Soil salinization of irrigated lands is a global problem in providing the necessary food and feed to meet the needs of a growing world population. Salinization in arid and semiarid areas can occur when the water table is three and more meters above the soil surface. Nowadays, innovative technologies are widely implemented in agriculture to increase yields and monitor changes in any area timely. Advanced technologies such as remote sensing (R.S.) data have become an economically efficient tool for assessing, detecting, mapping, and monitoring saline areas. This study aims to develop a spatial database for evaluating salinization using R.S. and GIS. This research employs various soil salinity indices based on Landsat 8 OLI images and other related geospatial datasets of the study areas. It aims to predict soil salinity using four machine learning methods (Gaussian Mixture Model (GMM), Random Forest (R.F.), Support Vector Machines (SVM), and K-Nearest Neighbors (KNN)). Results showed that R.F. is the most suitable for predicting the soil salinity in the study area with 93 percent overall accuracy. This research contributes to improving the quality of monitoring and improvement of the state of irrigated lands. Also, it develops a preliminary step toward decision-making tools for agricultural policies, such as managing saline areas related to crop production.

The study assessed the determinants of efficiency of poultry egg production in Surkhandarya province of Uzbekistan. Data was collected through a multi-stage sampling technique and analysed using stochastic production frontier. The results revealed that feed intake and utility were the most important inputs in poultry egg production in the area. Furthermore, the study found the average efficiency estimate to be 87.64% and this was influenced positively by education, access to credit and experience. However, about 12.36% of the profit was lost to technical inefficiency. Findings from the study also showed that farmers were operating in stage one of production at 1.04, which is the area of increasing returns to scale. The study thus recommends that efforts should be made at ensuring the poultry farmers have access to credit and educational programs should be organized to sensitize farmers more on how to improve on their efficiency level. It is also recommended that farmers increase their stock of birds, have membership of Parrandasanoat Association, feed and utilities in other to operate at the stage two of production.