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Predicting Phosphorus and Potato Yield Using Active and Passive Sensors
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Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as triple superphosphate (46% P2O5). Vegetation indices (VIs) and plant pigment levels were calculated at various time points during the potato growth cycle, correlated with total potato yields and P uptake by the stepwise fitting of multiple linear regression models. Data generated by Crop Circle™ and GreenSeeker™ had a low predictive value of potato yields, especially early in the season. Crop Circle™ performed better than GreenSeeker™ in predicting plant P uptake. In contrast, the passive sensor data provided good estimates of total yields early in the season but had a poor correlation with P uptake. The combined use of active and passive sensors presents an opportunity for better P management in potatoes.

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Spectroscopic studies of activated carbon fabricate from potato peel
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Publication Date
Mon Jan 01 2024
Journal Name
African Journal Of Biomedical Research
Yogurt Acid Whey Effect on Enamel Resistance to Phosphorus Dissolution Against Acid Challenge
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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Irrigation Systems, Bio-Fertilizers and Polymers on some Growth Characteristics and Potato Production in Desert Soils, Karbala Governorate
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Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF YIELD AND ITS COMPONENTS OF INTRODUCED VARIETIES OF MAIZE UNDER DIFFERENT PLANTING DENSITIES: STUDY OF YIELD AND ITS COMPONENTS OF INTRODUCED VARIETIES OF MAIZE UNDER DIFFERENT PLANTING DENSITIES
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In order to evaluate the performance of introduced varieties of maize and test them under different levels of plant density, and to determine which of the introduced varieties give a high yield and at what plant density, a field experiment was carried out at Station A in the Department of Field Crops- College of Agricultural Engineering Sciences - University of Baghdad- Jadiriyah, for the fall season 2021, the RCBD design was used with four replications, in a split plot arrangement, the three plant densities (50.000, 70.000, and 90.000 Plant s ha-1) were the main plates, while the varieties represented the secondary factor, which is six varieties of maize, class 2 = 5783 DKC, Class 3 = 6315 DKC, Class 4= 6590 DKC, whic

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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Publication Date
Mon Jun 22 2015
Journal Name
Photonic Sensors
Capacitive-resistive measurements of cobalt-phthalocyanine organic humidity sensors
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Publication Date
Thu Jun 15 2017
Journal Name
Ieee Sensors Journal
Calibrating Distance Sensors for Terrestrial Applications Without Groundtruth Information
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Publication Date
Mon Jun 22 2015
Journal Name
Photonic Sensors
Capacitive-resistive measurements of cobalt-phthalocyanine organic humidity sensors
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Publication Date
Wed Sep 20 2023
Journal Name
Environmental Progress & Sustainable Energy
Production and characterization of composite activated carbon from potato peel waste for cyanide removal from aqueous solution
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Abstract<p>This research presents a response surface methodology (RSM) with I‐optimal method of DESIGN EXPERT (version 13 Stat‐Ease) for optimization and analysis of the adsorption process of the cyanide from aqueous solution by activated carbon (AC) and composite activated carbon (CuO/AC) produced by pyro carbonic acid microwave using potato peel waste as raw material. Pyrophosphate 60% (wt) was used for impregnation with an impregnation ratio 3:1, impregnation time of 4 h at 25°C, radiant power of 700 W, and activation time of 20 min. Batch experiments were conducted to determine the removal efficiency of cyanide from aqueous solution to evaluate the influences of various experimental parameters su</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Dimensional analysis of predicting the removal of chemical oxygen demand from domestic wastewater using moving bed biofilm reactor
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Municipal wastewater sources are becoming increasingly important for reuse, for irrigation purposes, so they must be treated to meet environmentally friendly local or global standards. The aim of this study is to establish, calibrate, and validate a model for predicting chemical oxygen demand for the pilot plant of mobile biofilm reactors operating from municipal wastewater in Maaymyrh located in Hilla city Using the approach of dimensional analysis. The approach of Buckingham's theorem was used to derive a model of dimensional analysis design for the forecast of (COD) in the pilot plant. The effluent concentration (COD) It has been derived as a result of the influential concentration of (COD), dissolved oxygen (DO), volume of pilot plant

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