على الرغم من تخصيص قدر كبير من الاستثمار في مجال القطاع الصناعي، إلا أن نسبة الاستثمارات الموجهة لنشاط الصناعات الغذائية بقيت منخفضة،حيث قدرت المصروفات على الآلات المستوردة في هذا النشاط الغذائي حوالي 362 مليون دينار ليبي خلال الفترة 1990–2007، وأن مجموع القروض الممنوحة لهذا النشاط خلال نفس الفترة بلغ حوالي 119 مليون دينار وأن عدد العاملين بهذا النشاط بلغ141 ألف عامل عام 2007، وأن إنتاجية العمل قد ارتفعت من 22 ألف دينار عام 1990 إلى 23.6ألف دينار لكل عامل في السنة عام 2007 , وعلى الرغم من ذلك لازال الناتج المحلي للصناعات الغذائية ضعيف و مساهمته في الناتج المحلي الصناعي والإجمالي منخفضة ،وهدفت الدراسة إلى دراسة واقع الصناعات الغذائية وتطور مساهمتها في الاقتصاد الوطني، بالإضافة إلى دراسة أهم العوامل المؤثرة على الناتج الصناعي الغذائي في الجماهيرية على بيانات سنوية للفترة 1990 – 2007، حيث تفترض الدراسة وجود علاقة طردية بين قيمة الناتج من الصناعات الغذائية وبعض المتغيرات الاقتصادية المتمثلة في العمالة والآلات المستخدمة والقروض الممنوحة لهذا النشاط، وأن مساهمة هذا النشاط في تكوين الناتج المحلي الصناعي والناتج المحلي الإجمالي لازالت منخفضة إلى حد كبير حيث متلث فقط 9.3% ،0.41%علي التوالي عام 2006. وقد تم صياغة دالة خطية للتعبير عن أهم العوامل المؤثرة على الناتج المحلي للصناعات الغذائية في الجماهيرية باستخدام برنامج الحاسوب الإحصائي(SPSS) تم تقدير العلاقة الرياضية وأظهرت النتائج وجود علاقة قوية بين المتغيرات المستقلة والمتغير التابع بلغت 87.4% وأن كل 1000 عامل في هذا النشاط يحققون 0.433 مليون دينار فقط في السنة خلال فترة الدراسة كما أن كل مليون دينار يتم استخدامه في الآلات المستخدمة في هذا النشاط يحقق فقط 0.157 مليون دينار فقط في السنة إلا أن كل مليون دينار يمنح كقروض لهذا النشاط يحقق حوالي 0.115 مليون دينار في السنة خلال فترة الدراسة ، وعند استخدام أسلوب الانحدار المتدرج Stepwise Regression اتضح بأن قيمة القروض الممنوحة للصناعات الغذائية وكذلك عدد العمالة بأنشطة الصناعات الغذائية تعتبر من أهم العوامل المؤثرة على الناتج من الصناعات الغذائية خلال فترة الدراسة، حيث تبين أن كل مليون دينار يمنح كقروض للصناعات الغذائية يحقق فقط 0.179 مليون دينار في نفس السنة وأن كل 1000 عامل يحقق فقط 0.425 مليون دينار وفي نفس إتجاه تغير الناتج من الصناعات الغذائية ، ولقد أوصت الدراسة بمجموعة من التوصيات من أهمها زيادة الاهتمام بهذا النشاط وتذليل الصعوبات من شأنه أن يزيد من فاعلية التنمية الاقتصادية في الدولة. Abstract Although a great deal of investment was put towards the industrial sector, but the rate of investments directed to the activity of food production remained lower. The expenditure on machinery imported for this activity was estimated for LYD 362 Million during 1990 to 2007, and the total loans granted for this activity during the same period reached aound LYD 119 Million, and that the number of employees in this sector reached 141 thousands employees during 2007. The productivity of employment has risen up from LYD 22 thousands for 1990 to LYD 23.6 thousands per worker for 2007. However, the domestic food product is still weak and its contribution in the industrial sector gross national product is low. The study aimed to analyze the reality of the food production and its developing contribution in the national economy. In addition, it is determine the most important factors affecting the food production output in Libya based on annual data of 1990 – 2007. The study presumes the existence of a direct relationship between the output value of the food production and some economic variables represented in the lobor and machinery and the loans granted for this activity. The contribution of this activity in forming the industrial and gross domestic product is still low significantly where it only represented 9.3%, 0.41% for 2006 resepctirly. A linear function was drafted to express the main factors affecting the domestic product of food manfactory in Libya using the SPSS to estimate the mathematical relationship. The results revealed an existence of a powerful relationship between the independent variables and the subsequent variable reached 87.4%, and that each 1000 employees in this activity achieves LYD 0.433 Million per year during the time of the study, and each LYD one Million spent on the machinery used in this activity achievess only LYD 0.157 Million per year, but each LYD one Million granted as loans for this activity achieves almost LYD 0.115 Million per year during the time of the study. When the Stepwise Regression method was used, it was clear that the value of the loans granted for food productions as well as the number of employees working at the food production activity are the main factors affecting the output of the food products during the time of the study. It was also clear that each LYD one Million granted as loans for the food production achieves only LYD 0.179 Million at the same year, and that each 1000 employees achieves only LYD 0.425 Million at the same direction of the food productions output variation. The study has made a number of recommendations, most important of which is to pay more attention for this activity, and to overcome the difficulties, which would increase the effectiveness of the state economic development.
مصطفى فرج ميلود (2010)

Evapotranspiration is an important component in many hydrological, ecological and agricultural studies. There are many available direct and indirect methods to determine the evapotranspiration rate. In this study, alternative model based on multilayer Artificial Neural Network (ANN) using the backpropagation algorithm was proposed to estimate evapotranspiration as referred to pan evaporation. The meteorological data used in this study were obtained from Al-Zahra and Al-Zawia stations which located on the coastal area of western Libya lie. The input data were consisted of mean temperature, mean relative humidity and mean of actual sunshine hours of consecutive years (1995, 1996, 1997 and 1999). The performance of the ANN model was evaluated against a set of data that never seen by the model during the training phase. The evaluation of ANN model was also performed against Blaney and Criddle, Radiation and modified Penman methods. The results showed that ANN forecasts were superior to the ones obtained by Blaney and Criddle and Radiation methods. Due to its little input data, ANN is considered to be more efficient as compared with the modified Penman method. However, this application of ANN as a fitting tool should be useful in evapotranspiration modeling. Keywords: Evapotranspiration Pan evaporation, Artificial neural networks, Backpropagation algorithm.
Ahmed Ibrahim Ekhmaj(1-2012)

The broiler industry in Peninsular Malaysia has undertaken significant structural changes; mainly there has been a gradual move towards contract farming with an increasing number of broiler farmers working under contract arrangements for commercial firms and integrators. DVS indicated that the broiler contract farming system dominated around 75% of the domestic broiler production in Malaysia. Private Profitability plays a vital role in the sustainability of the broiler industry. To enhancement the agricultural performance in the country, the Malaysian government has been introduced several policies. Financial profitability is gauged using three agriculture incentives namely Pioneer Status (PS), Investment Tax Allowance (ITA) and Accelerated Capital Allowance (ACA). Though, the lack of effectiveness of the program is still of concern to the agricultural sector given the significance of poultry in Malaysia. The purpose of the study was to determine the extent to which those incentives affect the feasibility of the industry and financially assisting the viability of the project of contract farming in Peninsular Malaysia. Financial evaluation instruments were used to compute the assessment of firm’s financial projection mainly, Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP) and Profitability Index (PI). The questionnaire used as a tool for data collection and a face-to-face interview was organized for the 206 broiler contract farmers as respondents. The result reveals that the stock farmers who involve in contract farming are viable; highly profitable and rapidly recover its initial investment Moreover, with Government Incentives, the …
Zineb Abdulaker Benalywa , Mohd Mansor Ismail , Mad Nasir Shamsudin , Zulkornain Yusop (11-2018)