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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Unidades Centrais. |
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Data corrente: |
13/07/2001 |
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Data da última atualização: |
04/07/2005 |
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Autoria: |
TSURUTA, J. H. |
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Título: |
A Study on the selection of agricultural adaptive development areas using genetic algorithms applied to many crops. |
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Ano de publicação: |
2001 |
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Fonte/Imprenta: |
2001 . |
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Páginas: |
205 p. |
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Idioma: |
Inglês |
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Notas: |
Tese (Doutor) - University Ibaraki, Ibaraki-USA. |
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Conteúdo: |
According to the Population Division of the United Nations, the medium scenario for the year 2150 is a world population of 9.7 billion inhabitants, considering that the fertility will stabilize. But, if the fertility is considered to maintain at 1995 levels, the world population will reach 256 billion. In relation to hunger, the number of undernourished people in the world rose by 6 million from the 1990-92 period to the 1994-96. Therefore, there is a prospect of the increase of global demand for food in the future, and research on food production prediction models will become important. The increase of food production can be accomplished with the increase of new cultivated areas, and/or with the increase of agricultural productivity. Generally, geographical information on great areas can be obtained in a microscopic way, based on image data of natural resources satellites.Selection of agricultural development areas is based on geographical information, soil and climate analysis. But the existent methodologies have been applied to one crop and in restricted regions, and only in these conditions were proved efficient. The objective of this study is to make possible the application of genetic algorithms that obtain the optimization of one crop to many crops, enlarging the applicability and clarifying the praticability and making possible to select agricultural areas by adaptive development procedures. These algorithms, which are part of the computational models inspired by nature and used to solve search and optimization problems, are used to maximize the productivity of planted crops and adapted to maximize the total net income. The study area is located in the municipal district of Irai de Minas, MG, in Cerrado region, where an agricultural frontier of 80 million hectares still exists, and where the application of the model in unexplored regions can be verified. The main characteristic of this region is the presence of two defined seasons, the drought season, from April to September, and rainy season, from October to March, and where in this last period falls 90% of total amount of rain. Other characteristics are the low fertility and the acidity of the soil. Thus, better economical results can be expected with chemical improvements of the soil than with physical ones. This study initially focused on the production of soybean and corn that represents 88% of total grain produced in Cerrado region. For the adaptation and production of crops in agricultural region, the adjustment of pH of the soil was considered, applyng the amount to lime to the soil, depending on the analysis of soil type. The productivity of the crops in measured as a function of the quantities of apple phosphor to the soil. To avoid risk of harvest loss to the farmers, it is important to make diversification of crops, modeling the system to force to plant the two crops. The productivity as a function of new varieties of sobyean seeds, developed mainly for this region, is also considered. Afterward, two more crops are introduced, the rice and the edible bean, totaling four crops in the model. Each crop production is esmated as a function of basic input applied in the soil (lime and fertilizers), besides the production system costs. The quantities of these inputs were adjusted at production system costs of the region. The introduction of irrigation systems with the objective of avoiding loss in the production caused by drought days called veranico was considered. The competing four crops in the cultivable area is very defined by a genetic algotithm, that tries to choose the one of better profitability, what could result in a monoculture. Thus, in this model, rice is prioritized followed by edible bean that are the main products of Brazilian consumption. Afterward, an area is granted for the corn, and the rest for the soybean, according to available capital for investment. Thus, the Pareto solution is obtained, and the practicability of the optimization model to select agricultural adaptive development areas using genetic algorithms for many crops was evidenced.Consequently, this study contributes to the efficiency of the development of the agriculture and to the increase of food production through the search and optimization mechanism. MenosAccording to the Population Division of the United Nations, the medium scenario for the year 2150 is a world population of 9.7 billion inhabitants, considering that the fertility will stabilize. But, if the fertility is considered to maintain at 1995 levels, the world population will reach 256 billion. In relation to hunger, the number of undernourished people in the world rose by 6 million from the 1990-92 period to the 1994-96. Therefore, there is a prospect of the increase of global demand for food in the future, and research on food production prediction models will become important. The increase of food production can be accomplished with the increase of new cultivated areas, and/or with the increase of agricultural productivity. Generally, geographical information on great areas can be obtained in a microscopic way, based on image data of natural resources satellites.Selection of agricultural development areas is based on geographical information, soil and climate analysis. But the existent methodologies have been applied to one crop and in restricted regions, and only in these conditions were proved efficient. The objective of this study is to make possible the application of genetic algorithms that obtain the optimization of one crop to many crops, enlarging the applicability and clarifying the praticability and making possible to select agricultural areas by adaptive development procedures. These algorithms, which are part of the computational models inspired by nat... Mostrar Tudo |
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Palavras-Chave: |
agricultural development; algoritmo; cultura; Genética de algoritmos. |
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Thesagro: |
Desenvolvimento Agrícola; Genética. |
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Thesaurus Nal: |
algorithms; crops; genetics. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 04974nam a2200241 a 4500
001 1103794
005 2005-07-04
008 2001 bl uuuu m 00u1 u #d
100 1 $aTSURUTA, J. H.
245 $aA Study on the selection of agricultural adaptive development areas using genetic algorithms applied to many crops.
260 $a2001 .$c2001
300 $a205 p.
500 $aTese (Doutor) - University Ibaraki, Ibaraki-USA.
520 $aAccording to the Population Division of the United Nations, the medium scenario for the year 2150 is a world population of 9.7 billion inhabitants, considering that the fertility will stabilize. But, if the fertility is considered to maintain at 1995 levels, the world population will reach 256 billion. In relation to hunger, the number of undernourished people in the world rose by 6 million from the 1990-92 period to the 1994-96. Therefore, there is a prospect of the increase of global demand for food in the future, and research on food production prediction models will become important. The increase of food production can be accomplished with the increase of new cultivated areas, and/or with the increase of agricultural productivity. Generally, geographical information on great areas can be obtained in a microscopic way, based on image data of natural resources satellites.Selection of agricultural development areas is based on geographical information, soil and climate analysis. But the existent methodologies have been applied to one crop and in restricted regions, and only in these conditions were proved efficient. The objective of this study is to make possible the application of genetic algorithms that obtain the optimization of one crop to many crops, enlarging the applicability and clarifying the praticability and making possible to select agricultural areas by adaptive development procedures. These algorithms, which are part of the computational models inspired by nature and used to solve search and optimization problems, are used to maximize the productivity of planted crops and adapted to maximize the total net income. The study area is located in the municipal district of Irai de Minas, MG, in Cerrado region, where an agricultural frontier of 80 million hectares still exists, and where the application of the model in unexplored regions can be verified. The main characteristic of this region is the presence of two defined seasons, the drought season, from April to September, and rainy season, from October to March, and where in this last period falls 90% of total amount of rain. Other characteristics are the low fertility and the acidity of the soil. Thus, better economical results can be expected with chemical improvements of the soil than with physical ones. This study initially focused on the production of soybean and corn that represents 88% of total grain produced in Cerrado region. For the adaptation and production of crops in agricultural region, the adjustment of pH of the soil was considered, applyng the amount to lime to the soil, depending on the analysis of soil type. The productivity of the crops in measured as a function of the quantities of apple phosphor to the soil. To avoid risk of harvest loss to the farmers, it is important to make diversification of crops, modeling the system to force to plant the two crops. The productivity as a function of new varieties of sobyean seeds, developed mainly for this region, is also considered. Afterward, two more crops are introduced, the rice and the edible bean, totaling four crops in the model. Each crop production is esmated as a function of basic input applied in the soil (lime and fertilizers), besides the production system costs. The quantities of these inputs were adjusted at production system costs of the region. The introduction of irrigation systems with the objective of avoiding loss in the production caused by drought days called veranico was considered. The competing four crops in the cultivable area is very defined by a genetic algotithm, that tries to choose the one of better profitability, what could result in a monoculture. Thus, in this model, rice is prioritized followed by edible bean that are the main products of Brazilian consumption. Afterward, an area is granted for the corn, and the rest for the soybean, according to available capital for investment. Thus, the Pareto solution is obtained, and the practicability of the optimization model to select agricultural adaptive development areas using genetic algorithms for many crops was evidenced.Consequently, this study contributes to the efficiency of the development of the agriculture and to the increase of food production through the search and optimization mechanism.
650 $aalgorithms
650 $acrops
650 $agenetics
650 $aDesenvolvimento Agrícola
650 $aGenética
653 $aagricultural development
653 $aalgoritmo
653 $acultura
653 $aGenética de algoritmos
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Embrapa Unidades Centrais (AI-SEDE) |
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| Registros recuperados : 15 | |
| 15. |  | FIGUEIREDO, A. M. C. M.; GUSMAO, G. L.; TSURUTA, J. H.; FREITAS, J. B. P. G. de; CAMARGO NETO, J.; LUZ, M. de C. P. da; ARGOLLO JUNIOR, M. de T. e; COLOMBO, R. M. T. Iconus: a user interface management system. In: INTERNATIONAL WORKSHOP ON THE BRAZILIAN SOFTWARE PLANT PROJECT, 2., 1990, Campinas. Proceedings... Campinas: Banco do Brasil: EMBRAPA-NTIA: CTI, 1990. p. 57-71.| Biblioteca(s): Embrapa Agricultura Digital. |
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