scholarly journals Resource Productivity in the Punjab's Agriculture

1976 ◽  
Vol 15 (2) ◽  
pp. 115-133 ◽  
Author(s):  
Abdul Salam
Keyword(s):  
Agricultural Sector ◽  
Function Analysis ◽  
Basmati Rice ◽  
Resource Productivity ◽  
Intelligent Decision Making ◽  
Farm Production ◽  
Intelligent Decision ◽  
Short Run ◽  
Factor Inputs ◽  
Farm Inputs

Concerted efforts are being made at micro as well as macro levels in Pakistan to increase farm production and raise productivity in the agricultural sector. For diagnostic purposes and for formulation of general guidelines for an intelligent decision making, at micro and macro levels, it is important to identify and quantify the contribution of various factor inputs, especially of those factors whose supplies can be more easily changed in the short run. Satisfactory quantitative estimates of resource productivity in the pro¬duction of major crops in Pakistan are generally not available. Except for a few studies carried out on wheat [2], not much is known about the contribution of various factor inputs, such as farm labour, fertilizers, etc., to the final output. The main objective of this paper is to estimate and analyse the resource pro¬ductivity of various factor inputs obtaining in the Punjab's agriculture. The estimates are derived from production function analysis performed on the major crops of the province, i.e. Mexi-Pak and local wheat, Basmati rice, IRRI rice, Jhonna rice, maize (corn), cotton and sugarcane. The marginal product¬ivities of various farm inputs in the production of various crops are computed from the estimated production functions.

Intelligent Decision-Making Approaches for Agricultural Sectors of Odisha in India

2019 ◽  
Vol 11 (4) ◽  
pp. 67-95
Author(s):  
Debesh Mishra ◽  
Suchismita Satapathy
Keyword(s):  
Agricultural Sector ◽  
Policy Formulation ◽  
Rice Farming ◽  
Extension Programs ◽  
Intelligent Decision Making ◽  
Personal Interaction ◽  
Intelligent Decision ◽  
Management Techniques ◽  
Best Worst Method ◽  
Made In

Agriculture lacks organizational frameworks which are needed for OHS management techniques to operate effectively. Thus, it becomes essential to analyze the magnitude of OHS problems within the agricultural sector. Hence, an attempt was made in this study to explore the prevalence of OHS disorders and discomforts among the farmers of Odisha in India. There are three contributions in this study. At first, OHS issues of farmers were analyzed based on the literature review and the data was collected by personal interaction and questionnaires. In the second part, the “Best Worst Method (BWM)” was used to rank the different rice farming processes, and the different occupational disorders and discomforts, respectively. Furthermore, the RULA tool was used to assess the ergonomics involved in various postures taken by farmers in different rice farming processes, and based on the obtained RULA scores the necessary actions were recommended accordingly. The findings in this study may have positive implications for extension programs and policy formulation in agricultural sectors.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

Terms and Balance of Trade of Indian Agricultural Sector during Pre and Post-WTO Period

2020 ◽  
pp. 288-293
Keyword(s):  
Agricultural Sector ◽  
Secondary Data ◽  
Terms Of Trade ◽  
Basmati Rice ◽  
Agricultural Exports ◽  
Unit Value ◽  
The Us ◽  
Balance Of Trade ◽  
Frozen Shrimp ◽  
Plantation Crops

India is the world’s third-largest economy after the US and China. India is also one of the leading producer of spices, fish, poultry, livestock and plantation crops, and leading exports consisted of basmati rice, meat of bovine animals, frozen shrimp and prawns, cotton and refined sugar. The study was based on secondary data collected from the various published sources, viz., various issues of handbook of RBI, FAO trade yearbook, Statistical Abstract of India, FAOSTAT, etc. The data were grouped into two periods Pre-WTO 1975-94 and Post-WTO 1995-2015.The exports volume indices for agricultural sector of India were increased by 129.41 percent from 17 in 1975 to 39 in 1994. Besides, the volume indices of imports declined by 56.16 percent from 73 in 1975 to 32 in 1994 for agricultural sector of India. The unit value indices of agricultural exports of India declined by 17.69 percent from 113 in 1975 to 93 in 1994. However, the agricultural import indices grew considerably 171.42 percent from 42 in 1975 to 114 in 1994.The quantity terms of trade for agricultural sector of India was deteriorated by 80.89 percent from 429.41 in 1975 to 82.05 in 1994. Likewise, value terms of trade for agricultural sector of India also depreciated by 67.44 percent from 269.05 in 1975 to 81.58 in 1994. The exports volume indices for agricultural sector of India were increased by 125 percent from 72 in 1995 to 162 in 2015. The volume indices of imports were also enlarged by 934.78 percent from 23 in 1995 to 238 in 2015 for agricultural sector of India. The unit value indices, which measure the average price realization, indicated a significant increase in unit value indices of agricultural exports of India turn up by 131.76 percent from 85 in 1995 to 197 in 2015. However, the agricultural import indices declined by 0.64 percent during post-WTO period. The quantity terms of trade, as well as value terms of trade for agricultural sector of India, was improved by 359.95 and 133.25 percent, respectively during post-WTO regime. The trade balance of Indian agricultural sector showed a favorable balance during pre-WTO period as well as post-WTO period.

scholarly journals The Integration of Conventional Equity Indices with Environmental, Social, and Governance Indices: Evidence from Emerging Economies

2021 ◽  
Vol 13 (2) ◽  
pp. 676
Author(s):  
Ramiz ur Rehman ◽  
Muhammad Zain ul Abidin ◽  
Rizwan Ali ◽  
Safwan Mohd Nor ◽  
Muhammad Akram Naseem ◽  
...  
Keyword(s):  
South Africa ◽  
Function Analysis ◽  
Impulse Response Function ◽  
Decomposition Analysis ◽  
Individual Country ◽  
Brics Countries ◽  
Long Run ◽  
Integration Test ◽  
Short Run ◽  
Equity Indices

This study investigates the integration of environmental, social, and governance (ESG) equity indices with conventional indices in Brazil, Russia, India, China, and South Africa (BRICS) individually and across all BRICS countries to better understand regional economic cooperation. Accordingly, we look at daily returns from 13 July 2013 to 28 February 2018 for the Morgan Stanley Capital International (MSCI) ESG indices and MSCI composite indices of the respective countries. To analyze the integration between the ESG equity indices of the sampled countries with their regional and across regional conventional counterparts, the Johansen Co-integration test is employed in this study. Further, the vector error correction model (VECM) is applied to test the causality between the sampled time-series. The impulse response function analysis further explains the impulse responses of each country’s MSCI ESG returns to one standard deviation of innovations to MSCI composite returns of the same country and across countries. Finally, the extent of the MSCI composite returns’ impact on the MSCI ESG returns in the same country indices, and cross-regional indices is examined with variance decomposition analysis. The results suggest that all ESG equity indices are integrated with conventional indices in all BRICS countries. Furthermore, there is a short-or long-run causality between MSCI ESG and MSCI composite equity indices of China and South Africa. Moreover, the study finds only short-run causality between conventional and non-conventional equity indices of Brazil and Russia, whereas we find only long-run causality between India’s non-conventional and conventional equity indices. Finally, the study finds that the all-individual country MSCI ESG equity indices shows a long-run causality with MSCI composite equity indices of all other BRICS countries. The findings also confirm the economic and financial cooperation between the BRICS countries.

THE IMPACT OF RESEARCH AND DEVELOPMENT INVESTMENT ON AGRICULTURAL SECTOR PERFOMANCE IN KENYA

2017 ◽  
Vol 2 (1) ◽  
pp. 34-57
Author(s):  
John Githii Kimani ◽  
Dr. George Ruigu Ruigu
Keyword(s):  
Research And Development ◽  
Agricultural Sector ◽  
Research Policy ◽  
Trade Openness ◽  
Policy And Practice ◽  
Long Run ◽  
Short Run ◽  
The Government ◽  
Parsimonious Model ◽  
The Impact

Purpose: The purpose of the study was to assess the impact of research and development investment/expenditure on the agricultural sector performance in Kenya.Methodology: The study took the peoples impact assessment direction. The data for this study was collected from various government agencies such as KARI, ASTI, Kenya Agricultural Sector Data compendium website, FAOSTAT, World Bank among others. Co-integration and error correction modeling methods were used in analyzing the data for this study.Results: Co-integration results for both the parsimonious and non-parsimonious model indicated that that there is a long-run relationship among the variables in the agriculture performance in Kenya. Further, findings in this study indicated that the variables under study were insignificant determinants of the long run Total Factor Productivity of the agricultural sector.  Meanwhile, Trade openness was the only significant determinant of the short run agricultural Total Factor Productivity.Unique Contribution to Policy and Practice: This study recommends the institutionalization of policies aimed at ensuring interaction between the various stakeholders in the agricultural sectors. This interaction will ensure that resources are better allocated to reduce duplication of research and dissemination activities. In addition, greater collaboration among the stakeholders will promote and strengthen the connection between research, policy and the application of research findings. The study further advocates that the government should follow a trade liberazation oriented approach to the agricultural sector as opposed to a trade tightening approach.

scholarly journals Enhanced Clean-In-Place Monitoring Using Ultraviolet Induced Fluorescence and Neural Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3742 ◽  
Author(s):  
Alessandro Simeone ◽  
Bin Deng ◽  
Nicholas Watson ◽  
Elliot Woolley
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Computation Time ◽  
Cleaning Process ◽  
Food Manufacturing ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Potential Benefits ◽  
Image Acquisition System ◽  
Nonlinear Autoregressive

Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.

Sign in / Sign up

Export Citation Format

Share Document