inoculation. At all time points tested, miR159, miR164a-3p, miR164a-5p, miR166c-5p and miR319c-5p were up-regulated while miR160, miR319a, miR319b, miR319c-3p were down-regulated in most cases. Our data could provide new insights into the role of miRNAs in tomato-TMV interaction and in developing efficient strategies for improving tomato resistance against viral infection.
Volume 24, Issue 6 (11-2022)
Abstract
Grass pea (Lathyrus sativus L.) is an important dual-purpose crop in drought and famine prone areas as it is used as human food as well as livestock feed and fodder. However, the variation for forage quality traits of grass pea remains largely unexplored. This study aimed to characterize the genetic diversity of grass pea collections from Africa, Asia, and Europe, and identify genotypes for superior agronomic and forage nutritional quality traits. The principal component analysis revealed that the first three principal components from nutritional quality parameters viz., NDF, ADF, cellulose, lignin and ash percent, and from agronomic traits viz., plant height, nodes per plant, leaf area, green and dry biomass accounted for the majority of the total variation. In addition, a total of 59 polymorphic alleles were detected at 11 SSR loci with an average of 5.36 alleles per locus and the polymorphic information content ranged from 0.49 to 0.76. Three accessions (IF1872, IF2177 and IF2156) with higher biomass than the check and four accessions (IF1327, IF1312, IL-10-76 and IF1307) with excellent nutritive value in both green forage as well as straw were identified. The present study revealed high genetic variation for biomass and nutritional quality traits in grass pea collections that could be useful for development of high-yielding, nutritionally rich, and dual-purpose varieties.
Volume 25, Issue 3 (5-2023)
Abstract
This study was conducted to examine the sensitivity of weather parameters and CO2 concentration to wheat production under two irrigation regimes viz. full irrigation and limited irrigation, using CERES-Wheat model. Field experiment data from the 2016-17 and 2017-18 rabi seasons on wheat cultivar HD-2967 with three sowing dates and five irrigation regimes were used to calibrate and validate the CERES-Wheat crop simulation model. Validation results indicated very good agreement between simulated and observed values under five, four, and three irrigations regimes as compared to lower irrigation regimes. Under full irrigation and limited irrigation, grain yield sensitivity to incremental unit of mean temperature from 1 to 3°C revealed a decrease of 6 to 22% and 8 to 16%, respectively. Temperature decreases of 1-3°C resulted in a gradual increase in yield of 10-28 and 6.5- 20%, respectively, under full and limited irrigation. The combined effect of higher mean temperature and lower solar radiation revealed that wheat yield was more sensitive to temperature than solar radiation. Furthermore, the combined effect of mean temperature and CO2 level revealed that higher levels of CO2 concentration yielded the greatest benefits with a 1 °C increase in temperature, but further increases in temperature reduced the beneficial effect of elevated CO2 level under both irrigation conditions.