Ajit,NRCAF - National Research Center for Agroforestry |
Das D.K.,Rajendra Agricultural University |
Chaturvedi O.P.,Central Soil and Water Conservation Research and Training Institute |
Jabeen N.,Punjab Agricultural University |
Dhyani S.K.,NRCAF - National Research Center for Agroforestry
Biomass and Bioenergy | Year: 2011
This article concentrates on development of statistical models for prediction of biomass components (above and below ground) of standing trees of Populus deltoides. Twenty seven trees (three each from age one to nine years) were destructively harvested, separated, sorted, sub-sampled, dried to constant weight at 60 °C and weighted for biomass components (leaf, twig, branch, bole, stump root, lateral root, fine root). Harvesting in a similar manner, was continued annually up to nine years of tree age and thus in all 27 sampled trees were available for analysis and fitting of models. Diameter at breast height (dbh) alone was a very good predictor of dry weight and accordingly the height was not included in the model. Various functions viz (linear, allometric, logistic, gompertz and chapman-richards), were attempted for dry weight estimation. The linear model, though easiest to fit, suffered from the 'negative estimation problem', specifically for the lower range of explanatory variate. Of the remaining non-linear models, the allometric model outperformed the others on the basis of validation criterions. The value of R2 ranged from 0.95 to 0.99, for the allometric models fitted on various biomass components. The proposed models can be used for prediction of component wise dry biomass of P. deltoides for a wide range of dbh values (1-50 cm) at one end and can also help farmers in the choice of economical harvest rather than the traditional physical rotation. In addition, they can be used in carbon sequestration studies, which needs complete biomass estimation. © 2010 Elsevier Ltd.
Sinha S.K.,Rajendra Agricultural University
Physiology and Molecular Biology of Plants | Year: 2010
The RNA silencing is one of the innovative and efficient molecular biology tools to harness the down-regulation of expression of gene(s) specifically. To accomplish such selective modification of gene expression of a particular trait, homology dependent gene silencing uses a stunning variety of gene silencing viz. co-suppression, post-transcriptional gene silencing, virus-induced gene silencing etc. This family of diverse molecular phenomena has a common exciting feature of gene silencing which is collectively called RNA interference abbreviated to as RNAi. This molecular phenomenon has become a focal point of plant biology and medical research throughout the world. As a result, this technology has turned out to be a powerful tool in understanding the function of individual gene and has ultimately led to the tremendous use in crop improvement. This review article illustrates the application of RNAi in a broad area of crop improvement where this technology has been successfully used. It also provides historical perspective of RNAi discovery and its contemporary phenomena, mechanism of RNAi pathway. © 2010 Prof. H.S. Srivastava Foundation for Science and Society.
Vibha,Rajendra Agricultural University
Archives of Phytopathology and Plant Protection | Year: 2011
Three fungal and one bacterial bioagents were tested for efficacy against Rhizoctonia solani under in vivo and in vitro conditions. Organisms including native isolates of Trichoderma virens 7109, Paecilomyces lilacinus 7115, Aspergillus niger and Pseudomonas strain were investigated in different combinations to get effective antagonists. T. virens 7109 and A. niger significantly reduced the growth of R. solani under laboratory and field conditions, respectively. Fungal combination had stimulatory effect on total fungal population and was recorded the highest (25.04 × 10 4 cfu/g soil) in T. virens 7109 + P. lilacinus 7115 combination. Soil treatments with individual bioagents have shown uniformity in disease suppression when compared to combinations. Treatment with combination of bioagents yielded higher fruit harvest when compared to that with single bioagent. © 2011 Taylor & Francis.
Pandey V.,Rajendra Agricultural University
Archives of Phytopathology and Plant Protection | Year: 2011
Soil mycofloral diversity plays a pivotal role in crop production and is an integral part of any ecosystem. Pigeonpea cropping system provides a congenial environment to soil microbes by fixing nitrogen and solubilizing phosphorus which in turn provides sufficient nutrients for their prolific growth. The present study was undertaken to know the fungal diversity in calcareous soil of Bihar region in India, which are not supportive to growth of many fungi owing to high calcium content. Soil samples were collected from pigeonpea cropping system treated with native and commercial isolates of phosphorus solubilizing bacteria (PSB) and plant growth promoting rhizobacteria (PGPR) along with Rhizobium. Thirty-seven species belonging to seven genera and a group of unidentified species were isolated. Aspergillus and Penicillium were the dominant genera in all the treatments. Absidia and Cunnighmella were distributed only once as rare genera. Though single species of Pythium, Rhizopus, Periconia, Geotrichum and Gliocladium genera were recorded but their occurrence was even in all the treatments. The diversity and equitability index were not varied much in different treatments except one. The deuteromucetous fungi occupied the highest space followed by zygomycetous, mycelia sterilia and mastigomycetous fungi. ©2011 Taylor & Francis.
Kumar N.,Rajendra Agricultural University
Indian Journal of Agronomy | Year: 2012
An experiment was conducted during spring season of 2008-09 and 2009-10 on sandy loam soil at Pusa to assess the effect of farmyard manure and fertilizer levels on sugarcane (Saccharum spp. hybrid complex). The experiment was laid out in factorial randomized block design and replicated thrice with two FYM viz., 0 and 20 tonnes/ha and four fertilizer levels viz., F1, 150 + 37.1 + 49.8, RDF; F2, 150 + 43.6 + 66.4; F3, 200 + 43.6 + 83.0 and F4, 200 + 54.6 + 99.6 kg N + P + K/ha. Application of 20 tonnes FYM/ha to sugarcane recorded significantly higher mean growth (tillers, 1,70,200/ha; cane height, 208.9 cm; drymatter accumulation, 33.3 t/ha), yield attributes (millable canes, 1,13, 600/ha; cane diameter, 2.18 cm) and cane yield (87.5 t/ha) over no FYM. An increase of 16.2% in cane yield, 26.31% in net return, 8.5% in benefit: cost ratio and 15.6% in sugar yield was noticed with FYM over its control. FYM @ 20 tonnes/ha registered an increase of 20.9% in N uptake, 20.3% in P uptake, 20.2% in K uptake, 10.0% in available N, 23.3% in available P and 6.4% in available K over no FYM. Net gain of N (65 kg), P (6.1 kg) and K (31 kg) were also highest in FYM added plots. Crop receiving 200 + 54.6 + 99.6 kg N + P + K/ha gave significantly higher tillers (1,83,800/ha), cane height (213.8 cm), drymatter (34.5 t/ha), cane diameter (2.22 cm) and number of millable cane (1,20,800/ha) though, it was statistically at par with 200 + 43.6 + 83.0 kg N + P + K/ha. There was an increase in cane and sugar yield with each successive increase in N + P + K level from 150 + 37.1 + 49.8 kg/ha to 200 + 43.6 + 83.0 kg/ha. Increasing N + P + K levels from F1 to F3 significantly increased the net returns. However, further increase to F4 level did not proved profitable option. Fertilizer application increased the N uptake from 164 to 238 kg/ha, P uptake from 14.9 to 21.9 kg/ha and K uptake from 191.3 to 277.6 kg/ha. Significant increase in available N status was recorded with an application of 200 + 43.6 + 83.0 kg N + P + K/ha. However, available P status in post harvest soil increased significantly with each successive increase in fertilizer up to highest levels i.e. 200 + 54.6 + 99.6 kg N + P + K/ha. Available K status was the highest (121 kg K/ha) at 200 + 54.6 + 99.6 kg N + P + K/ha though it was on par with 200 + 43.6 + 83.0 kg N + P + K/ha. Net gain of N, P and K were progressively increased with increase in N + P + K levels from 150 + 37.1 + 49.8 to 200 + 54.6 + 99.6 kg/ha.