Clubroot, caused by Plasmodiophora brassicae, has become a serious threat to canola (Brassica napus) production in western Canada. Experiments were conducted to assess the effect of growing resistant and susceptible canola genotypes on P. brassicae soil resting spore populations under greenhouse, mini-plot and field conditions. One crop of susceptible canola contributed 1AE4 · 10 8 spores mL )1 soil in mini-plot experiments, and 1 · 10 10 spores g )1 gall under field conditions.Repeated cropping of susceptible canola resulted in greater gall mass compared to resistant canola lines. It also resulted in reduced plant height, increased clubroot severity in susceptible canola, and increased numbers of resting spores in the soil mix.

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All investors are very keen to know about the trend of the Contribution/ OriginalityThis study contributes in the existing literature related to forecasting of daily gold price. In this study, a methodology of statistical time series modelling is utilized known as Box-Jenkins. It is found that, model formulated by this methodology perform better than the other models presented in literature.

Estimation of population mean of study variable Y suffers loss of precision in the presence of high variation in the data set. The use of auxiliary information incorporated in construction of an estimator under ranked set sampling scheme results in efficient estimation of population mean. In this paper, we propose an efficient generalized chain regression-cum-chain ratio type estimator to estimate finite population mean of study variable under stratified extreme-cum-median ranked set sampling utilizing information on two auxiliary variables. Mean square error (MSE) of the proposed generalized estimator is derived up to first order of approximation. The applications of the proposed estimator under symmetrical and asymmetrical probability distributions are discussed using simulation study and real-life data set for comparisons of efficiency. It is concluded that the proposed generalized estimator performs efficiently as compared to some existing estimators. It is also observed that the efficiency of the proposed estimator is directly proportional to the correlations between the study variable and its auxiliary variables.