Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference vegetation index (NDVI) and chlorophyll index (CI) measurements were obtained weekly from the active optical sensors, GreenSeeker (GS) and Crop Circle (CC). The 168 kg N ha−1 produced the maximum potato yield. Indices measurements obtained at the 16th and 20th leaf growth stages were significantly correlated with tuber yield. Multiple regression analysis (potato yield as a dependent variable and vegetation indices, NDVI and CI, as independent variables) could make a remarkable improvement to the accuracy of the prediction model and increase the determination coefficient. The exponential and linear models showed a better fit of the data. Soil organic matter content increased the yield significantly but did not affect the prediction models. The 18th and 20th leaf growth stages are the best time to use the sensors for yield prediction.
Fresh water production from saline or waste water utilizing solar stills is the secured future approach in water industry with low cost and no environmental pollution accompanied with low productivity. In this work, the effect of inserting different available materials in a passive Single Slope Solar SSS stills on their productivity is accomplished. Side by side tests are performed on a conventional still, and three SSS stills inserted with carbon filter media, Copper wire mesh, and Cellulose sheets. All these stills are symmetrical in dimensions with 0.5 m2 base area tested for 20mm water level. The stills have been manufactured, instrumented, and tested in July 2021 under DhiQar-Iraq climate conditions (latitude 31.2° N, longitude 46.34
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This study was aimed to assess the impact of vermicompost, glutathione, and their interaction on beetroot (Beta vulgaris L.) growth, yield, and antioxidant traits. The experiment carried out at vegetable field of the College of Agricultural Engineering Sciences - University of Baghdad during fall season 2019. The experiment was conducted using factorial arrangement within Randomized Complete Block Design with two factors and three replicates (3X3X3). Applying vermicompost before cultivation represented the first factor (0, 15, 30 ton.ha-1), which symbolized (V0, V1, V2). Glutathione (0, 75, 150 mg.L-1) which symbolized (G0, G1, G2) represented the second factor. Results showed the superiority of secondary interaction treatment V2G2
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The goal of this investigation is to prepare zinc oxide (ZnO) nano-thin films by pulsed laser deposition (PLD) technique through Q-switching double frequency Nd:YAG laser (532 nm) wavelength, pulse frequency 6 Hz, and 300 mJ energy under vacuum conditions (10-3 torr) at room temperature. (ZnO) nano-thin films were deposited on glass substrates with different thickness of 300, 600 and 900 nm. ZnO films, were then annealed in air at a temperature of 500 °C for one hour. The results were compared with the researchers' previous theoretical study. The XRD analysis of ZnO nano-thin films indicated a hexagonal multi-crystalline wurtzite structure with preferential growth lines (100), (002), (101) for ZnO nano-thin films with different thi
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Compounds of (ZnO)1-x(SnO 2 ) x were prepared with various proportions of tin oxide (SiO 2) (x = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0) by mixing zinc oxide (ZnO) with highpurity tin oxide and then sintering the mixture in an oven at a temperature of 1000 °C for a period of 1 h. The resulting powders were ground and pressed into tablets of 1 cm diameter and 0.5 cm thickness. The properties of (ZnO) 1-x(SnO 2 ) x composites flms were prepared and studied as sensitive to the diferent gases NO2 and H2 S. Thin flms were prepared from (ZnO) 1-x(SnO 2 ) x via pulsed laser deposition method using glass and single crystal silicon for investigation the morphology and gas sensing properties with a thickness of 150 nm. The morphology examinat
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The agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO2 concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1
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Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du
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