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Gestão do Risco na Orizicultura num Contexto de Alterações Climáticas
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O contexto de alterações climáticas em que vivemos apresenta novos riscos ao setor
agrícola. Pertencente a este setor, a Orizicultura, referente à cultura do arroz, está também
exposta à incerteza provocada por estes riscos. O arroz constitui a base da alimentação de
grande parte da população mundial, sendo que, a nível europeu, Portugal é um dos principais
produtores e o país com maior consumo per capita. Assim, pretende-se investigar qual o impacto esperado das alterações climáticas na produção de arroz em Portugal e identificar a existência de mecanismos de gestão do risco que suportam a atividade agrícola em geral.
Da análise efetuada ao impacto esperado das alterações climáticas na produção de arroz
é possível concluir, que, pela sua localização geográfica, Portugal está exposto a efeitos que
afetam negativamente os fatores climáticos mais relevantes na produção de arroz, a temperatura e a precipitação, com consequências negativas no rendimento das colheitas. De entre as
medidas de mitigação e adaptação adotadas em Portugal, destaca-se o melhoramento genético do arroz, que permite a criação de novas variedades de arroz com índices de produção melhorados e com melhor resistência a pragas e doenças.
Foi identificada a possibilidade da utilização de mecanismos de inteligência artificial no
apoio à gestão de risco no setor agrícola, através da investigação de estudos relacionados com
mecanismos de Machine Learning aplicados a este setor. Conclui-se que devem ser disponibilizadas às organizações do setor agrícola ferramentas que permitam dar resposta aos crescentes riscos a que estão expostas, em particular aos riscos de produção.
The climate change context in which we live presents new risks to the agricultural sector. As part of this sector, rice farming is also exposed to the uncertainty caused by these risks. Rice forms the basis of the diet of a large part of the world's population and, at European level, Portugal is one of the main producers and the country with the highest per capita consumption. The aim is therefore to investigate the expected impact of climate change on rice production in Portugal and to identify the existence of risk management mechanisms that support agricultural activity in general. From analysing the expected impact of climate change on rice production, it can be concluded that, due to its geographical location, Portugal is exposed to effects that negatively affect the most important climatic factors in rice production, temperature and rainfall, with negative consequences for crop yields. Among the mitigation and adaptation measures adopted in Portugal, rice genetic improvement stands out, allowing for the creation of new rice varieties with improved production rates and better resistance to pests and diseases. The possibility of using artificial intelligence mechanisms to support risk management in the agricultural sector was identified by investigating studies related to Machine Learning mechanisms applied to this sector. It can be concluded that organisations in the agricultural sector should be provided with tools to address the growing risks to which they are exposed, particularly production risks.
The climate change context in which we live presents new risks to the agricultural sector. As part of this sector, rice farming is also exposed to the uncertainty caused by these risks. Rice forms the basis of the diet of a large part of the world's population and, at European level, Portugal is one of the main producers and the country with the highest per capita consumption. The aim is therefore to investigate the expected impact of climate change on rice production in Portugal and to identify the existence of risk management mechanisms that support agricultural activity in general. From analysing the expected impact of climate change on rice production, it can be concluded that, due to its geographical location, Portugal is exposed to effects that negatively affect the most important climatic factors in rice production, temperature and rainfall, with negative consequences for crop yields. Among the mitigation and adaptation measures adopted in Portugal, rice genetic improvement stands out, allowing for the creation of new rice varieties with improved production rates and better resistance to pests and diseases. The possibility of using artificial intelligence mechanisms to support risk management in the agricultural sector was identified by investigating studies related to Machine Learning mechanisms applied to this sector. It can be concluded that organisations in the agricultural sector should be provided with tools to address the growing risks to which they are exposed, particularly production risks.
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Agricultura Arroz Gestão de Risco Alterações Climáticas Inteligência Artificial