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The ground validation of satellite-based precipitation products (SPPs) is very important for their hydroclimatic application. This study evaluated the performance assessment of four soil moisture-based SPPs (SM2Rain, SM2Rain- ASCAT, SM2Rain-CCI, and GPM-SM2Rain). All data of SPPs were compared with 64 weather stations in Pakistan from January 2005 to December 2020. All SPPs estimations were evaluated on daily, monthly, seasonal, and yearly scales, over the whole spatial domain, and at point-to-pixel scale. Widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (rBias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI) were evaluated for performance analysis. The results of our study signposted that: (1) On a monthly scale, all SPPs estimations were in better agreement with gauge estimations as compared to daily scales. Moreover, SM2Rain and GPM-SM2Rain products accurately traced the spatio-temporal variability with CC >0.7 and rBIAS within the acceptable range (±10) of the whole country. (2) On a seasonal scale (spring, summer, winter, and autumn), GPM-SM2Rain performed more satisfactorily as compared to all other SPPs. (3) All SPPs performed better at capturing light precipitation events, as indicated by the Probability Density Function (PDF); however, in the summer season, all SPPs displayed considerable over/underestimates with respect to PDF (%). Moreover, GPM-SM2RAIN beat all other SPPs in terms of probability of detection. Consequently, we suggest the daily and monthly use of GPM-SM2Rain and SM2Rain for hydro climate applications in a semi-arid climate zone (Pakistan). [ABSTRACT FROM AUTHOR]

The main purpose of the study was to determine the suitable selection method for genetic improvement in chickpea. The current investigation was conducted at the research area of the Arid Zone Research Institute, Bhakkar, Punjab, Pakistan. Twelve chickpea genotypes were sown in RCBD following three replicates. Data regarding primary & secondary per plant, days for maturity, plant height as well as potential yield were recorded. The measured data were analyzed to principal component analysis (PCA), correlation, and path coefficient analysis. Analysis of variants revealed good variation among the accessions for the data recorded traits. Principal coefficient analysis differentiates all the traits into six PCs. Two components expressed more than one Eigenvalue which collectively contributed 80.12% towards the genetic variation. High positive loadings were expressed by the secondary branches per plant and pods per plant in all components. Path analysis revealed that secondary branches/plants expressed the highest direct positive effect (0.872) grain yield followed by the pods per plant (0.623). Analysis of correlation coefficient also confirmed the highest significant contribution of secondary branches per plant (91.57%) followed by pods (78.12%) and each plant's primary branches (64%). It was proved from the current experiment that Plants with secondary branches as well as pods may be focused on while assessing meaningful selection criteria for genetic improvement in chickpea. [ABSTRACT FROM AUTHOR]