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| Aye, Goodness C.; Mungatana, Eric D.. |
| The current food crisis all over the globe has necessitated alternative policy actions by various stakeholders in almost all countries of the world. Consequently, efforts are focused on increased investment in agricultural research and development. The study evaluates impact of technological innovations on estimates of technical, allocative and cost efficiency from a parametric stochastic and non-parametric distance functions. Inefficiency effects are modelled in a second stage endogeniety-corrected Tobit regression model as a function of technological innovation and other policy variables. The results from both approaches show there is substantial technical, allocative and cost inefficiency in maize production and that analysis of technical, allocative... |
| Tipo: Journal Article |
Palavras-chave: Technology; Efficiency; Maize; Parametric; Non-parametric; Distance function; Nigeria; Crop Production/Industries. |
| Ano: 2010 |
URL: http://purl.umn.edu/95965 |
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| Freiria,Gustavo Henrique; Gonçalves,Leandro Simões Azeredo; Furlan,Felipe Favoretto; Fonseca Junior,Nelson da Silva; Lima,Wilmar Ferreira; Prete,Cássio Egidio Cavenaghi. |
| ABSTRACT The grains of food-type soybean cultivars, which are characterized by the absence of lipoxygenases and the presence of high levels of proteins and isoflavones, are regarded as functional foods with high acceptance by consumers. However, few cultivars of food-type soybeans are currently available in the Brazilian market. The aim of this work was to study the adaptability and stability of various genotypes of food-type soybeans and to compare the performance of methods, which are based on analysis of variance, non-parametric, regression, multivariate and mixed models. Ten lines of food-type soybeans obtained from the Breeding Program of Soybeans for Human Consumption of the State University of Londrina (UEL/BPSHC) and two commercial varieties, the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Glycine max; Yield; Non-parametric; Regression; Multivariate; Mixed models. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052018000200253 |
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