Muhammad Amanullah

PHYSIOLOGICAL AND MOLECULAR RESPONSE OF WHEAT TO SOIL-APPLIED ENCAPSULATED CALCIUM CARBIDE UNDER SALINITY STRESS

The objective of this study was to explore the potential of encapsulated calcium carbide (ECC) for improving performance of wheat (Triticum aestivum L.) under salinity stress. Three levels of salinity, 0, 1250 and 2000 mg kg−1 soil, were developed with sodium chloride (NaCl) salt, whereas ECC formulation was applied at 0, 15 and 30 mg kg−1 soil. The gas chromatography (GC) analysis revealed that 30 mg kg−1 soil of the formulation produced 154.12 μmols of ethylene (C2H2) and 8.44 μmols of C2H4 over a period of 60 days. The ECC decreased plant height, conductance (C), and transpiration (E) up to 7, 19 and 21%, respectively, over control. There was substantial elevation in net photosynthesis (Pn), number of tillers, grain yield and relative leaf water content (RWC) up to 14, 19, 17 and 3% with ECC over control. Both levels of ECC increased protein content significantly in wheat leaves up to 46 and 60% over control. Similarly, salinity increased the protein content up to 54 and 168% over control in the presence of ECC and salinity stress. SDS-PAGE protein profile of wheat leaves after the treatments of 15 mg ECC kg−1 soil and 2000 mg NaCl kg−1 soil showed a significant set of induced proteins of 8, 60 and 70 kDa. Similarly exposure of plants to 30 mg of ECC kg−1 soil and 2000 mg NaCl kg−1 soil resulted in the appearance of protein bands of 9, 10, 23 and 70 kDa. The induced levels of proteins detected at various levels of ECC and NaCl treatments correlated with its salinity tolerance.

Empirical evaluation of the inverse Gaussian regression residuals for the assessment of influential points

Influential analysis is the main diagnostic process to obtain reliable regression results. Same is true for the generalized linear model. The present article empirically compares the performance of different residuals of the inverse Gaussian regression model to detect the influential points. The inverse Gaussian regression model residuals are further divided into two categories, that is, standardized and adjusted residuals. Cooks distance has been computed for both of the stated residuals, and then comparison of these residuals for the detection of influential point has been carried out with the help of simulation and a chemical related data set. The simulation results show that for small dispersion, the likelihood residuals are better than others and all the adjusted forms of residuals perform identically but not better than the standardized form. While for larger dispersion, all the standardized residuals perform in the same fashion, and they are better than the likelihood residuals for detection of influential points. Copyright

Salt-Induced Variations in Physiological Parameters and Nutrient Concentrations of Two Wheat Cultivars

Two wheat cultivars, Pasban-90 and Sehr-2006, were screened and sown under different levels of sodium chloride (NaCl) concentrations, following the factorial design with four replications, to evaluate the effects of salinity and stress duration on growth of seedling, photosynthetic productivity, and ion contents. Leaf chlorophyll and relative growth rate were determined after an interval of a week while other parameters were determined 25 days after treatment. The two cultivars differed significantly for all the parameters measured at 200 mM NaCl. The lowest concentration of NaCl (50 mM) decreased total leaf area up to 19 and 29% and dry weight by 55 and 63% in Pasban-90 and Sehr-2006, respectively. Salinity concentrations increased sodium (Na) and calcium (Ca) concentrations in tissues. The results of the study indicate great variation for salinity tolerance in two cultivars and greater photosynthetic capacity, comparatively low tissue Na accumulation at high salt levels, and greater relative growth rate. These results are related with the capacity of wheat to salt tolerance.

On the performance of some new Liu parameters for the gamma regression model

Abstract The maximum likelihood (ML) method is used to estimate the unknown Gamma regression (GR) coefficients. In the presence of multicollinearity, the variance of the ML method becomes overstated and the inference based on the ML method may not be trustworthy. To combat multicollinearity, the Liu estimator has been used. In this estimator, estimation of the Liu parameter d is an important problem. A few estimation methods are available in the literature for estimating such a parameter. This study has considered some of these methods and also proposed some new methods for estimation of the d. The Monte Carlo simulation study has been conducted to assess the performance of the proposed methods where the mean squared error (MSE) is considered as a performance criterion. Based on the Monte Carlo simulation and application results, it is shown that the Liu estimator is always superior to the ML and recommendation about which best Liu parameter should be used in the Liu estimator for the GR model is given.

Pena's statistic for the Liu regression

ABSTRACT In fitting regression model, one or more observations may have substantial effects on estimators. These unusual observations are precisely detected by a new diagnostic measure, Penas statistic. In this article, we introduce a type of Penas statistic for each point in Liu regression. Using the forecast change property, we simplify the Penas statistic in a numerical sense. It is found that the simplified Penas statistic behaves quite well as far as detection of influential observations is concerned. We express Penas statistic in terms of the Liu leverages and residuals. The normality of this statistic is also discussed and it is demonstrated that it can identify a subset of high Liu leverage outliers. For numerical evaluation, simulated studies are given and a real data set has been analysed for illustration.

Improved Inference for the Panel Data Model with unknown Unit-Specific Heteroscedasticity: A Monte Carlo Evidence

Abstract For a panel data model (PDM), it is common that the error terms of panel regression model are heteroscedastic. In the available literature, the heteroscedastic consistent covariance matrix estimators (HCCMEs) have been used for adequate testing of the coefficients of PDM. Usually, these HCCMEs are based on the residuals derived from ordinary least square (OLS) estimator which is considerably inefficient in the presence of heteroscedasticity. To get efficient estimation, the existing literature proposes some adaptive estimators for the PDM. This paper presents the HCCMEs, derived from some adaptive estimator, while considering the panel data-set with unit-specific heteroscedasticity. Through the Monte Carlo simulations, we present the numerical evaluation and attractive findings.

Influence Diagnostics in the Gamma Regression Model with Adjusted Deviance Residuals

ABSTRACT In this study, we develop the adjusted deviance residuals for the gamma regression model (GRM) by following Cordeiros (2004) method. These adjusted deviance residuals under the GRM are used for influence diagnostics. A comparative analysis has been sorted out between our proposed method of the adjusted deviance residuals and an existing method for influence diagnostics. These results are illustrated by a simulation study and using a real data set. They are presented for different values of dispersion and sample sizes and indicate the significant role of the GRM inferences.

Effect of Substrate Dependent Ethylene on Cotton (Gossypium hirsutum L.) at Physiological and Molecular Levels Under Salinity Stress

The potential of encapsulated calcium carbide (ECC) in improving growth, yield and physiology of cotton under salinity was evaluated in pot experiment. Salinity was induced by sodium chloride (NaCl) at 0, 1250 and 2000 ppm. The ECC was applied at the rate of 0, 15, and 30 mg kg−1 soil. The results revealed that ECC improved number of branches, yield, shoot dry biomass, root dry biomass, by 57, 67, 40, 22, and 18% respectively, over control. Similarly, net photosynthesis, stomatal conductance nitrogen, phosphorus and potassium (N, P and K) concentration of shoot were enhanced by 38, 34, 7, 25 and 11% over control, respectively. The induction of new set of proteins ranging from 11 to 26 kDa was also observed at various levels of ECC and salinity stress. These results proved the efficacy of very lower concentrations of ethylene produced by ECC and showed the behavior of different parameters of cotton to it under saline stress.