Australian Journal of Basic and Applied Sciences

December 2019


Agroindustry Waste as Source of Nutrients for Soybean Production and Influence on Soil Microbiology

João Carlos Gonçalves, Francielli Gasparotto, Márcia Aparecida Andreazzi, Edison Schmidt Filho, Cleiltan Novais da Silva, Natália Caetano Vasques, Bárbara Maria Lustri

Abstract The use of agroindustrial and livestock residues as fertilizers for crops is a promising alternative aiming at environmental and economic sustainability. Residues can be obtained through various agricultural and agroindustrial activities such as sugar cane processing and animal production such as poultry farming and are commonly used on different vegetables. Therefore, the objective of this work was to evaluate the influence of the application of chicken litter and filter cake, associated or not to mineral fertilization, in the soil microbial population and in the development of soybean plants. Organic fertilization (cane filter cake - SFC, chicken bed - PL) and chemical fertilization (nitrogen - phosphorus - potassium - NPK - 04 - 30 - 10) were applied. The treatments were: T1-PL (5 ton ha-1), T2-PL (5 ton ha-1) + NPK (139 kg ha -1), T3-SFC (25 ton ha -1), T4- 5 ton ha-1) + NPK (257 kg ha-1), T5 - NPK (139 kg ha-1) and T6 - control (without fertilizer application). The number of colonies of fungi, bacteria and actinomycetes was evaluated. The development of the soybean crop was analyzed by counting the number of emerged seedlings, number of root nodules and yield of grains. Statistical differences (p <0.05) were observed in the population of actinomycetes submitted to T2, T4 and T6 treatments. The other factors presented similar results for all treatments. Therefore, it is suggested the possibility of using filter cake and chicken bed as a source of nutrients for soybean cultivation, since the application improves soil properties and does not cause negative changes in the microbial population.

[ FULL TEXT PDF 1-6 ] DOI: 10.22587/ajbas.2019.13.12.1


Allelopathy in Aqueous Extract of Bixa Orellana on Euphorbia heterophylla, Raphanus sativus and Bidens pilosa

Maira Cristina Schuster Russiano, Pedro Valério Dutra de Moraes, Thiago Cacção Villa, Carlos Guilherme dos Santos Russiano Alberto Ricardo Stefeni, Rayanah Stival Svidzinski, Darlin Ramos

Abstract Bixa orellana commonly known as urucum or colorau is very much utilized in culinary, since it is a species endowed with several chemical compounds, it becomes a good candidate to allelopathy. Given the crescent use of alternative agricultural inputs, less aggressive to the human and environmental health, the present work set as its goal to verify the allelopathy activity in the aqueous extract of Bixa Orellana on Euphorbia heterophylla, Raphanus sativus and Bidens pilosa. The adopted experimental outline has been entirely randomized, with four repetitions. The treatments were: concentrations of 1.25, 2.5, 5 and 10% of aqueous extract, and witness with distilled water, conducted in germitest paper rolls with 50 seeds of wheat per soil, under temperature of 25ºC. The length of the aerial part, root length, percentage of germination, germination speed index, vigor and average speed of germination. After the data has been tabulated, they were submitted to the Tukey test under 5% of error probability in the R bio software. The aqueous extract of Bixa Orellana did not present allelopathy activity on the evaluated parameters in germination of Euphorbia heterophylla and Raphanus sativus, however there has been a reduction in the average speed of germination and germination speed index of Bidens pilosa.

[ FULL TEXT PDF 7-9 ] DOI: 10.22587/ajbas.2019.13.12.2


Water Flow forecasting using Artificial Intelligence techniques and Markov chain model: The Blue Nile Scenario

Atika Hussein, Johnson Agbinya

Abstract Water flow forecasting is expected to be achieved to overcome water disasters in Sudan. Daily Flow Forecasting of the Blue Nile is expected to be achieved using real data sets of river flow and weather parameters from metrological station Sudan.When the Renisunse Dam is filled up for the first time, the margin of safety has to be high to avoid unpredictable disasters. If there is a defect in Renisunse Dam, such as overflow or collapse of the Dam partially or wholly, it is going to endanger Sudan up to the Great Desert.So, it is imperative in hydrology to allow accurate evaluation in water budget, floods erosion, and even for local river navigation. In this paper, three models for forecasting water flow in Blue Nile using Artificial Neural Network, Support Vector Machine, and Markov Chain are built. An ensemble model for forecasting water flow periodically will be built and compared to the results of each model separately. Single models usually give predictions that do not consider all phenomena or events. Ensemble modeling gives better accuracy than single classifiers. In this research, real data was collected from the metrological stations (Soba and Eldeim) and the Ministry of Irrigation for the years 2003 until 2015. It includes the daily data of river flow, level, discharge, relative humidity, Sunshine Duration (SSD), rainfall, temperature maximum, temperature minimum, pressure, wind speed, and wind direction from the ground measurement. This data was used for building an ensemble model predicting the flow of the Blue Nile using three different algorithms. These algorithms, which are (Artificial Neural Network, Support vector regression, and Markov chain), were trained and applied separately for the prediction of flow. The results were compared, showing that the Markov chain gives the best accuracy for predicting river flow in the Blue Nile. Although tested on the Blue Nile, the models should apply to other rivers provided the parameters are also derived from the statistics for those rivers. Two ensemble techniques, which were voting and bagging, were implemented. The results showed that using ensemble models with bagging and voting improved the accuracy of prediction. Also, the analysis indicated that bagging gives better accuracy than voting. The software used in this research is the R language, and Rapid Miner. It is concluded that it is difficult to determine the best algorithm to be used in a specific application. The only way to solve this problem is by trying many algorithms to find which one is better. This paper focused attention on the importance of selecting the right data or algorithm before using a particular modeling technique. The performance is compared using the correlation coefficient and accuracy.

[ FULL TEXT PDF 10-18 ] DOI: 10.22587/ajbas.2019.13.12.3


Poverty Data Retrieval Services Blockchain based on local governments

Moh. Hidayat Koniyo, Made Sudarma, Moh. Syafri Tuloli

Abstract This study was conducted using a literature review with a systematic review (Dotsika, 2017). The literature related to Blockchain is examined for a description of the needs (requirement) needed for the poverty data retrieval service, and the research show that the distribution of KEP help There is an underprivileged community on an area always identical to the problem on duplicating help and manipulation of family data that does not may have help data on underprivileged families. To ensure the integrity of the captured data is not duplicated and non-rejection, a blockchain-based poverty data retrieval plan is one solution. The purpose in this study is to ensure that the data taken cannot be changed after data retrieval and the database cannot be denied that such data has been provided because of certain requests. The proposed service eligibility using a blockchain method is a demand for poverty databases in the form of poor family data and the help data placed in the blockchain network and tested with a hash value that has been Created from the blockchain.

[ FULL TEXT PDF 19-25 ] DOI: 10.22587/ajbas.2019.13.12.4


The Relationship between Socio demographic Factors and Terminated Pregnancy among Nigerian Women

Samuel Adewale Aderoju

Background: Pregnancy termination is an illegal medical procedure in Nigeria except in a situation of having the child puts the mother’s life at risk. Hence, the act is a rare event in the country and associated with some socio-demographic factors. Objective: The aims of the study were to appropriately model pregnancy termination so as to evaluate socio-demographic factors contributing to having terminated pregnancy among Nigerian women. Methods: The data were extracted from the 2013 Nigeria Demographic and Health Survey (NDHS) which exhibited class imbalanced, hence, logistic regression in large rare events and imbalanced data using different resampling techniques were exploited to improve the model’s performance. Synthetic Minority Oversampling Technique (SMOTE) function was used to improve the model’s performance. The analysis was done using R software. Results: The results showed that the model’s sensitivity and Precision values improved from zero to 50% and 32.43% respectively; this aspect is missing in the previous literatures to the best of my knowledge. Keeping other factors constant, a unit increase in age the odds of having pregnancy termination increases by 3.6%; women living in urban area were 50% more likely to experience pregnancy termination than women living in rural area; women from North East (NE), North West (NW), South East (SE), South South (SS) and South West (SW) were 83.5%, 22.5%, 43.2%, 25.3% and 25.9% , respectively, more likely to experience pregnancy termination than women from North Central (NC); women with primary, secondary and higher education levels were 39.2%, 50.1% and 44%, respectively, more likely to experience pregnancy termination compared to women with no education. Conclusion: The findings of this study shows that in using predictive model, there is need to evaluate the model’s accuracy, sensitivity and precision in order to ascertain the reliability of the model’s results. Moreover, family planning projects in Nigeria should stress on advancing the use of modern preventative techniques to further reduce the cases of pregnancy termination. Above all, there is need to improve maternal healthcare services in order to help women during the difficulties of unintended pregnancy.

[ FULL TEXT PDF 26-30 ] DOI: 10.22587/ajbas.2019.13.12.5


Effect of water availability on the development of Paspalum virgatum L.

Paulo Cesar Laurindo Silva, Oscar Mitsuo Yamashita, Ivone Vieira da Silva, Adriano Maltezo da Rocha, Bruna Zonta de Brito, Vanessa de Andrade Royo, Keyla Laisa Araújo Saldanha, Marco Antonio Camillo de Carvalho

Abstract Paspalum virgatum (L.) is a monocotyledonous species considered to be an important weed. It is a difficult to control plant, as it has the same morphological, physiological and biochemical characteristics of plants cultivated for use as fodder. Due to the difficulty of control, this plant has caused damage in the pasture areas. In periods of lack of rainfall in the Amazon region, there is the possibility of adopting management practices. However, the behavior of P. virgatum under conditions of water stress is not known. The hypothesis is that, due to its characteristics, the species is tolerant to the lack or excess of water, which allows it to survive even after several months without water supply or also in rainy periods where there is water abundance, very common situations in the region. Amazon. The aim of this study was to evaluate the behavior of P. virgatum in situations of water stress (lack and excess of water). The experiment was carried out in a greenhouse. In a 3 x 2 factorial scheme, three water availability (water deficit, field capacity and flooding) were evaluated in two evaluation periods (28 and 56 days). Plants subjected to water deficit were lower than those under field capacity and flooding, presenting higher values for height, stem diameter, number of leaves and number of tillers. There was variation of response to the other variables when the plants were kept in the three different water conditions. However, no plants died, demonstrating rusticity and adaptation of the species to these conditions. The water deficit condition promoted higher values than the field capacity and flooding only for the chlorophyll content of the plants. Thus, it is concluded that P. virgatum is less resistant to water deficit than to soil flooding; whereas water deficit causes a higher nitrogen concentration in P. virgatum shoot; Although the water deficit reduces the development of the species, it still showed high aggressiveness and recovery under water stress conditions. From this information, it is verified that waiting for the plant to wither due to lack or excess of water, or use of controlled floods will not promote satisfactory control of the species. Thus, it is necessary to develop management practices that consider this capacity of P. virgatum to survive both under and under water in the substrate where it develops, and can stay alive for long periods.

[ FULL TEXT PDF 31-40 ] DOI: 10.22587/ajbas.2019.13.12.6


Modelling of the traditional solar drying kinetics of cassava (Manihot esculenta Crantz) using Multilayer Perceptron: A case study

Yao Marcel Konan, Kabran E.E. Andrée-Marie, Trokourey Albert

Abstract Studies relating to the modelling of the traditional solar drying kinetics of cassava (Manihot esculenta Crantz) by artificial neural networks, particularly by the multilayer perceptron, are very little provided in the scientific literature. So, it is important to lead studies on this subject to contribute to thorough knowledge of this drying process of cassava. It is in this context this study was carried out, with its main objective the static and hourly dynamics modelling of the moisture contents of six cassava varieties intensively grown in Côte d'Ivoire by using the multilayer perceptron, hence its originality. In this study, the implementation of the multilayer perceptron was done with the Levenberg-Marquardt algorithm for model optimization. The best model for the static modelling of the moisture contents for all cassava varieties considered in this study is 7- 4-1 model. This model explains to 97.61% (R2app) the variations of the seven input parameters and predicts at 95.45% (R2test) the static evolution of their moisture contents. For the hourly dynamics modelling of the moisture contents for all cassava varieties considered in this study, it is best translated by 8-2-1 model. This model explains to 98.01% (R2app) the hourly variations of the 8 input parameters and predicts at 96.24% (R2test) the hourly dynamics of theirs moisture contents. These two models obtained present a good approach to the modeling of the traditional solar drying kinetics of cassava. So, this study has once again shown the great capacity of artificial neural networks in general, and in particular of the multilayer perceptron, for the modelling of any complex phenomenon, such as the traditional solar drying kinetics of plants.

[ FULL TEXT PDF 41-48 ] DOI: 10.22587/ajbas.2019.13.12.7


Effective removal of Cu2+ and Pb2+ ions by Zeolite NaY synthesized from M’Batra clay (Cote d’Ivoire)

Koffi Jean Baptiste ALLOKO, Tchirioua EKOU, Olivier LAFON, Lynda EKOU

Abstract Water pollution from heavy metals is a particular problem due to their recalcitrance and persistence in the environment. With the development of research, wastewater treatment has reached a certain level. Adsorbents such as zeolite effectively remove metal ions in the water. The main objective of this research is to study the efficiency of zeolite NaY synthesized from M’Batra clay to remove Cu2+ and Pb2+ ions in aqueous solution by adsorption. The effects of pH solution, initial concentration, contact time and amount of adsorbent on the removal of copper and lead were studied in batch experiments. The characterization of this zeolite NaY and natural clay was done in a previous work. The results showed that the removal of Cu2+ and Pb2+ ions over zeolite NaY synthetized with clay extracted from M’Batra village (Cote d’Ivoire) and natural clay is very fast in the first 40 minutes and reaches equilibrium around the 60 minute. The retention capacity of copper and lead on zeolite NaY increases with increased with adsorbent dose, with pH and reaches its maximum at pH = 5. The removal rate of Cu2+ and Pb2+ increases with the mass of the adsorbent, reaches a plateau around 0.5 g and becomes constant. Freundlich and Langmuir adsorption isotherms indicate that the zeolitic support has a very high adsorption capacity of metal ions of Cu2+ and Pb2+ in aqueous solution. The adsorption isotherm data fitted well to the Langmuir isotherm. In conclusion, the zeolite NaY synthesized from M'Batra kaolin is an effective adsorbent in the removal of Cu2+ and Pb2+ metal ions.

[ FULL TEXT PDF 49-55 ] DOI: 10.22587/ajbas.2019.13.12.8


Bell Pepper Sprouts Produced in Polystyrene Trays with the addition of Turkey Manure in the Substrate

Lucheli Sirtoli Corá, Francielli Geremia, Maurício Grassi, Alberto Ricardo Stefeni, Rayanah Stival Svidzinski, Fernando Luiz Schneider

Abstract The production of seedlings depends on several factors, and the composition of the substrates is an extremely relevant factor, since the development of the plant is directly related to the physical, biological and chemical properties of the substrate, in this sense, aiming to analyze the viability of seedling production in bell peppers on polystyrene trays (Capsicum annuum L.), with the addition of different turkey manure in doses to the substrate. The experiment was carried out in the experimental area belonging to Faculdade Educacional de Dois Vizinhos - UNISEP – Union de Ensino do Sudoeste do Paraná, Câmpus Dois Vizinhos-PR. The design of this experiment was the completely randomized design (DIC), consisting of five treatments and four replicates of 30 plants each. The treatment consisted of the addition of turkey manure at 0% (control - without turkey manure), 10%, 20%, 30% and 40%, on commercial substrates. The commercial Substrate used was Plantmax®. Sowing of the experiment was carried out in expanded polystyrene trays of 120 cells, which were filled with commercial substrate and the different concentrations of turkey manure. At the transplant stage, shoot height, root length, number of leaves, fresh mass and shoot mass were evaluated. Data were submitted to regression analysis. Plant height responded positively up to the 30% addition rates of turkey manure in the substrate. All the growth and development variables analyzed with the exception of root length showed satisfactory results, when the seedlings were submitted to planting with the addition of 20% turkey manure in substrate. Therefore, the use of turkey manure is efficient in the production of bell pepper seedlings in trays under protected cultivation. However, there is a need to develop further studies.

[ FULL TEXT PDF 56-60 ] DOI: 10.22587/ajbas.2019.13.12.9


A Review of Parallel Support Vector Machines (PSVMs) for Big Data classification

Iatimad Satti Abd Elkarim, Johnson Agbinya

Abstract Extending technology capability and growth of data have resulted in the need for processing large data sets faster and accurately. Machine learning techniques are used excessively to represent knowledge and classify big data. This study aims to deal with big data analysis, using parallel computing through k-means clustering applied to SVM algorithm Support Vector Machines are a reliable, efficient classification method in the area of machine learning because it has a good generalization capability and ability to classify big data accurately. However, canonical SVM is not suitable for big data sets due to its high computational complexity. Many scientists and researchers are therefore worried about how to improve the computation speeds and efficiency of different classification algorithms, and substantial accomplishments have been made. This paper gives a review of articles of the current state of research regarding an improved form of SVM and Parallel Support Vector Machine (PSVMs) based on MapReduce and their applications in different fields. The paper further applies PSVM on realistic data. k-means clustering is used for partitioning the data points and then applied to support vector machine model. These two algorithms are implemented in four datasets for classification. Real water quality dataset from the ministry of health and different water stations in Sudan (2006-2017) is used to classify whether the water is suitable for drinking or not. The Adult dataset is used to classify the income of a person, whether it exceeds $50k/yr or not based on different parameters. The diabetes data set is used to classify whether the patient has diabetes or not based on various attributes. The Cover type dataset is used to do the classification process to five types of forest areas found in the Roosevelt National Forest in Colorado. The results of both algorithms are compared. The results showed that the applying of the k-means with the support vector machine give very strong accuracy and has a good impact on reducing computation time. The numerical experiment of applying of the k-means applied to SVM is compared with other SVM frameworks. The performance is compared using accuracy and time consuming.

[ FULL TEXT PDF 61-71 ] DOI: 10.22587/ajbas.2019.13.12.10


Exploring the Critical Success Factors for Effective Implementation of the ISO 9001 Quality Management System

Mahmoud Aburas, Angela Lee

Abstract Background: Interest in quality began to emerge during the 1940s, where companies from various sectors started to incorporate quality systems while establishing specific criteria for their suppliers' compliance. This sporadic approach led to the creation of barriers to trade resulting from inconsistent characteristics and quality standards, and thus the introduction of common standards was required to satisfy the client's requirements, as realized by the International Organization for Standardization (ISO). Quality management under ISO 9001 is globally accepted and has moved into other sectors, including the construction industry. Nevertheless, research has revealed that project managers tend to consider the primary benefit of quality management systems (QMSs) as marketing and procurement tools, with challenges identified regarding the implementation. Objective: This study seeks to explore the critical success factors (CSFs) for the successful implementation of the ISO 9001 QMS in UK construction projects. Methods: A review of the literature on QMSs, ISO 9001 and the UK construction industry were conducted. Then, semi-structured interviews were carried out with six project managers from UK construction companies to explore their perceptions on ISO 9001 implementation through content analysis. Results: The findings of this research confirm a set of seven CSFs (i.e. client focus, engagement of people, leadership, the process approach, relationship management, continuous improvement, and change management) as being vital to the successful implementation of the ISO 9001 QMS in UK construction projects. Conclusion: This study identifies seven CSFs for the successful implementation of the ISO 9001 QMS in the UK context, six of which are established quality management principles (QMPs), while the seventh, change management, represents a CSF that has potential for inclusion in future revisions of the QMS as a QMP, thus contributing to the quality management literature in general, and specifically from a UK perspective.

[ FULL TEXT PDF 72-77 ] DOI: 10.22587/ajbas.2019.13.12.11