Watermelon is known to be infested by multiple insect pests both simultaneously and in sequence. Interactions by pests have been shown to have positive or negative, additive or non additive, compensatory or over compensatory effects on yields. Hardly has this sort of relationship been defined for watermelon vis-à-vis insect herbivores. A 2-year, 2-season (4 trials) field experiments were laid in the Research Farm of Federal University Wukari, to investigate the interactive effects of key insect pests of watermelon on fruit yield of Watermelon in 2016 and 2017 using natural infestations. The relationship between the dominant insect pests and fruit yield were determined by correlation (r) and linear regression (simple and multiple) analyses. Multimodel inference was used to define the predictor that impacted on fruit yield the most. Results indicated that, each pest had highly negative and significant (p < 0.05) impact on yield (range of r = -0.78 to -0.92), and that the coefficient of determination (R2) values (which were indicative of the effect of pests or their complexes on yield) did not rise on addition of interaction terms. This reveals a non additive negative impact of insect interactions on the fruit yield of watermelon. This may be due to among others; competition by the pest, phenology, plant defenses or changes in nutritional content of the plant. The need to therefore employ discriminate analysis to ascertain the contribution of each pest to yield loss when multiple pest infest a crop is thus highlighted.
Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
... Show MoreLeishmaniasis is one of the important parasitic diseases, affecting mainly low social class people indeveloping countries, and is more prevalent and endemic in the tropical and subtropical regions of old worldand new world. Despite ofbroad distribution in Iraq,little known about the geneticcharacteristics of thecausative agents. So this study was aimed to evaluate the genetic varietyoftwo IraqiLeishmaniatropicaisolatesbased on heat shock protein gene sequence 70 (HSP70) in comparison with universal isolates recordedsequences data. After amplification and sequencing of HSP70 gene,the obtainedresults were alignment alongwith homologous Leishmania sequences retrieved from NCBI by using BLAST. The analysis results showedpresence of particular g
... Show MoreUV-Vis technique has been used to study the adsorption of para-nitroaniline (PNA) on Iraqi siliceous rocks powder. Adsorption isotherms were investigated, temperature effect on adsorption was calculated, Results showed that the adsorption was an exothermic process and the thermodynamic functions were calculated. The effect of the pH on adsorption was studied and the ionic strength effect on adsorption was studied, It was found that adsorption increases with the presence of sodium chloride ions. The kinetic study of adsorption before equilibrium showed that the adsorption was pseudo first order according to according (Lagergren equation).
The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show Morethe behavior of the first-order black and gray solitons propagtedin optical fiber in the presence of frequency chirp is studied analytically and numerically results show that phase profile of black solitons changes abruptly
Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences.
Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences.