BIBLIOS

Tipo
Documentos Académicos

Tipo de Documento
Dissertação de Mestrado

Título
Integrative Approach to Analyze Water Use Efficiency in a Maize Crop Using Machine Learning

Participantes na publicação
Miguel M Alves (Author)
FACULDADE DE CIÊNCIAS E TECNOLOGIA DA UNIVERSIDADE NOVA DE LISBOA
Filipa A M Ferrada (Adviser)
FACULDADE DE CIÊNCIAS E TECNOLOGIA DA UNIVERSIDADE NOVA DE LISBOA
Patrícia M F Correia (Co-adviser)
Jorge Marques da Silva (Co-adviser)
Dep. Biologia Vegetal
BioISI

Resumo
The impact of global climate change on agriculture is apparent, with increasing drought\\nscenarios leading to a reduction in crop yields. There is, therefore, an urgent need for new\\nmethods to improve growth in maize crops. In this context, it has been proposed the use\\nof microbial biostimulants as a developing biological strategy to improve plant tolerance\\nto water stress.\\nThis work encompasses a two-phased strategy: A first part consisting of an experimental\\nphase executed at "Asfertglobal" - a Portuguese company focused on the development\\nof biostimulants and biocontrol solutions based on the use of microorganisms and new\\norganic molecules - and a second phase, where machine learning algorithms are used to\\nanalyze and process the collected data, aiming to predict or estimate absolute values for\\nvarious indexes.\\nThis approach provides additional information related to hydric stress and water-use\\nefficiency (WUE), offering a large spectrum of parameters to support conclusions.\\nThis thesis focuses on applying machine learning algorithms to calculate water-use\\nefficiency and predict the effects of different the biostimulants and how that effect is\\nconditioned by the hydric regime; with the ultimate goal of analyzing and optimizing\\nwater consumption in maize plants.\\nIn parallel with this process, an interactive user interface was developed to streamline\\nthe company’s access to models and automation workflows. This interface accepts specific\\ntypes of input and, in addition to applying the models to calculate water use efficiency, it\\nautomates processes based on received data. As a result, it functions not only as proof of\\na concept, but also as an industrial tool that will be used internally by the company.


Instituição
FACULDADE DE CIÊNCIAS E TECNOLOGIA DA UNIVERSIDADE NOVA DE LISBOA

Identificadores da Publicação