Home > An Analysis of Effectiveness of Extension Work Conducted under Farmers Field School Ffs Approach for Sustainable Agricultural Development in the Punjab, Pakistan
An Analysis of Effectiveness of Extension Work Conducted under Farmers Field School Ffs Approach for Sustainable Agricultural Development in the Punjab, Pakistan
Agriculture is vital for Pakistan''s economy. Whatever happens to agriculture is bound to affect not only the country’s growth performance but a large segment of the country’s population as well. The development of agriculture depends on many factors including agricultural extension as an institutional component. Since independence many extension approaches have been tried from time to time but met with partial success in increasing farm productivity. Recently, government of Punjab has introduced a new extension approach known as farmers field school (FFS) in 15 districts of province. But, how do farmers view its effectiveness in meeting their needs is the forehand question which needs to be answered. Keeping this in view, the present study was designed and conducted in the randomly selected three districts under FFS. A multi-stage sampling technique was used for the selection of sample from study districts. Three districts were selected randomly, and then one tehsil from each randomly selected district was taken randomly, the randomly selected tehsils were Sargodha, Sheikupura and mailsy, from fruit, vegetables and cotton areas respectively. A sample of 341 respondents from the population of 3000 registered FFS farmers were taken randomly. The sample size was determined by using table developed by Fitzgibbon et al (1987). Data were collected through an interview schedule, and data obtained were statistically analyzed by using computer software i.e. SPSS. According to the data, 36.4% respondents were of age 41 years and above. Only 14.67% respondents were illiterate, a simple majority (53.1%) of the respondents had less than 12.5 acres land holding and 88% respondents were owner. Majority (65.1%) of the respondents'' source of income was only farming and 37.5% respondents had annual income less than Rs.100000. All the respondents were acquainted with the FFS staff, and regarding acquaintance with qualities of FFS staff, dutifulness gained the weighted score 1168 and was ranked at top, similarly regarding acquaintance with the duties of FFS staff and responsibilities of FFS member farmers, the duty "to coordinate all FFS personnel" gained a weighted score 1174 and responsibility "To roll call in the end of FFS meeting" gained a weighted score 1131 and were ranked at top, respectively. Overwhelming a majority (82.40%) of respondents were of the view that FFS staff had weekly contact with them. Similarly 71.6, 79.8, 88.6, 61.6, and 64.8% respondents reported that the FFS was 1-square distance from their home, situated at a central place, established at Dera, selected with mutual consultation of farmers and conducted on a need based survey, respectively, whereas 79.18% respondent''s source of information was fellow farmers. Information provided about fertilizer requirement gained a weighted score 1086 and was ranked at the top, and regarding effectiveness, the information about hoeing was ranked at the top with a weighted score 1207 and majority(57.42%) of the respondents reported that "special topic/hot issue" was performed in the FFS to an average extent. Similarly, 63.58% and 58.6% respondents were of the view that the group discussion method was used and effective to an average extent and was ranked at the top with a weighted score 1107 and 1128, respectively. It was also concluded that during the use of different extension methods the pre-requisites of each extension method were used to below an average extent. Similarly FFS material was provided to below an average extent, whereas 41.31% of the respondents considered the lead pencil as effective to an average extent. An AESA/CESA activity like "farmers are properly briefed before field activity" was ranked at the top with weighted score 1081 and was performed to an average extent. There existed significant association of age with qualities of FFS staff, use of extension methods by FFS staff, responsibilities of FFS member farmers and effectiveness of information provided by FFS staff. Size of land holding had highly significant negative association with qualities of FFS staff and responsibilities of FFS member farmers. Annual income of respondents had also highly a significant positive association with qualities of FFS staff, whereas there existed highly significant positive association of education with qualities of FFS staff, use of extension methods by FFS staff, responsibilities of FFS member farmers and effectiveness of information provided by FFS staff.
حافظ محمد ابراہیم افسوس ہے جنوری کے تیسرے ہفتہ میں حافظ محمد ابراہیم صاحب ایک طویل علالت کے دہلی میں وفات پاگئے۔ نماز جنازہ شاہ جہانی جامع مسجد میں پڑھی گئی اوراس کے بعد تدفین نگینہ میں ہوئی۔انتقال کے وقت عمر ۷۷۔ ۷۸ برس کی ہوگی۔ مرحوم علی گڑھ کی پرانی نسل کے ایک فرد تھے۔یہیں فلسفہ اور اقتصادیات کے مضامین کے ساتھ بی۔اے اورپھرایل۔ایل۔بی کیا۔اپنی ذہانت،طباعی اور لیاقت کے باعث اساتذہ اورطلباء میں ہمیشہ نیک نام اورہر دل عزیز رہے۔ دیوبند کے مکتبۂ فکر کے زیر اثر قوم پرورانہ خیالات اور جذبات شروع سے رکھتے تھے۔ چنانچہ جن لوگوں نے مرحوم کا عہد طالب علمی دیکھاہے ان کابیان ہے کہ مرحوم اس زمانہ میں بھی سرسید کے سیاسی افکار کے مخالف تھے اور اس پر اپنے ساتھیوں سے محبت کرتے تھے۔علی گڑھ سے فراغت کے بعد اپنے وطن نگینہ میں پریکٹس شروع کی اورایڈوکیٹ کی حیثیت سے بہت جلد صوبہ بھر میں مشہور ہوگئے لیکن نیشنلسٹ فطرتاًتھے۔اس لیے تحریک موالات شروع ہوئی تواُس میں بڑھ چڑھ کرحصہ لیااورپھر جنگ آزادی کادورآیا توہمیشہ اُس کے ہراوّل دستہ میں رہے۔اس سلسلہ میں جیل گئے اوردوسری پریشانیاں بھی اٹھائیں لیکن پائے ثبات میں لغزش نہ ہوئی۔ پھر جب قومی وزارتوں کا عہد شروع ہوا تو پہلے اتر پردیش میں اور پھر مرکز میں وزیر رہے، آخر میں پنجاب کے گورنر تھے۔ بیماری کے باعث اس سے مستعفی ہوکرگھر آ بیٹھے تھے اوریہی بیماری آخرجان لیوا ثابت ہوئی۔ نہایت خوش خلق، مہمان نواز اور فیاض و سیرچشم تھے۔اﷲ تعالیٰ مغفرت ورحمت کی نعمتوں سے سرفرازفرمائے۔آمین [فروری۱۹۶۸ء]
This study addresses the issue of interpersonal communication patterns in establishing a harmonious family. Communication is emphasized in the holy Qur'an as a crucial aspect of human life, particularly for Muslims. Poor communication is one of the factors that can lead to marital disharmony or discomfort within the family. Therefore, effective communication is essential for a healthy family life. To achieve a harmonious and content family, it is essential to understand the patterns of interpersonal communication within the family. This will lead to a peaceful and comfortable environment for all members. The authors aim to discuss effective communication techniques, both in general and within a religious context, to establish a happy family. The research focuses on examining theories related to positive communication patterns within the family. The methodology employed for this research is library research. A balanced communication pattern is essential for forming a harmonious family. Additionally, precise subject-specific vocabulary should be used when it conveys the meaning more precisely than a similar non-technical term. This involves open communication where each member has an equal opportunity to express their opinions about family life. It is important to avoid any biased or emotional language and to use clear, objective, and value-neutral language. The text is grammatically correct and follows conventional academic structure and formatting. No changes in content have been made.
The study addresses the significance of biomedical data to be analyzed by Statistical Community in collaboration with the expertise of personnel in the biomedical field. The data has its own particular constraints and difficulties being privacy-sensitive, heterogeneous and voluminous data. The mathematical understanding of patterns and structures and estimation procedures may be fundamentally different from those of data collected in other fields. For the purpose complicated genomic data of leukemia cancer type of Golub et al (1999) is selected for the study. This dataset comes from a study of gene expression in two types of acute leukemia’s, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The training data set consisted of 38 bone marrow samples, 27 of which were taken from ALL patients (19 B-ALL and 8 T-ALL) and 11 of which were taken from AML patients. Each gene expression is the quantitative level of messenger RNA found in the cells. Understanding the genetic underpinnings of disease is important for screening, treatment, drug development, and basic biological insight. Thus exploring genomic data has drawn on mathematical, statistical, and computational methods to discover meaningful genetic relationships from large-scale measurements of genes. Since this is a continuously growing area and is constantly being seeded with new approaches and interpretations. Most of this new material is easily accessible given a familiarity with basic genetics and multivariate statistics. The application of multivariate techniques need a thorough study of the data in hand and the primary objective in the study has been to “let the data speak for itself”. For the proper interpretation of these data, experimental and computational genomics need to have a firm grasp of statistical methodology. An aspect of prime importance, keenly taken into consideration in the 1study. For the multivariate genomic data of leukemia cancer type an initial exploratory data analysis has been performed in the study with the graphical tools of Histograms and Box plots in conjunction with one another. This has exposed that such a data set has a thorough fit for the extreme value distributions, which apart for the study undertaken has not been found in literature for the data type. The fitting of extreme value distributions has opened many new avenues for the data type for the new researchers to work on. Another output of the exploratory data analysis is the application of an appropriate transformation (the classical Box Cox transformation) to deal with the sharp skewness the data, and not relying only on the traditionally used logarithmic transformation. The appropriate data transformation has been another high point in the application of PCA for visualizing clusters present in the data set. Previously PCA and other complicated techniques like SOM and SVM has been applied and new adaptations are continuously being tried on these apart from the traditional clustering methodologies. Here the focus has not been just on the application of multivariate techniques to locate the clusters as predefined by the biological knowledge, rather it is on the methodologically simple yet most appropriate technique to be applied after a thorough look into the interior of the data set. Thus the data set revealed a patterned correlation matrix which in itself explained the number and configuration of clusters. This provided a groundwork for the application of PCA on box cox transformed data using the patterned correlation matrix as the interrelationship matrix. Indeed a comparison has been made with other interrelationship matrices as well. The clear cluster structure presented was, with no any misclassification in the configuration of clusters and exactly coincided with the prior biological knowledge. Therefore as per our hopes this introduction to prototypical methods for 2studying the data and interpreting in the context of biological genomic knowledge has been successful to get started. Addressing the next immediate issue in the study of the biomedical genomic data was finding genes that may be specific for one leukemia type or the cluster. The initial exploratory data analysis exposed certain data values that were of prime biological significance and played statistically significant role in the specification of genes for each cluster defined or the leukemia type. Resultantly a criterion developed from the data set, classifying each gene into its specific single cluster, or two of the three clusters or in all of the three clusters (the common genes).Thus a classified data set of the most variant genes across all the samples was taken as a training data set. Based on the classified grouping a linear discriminant analysis was successfully performed to find the discriminating genes for the specific leukemia type with 99.97% probability of correct classification. The collections of the discriminating genes from the three clusters formed were then needed to be checked for the previously found externally valid cluster structure. PCA was then applied in a new dimension as a check for the discriminating genes. For the discriminating genes the cluster formed for the sample expression profiles were expected to be distinctively clear for the genes to term as a leukemia type specific or cluster specific. Thus the clusters formed were very clearly distinguishable from one and other in contrast to the clusters of the sample expression profiles comprising of the common genes in all. These presented no any distinctive cluster rather a big bulk of a cluster that did not showed any difference in the biologically different leukemia types. The two major issues of the biomedical genomic data have been addressed successfully with an appropriate proposed model for the data type. Thus the study has been based on methodologically simple yet appropriate statistical techniques for such a data type filling 3the inevitable space left in for a statistical community the Pakistani statistical community for the very first time for such a internationally important field, the genomic biomedical field. With the results being unequivocal: Simplest is best! Can cluster genes, cell samples, or both. Yet the study has explored many new dimensions that need to be explored to establish relationship between an experiment based leukemia class and its subclass and a clinical out come. Since the data has many dimensions and concentrating on few precisely has been a difficult task yet accomplished.