Effect of rice husk biochar, carpet waste, farm yard manure and plant growth promoting rhizobium on the growth and yield of rice (Oryza sativa)

The present investigation was aimed for improving growth and yield of crop using waste products of differ-ent activities and also useful in ecological stability of soil environment. This objective is not only an economic option for poor farmer but also an effective strategy for increasing yield. The experiment was conducted in the organic farm-ing plot of the Institute of Agricultural Sciences, BHU, Varanasi during kharif season of rice crop in 2014. The field experiment was laid out in randomized block design (RBD) with 10 treatments and three replications. Application of graded level of biochar, carpet waste farm yard manure (FYM) and plant growth promoting rhizobium (PGPR) was found to significantly enhance the grain and straw yield of rice by 57.70% and 56.08% over control, respectively

Floating Raft Wastewater Treatment System: A Review

Recently more imbalances are observed in availability and quality of natural resources such as water, which is most precious as well as playing a vital role in the governance of entire natural as well as manmade ecosystem. Hence, the presence of water in good quality is extremely necessary for overall sustainable and eco-friendly development. The floating raft wastewater treatment system is most emerging sustainable and plant-based-eco-friendly method for wastewater treatment since it is totally plant based and there is no more initial requirement of inputs as well as there is no production of harmful by-products into the environment

Investigation of wear behavior of nanoalumina and marble dust-reinforced dental composites

In the present work, the effects of adding nanoalumina and marble dust on the wear behavior of dental composites were investigated. The hardness of dental composite was determined using Vickers micro-hardness tester. A two-body abrasive wear test was performed on the dental wear simulator under the medium of artificial saliva. The experiments were performed as per the Taguchi orthogonal array and steady state condition by varying parameters such as filler content, normal load, sliding velocity, and number of cycles. The hardness results indicated that the incorporation of 5 wt. % of nanoalumina increased the hardness of the dental composite by 12%, whereas the incorporation of 5 wt. % of marble dust increased the hardness of the dental composite by 7%. Also, for the experiments as per the Taguchi orthogonal array, the mean volumetric wear in the case of nanoalumina-filled dental composite was 9.6% less than that of marble dust-filled dental composite. However, in both the cases, the volumetric wear increased with the increase in normal load, sliding speed, and number of cycles but decreased with the increase in filler content. Analysis of variance (ANOVA) of the results indicated that normal load was less significant compared to filler content, sliding speed, and number of cycles

Soil Test Based Fertilizer Application Improves Productivity, Profitability and Nutrient Use Efficiency of Rice (Oryza sativa L.) under Direct Seeded Condition

A field investigation on direct seeded rice (DSR) was carried out in the two consecutive rice growing seasons of 2017 and 2018 at Pantnagar, Uttarakhand, India for the development and validation of soil test crop response (STCR) to fertilizer and for assessing the performance of STCR-treatments as compared to the general recommended dose (GRD) in terms of yield, nutrient uptake and use efficiency, and the economics of DSR. For producing 1 Mg of rice-grain, the required nutrients (N, P, and K) were 2.01 kg, 0.44 kg, and 3.06 kg; the contribution from the soil was 22.05%, 37.34%, and 41.48%; from applied farmyard manure 23.25%, 28.34%, and 16.80%, from fertilizer 38.08%, 49.93%, and 252.98%; and from fertilizer with FYM 44.83%, 60.57%, and 278.70%; for N, P, and K, respectively. The STCR approach, with or without FYM, at both the target yields (4.5 Mg ha−1 and 5.0 Mg ha−1) markedly enhanced the grain yield (20.2% to 32.3%) and production efficiency over the GRD. It also exhibited a higher NPK uptake and use efficiency, along with better profitability, than the GRD. Therefore, the STCR-targeted yield approach could improve the yield, economics, and efficiency of nutrient use for direct seeded rice

Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane

Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder’s equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement

Genetic relationship among 86 <i>lens</i> accessions using Unbiased neighbouring joining dendrogram of 43 microsatellite loci.

<p>Red colored—<i>L</i>. <i>culinaris</i> subsp. <i>culinaris</i> (1–26), Green colored-<i>L</i>. <i>culinaris</i> subsp. <i>orientalis</i> (27–56), Blue colored—<i>L</i>. <i>nigricans</i> (57–62), Purple colored—<i>L</i>. <i>culinaris</i> subsp. <i>odemensis</i> (63–68), Yellow colored—<i>L</i>. <i>ervoides</i> (69–83), Brown colored—<i>L</i>. <i>culinaris</i> subsp. <i>tomentosus</i> (84–86).</p

Genetic Diversity in <i>Lens</i> Species Revealed by EST and Genomic Simple Sequence Repeat Analysis

<div><p>Low productivity of <i>pilosae</i> type lentils grown in South Asia is attributed to narrow genetic base of the released cultivars which results in susceptibility to biotic and abiotic stresses. For enhancement of productivity and production, broadening of genetic base is essentially required. The genetic base of released cultivars can be broadened by using diverse types including bold seeded and early maturing lentils from Mediterranean region and related wild species. Genetic diversity in eighty six accessions of three species of genus <i>Lens</i> was assessed based on twelve genomic and thirty one EST-SSR markers. The evaluated set of genotypes included diverse lentil varieties and advanced breeding lines from Indian programme, two early maturing ICARDA lines and five related wild subspecies/species endemic to the Mediterranean region. Genomic SSRs exhibited higher polymorphism in comparison to EST SSRs. GLLC 598 produced 5 alleles with highest gene diversity value of 0.80. Among the studied subspecies/species 43 SSRs detected maximum number of alleles in <i>L</i>. <i>orientalis</i>. Based on Nei’s genetic distance cultivated lentil <i>L</i>. <i>culinaris</i> subsp. <i>culinaris</i> was found to be close to its wild progenitor <i>L</i>. <i>culinaris</i> subsp. <i>orientalis</i>. The Prichard’s structure of 86 genotypes distinguished different subspecies/species. Higher variability was recorded among individuals within population than among populations.</p></div

Changes in number of alleles (Na), genetic diversity (He) Shannon index (I) and Nei’s genetic diversity (He) using EST and Genomic SSR.

<p>Changes in number of alleles (Na), genetic diversity (He) Shannon index (I) and Nei’s genetic diversity (He) using EST and Genomic SSR.</p

Nei’s unbiased measures of genetic distance among different subspecies/species of genus <i>Lens</i>.

<p>Nei’s unbiased measures of genetic distance among different subspecies/species of genus <i>Lens</i>.</p

STURUCTURE analysis of genus <i>Lens</i> based on EST and Genomic SSR.

<p>STURUCTURE analysis of genus <i>Lens</i> based on EST and Genomic SSR.</p