Effect of Metal Ions, Solvents and Surfactants on the Activity of Protease from Aspergillus niger KIBGE-IB36 Pages 491-495

Effect of Metal Ions, Solvents and Surfactants on the Activity of Protease from Aspergillus niger KIBGE-IB36
Pages 491-495Creative Commons License

Hafsa Sattar, Afsheen Aman and Shah Ali Ul Qader
DOI: https://doi.org/10.6000/1927-5129.2017.13.80

Published: 13 September 2017

Abstract: Metal ions greatly impact on the enzymatic activity, they may form strong interaction by forming coordinate bond with enzyme-substrate at the catalytic site which may activate, inhibit or stabilized the enzyme molecules. In this study, extracellular protease from Aspergillus niger KIBGE-IB36 was precipitated with 40% ammonium sulfate. It was revealed that K+, Ba2+, Na+, Mg2+ Zn2+, Ca2+ boosted the protease activity whereas, Cs+, Mn2+, Cu2+, Ni2+, V2+, Co2+, Hg2+ and Al3+ showed to be inhibitor of protease. Dimethyl sulfoxide (5.0 mM) and methanol (5.0 mM) showed catalytic activity while ethanol at same concentration exhibited inhibitory effect. Protease activity augmented with Tween 80, while SDS, Triton X-100, EDTA and PMSF exhibited inhibitory effect.

Keywords: Metals, Inhibition, Activation, Protease, Aspergillus niger, Organic Solvents.

Huge and Real-Time Database Systems: A Comparative Study and Review for SQL Server 2016, Oracle 12c & MySQL 5.7 for Personal Computer Pages 481-490

Huge and Real-Time Database Systems: A Comparative Study and Review for SQL Server 2016, Oracle 12c & MySQL 5.7 for Personal Computer
Pages 481-490Creative Commons License

Khawar Islam, Kamran Ahsan, S.A.K. Bari, Muhammad Saeed and Syed Asim Ali
DOI: https://doi.org/10.6000/1927-5129.2017.13.79

Published: 07 September 2017

Abstract: Complexity, and Handling of huge data is a crucial target for all management systems. Databases are the backbone, central and core component of a computer application to store data in a logical way, which define the structure and mechanism for manipulation of data. Many Databases are available for handling and saving huge data including commercial and non-commercial like Microsoft SQL Server, Oracle Database, and MYSQL etc. Many vendors are working on modern techniques of databases spatio-temporal, object-relational, parallel databases etc. This novel research evaluates the comparative study and execution performance of top three databases according to their particular scenario and situation, after reading the paper the computer related experts especially developers easily judge, which database is most reliable in particular scenario, choosing the right decision for development of huge computer applications for hospitals, banks, and industries.

Keywords: Microsoft SQL Server, Oracle, MySQL, Huge Databases.

Management of Different Dairy Production Systems in Sindh Pages 472-480

Management of Different Dairy Production Systems in Sindh
Pages 472-480Creative Commons License

Huma Rizwana, Muhammad Khaskheli, Ghous Bakhsh Isani and Gul Muhammad Baloch
DOI: https://doi.org/10.6000/1927-5129.2017.13.78

Published: 07 September 2017

Abstract: The study of management of different dairy production system in Sindh was conducted in randomly selected from three zones consisting of nine districts of Sindh province of Pakistan. The data was collected from central zone consisting of three districts (Hyderabad, Mirpurkhas and Shaheed Benazirabad) in 2005-06, from upper zone (districts i.e. Larkana, Sukkur and Shikarpur) in 2006-07, and from lower Sindh zone(Karachi, Thatta and Badin) in years 2007-08. The educational status indicated that the graduate dairy farmers were significantly (P<0.05) high (21.11%) at urban dairy farming systems compared to peri-urban, rural market oriented, rural subsistence and mixed dairy farming systems. The results shows that urban and peri urban farming mostly was operated by ≥ 40 years of age group but under, rural market oriented , rural subsistence and mixed dairy farming ≥50 years of age group. The average herd size of urban dairy farming system was (52.67 animals per farm) higher as compare to peri-urban, rural market oriented, mixed and rural subsistence dairy farming system in upper zone. In central zone the results showed that the average herd size of peri-urban dairy farming system was significantly (100.00/farm) higher followed by other farming systems. The average herd size under urban dairy farming system in lower zone observed significantly (P<0.05) high (167.00/farm) as compared to other dairy farming systems. The overall average annual inventories at the beginning of the year urban, peri-urban, rural market oriented, rural subsistence and mixed farming were 129049, 82920, 74634, 35300 and 46658 rupees, respectively and averaging 73712 rupees. The total cost were relatively higher Rs.64506 per animal under urban farming, and the lowest total costs of Rs.31884 per animal were noted under mixed farming system. The total income generated by operators of urban dairy farms in nine districts were recorded high followed by peri-urban, rural market oriented, rural subsistence and mixed dairy farming system. It was observed that from the results that the cost: benefit ratio was significantly higher 1:0.47 under mixed farming system, followed by rural market oriented farming with average cost benefit ratio of 1:0.44. However, the cost benefit ratio under peri-urban, urban, rural subsistence dairy farming systems was 1:0.42, 1:0.36 and 1: 0.34 respectively. The results indicated that the capital turnover was higher 5.66 in case of urban farming indicating that the entrepreneur of urban dairy farming system will recoup their capital investment in 5.66 years, while the capital turnover of peri urban, rural subsistence, rural market oriented and mixed dairy farming systems was 4.33, 4.25, 3.82 and 3.72 indicates that they will recoup their capital investment in 4.33, 4.25 and 3.82 years, respectively. However, the entrepreneurs of mixed farming system will recoup their capital investment in 3.72 years, respectively.

Keywords: Dairy, production, farming, literacy, economic efficiencies, zones, Sindh.

Analyzing Diabetes Datasets using Data Mining Pages 466-471

Analyzing Diabetes Datasets using Data Mining
Pages 466-471Creative Commons License

Saman Hina, Anita Shaikh and Sohail Abul Sattar
DOI: https://doi.org/10.6000/1927-5129.2017.13.77

Published: 29 August 2017

Abstract: Data mining techniques explore critical information in various domains (for example in CRM (customer relationship management), HR (Human Resource), GIS (Geographic Information System) etc.) but most importantly in medical domain. In medical domain, data mining can assist in minimizing the risk of developing some stereotyped diseases such as cancer, heart diseases, diabetes etc. In this paper, authors have focused data of Diabetic patients. Diabetic patient’s body lacks ability to manage the glucose level in blood which can affect the other body mechanism. This can lead to the dysfunctioning of other physiological and psychological parameters such as reduced weight, skin folding. These parameters may be a valuable data source for the research. Diabetes mellitus placed 4th among Noncommunicable diseases-NCDs, caused 1.5 million global deaths each year worldwide [1]. The increase in digital information has elevated numerous challenges especially when it comes to automated content analysis and to make use of some machine learning techniques to aid mankind for predicting the non-communicable diseases like diabetics. . In this research different classifying algorithms such as Naïve bayes, MLP, J.48, ZeroR, Random Forest, and Regression were applied to depict the result. The conducted research aims to extract knowledge from the given set of data and to generate comprehensive and intelligent results.

Keywords: Data mining, Classification, Algorithm, Diabtes MelitusType II.

Classification Techniques in Machine Learning: Applications and Issues Pages 459-465

Classification Techniques in Machine Learning: Applications and Issues
Pages 459-465Creative Commons License

Aized Amin Soofi and Arshad Awan
DOI: https://doi.org/10.6000/1927-5129.2017.13.76

Published: 29 August 2017

Abstract: Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic classification techniques. Later we discuss some major types of classification method including Bayesian networks, decision tree induction, k-nearest neighbor classifier and Support Vector Machines (SVM) with their strengths, weaknesses, potential applications and issues with their available solution. The goal of this study is to provide a comprehensive review of different classification techniques in machine learning. This work will be helpful for both academia and new comers in the field of machine learning to further strengthen the basis of classification methods.

Keywords: Machine learning, classification, classification review, classification applications, classification algorithms, classification issues.

Effect of Different Synthetic Pesticides Against Pink Bollworm Pectinophora gossypiella (Saund.) On Bt. and non-Bt. Cotton Crop Pages 454-458

Effect of Different Synthetic Pesticides Against Pink Bollworm Pectinophora gossypiella (Saund.) On Bt. and non-Bt. Cotton Crop
Pages 454-458Creative Commons License

Imran Ali Rajput, Tajwer Sultana Syed, Arfan Ahmed Gilal, Agha Mushtaque Ahmed, Fahad Nazir Khoso, Ghulam Hussain Abro and Maqsood Anwar Rustamani
DOI: https://doi.org/10.6000/1927-5129.2017.13.75

Published: 29 August 2017

Abstract: The field studies were conducted at the farmer’s field in 2015-2016 to determine the effect of three different insecticides (triazon, radiant and polytrin C) on Bt. and non-Bt. cotton varieties against pink bollworm. The results revealed that triazon was observed the most effective pesticide against PBW on both cotton varieties. The mortality reduction percent of 33.99 to 30.45% was recorded at triazon, 27.72 to 26.95% at radiant and 24.68 to 14.48% at polytrin C respectively, in 2015. However, in 2016 the mortality reduction percent decreased but effective trend of these selected pesticides were observed same with mortality reduction percent of 28.15 to 25.46% at triazon, 21.95 to 23.52% at radiant and 19.96 to 16.37% at polytrin C in Bt. and non-Bt. cotton varieties. In present investigation, triazon was observed the most effective pesticide than radiant and polytrin C on larvae of PBW in both Bt. and non-Bt. varieties.

Keywords: Pesticides, pink bollworm, Bt. and non-Bt. Cotton.

Effect of Varying Levels of Nitrogen on the Growth and Yield of Muskmelon (Cucumis melo L.) Pages 448-453

Effect of Varying Levels of Nitrogen on the Growth and Yield of Muskmelon (Cucumis melo L.)
Pages 448-453Creative Commons License

Niaz Ahmed Wahocho, Aftab Ahmed Maitlo, Qadir Bux Baloch, Arshad Ali Kaleri, Lubna Bashir Rajput, Naheed Akhtar Talpur, Zeeshan Ahmed Sheikh, Fida Hussain Mengal and Safdar Ali Wahocho
DOI: https://doi.org/10.6000/1927-5129.2017.13.74

Published: 25 August 2017

Abstract: Nitrogen (N) fertilization at higher rates enhances the yield of crop plants; however, overuse of N in cultivation of crop not only decreased Nitrogen Use Efficiency of crop plants but caused severe environmental pollution. Hence, the optimum use of N is perquisite for sustainable development of Agriculture. This study was carried out during 2016, to evaluate the effect of various nitrogen applications on the economic performance of muskmelon. This research work was laid out at experimental site of Horticulture orchard SAU Tandojam with three replications in RCBD. The growth and yield performance of muskmelon was assessed by using six nitrogen (N) levels viz; 0, 30, 60, 90, 120 and 150 kg ha-1. Two varieties including Chandny and golden tumbro were used in the current study.The result showed that effect of different nitrogen doses on the economic important parameters of muskmelon was significant (P<0.05) for all the studied traits. The crop fertilized with maximum N had positive effect on vegetative traits and produced tallest plants with more branches. Nitrogen also showed significant effects on fruits characteristics and produced plants with more fruits, highest weight and maximum yield. The results further reflected that there was a significant reduction in all vegetative and fruit contributing characters with each reduction in N application rate. The cultivars revealed a highly significant response to various N doses. The variety Golden Tumbro showed maximum vine length (201.00 cm), more branches vine-1 (3.4222), more fruit vine-1 (6.7339), highest fruits weight vine-1 (3.0056), maximum single fruit weight (656.83 g), fruit yield plot-1 (4.4450 kg) and fruit yield (24.635 t ha-1).

Keywords: Muskmelon, Nitrogen, Fertilizer, Fruit, Vine.

Business Intelligence Solution for Food Industry Pages 442-447

Business Intelligence Solution for Food Industry
Pages 442-447Creative Commons License

Raheela Asif, Saman Hina and Sukaina Mushtaq
DOI: https://doi.org/10.6000/1927-5129.2017.13.73

Published: 25 August 2017

Abstract: Before the 1960’s organizations used to calculate figures on speculation. But ever since the demand for data analysis increased, Business Intelligence and Analytics is growing so rapidly that today it has been used for government, non-government, profitable, non profitable as well as the corporate world. The effect and impact on business intelligence system on various aspects of economy are increasing year to year. Recently, it is being used in the food industry as well. Many advanced techniques give rise to efficient methods and ways to provide a robust and effective environment for implementing BI systems in the food manufacturing industry domain; which is one of the most important industries across the globe. Hence this makes quite sense that this area would make use of such BI tools and take advantage in the similar manner as marketing firms and financial departments for understanding their customer needs, increasing efficiency and for keeping track of the rising demands. This paper discusses a BI system on a food manufacturing industry; National Foods Canada along with the characteristics, data, methodology as well as tools used in the system. Also examples with references of the business intelligence systems used in the food manufacturing industries are presented.

Keywords: Business intelligence, data warehouse, foods industry.

Evaluation of Different Brinjal (Solanum melongena L.) Varieties for Yield Performance and Sucking Insect Pests in Bahawalpur, Pakistan Pages 437-441

Evaluation of Different Brinjal (Solanum melongena L.) Varieties for Yield Performance and Sucking Insect Pests in Bahawalpur, Pakistan
Pages 437-441Creative Commons License

Hafiz Muhammad Irfan Ashraf, Muhammad Waqar Hassan and Moazzam Jamil
DOI: https://doi.org/10.6000/1927-5129.2017.13.72

Published: 23 August 2017

Abstract: This study investigated the relative performance of ten brinjal (Solamum melongena L.) varieties for yield in fall 2014 in Bahawalpur. The study was conducted at farm area of Islamia University of Bahawalpur. Ten brinjal varieties were evaluated for yield performance in a research trial following randomized complete block design. Significant differences existed in the yield generated by tested varieties. Significantly more yield was recorded in Shamli and Eggplant deep black followed by Advanta 306, Sandhya F1, Black boy, Black nagina and Advanta 305 in descending order. Twinkle star and Kalash F1 generated significantly less yield while the significantly least yield was recorded for Xingchangjishi than all the tested varieties. Whitefly Bemesia tabaci (Homoptera: Aleyrodidae) and jassid Amrasca biguttula biguttula (Homoptera: Cicadellidae) were the major sucking insects attacking this crop. Populations of both pest insects were recorded significantly more on Xingchangjishi while least populations of these pests were recorded on Egg plant deep black and Sandhya F1. Correlation of insect populations with yield showed inverse relationships. These results are important regarding varietal performance for yield test conducted for ten brinjal varieties. Varieties i.e.,Eggplant deep black and Shamli with significantly more yields are recommended for cultivation in this area to get more brinjal yield.

Keywords: Egg plant, solanaceae, sucking pests, yield comparison.

An Update on Secondary Metabolites from Glycyrrhiza Species Pages 431-436

An Update on Secondary Metabolites from Glycyrrhiza Species
Pages 431-436Creative Commons License

Azizuddin Shaikh
DOI: https://doi.org/10.6000/1927-5129.2017.13.71

Published: 23 August 2017

Abstract: Secondary metabolites have been obtained from the Glycyrrhiza species (Fabaceae) including G. glabra, G. echinata, G. uralensis, G. triphylla and G. macedonica. These compounds 1-25 belong to the classes, steroid, saponin, flavonoid, flavonoid glycoside, triterpenic acid, coumarin, phenolic derivative, chalcone and chalcone glycoside. This review will describe the isolated compounds 1-25, obtained from Glycyrrhiza species with their biological activities up to 1966.

Keywords: Glycyrrhiza glabra, Glycyrrhiza echinata, Glycyrrhiza uralensis, Glycyrrhiza triphylla, Glycyrrhiza macedonica, Licorice.