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Genome and environment based prediction models and methods of complex traits incorporating genotype × environment interaction. Genomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includ... ... Repository: BDPA Publication year: 2022
Predictive models to estimate carbon stocks in agroforestry systems. Abstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which co... ... Repository: BDPA Publication year: 2021
Confronting model predictions of carbon fluxes with measurements of Amazon forests subjected to experimental drought. Considerable uncertainty surrounds the fate of Amazon rainforests in response to climate change. Here, carbon (C) flux predictions of five terrestrial biosphere models (Community Land Model version 3.... ... Repository: BDPA Publication year: 2013
Evaluation of three models for predicting Venturia inaequalis ascospore release in Southern Brazil. Ascospores of Venturia inaequalis constitute the principal source of primary inoculum for epidemics of apple black spot (scab). Mathematical models that describe ascospore release have been developed... ... Repository: BDPA Publication year: 2013
Genome prediction accuracy of common bean via Bayesian models. We aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits ?stay-green? (SG), plant architecture (PA), grain aspect (GA) and g... ... Repository: BDPA Publication year: 2018
Models and applications for risk assessment and prediction of Asian soybean rust epidemics. Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas repr... ... Repository: BDPA Publication year: 2006
Models for predicting biometric variables in cowpea using multispectral aerial images. Models based on vegetation indices (VI) from digital aerial images are promising for predicting biometric variables in agricultural crops. The objective of this study was to generate prediction models... ... Repository: BDPA Publication year: 2023
Prediction of geographic distribution and ecological niche modeling of açaí palm trees in the Amazon. Euterpe precatoria Mart. (açaí-do-amazonas) and Euterpe oleracea Mart. (açaí-do-pará) are palm trees of socioeconomic importance to Brazil, and fruit demand has increased due to its nutritional charac... ... Repository: BDPA Publication year: 2024

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