In recent years, intelligent sensor techniques have achieved significant attention in agriculture. It is applied in agriculture to plan the several activities and missions properly by utilising limited resources with minor human interference. Currently, plant cultivation using new agriculture methods is very popular among the growers. However, the aeroponics is one of the methods of modern agriculture, which is commonly practiced around the world. In the system, plant cultivates under complete control conditions in the growth chamber by providing a small mist of the nutrient solution in replacement of the soil. The nutrient mist is ejected through atomization nozzles on a periodical basis. During the plant cultivation, several steps including temperature, humidity, light intensity, water nutrient solution level, pH and EC value, CO₂concentration, atomization time, and atomization interval time require proper attention for flourishing plant growth. Therefore, the object of this review study was to provide significant knowledge about early fault detection and diagnosis in aeroponics using intelligent techniques (wireless sensors). So, the farmer could monitor several paraments without using laboratory instruments, and the farmer could control the entire system remotely. Moreover, the technique also provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system. It offers full control of the system, not by constant manual attention from the operator but to a large extent by wireless sensors. Furthermore, the adoption of the intelligent techniques in the aeroponic system could reduce the concept of the usefulness of the system due to complicated manually monitoring and controlling process.

Root morphology and its components’ behavior could show a considerable response under multiple water application points per plant to help the ultimate effect of fruit yield and fruit quality. In this study, a comparison of a single emitter per plant was made with two, three, and four emitters per plant under drip irrigation and two irrigation levels (full irrigation 100% and deficit irrigation 75% of crop evapotranspiration) to investigate their effects on physiological parameters, root, yield, and their associated components for potted cherry tomato under greenhouse conditions in Jiangsu-China. The experimental results showed that the plants cultivated in the spring-summer planting season showed significantly higher results than the fall-winter planting season due to low temperatures in the fall-winter planting season. However, the response root length, root average diameter, root dry mass, leaf area index, photosynthetic rate, transpiration rate, fruit unit fresh weight, the number of fruits, and pH were increased by multiple emitters per plant over a single emitter per plant, but total soluble solids decreased. Besides, a decreasing trend was observed by deficit irrigation for both planting seasons, and vice versa for the case for tomato total soluble solids. Due to an increase in measured parameters for multiple emitters per plant over a single emitter per plant, the yield, water use efficiency, and water use efficiency biomass significantly increased by 18.1%, 17.6%, and 15.1%, respectively. The deficit irrigation caused a decrease in the yield of 5% and an increase in water use efficiency and water use efficiency biomass of 21.4% and 22.9%, respectively. Two, three, and four emitters per plant had no significant effects, and the obtained results were similar. Considering the root morphology, yield, water use efficiency, water use efficiency biomass, and fruit geometry and quality, two emitters per plant with deficit irrigation are recommended for potted cherry tomato under greenhouse conditions. The explanation for the increased biomass production of the plant, yield, and water use efficiency is that two emitters per plant (increased emitter density) reduced drought stress to the roots, causing increased root morphology and leaf area index and finally promoting the plant’s photosynthetic activity.

The working capability of multi-stage pumps, such as electrical submersible pumps (ESPs) handling multiphase flow, has always been a big challenge for petroleum industries. The major problem is associated with the agglomeration of gas bubbles inside ESP-impellers, causing pump performance degradation ranging from mild to severe deterioration (surging/gas pockets). Previous literature showed that the two-phase performance of ESPs is greatly affected by gas involvement, rotational speed, bubble size, and fluid viscosity. Thus, it is necessary to understand which parameter is actually accountable for performance degradation and different flow patterns in ESP, and how it can be controlled. The present study is mainly focused on (1) the main parameters that impede two-phase performance of different ESPs; (2) comparison of existing empirical models (established for two-phase performance prediction and surging initiation) with our single-stage centrifugal pump results to determine their validity and working-range; (3) gas-handling techniques applied to enhance the multiphase performance of ESPs. Firstly, it aims at understanding the internal flow mechanism in different ESP designs, followed by test studies based on empirical models, visualization techniques, bubble-size measurements, and viscosity analysis. The CFD-based (computational fluid dynamics) numerical analysis concerning multiphase flow is described as well. Furthermore, gas-handling design methods are discussed that are helpful in developing the petroleum industry by enhancing the multiphase performance of ESPs.

Accurate estimation of reference evapotranspiration (ET_o) plays a vital role in irrigation and water resource planning. The Penman–Monteith method recommended by the Food and Agriculture Organization (FAO PM56) is widely used and considered a standard to calculate ET_o. However, FAO PM56 cannot be used with limited meteorological variables, so it is compulsory to choose an alternative model for ET_o estimation, which requires fewer variables. This study built ten machine learning (ML) models based on multi-function, neural network, and tree-based structure against the FAO PM56 method. For this purpose, time series temperature data on a monthly scale are only used to train ML models. The developed ML models were applied to estimate ET_o at different test stations and the obtained results were compared with the FAO PM56 method to verify and validate their performance in ET_o estimation for the selected stations. In addition, multiple statistical indicators, including root-mean-square error (RMSE), coefficient of determination (R²), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), and correlation coefficient (r) were calculated to compare the performance of each ML model on ET_o estimation. Among the applied ML models, the ET_o tree boost (TB) ML model outperformed the other ML models in estimating ET_o in diverse climatic conditions based on statistical indicators (R², NSE, r, RMSE, and MAE). Moreover, the observed R², NSE, and r were the highest for the TB ML model, while RMSE and MAE were found to be the lowest at the study sites compared to other applied ML models. Lastly, ET_o point data yielded from the TB ML model was used in an interpolation process to create monthly and annual ET_o maps. Based on the ET_o maps, this study suggests mainly a focus on areas with high ET_o values and proper irrigation scheduling of crops to ensure water sustainability.

The spatial distribution of root systems in the soil has major impacts on soil water and nutrient uptake and ultimately crop yield. This research aimed to optimize the root distribution patterns, growth, and yield of cherry tomato by using a number of emitters per plant. A randomized complete block design technique was adopted by selecting eight treatments with two irrigation regimes and four levels of emitters under greenhouse conditions. The experiment results showed that the root distribution extended over the entire pot horizontally and shifted vertically upwards with increased emitter density. The deficit irrigation resulted in reduced horizontal root extension and shifted the root concentrations deeper. Notably, tomato plants with two emitters per plant and deficit irrigation treatment showed an optimal root distribution compared to the other treatments, showing wider and deeper dispersion measurements and higher root length density and root weight density through the soil with the highest benefit–cost ratio (1.3 and 1.1 cm cm⁻³, 89.8 and 77.7 µg cm⁻³, and 4.20 and 4.24 during spring–summer and fall-winter cropping seasons, respectively). The increases in yield and water use efficiency (due to increased yield) were 19% and 18.8%, respectively, for spring–summer cropping season and 11.5% and 11.8%, respectively, for fall–winter cropping season, with two emitters per plant over a single emitter. The decrease in yield was 5.3% and 4%, and increase in water use efficiency (due to deficit irrigation) was 26.2% and 27.9% for spring-summer and fall-winter cropping seasons, respectively, by deficit irrigation over full irrigation. Moreover, it was observed that two, three, and four emitters per plant had no significant effects on yield and water use efficiency. Thus, it was concluded that two emitters per plant with deficit irrigation is optimum under greenhouse conditions for the cultivation of potted cherry tomatoes, considering the root morphology, root distribution, dry matter production, yield, water use efficiency, and economic analysis.

The industrial augmentation and unguided anthropogenic activities contaminate water sources in most parts of the world especially in developing countries like Pakistan. High concentration of pollutants in groundwater affects human, soil, and crop health badly. The present study was conducted to investigate groundwater quality for drinking and irrigation purposes in an industrial zone of Pakistan. A GIS tool was used to investigate the spatial distribution of different physico-chemical parameters. In this study, the average results exceeding World Health Organization (WHO) and National Environmental Quality Standards (NEQS) were found for pH 7.84, total dissolved solids (TDS) 1492 mg/L, phosphate 0.51 mg/L, dissolved oxygen (DO) 9.92% saturation, F-coli 6.48 colonies/100 mL, Na⁺ 366 mg/L, HCO₃⁻ 771 mg/L, sulfate 251 mg/L, chlorides 427 mg/L, total hardness (as CaCO₃) 292 mg/L, electrical conductivity (EC) 2408 μS/cm, iron (Fe) 0.48 mg/L, chrome (Cr) 0.50 mg/L, arsenic (As) 0.04 mg/L, total phosphorus (TP) 0.17 mg/L, sodium adsorption ratio (SAR) 9.76 (in meq/L), residual sodium carbonate (RSC) 9.28 meq/L, % ion balance 14.4 (in meq/L), percentage sodium ion (% Na⁺) concentration 58.9 meq/L, and water quality index (WQI) 69.0. The trend of cations and anions were (in meq/L) Na > Mg > Ca > K and HCO₃ > Cl > CO₃ > SO₄ respectively. Although the results of the present study showed poor conditions of the groundwater for drinking as WQI but and irrigation purposes as SAR, it needs to improve some more conditions for the provision of safe drinking water and irrigation water quality.