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	Provedor de dados AgEcon (4) Scientia Agricola (1) Autor Hernandez-Villafuerte, Karla Vanessa (2) Alemu, Zerihun Gudeta (1) Bergstrom, John C. (1) Cai, Ruohong (1) Lin,Chinsu (1) Magingxa, Litha Light (1) Mullen, Jeffrey D. (1) Shurley, W. Donald (1) Trianingsih,Desi (1) Wetzstein, Michael E. (1) van Schalkwyk, Herman D. (1) Mais... Palavra-chave Principal component regression (5) Cointegration (2) Demand and Price Analysis (2) Geographical distance (2) Price transmission (2) Rice (2) Structural breaks (2) Agricultural and Food Policy (1) Brazil (1) Brazil. (1) C32 (1) Climate change. (1) Crop Production/Industries (1) Crop yield response (1) D1 (1) Ecological impact values (1) Forest planning and zoning (1) Geospatial biodiversity mapping (1) Irrigation projects (1) O13 (1) Mais... Tipo do documento Conference Paper or Presentation (3) Info:eu-repo/semantics/article (1) Working or Discussion Paper (1) Ano 2016 (1) 2011 (3) 2006 (1) País United States (4) Brazil (1) Idioma Inglês (5)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 5 Primeira ... 1 ... Última Principal Component Analysis of Crop Yield Response to Climate Change AgEcon Cai, Ruohong; Bergstrom, John C.; Mullen, Jeffrey D.; Wetzstein, Michael E.; Shurley, W. Donald. The objective of this study is to compare the effects of climate change on crop yields across different regions. A Principal Component Regression (PCR) model is developed to estimate the historical relationships between weather and crop yields for corn, soybeans, cotton, and peanuts for several northern and southern U.S. states. Climate change projection data from three climate models are applied to the estimated PCR model to forecast crop yield response. Instead of directly using weather variables as predictor variables, the PCR model uses weather indices transformed from original weather variables by the Principal Component Analysis (PCA) approach. A climate change impact index (CCII) is developed to compare climate change effects across different... Tipo: Working or Discussion Paper Palavras-chave: Principal component regression; Crop yield response; Climate change.; Crop Production/Industries. Ano: 2011 URL: http://purl.umn.edu/103947 Factors Influencing the Success Potential in Smallholder Irrigation Projects of South Africa: A Principal Component Regression AgEcon Magingxa, Litha Light; Alemu, Zerihun Gudeta; van Schalkwyk, Herman D.. The objective of this paper is to examine the role of the factors expected to influence the success potential of small holder irrigation projects as they apply in the South African context. The study was conducted in six smallholder irrigation schemes in three provinces namely: Eastern Cape, Limpopo and Mpumalanga. To determine the farmers' potential success (dependent variable), a cluster analysis was conducted yielding two groups of farmers - the less successful and more successful. The principal component regression (PCR) tool was used to analyse the data and deal with the problem of multicollinearity, transforming the explanatory variables into principal component estimators. There were fourteen explanatory variables. Out of the nine statistically... Tipo: Conference Paper or Presentation Palavras-chave: Success potential; Smallholder; South Africa; Irrigation projects; Principal component regression; Resource /Energy Economics and Policy; D1; O13; Q1. Ano: 2006 URL: http://purl.umn.edu/25348 Relationship between Spatial Price Transmission and Geographical Distance in Brazil AgEcon Hernandez-Villafuerte, Karla Vanessa. Selected Paper prepared for presentation at the Agricultural & Applied Economics Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24-26, 2011. (Poster Presentation) Tipo: Conference Paper or Presentation Palavras-chave: Cointegration; Price transmission; Geographical distance; Structural breaks; Principal component regression; Rice; Brazil.; Agricultural and Food Policy; Demand and Price Analysis; C32; Q11; Q13. Ano: 2011 URL: http://purl.umn.edu/103677 RELATIONSHIP BETWEEN SPATIAL PRICE TRANSMISSION AND GEOGRAPHICAL DISTANCE IN BRAZIL AgEcon Hernandez-Villafuerte, Karla Vanessa. The price transmission between markets is often interpreted as providing insights into the market’s infrastructure efficiency and transaction costs. Thus, finding a possible explanation for the degree of integration has become an issue of special interest. Recent researchers have pointed out the distance between markets as one of the possible factors. However, the distance is closely related with other elements, such as road quality and the proximity to an export point, which affect transport costs, opportunity costs and thus the integration. Therefore, what the most important factor is when determining the relationship among markets remains unclear. The cointegration framework, OLS and principal component regressions are applied in order to investigate... Tipo: Conference Paper or Presentation Palavras-chave: Cointegration; Price transmission; Geographical distance; Structural breaks; Principal component regression; Rice; Brazil; Demand and Price Analysis. Ano: 2011 URL: http://purl.umn.edu/114545 Identifying forest ecosystem regions for agricultural use and conservation Scientia Agricola Lin,Chinsu; Trianingsih,Desi. ABSTRACT Balancing agricultural needs with the need to protect biodiverse environments presents a challenge to forestry management. An imbalance in resource production and ecosystem regulation often leads to degradation or deforestation such as when excessive cultivation damages forest biodiversity. Lack of information on geospatial biodiversity may hamper forest ecosystems. In particular, this may be an issue in areas where there is a strong need to reassign land to food production. It is essential to identify and protect those parts of the forest that are key to its preservation. This paper presents a strategy for choosing suitable areas for agricultural management based on a geospatial variation of Shannon's vegetation diversity index (SHDI). This index... Tipo: Info:eu-repo/semantics/article Palavras-chave: Species diversity; Ecological impact values; Forest planning and zoning; Geospatial biodiversity mapping; Principal component regression. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000100062 Registros recuperados: 5 Primeira ... 1 ... Última

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