The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mean Squared Error, Mean Absolute Error and R-squared and identified that after the inclusion of gradient boosting regression, the accuracy increased to 92.77%. The MAE value decreased from 26.20 Mg/ha to 21.58 Mg/ha. The results indicate that machine learning models can improve the prediction of crop yield.
The experiment was conducted at field of garden of Department of Biology, Collage
of Education (Ibn-Al-Haitham) University of Baghdad during winter season of 2009-2010.
The aim of present study is the effect of growth regulator Gibberellins by using two
concentrations (100, 200) ppm and also Thiamine in two concentrations (10, 50) ppm, on the
some yield component characters and active component of volatile oil Cumin (Cuminum
cyminum L.).
The results showed that GA3 in (100) ppm increased the yield component, protein
concentration and increased in Cuminaldehyde, Perillaldehyde and Thyoml concentration.
The results showed that the best concentration was (50) ppm of Thiamine showed an
increasing concentratio
Undesirable growth of potato (Solanum tuberosum L.) crop under an excessive N fertilizer application is the main obstacle presently. This research was conducted to investigate the response of different potato cultivars; Russet Burbank, Shepody, and Superior, and its qualitative characteristics under a series of N rates. Six rates of N fertilization (0–280 kg ha−1) were applied on 11 sites in a randomized complete block design, with four replications. Sites with ≥30 g kg−1 of soil organic matter (OM) produced total tuber yield, marketable yield, and tuber weight per plant 39.5, 45.2, and 54.9%, respectively, higher than sites with ≤30 g kg−1 of OM. Tubers specific gravity increased by 0.18% in the sites with ≥30 g kg−1 of OM.
... Show MoreKombucha(Khubdat Humza) is composed of yeast and acetic acid bacteria especially, Acetobacter xylinum which forms a cellulose pellicle on tea broth. Kombucha(Khubdat Humza) produces bacterial cellulose pellicles, with unique purity and fine structure. It can be used in many forms, such as an emulsifier, stabilizer, dispersing agent, thickener and gelling agent but these are generally subsidiary to its most important use of holding on to water. Recently, bacterial cellulose is used in many special applications such as a scaffold for tissue engineering of cartilages and blood vessels, also for artificial skin for temporary covering of wounds, as well as its used in the clothing industry. The yield of cellulose produced were investiga
... Show MoreAim of this research is the description with evaluation the photons rate probability at quark-gluon reactions processes theoretically depending on quantum color theory. In high energy physics as well as quantum field theory and quantum chromodynamics theory,they are very important for physical processes. In quark–gluon interaction there are many processes, the Compton scattering, annihilation pairs and quark–gluon plasma. There are many quantum features, each of three and systems that taken which could make a quark–gluon plasma in character system. First, electric quark charge and color quantum charge that’s satisfied by quantum number. Second, the critical temperature and
... Show MoreThe distribution of chilled water flow rate in terminal unit is a major factor used to evaluate the performance of central air conditioning unit. In this work, a theoretical chilled water distribution in the terminal units has been studied to predict the optimum heat performance of terminal unit. The central Air-conditioning unit model consists of cooling/ heating coil (three units), chilled water source (chiller), three-way and two-way valve with bypass, piping network, and pump. The term of optimization in terminal unit ingredient has two categories, the first is the uniform of the water flow rate representing in statically permanents standard deviation (minimum value) and the second category is the maximum heat transfer rate fro
... Show MoreExperimental study of heat transfer coefficients in air-liquid-solid fluidized beds were carried out by measuring the heat rate and the overall temperature differences across the heater at different operating conditions. The experiments were carried out in Q.V.F. glass column of 0.22 m inside diameter and 2.25 m height with an axially mounted cylindrical heater of 0.0367 m diameter and 0.5 m height. The fluidizing media were water as a continuous phase and air as a dispersed phase. Low density (Ploymethyl-methacrylate, 3.17 mm size) and high density (Glass beads, 2.31 mm size) particles were used as solid phase. The bed temperature profiles were measured axially and radially in the bed for different positions. Thermocouples were connecte
... Show MoreThe research dealt with the effectiveness of prediction and foresight in design as a phenomenon that plays a role in the recipient's engagement with the design, as it shows the interaction between the recipient and the interior space. The designer is keen to diversify his formal vocabulary in a way that secures visual values that call for aesthetic integration, as well as securing mental and kinetic behavioral understanding in the interior space.
As the designer deals with a three-dimensional space that carries many visual scenes, the designer should not leave anything from it without standing on it with study and investigation, and puts the user as a basic goal as he provides interpretive data through prediction and foresight that le
Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo
This study assessed the quality of hand-dug drinking water sources in Eku and its environs at Eku I, Samagidi, Eku 2, and Okuechi, using the weighted arithmetic water quality index method. Water samples collected from hand-dug wells at these locations returned values for analyzed parameters. Temperature 26 – 30(⁰C), dissolved Oxygen (D.O) 5.2-8mg/l, biological oxygen demand (BOD) 5.2-8(mg/l), Electrical Conductivity (EC) 77-119(µS/cm), Total suspended solids were (TSS) 20000-120000(mg/l), pH 5.31-7.09, Phosphates 2-9.2(mg/l), Alkalinity 28-160(mg/l), Turbidity, 0.02 -0.19(NTU) Total coliform 2 -48 (cfu/ml) and fungal count 1-502. Variations in the values of these parameters were only significant for phosphate, alkalinity, and turb
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