Sun drying in the open air is quite popular worldwide. However, the use of solar dryers to preserve various perishable agricultural products is a relatively new area of study, and the long-term effects of this method are not yet fully understood. The slow drying process in direct sunlight can contaminate the dried materials by soil and insects. To overcome these challenges, we devised a sun drying system that included a heating part, a drying area, a portable stand, fans, and a 50-W photovoltaic panel. An alternate energy source was used to power the drying process during cloudy days and at night. Fresh Freestone peach, Golden apple, and Anaheim chilies weighing 10 kg each with the initial moisture content of 89%, 87%, and 75% on a wet basis (w.b), respectively, were used in the experiments. The final moisture content of the samples was reduced by an average of 16%, 15%, and 11% for Freestone peaches, Golden apples, and Anaheim chilies, respectively. The quality analysis was carried out to determine sample composition, total bacteria, and color of dried products. The results indicated that the dried products met the recommended quality standards for food products in terms of composition, total bacteria, and color. This research supports the use of a hybrid mixed-mode solar dryer for drying a wide range of perishable agricultural products.

Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. All SPPs were evaluated on annual, seasonal, monthly, and daily bases from 2010 to 2017, over the whole spatial domain and at point-to-pixel scale. The assessment was conducted using 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)). Results showed: (1) PERSIANN and PERSIANN-DIR products efficiently traced the spatio-temporal distribution of precipitation over the Himalayan Mountains. (2) On monthly scale, the estimates of all SPPs were more consistent with the reference data than on the daily scale. (3) On seasonal scale, PERSIANN and PERSIANN-DIR showed better performances than the PERSIANN-CDR and PERSIANN-CCS products. (4) All SPPs were less accurate in sensing daily light to medium intensity precipitation events. Subsequently, for future hydro-meteorological investigations in the Himalayan range, we advocate the use of monthly PERSIANN and PERSIANN-DIR products.

In Pakistan, groundwater resources are depleting at an alarming rate due to intensive pumping, shifting of cropping patterns, and climate change vulnerability. The present study is aimed at investigating groundwater stress in the command area of Lower Chenab Canal (LCC) and associated branch canals. Groundwater stress is determined by considering the cropping patterns, surface water availability, groundwater levels, climatic variation, and crop water requirement (CWR) in the LCC command area. The climatic data is obtained from the Pakistan Meteorological Department (PMD) from 1990 to 2020. The records of temporal variation in cropping patterns are obtained from the Crop Reporting Service (CRS), Directorate of Agriculture, Lahore for the 1995–2020 period and classified according to Rabi season (November to April) and Kharif season (May to October). The LCC surface water flows data and groundwater levels are collected from the Punjab Irrigation Department (PID) Lahore from 2003 to 2018 and from 1995 to 2016, respectively. The CWR is estimated using the Cropwat 8.0 model and groundwater levels are estimated using the Inverse Distance Weighted (IDW) tool of ArcGIS software. It has been determined that Faisalabad, Sheikhupura, and Toba Tek Singh are highly groundwater stress cities having an average drawdown rate of 0.58 m/year. The surface water availability is also decreased from 7.75 to 4.81 billion cubic meters (Bm³) for the Kharif season whilst 4.17 to 2.63 Bm³ for the Rabi season. This study concluded that due to severe conditions in highly stressed areas, policy planners, decision-makers, and stakeholders should sincerely take some steps for maintaining groundwater levels either by capacity building workshops for the farmers or limiting the number of tubewells.

Weeds compete with crops for water, nutrients, and light consequently, have adverse effects on the crop yield and overall productivity. Mechanical weeding is the most common non-chemical method for weed control, which is applied in organic farming, and the weed cultivator is the most common implement in mechanical weeding. This study aimed to design and develop an innovative active tool to optimize the cultivation depth, which can avoid damage to crop roots and improve the key performance indicators of an inter-row cultivator. A quasi-Newton optimization method and a hybrid of the non-dominated sorting genetic algorithm (NSGA-II) and goal attainment method were separately applied to synthesize and develop a four-bar mechanism for weeding requirements. The transmission angle of the mechanism and the desired path of the weeding blade were simultaneously optimized using these multi-objective optimization techniques. The performance of the developed four-bar cultivator based on the optimization techniques was compared with the ones developed based on the classic methods and also with several conventional tools evaluated in other studies. The results showed that applying the quasi-Newton optimization method and hybrid genetic algorithm can propose a more effective weed cultivator in terms of performance indicators, namely weeding performance, mechanical damage to crop plants and cultivation depth. In addition, the optimization of the transmission angle guaranteed the smooth rotations in the mechanism’s joints.

HIGHLIGHTS. Canal lining has reduced seepage losses by ∼78%.Built cross-sections are ∼5% bigger than design cross-sections.Concrete lining (1:2:4 P.C.C.) is mor

Atmospheric water harvesting (AWH) can provide clean and safe drinking water in remote areas. The present study provides a comprehensive review of adsorption-based AWH by using the scientometric approach. The publication types are mainly composed of articles and reviews, accounting for 75.37% and 11.19% of the total, respectively. Among these publications, ~95.1% were published in English and came from 154 different journals which demonstrates that researchers have shown a great interest in this field. However, much less contribution has been received thus far on this topic from Pakistan. Therefore, this study aims to explore a solar-driven adsorption-based AWH system in terms of varying relative humidity (RH), solar irradiance, and various types of adsorbent materials. Geospatial mapping and Monte Carlo simulations are carried out to integrate the operational parameters of the system and materials with Pakistan’s climatic conditions to forecast the AWH potential (L/m²/d). Probability distribution of 100,000 trials is performed by providing lower, mode, and upper values of the independent parameters. The possible outcomes of the adsorbed volume of water are determined by generating random values for the independent parameters within their specified distribution. It was found that MIL-101 (Cr) achieved the highest water-harvesting rate (WHR) of 0.64 to 3.14 (L/m²/d) across Pakistan, whereas the WHR was lowered to 0.58 to 1.59, 0.83 to 0.94, and 0.45 to 1.26 (L/m²/d) for COF-432, zeolite, and silica gel, respectively. Furthermore, parameter optimization and sensitivity analysis are performed to finalize the boundary conditions of the adsorption-based AWH system by ensuring the maximum volume values within the desired specification limits (1–4 L/m²/d).