60 research outputs found

    Effect of intercropping of corn and soybean on dry matter yield and nutritive value of forage corn

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    Cereal-based forage production could be considered to have potential to supply great deal of energy-rich feed in animal diets. Experiment was conducted to evaluate effect of corn-soybean combinations of 75:25, 50:50 and 25:75 in addition to monocrops of corn and soybean to detremine forage dry matter (DM) yield and quality in corn-soybean intercropping. The crop combination ratio had significant effects on dry matter yield and nutritive quality of forage. The ratio of 75:25 and 50:50 recorded DM yields similar to those of monocropped corn (14.77 t/ha). Forage quality in terms of crude protein (CP) (75:25 ratio 12.75%, 50:50 ratio 13.73% and 25:75 ratio 14.68%) was improved by intercropping due to higher nitrogen availability for corn in intercropping compared with its sole crop (10.83% CP). Increase ratio of corn in corn-soybean mixture, negatively affectd neutral detergent fiber (NDF), acid detergent fiber (ADF) of forage and declined with increasing ratio of soybean plants. Combination ratio of 50:50 gave higher protein yield (1886.45 kg/ha) than other crop combination ratio. Among all the combination ratios, the 50:50 corn-soybean ratio was the optimum giving highest forage yield, protein content as well as protein yield

    FeCl 3 .nano SiO 2 : An Efficient Heterogeneous Nano Catalyst for the Synthesis of 14-Aryl-14H-dibenzo[a,j]xanthenes and 1,8-Dioxo-octahydro-xanthenes under Solvent-free Conditions

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    ABSTRACT A novel, efficient and eco-friendly procedure for the synthesis of 14-aryl-14H-dibenzo[a,j]xanthenes and 1,8-dioxo-octahydroxanthenes is described through one-pot condensation of 2-naphthol and dimedone with aryl aldehydes in the presence of nano silica-supported ferric chloride under solvent-free conditions. The present approach offers several advantages such as short reaction times, high yields, easy purification, recovery and reusability of the catalyst

    Allele mining strategies: principles and utilisation for blast resistance genes in rice (Oryza sativa L.)

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    Allele mining is a promising way to dissect naturally occurring allelic variants of candidate genes with essential agronomic qualities. With the identification, isolation and characterisation of blast resistance genes in rice, it is now possible to dissect the actual allelic variants of these genes within an array of rice cultivars via allele mining. Multiple alleles from the complex locus serve as a reservoir of variation to generate functional genes. The routine sequence exchange is one of the main mechanisms of R gene evolution and development. Allele mining for resistance genes can be an important method to identify additional resistance alleles and new haplotypes along with the development of allele-specific markers for use in marker-assisted selection. Allele mining can be visualised as a vital link between effective utilisation of genetic and genomic resources in genomics-driven modern plant breeding. This review studies the actual concepts and potential of mining approaches for the discovery of alleles and their utilisation for blast resistance genes in rice. The details provided here will be important to provide the rice breeder with a worthwhile introduction to allele mining and its methodology for breakthrough discovery of fresh alleles hidden in hereditary diversity, which is vital for crop improvement

    Molecular progress on the mapping and cloning of functional genes for blast disease in rice (Oryza sativa L.): current status and future considerations

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    Rice blast disease, which is caused by the fungal pathogen Magnaporthe oryzae, is a recurring problem in all rice-growing regions of the world. The use of resistance (R) genes in rice improvement breeding programmes has been considered to be one of the best options for crop protection and blast management. Alternatively, quantitative resistance conferred by quantitative trait loci (QTLs) is also a valuable resource for the improvement of rice disease resistance. In the past, intensive efforts have been made to identify major R-genes as well as QTLs for blast disease using molecular techniques. A review of bibliographic references shows over 100 blast resistance genes and a larger number of QTLs (∼500) that were mapped to the rice genome. Of the blast resistance genes, identified in different genotypes of rice, ∼22 have been cloned and characterized at the molecular level. In this review, we have summarized the reported rice blast resistance genes and QTLs for utilization in future molecular breeding programmes to introgress high-degree resistance or to pyramid R-genes in commercial cultivars that are susceptible to M. oryzae. The goal of this review is to provide an overview of the significant studies in order to update our understanding of the molecular progress on rice and M. oryzae. This information will assist rice breeders to improve the resistance to rice blast using marker-assisted selection which continues to be a priority for rice-breeding programmes

    Factor Structure and Psychometric Properties of Zung SelfRating Depression Scale in Women with a Sick Child

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    Background: Considering the necessity of using a valid and reliable tool to assess depression in women and the lack of similar tools in Iran, the purpose of this study was to investigate the psychometric properties of the Zung Self-Rating Depression Scale (ZSDS) with an emphasis on factor analysis among Iranian women with sick children.. Methods: In the cross-sectional psychometric study, 102 eligible women were selected by multistage cluster sampling from various environments such as healthcare centers, hospitals, and public and private institutions, who completed the ZSDS. The reliability of the questionnaire was assessed using testretest and internal consistency, and its validity was tested by confirmatory factor analysis (CFA). Results: Cronbach's alpha coefficients for the total scale were equal to 0.73, and high test-retest reliability indicated the appropriate reliability of ZSDS. The CFA results indicated a poor fit of the model in determining the factors as initially expressed in ZSDS. After removing six questions with low factor loadings and freeing the covariance error between the two questions, the model was adequately fitted (CMIN/DF= 1.3, CFI= 0.92, TLI= 0.90, GFI= 0.89).Conclusions: Based on our study, the ZSDS is convenient for identifying clinically significant depressive symptoms among women with sick children. Keywords: Child, Psychometric, Zung Self-Rating Depression Scale, Wome
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