7 research outputs found
Genetic Improvement of Sorghum for Biomass Traits Using Genomics Approaches
Nonrenewable energy resources deplete with the passage of time due to rapid increase in industrialization and population. Hence, countries worldwide are investing dearly in substitute energy resources like biofuel from miscellaneous set of feedstocks. Among the energy crops, sorghum serves as a model crop due to its drought tolerance, small genome size (730 Mb), high biomass, dry matter contents, quick growth, wide adaptability to diverse climatic and soil conditions and C4 photosynthesis. Sweet sorghum with high sugar content in stalk is an efficient feedstock for advanced biofuels and other bio-based products from sugars. However, high biomass sorghum has the utility as a feedstock for cellulosic biofuels. The enhanced yield of monomeric carbohydrates is a key to cheap and efficient biofuel production. The efficiency of lignocellulosic biofuels is compromised by recalcitrance to cell wall digestion, a trait that cannot be efficiently improved by traditional breeding. Therefore, scientists are looking for solutions to such problems in biomass crop genomes. Sorghum genome has been completely sequenced and hence this crop qualifies for functional genomics analysis by fast forward genetic approaches. This chapter documents the latest efforts on advancement of sorghum for biomass potential at morphological and molecular level by exploiting genomics approaches
Effect of Drought on Trichome Density and Length in Cotton (Gossypium Hirsutum)
Cotton is a major cash crop and backbone of the textile industry in Pakistan which is badly affected by sucking insects. Drought is an important abiotic factor in trichome development. The objective of the study was to determine the effects of drought on trichome density and length. Trichome density was measured in two ways, one through the scaling method and the other through counting the trichome density manually. The scaling method is qualitative grading while quantitative grading includes trichomecount in a card of optimized length. Three scales were finalized to classify leaves on the basis of trichomes which were counted in a specific area (0.25cm2) on abaxial side of the leaf. In drought stress, trichomes density and length were measured and compared to that in normal conditions. Trichome density varies from 12 to 56 in 0.25cm2 under drought stress. On the basis of correlation of trichome density with stomatal conductance, photosynthetic rate, PAR and transpiration ratio under drought and normal conditions, it was concluded that trichome density increased as a result of drought stress
Determination of Crop Coefficient of Hybrid Wheat under Arid Climate: A Pot Study
Climate change increases vulnerabilities for crop productivity in Pakistan. Water crises are increasing with an increase in temperature and change in precipitation patterns due to climate change which ultimately imposed a threat to the food security of the country. Water is indispensable for all plants to complete life cycle as the unavailability of water at critical growth stages drastically affects the development of the plant. The present pot study was conducted for the estimation of crop coefficient of hybrid wheat for irrigation scheduling at Muhammad Nawaz Shareef University of Agriculture, Multan during two growing seasons 2018-19 and 2019-20. In this experiment, three wheat varieties were used were Hybrid-1 (R26-3-1/DH-16), Hybrid-2(AR 7-5 / ZWB-14), and Galaxy-2013 as treatment. The soil moisture content was maintained between 50 to 100 % available water content (AWC) during both growing seasons. The crop coefficient (Kc) and actual evapotranspiration (Eta) were maximum in galaxy-13 and minimum in hybrid wheat. The grain yield for Hybrid-1, Hybrid-2, and galaxy-13 was 1, 1.5, and 0.6 g plant-1, respectively while the straw output was 4.8, 4.3, and 3 g plant-1, respectively. The harvest index for Hybrid-1, Hybrid-2, and galaxy-13 were 20, 34, and 20% respectively. The water use efficiency (WUE) for Hybrid-1, Hybrid-2, and galaxy-13 was 0.2. 0.3 and 0.1 g plant-1mm-1, respectively. The Hybrid-1 and Hybrid-2 produced more grain yield, straw yield, more spikes, and more grains per spikes and showed more water use efficiency with short plant height as compared to galaxy-13. The results of the study revealed that Hybrid-2 is more water-efficient with low water requirement and it was followed by Hybrid-1. The growing of Hybrid-2 will enhance the wheat yield to meet the food requirements of the increasing population under the climate change scenario with less water
Improving Growth and Yield of Sunflower with Integrated Use of Compost and PGPR (Variovorax Paradoxus) with Different Levels of N-Chemical Fertilizer
Plant growth-promoting rhizobacteria (PGPRs) stimulate plant growth through their ability, to increasing the root length and growth, by asymbiotic nitrogen fixation, by producing siderophores, solubilization of mineral phosphates and mineralization of other nutrients. Organic waste material of fruits and vegetables was collected and composted in a locally fabricated composting unit. A pot trial was conducted to study the effectiveness of compost and PGPR (Variovorax paradoxus) with recommended rate of PK and with different rates of N fertilizer i.e. 50 %, 75 % and 100 %, on growth and yield of sunflower. Results showed that the integrated use of 75 % N of recommended dose in combination with PGPR inoculation and compost caused a significant increase in grain yield and yield-contributing parameters compared with control. PGPR isolate Variovorax paradoxus in combination with 75 % N of recommended dose and compost gave maximum total achene’s yield 73 % more than control where recommended NPK was applied. Similarly, in case of Plant height, root length, head diameter, head weight, 100 – Achene’s weight and nitrogen content in straw were also increased by PGPR isolate Variovorax paradoxus in combination with 75 % N of the recommended dose and compost up to 11, 109, 27, 26, 17, and 54.0 % respectively over control
Effect of Drought on Trichome Density and Length in Cotton (Gossypium Hirsutum)
Cotton is a major cash crop and backbone of the textile industry in Pakistan which is badly affected by sucking insects. Drought is an important abiotic factor in trichome development. The objective of the study was to determine the effects of drought on trichome density and length. Trichome density was measured in two ways, one through the scaling method and the other through counting the trichome density manually. The scaling method is qualitative grading while quantitative grading includes trichomecount in a card of optimized length. Three scales were finalized to classify leaves on the basis of trichomes which were counted in a specific area (0.25cm2) on abaxial side of the leaf. In drought stress, trichomes density and length were measured and compared to that in normal conditions. Trichome density varies from 12 to 56 in 0.25cm2 under drought stress. On the basis of correlation of trichome density with stomatal conductance, photosynthetic rate, PAR and transpiration ratio under drought and normal conditions, it was concluded that trichome density increased as a result of drought stress
Correlation, Regression Analysis of Seed Oil Contents in Relation to Morphological Characters in Cotton
Cotton is the backbone of Pakistan’s economy. More than half of the export of Pakistan depends on cotton and cotton-based products. Morphological quantitative traits are important for estimation of cotton yield. In this regard, a study was conducted to evaluate the morphological responses on cotton crop at experimental farm of MNS-University of Agricultural Multan during the year 2019-2020. Four cotton varieties with different time windows (early, normal and late) were sown in a randomized complete block design (RCBD) in a split plot arrangement. Correlation and regression studies of cultivars of Gossypium and Malvaceae were analyzed for quantitative characters. Result revealed that significantly positive correlation of boll weight (r=0.211), seed volume (r=0.138), seed oil content (r=0.020) and negatively correlation with seed index (r= -0.005) was displayed by all traits with seed cotton yield, which showed that seed cotton yield was greatly influenced by all characters. Regression coefficients showed that a unit increase in seed index (b=71.375), seed volume (b=120.326), seed oil content (b=4.954) resulted into a proportional increased in seed cotton yield. In future, this study will helpful in selection program for improvement of cotton varieties towards the yield
Multi-epitopes vaccine design for surface glycoprotein against SARS-CoV-2 using immunoinformatic approach
Background: The recent COVID vaccinations have successfully reduced death and severity but did not stop the transmission of viruses by the emerging SARS-CoV-2 strain. There is a need for better and long-lasting dynamic vaccines for numerous prevailing strains and the evolving SARS-CoV-2 virus, necessitating the development of broad-spectrum strains being used to stop infection by reducing the spread rate and re-infection. The spike (S) glycoprotein is one of the proteins expressed commonly in the early phases of SARS-CoV-2 infection. It has been identified as the most immunogenic protein of SARS-CoV-2. Methods: In this study, advanced bioinformatics techniques have been exploited to design the novel multi-epitope vaccine using conserved S protein portions from widespread strains of SARS-CoV-2 to predict B cell and T cell epitopes. These epitopes were selected based on toxicity, antigenicity score and immunogenicity. Epitope combinations were used to construct the maximum potent multi-epitope construct with potential immunogenic features. EAAAK, AAY, and GPGPG were used as linkers to construct epitopes. Results: The developed vaccine has shown positive results. After the chimeric vaccine construct was cloned into the PET28a (+) vector for expression screening in Escherichia coli, the potential expression of the construct was identified. Conclusion: The construct vaccine performed well in computer-based immune response simulation and covered a variety of allelic populations. These computational results are more helpful for further analysis of our contract vaccine, which can finally help control and prevent SARS-CoV-2 infections worldwide