The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrients as possible per unit of land area. The energy required to harvest corn silage is affected by many factors, including crop moisture, cutting lengths, particle size distribution, etc. This requires understanding the energy requirements of the harvesters used in the process. Using micro-sensors, the feed rate into corn silage harvesters is measured based on load cell data. This method helps in understanding the energy consumption and efficiency of the harvester during the feeding process, leading to more efficient and productive operations. On the other hand, artificial intelligence techniques are used to measure core size and cutting length to control machining parameters. We conclude from this review that precision agriculture techniques help farmers understand the efficiency of corn silage harvesters and know silage yield and quality, which helps them make informed decisions regarding energy use and thus obtain high productivity.
A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λmax 496nm.The linearity range of sulfamethoxazole was 3-100 μg. mL-1, with (LOD) was 0.593 μg. mL-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of
... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
... Show MoreShumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ
... Show MoreThe increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot
... Show MoreA simple and accurate method to determinate furosemide (FUR) based on converting the secondary amine to primary amine with acidic hydrolysis then azotization by nitrous acid and coupled with resorcinol as a coupling agent in aqueous medium at pH 13. The optical characteristic like beers law limit found to be (0.25-2.5) μg.ml−1, detection and quantification limits (0.0196) (0.0654) μg.ml−1respectivly and Sandel sensitivity was 0.006738 μg.cm−2. The least-square method was used to evaluate the regression equation and the correlation coefficient. The resulted azo dye has a maximum absorbance at 430 nm with light oran
A new 5‐fluorouracil–naproxen conjugate is synthesized as a mutual prodrug for targeting cancer tissues. The structure of the target compound and their intermediate are characterized by their melting point, IR, 1H NMR, 13C NMR, and elemental microanalysis. The cytotoxic activity is preliminarily evaluated using nonsmall lung cancer CRL‐2049, human breast cancer CAL‐51, and one type of normal cell line; rat embryo fibroblast cell line. The synthesized compound shows a good cytotoxic effect at the cancer cell and no significant effect at rat embryo fibroblast cell line.
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
... Show MoreThis study aimed to incorporate hydroxyapatite nanoparticles (nHA) or amorphous calcium phosphate nanoparticles (nACP) into a self-etch primer (SEP) to develop a simplified orthodontic bonding system with remineralizing and enamel preserving properties.
nHA and nACP were incorporated into a commercial SEP (Transbond™ plus) in 7% weight ratio and compared with the plain SEP as a control. Shear bond strengths (SBS), enamel damage, and adhesive remnant index (ARI) scores were evaluated at 24 h