ABSTRACT: The Group frontier is a representation of the state of knowledge pertaining to the transformation of inputs into output in the regional level, while the Meta frontier represents the state of the knowledge at the country level. The ratio of the frontier score of Group and the Meta frontier represents the Meta technology Ratio (MTR). The study investigates productivity potentials and efficiencies of the farmers in different states in India by utilizing the concept of Group and Meta frontier technique. Empirical results are derived from a farm level disaggregated input- output data set of 13 Indian states comprising 3615 number of farmers. The results show a large technology gap ratio defined by MTR between the sampled states of the country. For calculating the efficiency measures the Data Envelopment Analysis is applied for the input-output data set.
This paper is the continuation of the paper published by the authors Arun Balaji and Baskaran [2].
Multiple linear regression (MLR) equations were developed between the years of rice cultivation and Feed
Forward Back Propagation Neural Network (FFBPNN) method of predicted area of rice cultivation / rice
production for different districts pertaining to Kuruvai, Samba and Kodai seasons in Tamilnadu. The
average r2 value in area of cultivation is 0.40 in Kuruvai season, 0.42 in Samba season and 0.46 in Kodai
season, where as the r2 value in rice production is 0.31 in Kuruvai season, 0.23 in Samba season and
0.42 in Kodai season. The Rice Data Simulator (RDS) predicted the area of rice cultivation and rice
production using the MLR equations developed in this research. The range of average predicted area for
Kuruvai, Samba and Kodai seasons varies from 12052.52 ha to 13595.32 ha, 48998.96 ha to 53324.54 ha
and 4241.23 ha to 6449.88 ha respectively whereas the range of average predicted rice production varies
from 45132.88 tonnes to 46074.48 tonnes in Kuruvai, 128619 tonnes to 139693.29 tonnes in Samba and
15446.07 to 20573.50 tonnes in Kodai seasons. The mean absolute relative error (ARE) between the
FFBPNN and multiple regression methods of prediction of area of rice cultivation was found to be 15.58%,
8.04% and 26.34% for the Kuruvai, Samba and the Kodai seasons respectively. The ARE for the rice
production was found to be 17%, 11.80% and 24.60% for the Kuruvai, Samba and the Kodai seasons
respectively. The paired t test between the FFBPNN and MLR methods of predicted area of cultivation in
Kuruvai shows that there is no significant difference between the two types of prediction for certain
districts.
Size and operational performance of manufacturing companies in pakistan using...Alexander Decker
This study uses data envelopment analysis to evaluate the efficiency of 49 manufacturing companies in Pakistan from 2008 to 2010. Three inputs (raw materials, staff expenses, and plant/machinery) and two outputs (net sales and earnings after tax) are used. Companies are categorized as large (assets over $100M), medium ($30-100M assets), or small (under $30M assets). The results show that small companies have the highest relative efficiency, and 2 large, 3 medium, and 5 small companies operate at the most productive scale size throughout the period.
Sustainable Empowerment Model of Beef Cattle Business Farmers in the Dry Land...IJSRED
1) The document describes a study that constructed a sustainable empowerment model for beef cattle farmers in the dry land area of Kediri Regency, Indonesia.
2) The study used a survey method and structural equation modeling to analyze data. It identified factors such as human capital, social capital, natural resources, and motivation that influence farmer empowerment.
3) The results showed that skills, training, experience and education were important human capital indicators, while norms, trust, and social networks were key social capital factors. Access to and management of natural resources also impacted empowerment.
This study measured the technical efficiency of 28 rose cut flower farms in three districts of Ethiopia using data envelopment analysis. The results found that on average, farms could reduce input use by 42% while maintaining output levels. Specifically, the mean technical, scale, and overall technical efficiencies were 92%, 61%, and 58% respectively, indicating scale inefficiencies were the primary source of inefficiency. Factors found to positively influence efficiency included farming experience and education of farm managers, while farm age negatively impacted efficiency. No conclusive relationship was found between farm size and efficiency. The study aims to help farms improve efficiency to reduce costs and increase profits in rose cut flower production.
Technical efficiency in agriculture in ghana analyses of determining factorsAlexander Decker
This document summarizes a journal article that estimates technical efficiency in Ghana's agricultural sector from 1976-2007 and investigates factors that influence the estimated efficiencies. The study finds decreasing returns to scale and that land is negatively related to output while fertilizer and machinery are positively related. The estimated level of inefficiency is 21% with decreasing returns to scale. No hypothesized variables for explaining technical efficiency were found to be statistically significant. The study calls for decreasing land use relative to other inputs to improve efficiency.
Paper presented International Conference on Data Science and Analytics - ICDSA'21 organized by Rathinam College of Arts and Science, Tamil Nadu, India on 19th February 2021
This paper is the continuation of the paper published by the authors Arun Balaji and Baskaran [2].
Multiple linear regression (MLR) equations were developed between the years of rice cultivation and Feed
Forward Back Propagation Neural Network (FFBPNN) method of predicted area of rice cultivation / rice
production for different districts pertaining to Kuruvai, Samba and Kodai seasons in Tamilnadu. The
average r2 value in area of cultivation is 0.40 in Kuruvai season, 0.42 in Samba season and 0.46 in Kodai
season, where as the r2 value in rice production is 0.31 in Kuruvai season, 0.23 in Samba season and
0.42 in Kodai season. The Rice Data Simulator (RDS) predicted the area of rice cultivation and rice
production using the MLR equations developed in this research. The range of average predicted area for
Kuruvai, Samba and Kodai seasons varies from 12052.52 ha to 13595.32 ha, 48998.96 ha to 53324.54 ha
and 4241.23 ha to 6449.88 ha respectively whereas the range of average predicted rice production varies
from 45132.88 tonnes to 46074.48 tonnes in Kuruvai, 128619 tonnes to 139693.29 tonnes in Samba and
15446.07 to 20573.50 tonnes in Kodai seasons. The mean absolute relative error (ARE) between the
FFBPNN and multiple regression methods of prediction of area of rice cultivation was found to be 15.58%,
8.04% and 26.34% for the Kuruvai, Samba and the Kodai seasons respectively. The ARE for the rice
production was found to be 17%, 11.80% and 24.60% for the Kuruvai, Samba and the Kodai seasons
respectively. The paired t test between the FFBPNN and MLR methods of predicted area of cultivation in
Kuruvai shows that there is no significant difference between the two types of prediction for certain
districts.
Size and operational performance of manufacturing companies in pakistan using...Alexander Decker
This study uses data envelopment analysis to evaluate the efficiency of 49 manufacturing companies in Pakistan from 2008 to 2010. Three inputs (raw materials, staff expenses, and plant/machinery) and two outputs (net sales and earnings after tax) are used. Companies are categorized as large (assets over $100M), medium ($30-100M assets), or small (under $30M assets). The results show that small companies have the highest relative efficiency, and 2 large, 3 medium, and 5 small companies operate at the most productive scale size throughout the period.
Sustainable Empowerment Model of Beef Cattle Business Farmers in the Dry Land...IJSRED
1) The document describes a study that constructed a sustainable empowerment model for beef cattle farmers in the dry land area of Kediri Regency, Indonesia.
2) The study used a survey method and structural equation modeling to analyze data. It identified factors such as human capital, social capital, natural resources, and motivation that influence farmer empowerment.
3) The results showed that skills, training, experience and education were important human capital indicators, while norms, trust, and social networks were key social capital factors. Access to and management of natural resources also impacted empowerment.
This study measured the technical efficiency of 28 rose cut flower farms in three districts of Ethiopia using data envelopment analysis. The results found that on average, farms could reduce input use by 42% while maintaining output levels. Specifically, the mean technical, scale, and overall technical efficiencies were 92%, 61%, and 58% respectively, indicating scale inefficiencies were the primary source of inefficiency. Factors found to positively influence efficiency included farming experience and education of farm managers, while farm age negatively impacted efficiency. No conclusive relationship was found between farm size and efficiency. The study aims to help farms improve efficiency to reduce costs and increase profits in rose cut flower production.
Technical efficiency in agriculture in ghana analyses of determining factorsAlexander Decker
This document summarizes a journal article that estimates technical efficiency in Ghana's agricultural sector from 1976-2007 and investigates factors that influence the estimated efficiencies. The study finds decreasing returns to scale and that land is negatively related to output while fertilizer and machinery are positively related. The estimated level of inefficiency is 21% with decreasing returns to scale. No hypothesized variables for explaining technical efficiency were found to be statistically significant. The study calls for decreasing land use relative to other inputs to improve efficiency.
Paper presented International Conference on Data Science and Analytics - ICDSA'21 organized by Rathinam College of Arts and Science, Tamil Nadu, India on 19th February 2021
11.impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
7.[55 64]impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
Application of Linear Programming for Optimal Use of Raw Materials in Bakeryinventionjournals
This document summarizes a study that utilized linear programming to optimize the use of raw materials in a bakery for profit maximization. The researchers formulated a linear programming model to determine the optimal production levels of small, big, and giant loaves. The results showed that producing 962 units of small loaf and 38 units of big loaf, while producing 0 units of giant loaf, would yield the highest profit of N20,385. In conclusion, more production of small and big loaves would maximize the bakery's profit.
Paper presented International Conference on Data Science and Analytics - ICDSA'21 organized by Rathinam College of Arts and Science, Tamil Nadu, India on 19th February 2021
This document summarizes a research paper on the modeling and analysis of a multifunctional agricultural vehicle designed for small farms in India. It begins with an introduction noting the need to increase mechanization and productivity on small Indian farms. It then discusses a literature review on previous related research and defines the problem of machines not being suitable for small farms. The proposed vehicle would have attachable/detachable accessories for seed sowing, fertilizer spreading, and grass cutting. The document describes the planned research work, expected outcomes, equipment selection, material selection, and preliminary analysis showing maximum deformations meet requirements. It concludes the vehicle could help small farms operate more efficiently and lists future potential attachments like water pumps and tilling. The overall goal is
A poultry yield prediction model have then designed using a data mining and machine learning technique called Classification and Regression Tree (CART) algorithm. The developed model has been optimized and pruned using the Reduced Error Pruning (REP) algorithm to improve prediction accuracy. An algorithm to make the prediction model flexible and capable of making predictions irrespective of poultry size or population has been proposed. The model can be used by poultry farmers to predict yield even before a breeding season. The model can also be used to help farmers take decisions to ensure desirable yield at the end of the breeding season.
A NEW MULTI CRITERIA DECISION MAKING METHOD : APPROACH OF LOGARITHMIC CONCEPT...ijaia
The primary aim of the study is to introduce APLOCO method which is developed for the solution of multicriteria
decision making problems both theoretically and practically. In this context, application subject of
APLACO constitutes evaluation of investment potential of different cities in metropolitan status in Turkey.
The secondary purpose of the study is to identify the independent variables affecting the factories in the
operating phase and to estimate the effect levels of independent variables on the dependent variable in the
organized industrial zones (OIZs), whose mission is to reduce regional development disparities and to
mobilize local production dynamics. For this purpose, the effect levels of independent variables on dependent variables have been determined using the multilayer perceptron (MLP) method, which has a wide use in artificial neural networks (ANNs). The effect levels derived from MLP have been then used as
the weight levels of the decision criteria in APLOCO. The independent variables included in MLP are also
used as the decision criteria in APLOCO. According to the results obtained from APLOCO, Istanbul city is
the best alternative in term of the investment potential and other alternatives are Manisa, Denizli, Izmir, Kocaeli, Bursa, Ankara, Adana, and Antalya, respectively. Although APLOCO is used to solve the ranking problem in order to show application process in the paper, it can be employed easily in the solution of classification and selection problems. On the other hand, the
study also shows a rare example of the nested usage of APLOCO which is one of the methods of operation
research as well as MLP used in determination of weights.
Este documento anuncia el Primer Encuentro de Malabaristas de Albendiego de 2013, que se celebrará del 30 de mayo al 2 de junio en honor a Estuartini El Magnifico. Los eventos incluyen talleres de malabares, espectáculos de circo, conciertos, DJs y quema de fuegos artificiales. La inscripción incluye acceso a todas las actividades. Se recuerda a los asistentes que deben cuidar el entorno natural y no consumir alcohol sin ofrecer antes a los organizadores.
Este documento describe los tipos de compuestos químicos inorgánicos como óxidos, ácidos, bases y sales. Explica que los óxidos pueden ser básicos o metálicos formados por un metal y oxígeno, o ácidos o no metálicos formados por un no metal y oxígeno. También cubre la determinación de números de oxidación y proporciona ejemplos de diferentes compuestos.
Analisis Ketahanan Minyak di 15 Negara Importir Minyak Tahun 2010Andry Satrio
Penelitian akhir mengenai ketahanan energi khususnya energi minyak di 15 negara pengimpor minyak. Hasil yang didapatkan menunjukkan bahwa Indonesia dan sebagian besar negara di Asia memiliki nilai ketahanan minyak yang rendah.
Лучшие онлайн игры на BMOG.RU
mmorpg бизнес
top 100 mmorpg games list
mmorpg police
mmorpg в стиле спанч боба
shadowcraft wow mmo
бесплатно играть браузер mmorpg
queen's blade mmo english
скачать онлайн игру mmorpg 7 элемент
mmorpg игры онлайн бесплатно linea
рейтинг онлайн игр в россии mmorpg
mmofps с техникой
mmo firewall
как понять клиентская mmorpg
топ mmorpg игры 2012 года
mmorpg онлайн игры иуеф еуые
mmorpg гонки коды
mmorpg мобильный телефон
mmorpg для ps3 в разработке
stargate worlds mmorpg
large scale mmo
mmorpg на iphone
mmo rpg top
mmorpg ролевые игры онлайн бесплатно
скачать новые онлайн mmorpg
mmorpg онлайн sis на телефон
mmorpg на движке от краизис
play online switchin mmo game
buhfnm jykfqy mmorpg
mmorpg top 2012
browser flash mmorpg
top mmorpg games of all time
бесплатные action mmo
mmorpg покемон
mmorpg бесплатные yjdst
mmorpg 2013 года новые
движок для создания mmorpg игр
mmorpg пошаговая система боя
новые бесплатные mmorpg pve
mmorpg новые смотреть видео
mmorpg для телефона скачать
mmorpg играть онлайн 2011
mmo wings of ikar
каталог онлайн mmorpg онлайн игры
лучшbt онлайн mmorpg
как обчно прощаютс в mmorpg
mmo игры с клиентом
mmorpg c lheujv
русские ники для mmorpg
mmorpg su world of warplanes
dc universe online mmorpg free
отзывы на 2012 mmorpg
Suicide Ideation in Abused Women as Related To Their Depressioninventionjournals
ABSTRACT: The present investigation was conducted to gain insight into suicide ideation in abused women as related to their depression from middle income group. Abuse in women here has been operationally defined as those women who are regularly physically and emotionally ill-treated by their spouses. The study was conducted on 100 abused women out of which 50 were with children and 50 without children. Standardized tools namely, Adult Suicidal Ideation Questionnaire and Beck Depression Inventory were used. The results showed that correlation between majority of the variables of depression and suicide ideation was significant. Multiple regression analysis showed that some of the variables of depression predicted suicide ideation in abused women.
Kajan Thayaparan's document summarizes several learning experiences including earning a high school diploma, receiving a Harmony Movement certificate, winning a math award, being part of a regional basketball championship team, and doing a public presentation. These experiences helped Kajan develop important skills like time management, confidence, problem solving, teamwork, communication, and motivating others. Kajan learned how to work with others to achieve goals and help teams succeed.
Effect of Image Quality Service and Schools Parents of Satisfaction in Surabaya.IOSR Journals
This study aimed to determine the effect of Quality of Service (X1), the image of School (X2) either partially or simultaneously to the satisfaction of Parents' (Y) in the School of Surabaya. This study has four hypotheses, namely: (1) there is an allegation of a positive and significant relationship between service quality in partial satisfaction of the Parents' School in Surabaya. (2) there are allegations about a positive and significant relationship between the partial image of the Parents 'Satisfaction (Y) in the School of Surabaya, (3) there is a suspicion of a positive and significant relationship between service quality and image simultaneously on Parents' Satisfaction in School Surabaya, (4) there is suspicion between the two independent variables and the image and quality of service, quality of service is the most significant effect on increasing Satisfaction Parents' School in Surabaya?
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
Ikhtilaf and Unity in Muslim Ummah: A Comparative Analysisinventionjournals
ABSTRACT: Disagreement (Ikhtilaf) on religious issues has been a common phenomenon in Muslim Ummah as a result of their different judgments and perceptions on various matters. But discussing historical facts or jurisprudential differences should not in any way discourage Muslim unity. Unity of the Ummah is such a clear reality that there can be no two opinions expressed in the matter.
Impact of Employment of Mothers on Self Concept of Adolescentsinventionjournals
ABSTRACT: Employment of women has become increasingly significant in the lives of women. The pertinent question that arises: Is the women happier and provide better parenting to their adolescents by relinquishing the traditional role or by combining the two roles? An attempt has been made to examine the effect of parenting of employed mothers on self-concept of their adolescents. A total of 200 parents were consisted for this study. 100 parents were with employed mothers and 100 were with homemaker mothers. 50 adolescent girls and 50 boys were further selected for measuring their self-concept from the schools of Dehradun, Haridwar and Roorkee district of Uttarakhand State, India. Parent child relationship scale was administered on parents and self-concept scale on adolescents. Study revealed significant difference in favour of parenting of homemaker mothers in the dimensions of marital conflict vs. marital adjustment and the faulty role expectations vs. realistic role expectations. Employed mother’s adolescents showed high self-concept on the dimension of social, temperamental and on total self concept. Boys of the same group found to be high self-concept on physical and temperamental and girls on the dimension of social self concept than the counter group. Implication of this research from the perspective of women employment and their parenting of adolescents regarding self-concept have been discussed.
Analysis of crop yield prediction using data mining techniqueseSAT Journals
Abstract
Agrarian sector in India is facing rigorous problem to maximize the crop productivity. More than 60 percent of the crop still depends on monsoon rainfall. Recent developments in Information Technology for agriculture field has become an interesting research area to predict the crop yield. The problem of yield prediction is a major problem that remains to be solved based on available data. Data Mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. This paper presents a brief analysis of crop yield prediction using Multiple Linear Regression (MLR) technique and Density based clustering technique for the selected region i.e. East Godavari district of Andhra Pradesh in India.
Keywords: Agrarian Sector, Crop Production, Data Mining, Density based clustering, Information Technology, Multiple Linear Regression, Yield Prediction.
IRJET- Analysis of Crop Yield Prediction using Data Mining Technique to Predi...IRJET Journal
This document discusses using data mining techniques to predict annual crop yields in India. It begins with an abstract that outlines how agriculture is important to the Indian economy but crop production depends on seasonal and environmental factors, making yield prediction challenging. The document then provides an introduction to data mining and its potential application to predict crop yields. It reviews literature on using various data mining methods like linear regression and k-nearest neighbor algorithms to predict yields of major crops in India based on historical data on climate, soil conditions and more. The goal is to help farmers choose optimal crops and improve farm productivity and profits.
This document discusses how precision farming and big data can help improve agriculture. It notes that a majority of India's population depends on agriculture but farmers often lack information which can hurt crop yields. New technologies using sensors, cloud computing, and mobile phones can now provide farmers real-time data on soil conditions, weather, and crop health to help maximize production. Data mining techniques like classification and clustering can analyze large agricultural data sets to predict outcomes and identify patterns. This information can help farmers choose optimal crops and growing practices and help businesses anticipate supply and demand trends to better match production and pricing.
IRJET - Enlightening Farmers on Crop YieldIRJET Journal
This document discusses using data mining techniques to predict crop yields to help farmers. It proposes using a random forest regression algorithm on past agricultural data from 2000-2014 to build a prediction model. The model would help farmers select optimal crops, understand weather patterns, and maximize yields. The system is described as gathering data, preprocessing it, training a random forest model on 60% of the data and testing it on 20%. It would then provide yield predictions and recommendations to farmers through a visualization tool. The goal is to help guide farmers' decisions around fertilizer use, soil management, and crop selection to improve production levels.
11.impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
7.[55 64]impact of input and output market development interventions in ethiopiaAlexander Decker
This study evaluated the impact of input and output market development interventions by the Improving Productivity and Market Success (IPMS) project in Ethiopia. The interventions aimed to improve agricultural markets, increase marketed surplus, and make households more market-oriented. The study used survey data and propensity score matching to compare participant and non-participant households in Alaba and Dale districts. The results showed that the interventions positively impacted institutional changes like increased credit availability and quality of extension services. Participants had significantly higher rates of credit receipt and marketed surplus compared to non-participants. The interventions also increased farmer organization by supporting the establishment of cooperatives. The study concluded that expanding these types of market development interventions could help Ethiopia achieve its growth and poverty
Application of Linear Programming for Optimal Use of Raw Materials in Bakeryinventionjournals
This document summarizes a study that utilized linear programming to optimize the use of raw materials in a bakery for profit maximization. The researchers formulated a linear programming model to determine the optimal production levels of small, big, and giant loaves. The results showed that producing 962 units of small loaf and 38 units of big loaf, while producing 0 units of giant loaf, would yield the highest profit of N20,385. In conclusion, more production of small and big loaves would maximize the bakery's profit.
Paper presented International Conference on Data Science and Analytics - ICDSA'21 organized by Rathinam College of Arts and Science, Tamil Nadu, India on 19th February 2021
This document summarizes a research paper on the modeling and analysis of a multifunctional agricultural vehicle designed for small farms in India. It begins with an introduction noting the need to increase mechanization and productivity on small Indian farms. It then discusses a literature review on previous related research and defines the problem of machines not being suitable for small farms. The proposed vehicle would have attachable/detachable accessories for seed sowing, fertilizer spreading, and grass cutting. The document describes the planned research work, expected outcomes, equipment selection, material selection, and preliminary analysis showing maximum deformations meet requirements. It concludes the vehicle could help small farms operate more efficiently and lists future potential attachments like water pumps and tilling. The overall goal is
A poultry yield prediction model have then designed using a data mining and machine learning technique called Classification and Regression Tree (CART) algorithm. The developed model has been optimized and pruned using the Reduced Error Pruning (REP) algorithm to improve prediction accuracy. An algorithm to make the prediction model flexible and capable of making predictions irrespective of poultry size or population has been proposed. The model can be used by poultry farmers to predict yield even before a breeding season. The model can also be used to help farmers take decisions to ensure desirable yield at the end of the breeding season.
A NEW MULTI CRITERIA DECISION MAKING METHOD : APPROACH OF LOGARITHMIC CONCEPT...ijaia
The primary aim of the study is to introduce APLOCO method which is developed for the solution of multicriteria
decision making problems both theoretically and practically. In this context, application subject of
APLACO constitutes evaluation of investment potential of different cities in metropolitan status in Turkey.
The secondary purpose of the study is to identify the independent variables affecting the factories in the
operating phase and to estimate the effect levels of independent variables on the dependent variable in the
organized industrial zones (OIZs), whose mission is to reduce regional development disparities and to
mobilize local production dynamics. For this purpose, the effect levels of independent variables on dependent variables have been determined using the multilayer perceptron (MLP) method, which has a wide use in artificial neural networks (ANNs). The effect levels derived from MLP have been then used as
the weight levels of the decision criteria in APLOCO. The independent variables included in MLP are also
used as the decision criteria in APLOCO. According to the results obtained from APLOCO, Istanbul city is
the best alternative in term of the investment potential and other alternatives are Manisa, Denizli, Izmir, Kocaeli, Bursa, Ankara, Adana, and Antalya, respectively. Although APLOCO is used to solve the ranking problem in order to show application process in the paper, it can be employed easily in the solution of classification and selection problems. On the other hand, the
study also shows a rare example of the nested usage of APLOCO which is one of the methods of operation
research as well as MLP used in determination of weights.
Este documento anuncia el Primer Encuentro de Malabaristas de Albendiego de 2013, que se celebrará del 30 de mayo al 2 de junio en honor a Estuartini El Magnifico. Los eventos incluyen talleres de malabares, espectáculos de circo, conciertos, DJs y quema de fuegos artificiales. La inscripción incluye acceso a todas las actividades. Se recuerda a los asistentes que deben cuidar el entorno natural y no consumir alcohol sin ofrecer antes a los organizadores.
Este documento describe los tipos de compuestos químicos inorgánicos como óxidos, ácidos, bases y sales. Explica que los óxidos pueden ser básicos o metálicos formados por un metal y oxígeno, o ácidos o no metálicos formados por un no metal y oxígeno. También cubre la determinación de números de oxidación y proporciona ejemplos de diferentes compuestos.
Analisis Ketahanan Minyak di 15 Negara Importir Minyak Tahun 2010Andry Satrio
Penelitian akhir mengenai ketahanan energi khususnya energi minyak di 15 negara pengimpor minyak. Hasil yang didapatkan menunjukkan bahwa Indonesia dan sebagian besar negara di Asia memiliki nilai ketahanan minyak yang rendah.
Лучшие онлайн игры на BMOG.RU
mmorpg бизнес
top 100 mmorpg games list
mmorpg police
mmorpg в стиле спанч боба
shadowcraft wow mmo
бесплатно играть браузер mmorpg
queen's blade mmo english
скачать онлайн игру mmorpg 7 элемент
mmorpg игры онлайн бесплатно linea
рейтинг онлайн игр в россии mmorpg
mmofps с техникой
mmo firewall
как понять клиентская mmorpg
топ mmorpg игры 2012 года
mmorpg онлайн игры иуеф еуые
mmorpg гонки коды
mmorpg мобильный телефон
mmorpg для ps3 в разработке
stargate worlds mmorpg
large scale mmo
mmorpg на iphone
mmo rpg top
mmorpg ролевые игры онлайн бесплатно
скачать новые онлайн mmorpg
mmorpg онлайн sis на телефон
mmorpg на движке от краизис
play online switchin mmo game
buhfnm jykfqy mmorpg
mmorpg top 2012
browser flash mmorpg
top mmorpg games of all time
бесплатные action mmo
mmorpg покемон
mmorpg бесплатные yjdst
mmorpg 2013 года новые
движок для создания mmorpg игр
mmorpg пошаговая система боя
новые бесплатные mmorpg pve
mmorpg новые смотреть видео
mmorpg для телефона скачать
mmorpg играть онлайн 2011
mmo wings of ikar
каталог онлайн mmorpg онлайн игры
лучшbt онлайн mmorpg
как обчно прощаютс в mmorpg
mmo игры с клиентом
mmorpg c lheujv
русские ники для mmorpg
mmorpg su world of warplanes
dc universe online mmorpg free
отзывы на 2012 mmorpg
Suicide Ideation in Abused Women as Related To Their Depressioninventionjournals
ABSTRACT: The present investigation was conducted to gain insight into suicide ideation in abused women as related to their depression from middle income group. Abuse in women here has been operationally defined as those women who are regularly physically and emotionally ill-treated by their spouses. The study was conducted on 100 abused women out of which 50 were with children and 50 without children. Standardized tools namely, Adult Suicidal Ideation Questionnaire and Beck Depression Inventory were used. The results showed that correlation between majority of the variables of depression and suicide ideation was significant. Multiple regression analysis showed that some of the variables of depression predicted suicide ideation in abused women.
Kajan Thayaparan's document summarizes several learning experiences including earning a high school diploma, receiving a Harmony Movement certificate, winning a math award, being part of a regional basketball championship team, and doing a public presentation. These experiences helped Kajan develop important skills like time management, confidence, problem solving, teamwork, communication, and motivating others. Kajan learned how to work with others to achieve goals and help teams succeed.
Effect of Image Quality Service and Schools Parents of Satisfaction in Surabaya.IOSR Journals
This study aimed to determine the effect of Quality of Service (X1), the image of School (X2) either partially or simultaneously to the satisfaction of Parents' (Y) in the School of Surabaya. This study has four hypotheses, namely: (1) there is an allegation of a positive and significant relationship between service quality in partial satisfaction of the Parents' School in Surabaya. (2) there are allegations about a positive and significant relationship between the partial image of the Parents 'Satisfaction (Y) in the School of Surabaya, (3) there is a suspicion of a positive and significant relationship between service quality and image simultaneously on Parents' Satisfaction in School Surabaya, (4) there is suspicion between the two independent variables and the image and quality of service, quality of service is the most significant effect on increasing Satisfaction Parents' School in Surabaya?
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
Ikhtilaf and Unity in Muslim Ummah: A Comparative Analysisinventionjournals
ABSTRACT: Disagreement (Ikhtilaf) on religious issues has been a common phenomenon in Muslim Ummah as a result of their different judgments and perceptions on various matters. But discussing historical facts or jurisprudential differences should not in any way discourage Muslim unity. Unity of the Ummah is such a clear reality that there can be no two opinions expressed in the matter.
Impact of Employment of Mothers on Self Concept of Adolescentsinventionjournals
ABSTRACT: Employment of women has become increasingly significant in the lives of women. The pertinent question that arises: Is the women happier and provide better parenting to their adolescents by relinquishing the traditional role or by combining the two roles? An attempt has been made to examine the effect of parenting of employed mothers on self-concept of their adolescents. A total of 200 parents were consisted for this study. 100 parents were with employed mothers and 100 were with homemaker mothers. 50 adolescent girls and 50 boys were further selected for measuring their self-concept from the schools of Dehradun, Haridwar and Roorkee district of Uttarakhand State, India. Parent child relationship scale was administered on parents and self-concept scale on adolescents. Study revealed significant difference in favour of parenting of homemaker mothers in the dimensions of marital conflict vs. marital adjustment and the faulty role expectations vs. realistic role expectations. Employed mother’s adolescents showed high self-concept on the dimension of social, temperamental and on total self concept. Boys of the same group found to be high self-concept on physical and temperamental and girls on the dimension of social self concept than the counter group. Implication of this research from the perspective of women employment and their parenting of adolescents regarding self-concept have been discussed.
Analysis of crop yield prediction using data mining techniqueseSAT Journals
Abstract
Agrarian sector in India is facing rigorous problem to maximize the crop productivity. More than 60 percent of the crop still depends on monsoon rainfall. Recent developments in Information Technology for agriculture field has become an interesting research area to predict the crop yield. The problem of yield prediction is a major problem that remains to be solved based on available data. Data Mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. This paper presents a brief analysis of crop yield prediction using Multiple Linear Regression (MLR) technique and Density based clustering technique for the selected region i.e. East Godavari district of Andhra Pradesh in India.
Keywords: Agrarian Sector, Crop Production, Data Mining, Density based clustering, Information Technology, Multiple Linear Regression, Yield Prediction.
IRJET- Analysis of Crop Yield Prediction using Data Mining Technique to Predi...IRJET Journal
This document discusses using data mining techniques to predict annual crop yields in India. It begins with an abstract that outlines how agriculture is important to the Indian economy but crop production depends on seasonal and environmental factors, making yield prediction challenging. The document then provides an introduction to data mining and its potential application to predict crop yields. It reviews literature on using various data mining methods like linear regression and k-nearest neighbor algorithms to predict yields of major crops in India based on historical data on climate, soil conditions and more. The goal is to help farmers choose optimal crops and improve farm productivity and profits.
This document discusses how precision farming and big data can help improve agriculture. It notes that a majority of India's population depends on agriculture but farmers often lack information which can hurt crop yields. New technologies using sensors, cloud computing, and mobile phones can now provide farmers real-time data on soil conditions, weather, and crop health to help maximize production. Data mining techniques like classification and clustering can analyze large agricultural data sets to predict outcomes and identify patterns. This information can help farmers choose optimal crops and growing practices and help businesses anticipate supply and demand trends to better match production and pricing.
IRJET - Enlightening Farmers on Crop YieldIRJET Journal
This document discusses using data mining techniques to predict crop yields to help farmers. It proposes using a random forest regression algorithm on past agricultural data from 2000-2014 to build a prediction model. The model would help farmers select optimal crops, understand weather patterns, and maximize yields. The system is described as gathering data, preprocessing it, training a random forest model on 60% of the data and testing it on 20%. It would then provide yield predictions and recommendations to farmers through a visualization tool. The goal is to help guide farmers' decisions around fertilizer use, soil management, and crop selection to improve production levels.
A Non-Parametric Approach for Performance Appraisal of Agricultural Market Co...IOSR Journals
Efficient performance of Agricultural Market Committees (AMCs) is considered to be the sine quo non for the economic development of an agrarian country like India. Though the number of AMCs has been steadily increasing in India, still the farmers are being exploited by one form or another in transacting the agricultural commodities. In view of this, several apprehensions and concerns were raised fearing about the performance of AMCs in discharging the regulatory provisions for efficient transaction of agricultural commodities. Various enactments have been formulated by Government from time to time to revamp the agricultural marketing system in the country and presently, Model act 2005 (The State Agricultural Produce Marketing (Development and Regulation) Act, 2005) has been under implementation. In this context of exploring the agricultural marketing system with a farmers ended approach, the present paper aims at analyzing the performance appraisal of AMCs in Coastal region of AP in India through Data Envelopment Analysis(DEA) approach. The analytical findings revealed that 53% of selected AMCs are being operated at Scale Efficiency <1. The remaining 47% AMCs are being operated at constant return to scale (CRS) and this directs the Government to continue the existing support even in the future.
Agriculture crop yield prediction using inertia based cat swarm optimizationIJECEIAES
Crop yield prediction is among the most important and main sources of income in the Indian economy. In this paper, the improved cat swarm optimization (ICSO) based recurrent neural network (RNN) model is proposed for crop yield prediction using time series data. The inertia weight parameter is added to position equation that is selected randomly, and a new velocity equation is produced which enhances the searching ability in the best cat area. By using inertia weight, the ICSO enhances performance of feature selection and obtains better convergence in minimum iteration. The RNN is applied to produce direct graph using sequence of data and decides current layer output by involving all other existing calculations. The performance of the model is estimated using coefficient of determination (R2), root mean square error (RMSE), mean squared error (MSE), and mean absolute error (MAE) on the yield from the years 2011 to 2021 with an annual prediction for 120 records of approximately 8 million nuts. The evaluated result shows that the proposed ICSO-RNN model delivers metrics such as R2, MAE, MSE, and RMSE values of 0.99, 0.77, 0.68, and 0.82 correspondingly, which ensures accurate yield prediction when compared with the existing methods which are hybrid reinforcement learning-random forest (RL-RF) and machine learning (ML) methods.
Analyzing Cost of Crop Production and Forecasting the Price of a CropIRJET Journal
This document discusses analyzing the cost of crop production and forecasting crop prices. It first discusses how various technologies like IoT, AI, and drones have been used to automate agriculture by helping with tasks like weather forecasting, inspecting crop quality, and pesticide spraying. However, finance management is still a major issue for farmers.
The document then reviews previous research on forecasting crop yields and prices. It finds that most studies only focus on specific crops in certain regions, and there is no global mechanism for price forecasting. The document also discusses how crop production costs are calculated, finding that current methods don't consider important variables like soil properties.
The document proposes using image processing and sensors to automatically measure soil
IRJET- Agricultural Data Modeling and Yield Forecasting using Data Mining...IRJET Journal
This document proposes using data mining techniques to develop a predictive model for forecasting crop yields. It involves collecting agricultural data on factors like rainfall, temperature, seed quality, and sowing procedures. Data preprocessing and clustering techniques like K-means are applied. Classification algorithms like Support Vector Machine and Naive Bayes are used to predict crop yield as low, medium, or high. The predictive model aims to help farmers plan cultivation for high crop yields by identifying the best combinations of agricultural factors.
Crop Recommendation System to Maximize Crop Yield using Machine Learning Tech...IRJET Journal
This document describes a crop recommendation system that uses machine learning techniques to maximize crop yields. The system collects soil data from testing labs and combines the data with crop information from experts. It then uses an ensemble model with majority voting to recommend crops for specific soil parameters. The ensemble uses support vector machine and artificial neural network learners to make recommendations with high accuracy. The goal is to help farmers choose crops best suited to their soil needs and increase productivity.
This document describes a mobile application called "Farmer's Friend" that aims to help farmers in India. It does this by providing farmers information on crop yields, prices, and suitable crops for their land conditions. The application analyzes past data on factors like rainfall, temperature, and market prices to predict crop performance and recommend optimal crop choices for farmers. This helps address economic issues facing farmers and balances crop varieties grown in different regions. The proposed system aims to suggest alternative crops to farmers if the crop they selected is already exceeding production limits for that area.
An Overview of Crop Yield Prediction using Machine Learning ApproachIRJET Journal
This document discusses using machine learning approaches to predict crop yields. It provides an overview of previous research that has used techniques like random forest regressors, decision trees, and neural networks to predict yields based on environmental and historical data. The document also summarizes several studies that evaluated different machine learning algorithms for crop yield prediction and found random forest to often provide the most accurate forecasts. Improving yield prediction can help farmers select optimal crops and farming practices.
This document summarizes different analytical models that can be used for crop prediction, including classification models. It discusses feature selection methods like principal component analysis and information gain that are important for crop prediction models. The document reviews different machine learning techniques used in previous studies for crop yield prediction, such as linear regression, k-nearest neighbors, neural networks, support vector machines, and decision trees. It aims to compare the performance of these classification techniques for predicting crop yields based on parameters like temperature, rainfall, soil characteristics, and more.
Statistical features learning to predict the crop yield in regional areasIJECEIAES
The plethora of information presented in the form of benchmark dataset plays a significant role in analyzing and understanding the crop yield in certain regions of regional territory. The information may be presented in the form of attributes makes a prediction of crop yield in various regions of machine learning. The information considered for processing involves data cleaning initially followed by binning to reduce the missing data. The information collected is subjected to clustering of data items based on patterns of similarity, The data items that are similar in nature is fed to the system with similarity measure, which involves understanding the distance of data items from its related data item leading to hyper parameters for analyzing of information while calculating the crop yield. The information may be used to ascertain the patterns of data that exhibit similarity with nearest neighbor represented by another attribute. Thus, the research method has yielded an accuracy of 89.62% of classification for predicting the crop yield in agricultural areas of Karnataka region.
1. The document discusses the development of a machine learning-based system to provide precise crop yield recommendations to farmers in India.
2. Over 60% of Indians work in agriculture but farmers often grow the same crops without trying new varieties and apply fertilizers inconsistently, affecting yields and soil quality.
3. The proposed system aims to address these issues by recommending the optimal crop for a given plot of land based on soil composition and environmental factors using machine learning algorithms.
Data driven algorithm selection to predict agriculture commodities priceIJECEIAES
Price prediction and forecasting are common in the agriculture sector. The previous research shows that the advancement in prediction and forecasting algorithms will help farmers to get a better return for their produce. The selection of the best fitting algorithm for the given data set and the commodity is crucial. The historical experimental results show that the performance of the algorithms varies with the input data. Our main objective was to develop a model in which the best-performing prediction algorithm gets selected for the given data set. For the experiment, we have used seasonal autoregressive integrated moving average (SARIMA) stack ensemble and gradient boosting algorithms for the commodities Tomato and Potato with monthly and weekly average prices. The experimental results show that no algorithm is consistent with the given commodities and price data. Using the proposed model for the monthly forecasting and Tomato, stack ensemble is a better choice for Karnataka and Madhya Pradesh states with 59% and 61% accuracy. For Potatoes with the monthly price for Karnataka and Maharashtra, the stack ensemble model gave 60% and 85% accuracy. For weekly prediction, the accuracy of gradient boosting is better compared to other models.
IRJET - Agrotech: Soil Analysis and Crop PredictionIRJET Journal
This document presents a system for soil analysis and crop prediction using data mining techniques. The system measures soil parameters like pH, nitrogen, phosphorus and potassium using sensors. It then uses a decision tree algorithm to classify the soil and predict suitable crops. The pH value is used to estimate other nutrient values. The nutrient values and soil type are sent over WiFi to a server, which uses machine learning to predict crops and provide fertilizer recommendations to the farmer. The proposed system automates the soil testing process and aims to help farmers select optimal crops and increase agricultural yields.
An Efficient and Novel Crop Yield Prediction Method using Machine Learning Al...IIJSRJournal
This document describes a proposed method for crop yield prediction using machine learning algorithms. It begins with an introduction to the importance of agriculture in India and challenges faced by farmers in predicting crop yields. It then discusses previous related work on predicting yields based on environmental factors. The proposed method uses a random forest algorithm and backpropagation neural network to predict yields based on data like rainfall, temperature, and land area. It also describes predicting fertilizer needs and crop prices. The method is evaluated on a dataset and results are discussed. It is concluded that this approach can help farmers predict yields and make better decisions about crop selection and management.
DETECTION OF NUTRIENT DEFICIENCIES IN CROPS USING SUPPORT VECTOR MACHINE (SVM)IRJET Journal
This document discusses a proposed method for detecting nutrient deficiencies in crop leaves using image processing and machine learning techniques. The method involves capturing leaf images, extracting color and texture features, storing feature data in training and testing databases, using k-means clustering to separate normal and deficient leaves, and applying k-NN classification to identify specific nutrient deficiencies by comparing testing features to the training database. The method is evaluated on a dataset of rice crop leaf images containing different nutrient deficiency types, with results showing the system can accurately detect deficiencies like boron deficiency and recommend appropriate remedies.
IMPLEMENTATION PAPER ON AGRICULTURE ADVISORY SYSTEMIRJET Journal
This document presents an implementation paper on an agriculture advisory system that uses machine learning algorithms to predict optimal crops and recommend fertilizers. It first reviews previous literature on similar crop prediction systems using data mining techniques. It then describes the proposed system's methodology, which involves 8 steps: data collection, preprocessing, training, supervised learning using Naive Bayes for crop prediction and KNN for fertilizer recommendation, priority-based crop recommendation, location- and year-based recommendations, output of results, and visual representation of recommendations. The system aims to help farmers select profitable crops and increase agricultural output by providing customized recommendations based on soil analysis and other input data. It concludes the proposed system could help address issues farmers face by streamlining information and facilitating efficient
This document discusses applications of data mining techniques in agriculture. It begins by explaining how data mining can extract useful patterns from large datasets and how fuzzy sets are well-suited for handling incomplete agricultural data involving human factors. Next, it summarizes several common data mining techniques like clustering, association rules, functional dependencies, and data summarization and provides examples of each applied to agriculture, such as for weather forecasting, soil classification, and yield prediction. The document concludes by comparing statistical analysis to data mining and finding data mining superior for analyzing agricultural datasets for speed, ease of use, and accuracy.
Similar to Productivity Potential and Technical Efficiency Differences among the Indian Framers (20)
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Productivity Potential and Technical Efficiency Differences among the Indian Framers
1. International Journal of Humanities and Social Science Invention
ISSN (Online): 2319 – 7722, ISSN (Print): 2319 – 7714
www.ijhssi.org Volume 4 Issue 3 || March. 2015 || PP.01-06
www.ijhssi.org 1 | Page
Productivity Potential and Technical Efficiency Differences
among the Indian Framers
Chandan Kumar Maity
Research Scholar, Department of Economics, University of Burdwan, Burdwan, West Bengal, India.
ABSTRACT: The Group frontier is a representation of the state of knowledge pertaining to the transformation
of inputs into output in the regional level, while the Meta frontier represents the state of the knowledge at the
country level. The ratio of the frontier score of Group and the Meta frontier represents the Meta technology
Ratio (MTR). The study investigates productivity potentials and efficiencies of the farmers in different states in
India by utilizing the concept of Group and Meta frontier technique. Empirical results are derived from a farm
level disaggregated input- output data set of 13 Indian states comprising 3615 number of farmers. The results
show a large technology gap ratio defined by MTR between the sampled states of the country. For calculating
the efficiency measures the Data Envelopment Analysis is applied for the input-output data set.
KEYWORDS: Data Envelopment Analysis, Metafrontier Function, Efficiency, Technology Gap
I. INTRODUCTION
There are numerous studies concerning the technological and productive performance of Agriculture in
developing countries including India (Kawagoe et al, [1]; Kawagoe and Hayami [2}; Rosegrant and Evenson
[3]; Fulginiti and Perrin [4]; Mark W Rosegrant and Kumar [5]; Trueblood [6]; Fulginiti and Perrin [7]; Fan,
Hazell and Thorat [8]; Murgai [9]; Kudaligama and Yanagida [10]; Mukherjee and Kuroda [11]; Nin et al [12];
Coelli et al [13]; Rao [14]; Kumar and Mittal [15]; Bhushan [16]; Alene [17]; Chand et al [18]). These studies
have used several yardsticks for such comparisons. Measures such as input intensities, partial productivity
measures, TFP indices, efficiencies, input use parameters are in most common used. A general technique of all
these procedure is to aggregate over the individual farmers to get region/state/country specific indicators. These
aggregative indicators are then used to assess the performances of the farmers. Though the procedure is widely
used, it suffers from some serious pitfalls. Aggregation often clouds the differences in individual responses to
macro results. In agriculture the problem is more serious because there is a huge difference across the farmer‟s
characteristics when we consider different geographical zone of a country.
Until recently, however, there was very little scope for considering such individual responses in such a
huge panorama. However, the recent development of the Data Envelopment Analysis (DEA), have enabled us to
consider such unit level differences of Efficiency level even in the macro space. The concept of the Meta
production function that was defined by Hayami and Ruttan [19] as “The meta production function can be
regarded as the envelope of commonly conceived neoclassical production functions.” The journey begun with
the classic article written by Førsund [20] where he attempted to made a comparison of farms across various
time points. After presenting the standard aggregative measures he commented “It would be a waste of
information to stop at presenting results for the average unit”. Førsund gave all alternative approach towards
measuring aggregative efficiencies. That depends on the definition of the reference technology. The idea was
elaborated to the concept of Meta frontier by a number of authors (Battese and Rao, [21]; Rao, O‟donnell and
Battese [22], Battese, Rao and O‟donnell [23]; Nyemeck and Nkamleu, Sanogo [24]; O‟donnell, Rao and
Battese [25]).
The general idea is to assume that farms of different regions are operating under a Meta production
function. The Meta Frontier corresponding to the Meta production function defined as the boundary of an
unrestricted technology set. Farmers of different states are however operating under Group frontier. That is
restricted version of the Meta Frontier. The non realisation of the Meta Frontier may be argued to have risen
from the structure of Economic functioning or the features of productive environment. The individual farm is
thus twice constraint. The first is its inability to reach the Group Frontier. The second is the inability of the
region to reach the Meta Frontier. Given this assumption it is then possible to have a meaningful discussion of
farmer‟s performances at different cross sectional points. This paper tries to utilise this concept to understand
the differences in the farm level performances across the states of India. For example, a farmer in Bihar has
twice constant. As an individual farmer he cannot achieve the frontier performance of Bihar. As a farmer in
Bihar he is again unable to reach the performance level of a farmer who belongs to Punjab. Thus his problems
are twofold – individual level that is a result of his own inefficiencies and a group level that is a result of him
being a resident of Bihar.The paper is divided into four sections. Section II discusses the material and methods
used for the study. Section III gives us the main results. We conclude in section IV.
2. Productivity potential and Technical Efficiency Differences among the Indian Framers
www.ijhssi.org 2 | Page
II. MATERIALS AND METHODS
The analysis is based on data drawn from the Department of Agriculture and Cooperation under the
Ministry of Agriculture, Government of India through the Cost of Cultivation Scheme. The data were collected
for every district of each state in India for each year. In this analysis farm level disaggregate input output data
are used pertaining to the year 2010-11. Since the selected crop under study is paddy, we have considered
thirteen paddy cultivating states in India. These are Punjab, Haryana, Uttar Pradesh from northern India, West
Bengal, Bihar and Orissa from Eastern India, Andhra Pradesh, Kerala, Tamil Nadu and Karnataka from southern
India and Gujarat, Madhya Pradesh and Maharashtra from central region of India.
This data set supplies information on various inputs like labour, bullock labour, fertiliser, manure,
machine and output of all crops cultivated in value and quantitative terms. For our analysis we have taken only
three inputs, namely, human labour hour, material cost (which includes the cost of bullock labour and cost of
machinery) and fertiliser that presumably explain production of paddy very well. In the data set output is
measured in quintal. All the variables are considered in per unit area. However, all of the paddy cultivating
farms do not use positive amount of the inputs. Only 3615 number of farms use positive amount of the
considered inputs. We have constructed summery statistics of the variable in the data set for the states under
study. These are shown in table 1.
2.1 Group and Meta Frontier Analysis
Farrell [26] originally introduced a production frontier to measure the efficiency of firms. Latter,
Hayami & Ruttan [19] defined a metafrontier concept based on the Meta production function. According to him
the Meta production function can be regarded as the envelope of commonly conceived neo-classical production
function. In this study, the DEA Meta frontier was used to assess Meta frontier function. The non parametric
DEA model has the high benefit of not requiring a particular functional shape for the frontier.
DEA is a linear programming technique for constructing a non parametric piece-wise linear envelope
to a set of observed output and input data. The mathematical programming approach of DEA makes no room for
„noise‟ and so does not „nearly envelop‟ a data set as the way most econometric models do. It is now possible to
define Farrell‟s input saving efficiency measure based on frontier technology as:
Ei = minαi
αi: Fi y , αi, x ≤ 0 (1)
The linear programming approach to measure efficiency from the envelope is to
maxEi,⋋ Ei (2)
Subject to yi ≤ Y ⋋
X ⋌ ≤ Eixi
⋋ ≥ 0
Where X is an n × I input matrix with columnsxi,
Y is an m × I output matrix with columnsyi.
⋋ is an I × 1 intensity vector
„I‟ is the number of farms in a particular set of observations.
Table 1: Summary Statistics of the variables in the data set
3. Productivity potential and Technical Efficiency Differences among the Indian Framers
www.ijhssi.org 3 | Page
Notes: AP=Andhra Pradesh, BI=Bihar, GU=Gujarat, HA=Haryana, KA=Karnataka, KE=Kerala,
MA=Maharashtra, MP=Madhya Pradesh, OR=Orissa, PU=Punjab, TN=Tamil Nadu, UP=Uttar Pradesh,
WB=West Bengal
Output is in quintal, labour means human labour hour, cost mean material cost in Rupees fertilizer is measured
in Kg and area means cultivated Area under paddy in hector.
Problem 2 has been solved for I time to get each producer‟s efficiency score which is being evaluated
under different sets of observations as envelope. Following this analysis, we get efficiency scores for each of the
individual farmer. Regarding frontier technology, the most common restrictions are strong disposability of input
and output and convexity of the set of feasible input-output combinations. One can assume three types of return
to scale viz., (i) Constant Return to Scale (CRS) (ii) Non Increasing Return to Scale (NIRS) (iii) Variable Return
to Scale (VRS). These returns to scale assumptions impose certain restrictions on the intensity vector⋋. Under
the CRS assumption, ⋋ is unrestricted. NIRS is incorporated within a DEA structure by adding to equation 2 the
constraint eT
⋋≤ 1 where e is a I × 1 vector of ones.Similarly; VRS might be specified by adding to equation 2
the constrainteT
= 1. According to Coelli (29), the VRS specification has been the most commonly used
specification in the 1990‟s. This study also opted for both CRS and VRS specifications. If we have data on Lk
number of states, the above linear program is solved LK times for each period to obtain group technical
efficiency. The Metafrontier is constructed using a DEA model for all the states in the country. Therefore, to
obtain the technical efficiency with respect to Metafrontier, we re –run the above linear program model with the
input and output matrices with data for all the states in the country together. I have used Data Envelopment
Analysis Computer Programme, - DEAP 2.1- and a multi stage DEA procedure (Coelli, [29]) to run the model.
If we denote the efficiency of a state „r‟ relative to its frontier (group frontier) by TEr
r
, and the technical
efficiency of the same state evaluated at the country level (meta Technology) by TEr
∗
, the productivity potential
or Meta Technology Ratio (MTR) of the state can be defined as (Battese et al., [23]):
MTRr
∗
=
TEr
∗
TEr
r (3)
Thus, the technical efficiency relative to the Meta frontier function is the product of the technical
efficiency relative to the frontier for a given state (which is called group frontier) and the MTR. These shows
that technical efficiency measured with reference to the Meta technology can be decomposed into the product of
the technical efficiency measured with reference to the group „r‟ technology, and Meta technology ratio between
the group technology and the Meta technology. Because the technical efficiency relative to the Meta frontier is
always less than the technical efficiency relative to the group frontier, TGR is bound between zero and one.
III. RESULTS AND DISCUSSION
After delving through the maze of data we finally arrive at the door step of our analysis. The analysis
begins with the estimation of efficiency scores using both CRS and VRS techniques. This micro comparison
over the span of thirteen states of India gives us a deep insight into the work of individual farms across length
and breadth of the country. No aggregate analysis can hope to reveal such a vast panorama in our eyes. Table 2
shows the average efficiency scores of the farmers in each of the sampled states. It is observed from the table
that the mean efficiency scores with VRS are generally higher than those of CRS technology. The table also
shows that the ranking of the states in terms of the efficiency scores for two types of returns to scale also
different.
4. Productivity potential and Technical Efficiency Differences among the Indian Framers
www.ijhssi.org 4 | Page
Table 2: Technical Efficiencies Obtained from Group Frontier
CRS VRS
State Mean Rank Maximum Minimum Mean Rank maximum Minimum
AP 0.5476 6 1 0.041 0.7227 4 1 0.101
BI 0.4989 11 1 0.111 0.5918 11 1 0.28
GU 0.5413 7 1 0.153 0.6993 6 1 0.273
HA 0.6878 2 1 0.187 0.7303 3 1 0.475
KA 0.5175 9 1 0.078 0.6339 10 1 0.274
KE 0.6159 4 1 0.162 0.7515 2 1 0.315
MA 0.2800 13 1 0.18 0.5892 12 1 0.384
MP 0.5765 5 1 0.151 0.7047 5 1 0.294
OR 0.5044 10 1 0.331 0.678 8 1 0.48
PU 0.7005 1 1 0.347 0.7878 1 1 0.472
TN 0.6172 3 1 0.194 0.6937 7 1 0.256
UP 0.3102 12 1 0.069 0.5816 13 1 0.161
WB 0.5219 8 1 0.186 0.666 9 1 0.38
Average 0.5323 1 0.168 0.6793 1 0.318
Notes: as on Table 1
From the sampled Indian states, the technical efficiency score ranged from 0.041 to 1.00 with an
average 0.5323, indicating that the agricultural sector produce on an average 53% of potential output given the
technology available in Indian agricultural sector as a whole. So as far the VRS specification is concern, the
technical efficiency score of the Indian farmers ranged from 0.101 to 1 with an average 0.6793, indicating that
this sector produce 68% of potential output as a whole. A state-wise comparison of average efficiency of the
farmers shows that there are 6 numbers of states which recorded the average efficiency less than all India
average efficiency scores (Such as Bihar, Karnataka, Maharashtra, Orissa, UP, and West Bengal). The states
from southern India (i.e., Andhra Pradesh, Tamil Nadu and Kerala) recorded efficiency scores higher than the
all India Average. It is observed from table 2 that Punjab appears to be the best state in terms of average
efficiency scores for both CRS and VRS specification. The average efficiency score for the state is found to be
0.7005 and 0.7878 respectively under CRS and VRS specification. With CRS specification Haryana appears to
be the second best zone with average efficiency 0.6878, however, under VRS specification, Kerala appears to be
the second best performing state. Consequently, Maharashtra recorded as the least performing state under CRS
as well as VRS specification. From a policy point of view, these state wise differences show the type of
interventions needed to be putted in place in each state for enhancing the productivity of Indian farmers. It
should be in the form of raising technology or with the improvement of the technical know- how.
In Meta Frontier, however, envelop is chosen as the background. Since, envelop encompasses all the
input – output combination, the problem of incomparability does not arise here. The empirical exercise now
concentrates on the Meta Frontier analysis. Ideally this analysis should be made over all the observations. It is
now feasible, not very advisable to represent the analysis obtained these huge data. The table 3 represent the
average efficiency scores of the state obtained from Meta Frontier.
Table 3: Technical Efficiencies Obtained from Meta Frontier
CRS VRS
State Mean Rank maximum Minimum Mean Rank maximum Minimum
AP 0.2733 7 1 0.041 0.4458 2 1 0.081
BI 0.2706 8 0.975 0.047 0.3476 11 1 0.064
GU 0.2613 9 0.949 0.071 0.4160 5 1 0.111
HA 0.3225 2 1 0.075 0.4129 6 1 0.146
KA 0.2281 12 0.604 0.033 0.3122 12 0.721 0.041
KE 0.3114 3 1 0.077 0.4268 4 1 0.015
MA 0.1795 13 0.48 0.053 0.2295 13 0.545 0.082
MP 0.2746 6 1 0.074 0.3739 10 1 0.115
OR 0.2578 10 0.975 0.088 0.3940 8 0.981 0.173
PU 0.4428 1 0.762 0.15 0.6680 1 1 0.304
TN 0.2460 11 0.555 0.067 0.3805 9 0.789 0.121
UP 0.2969 4 1 0.069 0.4431 3 1 0.129
WB 0.2868 5 0.987 0.071 0.4097 7 1 0.144
Average 0.2809 0.8682 0.0705 0.4046 0.9258 0.1174
Notes: as on Table 1
It is clear from the table that the technical efficiency under CRS specification of the farmers obtained
from Meta frontier ranged from 0.033 to 1.00 with an average of about 0.2809, indicating that farmers are
produce on an average 28% of the potential output given the available technology. The farmers from Punjab
achieved the highest mean technical efficiency and from Maharashtra achieved the least average efficiency
5. Productivity potential and Technical Efficiency Differences among the Indian Framers
www.ijhssi.org 5 | Page
score relative to the Meta frontier. The technical efficiency of the states from northern India (i.e. Punjab,
Haryana and UP) are higher than the all India average efficiency score in terms of Meta technology. Among the
states from Eastern India, West Bengal is only the state for which the technical efficiency score is higher than
the all India average level in terms of Meta frontier.
The more interesting feature is the difference between the average technical efficiency scores from the
Group and the Meta frontier model. For example, the average technical efficiency for Punjab relative to the
Meta technology is only 0.44% under CRS technology and 66% under VRS technology, while its mean
efficiency is quite large with respect to its own Group frontier (70% under CRS and 78% under VRS). The
difference between the two efficiency scores indicate the order of bias of the technical efficiencies obtained by
using the Group frontiers, relative to the technology available for the agricultural sector in India. Generally, the
technical efficiencies from the Group frontier should be greater than those obtained from the Meta production
frontier, because the constraints in the Group linear programming problem.
The Group frontier is a representation of the state of knowledge/technology pertaining to the
transformation of agricultural inputs into output in the region (state), while the Meta frontier represents the state
of the knowledge/technology at the country level. The ratio of the frontier score of region and the Meta frontier
represents the Meta technology ratio (MTR) of the region (or State). Now the study estimates the Meta
technology ratio (MTR) as presented in table 4.
Table 4: State wise Meta technology ratio (MTR) Estimates
States CRS VRS
AP 0.4991 0.6169
BI 0.5424 0.5874
GU 0.4827 0.5949
HA 0.4689 0.5654
KA 0.4408 0.4925
KE 0.5056 0.5679
MA 0.6411 0.3895
MP 0.4763 0.5306
OR 0.5111 0.5811
PU 0.6321 0.8479
TN 0.3986 0.5485
UP 0.9571 0.7619
WB 0.5495 0.6152
Notes: as on Table 1
The sampled Indian states have Meta Technology Ratio ranging between 0.3986 and 0.9571. These
values can be interpreted as the technological gap faced by the farmers in those regions when their performances
are compared with the all India level. Under CRS specification, farmers of Tamil Nadu have the lowest
productivity potential ratio followed by Karnataka. This suggest that even if Punjab and Haryana achieved best
practice with respect to the technology observed in the Group frontier as well as Meta Frontier, they will still be
lagging behind because their technology lag behind all India technology level with a technology gap ratio of
0.6321 and 0.4688 respectively. For VRS technology same type of conclusion can also be drawn. In the
inefficiency studies two types of causes viz. man-made errors (e.g., machines failure, input indivisibility etc.)
and natural factors (e.g. abnormal rainfall, drought etc.) are identified to explain the productivity potential of the
farmers. Of these two, the influence of natural factors, particularly rainfall, is considered to be the important
factor of determining productive potential of Indian farmers.
IV. CONCLUSIONS
The study investigates productivity potentials and efficiencies of the farmers in different states in India
by utilizing the concept of Group and Meta frontier technique. Since technology is a representation of the state
of knowledge pertaining to the transformation of agricultural inputs into output, the existence of an over-arching
technology, referred to as the Meta technology, represented by the Meta frontier production function has been
conceptualize. The methodology enables the estimation of state wise Meta Technology Ratio (MTR) by using
decomposition result involving both the Group and Meta frontier which examines comparative changes in the
efficiency of groups with respect to the Meta Frontier. Empirical results are derived from a disaggregated farm
level input output data set for the year of 2009-10 from 13 Indian states comprising 3615 number of farmers.
The results of this study show a large technology gap ratio defined by MTR between the sampled states
of the country. These values can be interpreted as the technological gap faced by the agricultural sector in those
regions when their performances are compared with the all India level. In terms of technical efficiency, the
states from northern region such as Punjab and Haryana achieved the highest technical efficiency relative to
their group frontier as well as Meta frontier.
6. Productivity potential and Technical Efficiency Differences among the Indian Framers
www.ijhssi.org 6 | Page
From a policy point of view, these Group differences show the type of interventions needed to be
putted in place in each region for enhancing the productivity of Indian Agriculture. In some states like Punjab,
Haryana, Andhra Pradesh, the first target should be on raising technology while in other states like in
Maharashtra, Karnataka it will be more urgent to first deal with the improvement of the know- how.
REFERENCES
[1] Kawagoe T., Hayami Y., Ruttan V. The inter country agricultural production function and productivity differences among
countries, Journal of Development Economics, 19, 1985, 113-132.
[2] Kawagoe T., Hayami Y. An inter country comparison of agricultural production efficiency, American journal of Agricultural
Economics, 67, 1985, 87-92.
[3] Rosegrant Mark W, Evenson, The rate of growth of Total Factor Productivity in Indian crop sector 1957-1985, American Journal of
Agricultural Economics, August, 1992, 757-763.
[4] Fulginiti L. E., and Perrin R.K, Agricultural Productivity in Developing Countries, Agricultural Economics, 19, 1988, 45-51.
[5] Mark W. Rosegrant, Kumar P, Productivity and Sources of Growth for Rice in India, Economic and Political Weekly 29(53), 1994,
A-183 to A-188.
[6] Trueblood M.A. An inter country comparison of agricultural efficiency and productivity, PhD dissertation, University of Minnesota,
1996.
[7] Fulginiti L. E., & Perrin R.K, Prices and Productivity in Agriculture”, Review of Economics and Statistics, 75, 1993, 471-482.
[8] Fan Shenggen, Hazell Peter, and Thorat Sukhadeo, Government Spending, Growth and Poverty: An Analysis of Inter linkages in
Rural India, EPTD Discussion Paper No. 33, Environment and Production Technology Division, International Food Policy
Research Institute, USA, 1998.
[9] Murgai Rinku, The Green Revolution and the Productivity Paradox- Evidence from the Indian Punjab”, Policy Research Working
Paper 2234, The World Bank Development Research Group, Rural Development, 1999.
[10] Kudaligama Viveka P. and Yanagida John F, A Comparison of Inter country Agricultural Production Functions: A Frontier
Function Approach, Journal of Economic Development, 25(1), 2000, 57-73.
[11] Mukherjee, Anit and Y. Kuroda, Effect of Rural Nonfarm Employment and Infrastructure on Agricultural Productivity: Evidence
from India. Discussion Paper No. 938. University of Tsukuba, Ibaraki, Japan, 2001.
[12] Nin Alejandro, Arndt Channing, Preckel Paul V, Is agricultural productivity in developing countries really shrinking? New evidence
using a modified nonparametric approach, Journal of Development Economics 71. 2003, 395-415.
[13] Coelli Tim, Rahman Sanzidur and Thirtle Colin, A Stochastic Frontier Approach to Total Factor Productivity measurement in
Bangladesh crop agriculture, Journal of International Development, 15, 2003, 321-333.
[14] Rao N. Chandrashekhara, Total Factor Productivity in Andhra Pradesh Agriculture, American Economics Research Review, 18(1),
2005, 1-19.
[15] Kumar Praduman, Mittal Surabhi, Agricultural Productivity Trends in India: Sustainability Issues”, Agricultural Economics
Research Review 19 (Conference No.), 2006, 71-88.
[16] Bhushan Surya, Total Factor Productivity Growth of Wheat in India: A Malmquist Approach, Indian Journal of Agricultural
Economics, 60(1),2005, 32-48.
[17] Alene Arega D, Productivity Growth and the Effects of Research and Development in African Agriculture, Contributed paper
prepared for the presentation at the International Association of Agricultural Economists Conference, Beijing, China, August 2009.
[18] Chand Ramesh, Kumar Praduman and Kumar Sant, Total Factor Productivity and Contribution of Research Investment to
Agricultural Growth in India, National Council for Agricultural Economic and Policy Research, Policy Paper 25, March 2011.
[19] Hayami, Y. and Ruttan, V.W., Agricultural Development: International perspective. (Baltimore, John Hopkins University Press),
1971.
[20] Førsund F.R. Malmquist Indices of Productivity Growth: An Application to Norwegian Ferries. In H.O. Fried, A.K. Lovel, S.S.
Schmidt (eds), The Measurement of Productive Efficiency: Techniques and Applications. (Oxford: Oxford University Press), 1993,
352-373.
[21] Battese, G.E. and Rao, D.S.P., Technology gap, efficiency, and a stochastic Metafrontier function. International Journal of Business
and Economics 1(2), 2002 87-93
[22] Rao, D.S.P., O‟donnell, J. and Battese, G.E., Metafrontier functions for the study of inter-regional productivity differences. Centre
for Efficiency and Productivity Analysis Working Paper 1, 2003.
[23] Battese, G.E., D.S.P.Rao and C.J. O‟Donnell, A Meta Production Function for Estimation of Technical Efficiencies and
Technological Gaps for Farms Operating Under Different Technologies, Journal of Productivity Analysis. 21, 2004, 91-103.
[24] NKamleu, G.B, J. Nyemeck and D. Sanogo, Meta frontier Analysis of Technology Gap and Productivity Difference in African
Agriculture, Journal of Agriculture and Food Economics; 1 (2), 2006, 111-120.
[25] O‟Donnell, C. J., D.S.P.Rao and G.E. Battese, Metafrontier Frameworks for the Study of Farm-Level Efficiencies and Technology
Ratios, Empirical Economics, 34, 2008, 231-255.
[26] Farrell, M.J., The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, Series A, 120(3), 1957, 253-281.
[27] Fare, R., Grosskopf S., & Lovell C.A.K., Production Frontiers, (Cambridge University Press, Cambridge, 1994)
[28] Government of India, Ministry of Agriculture, Ministry of Agriculture and Cooperation,
http://eands.dacnet.nic.in/Cost_of_Cultivation.htm
[29] Coelli, Tim, A guide to DEAP version 2.1: A data envelopment analysis (computer) program. Centre for Efficiency and
Productivity Analysis Working paper 96/08, 1996