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Deep learning for soybean monitoring and management. Author(s): BARBEDO, J. G. A. This review characterizes the current state of the art of deep learning applied to soybean crops, detailing the main advancements achieved so far and, more importantly, providing an in-depth analysis... ... Repository: BDPA Publication year: 2023
A review of deep learning algorithms for computer vision systems in livestock. Author(s): OLIVEIRA, D. A. B.; PEREIRA, L. G. R.; BRESOLIN, T.; FERREIRA, R. E. P.; DREA, J. R. R. In livestock operations, systematically monitoring animal body weight, bio-metric body measurements, animal behavior, feed bunk, and other difficult-to-measure phenotypes is manually unfeasible due to... ... Repository: BDPA Publication year: 2021
An analytical model of the relationship knowledge, learning, innovation and sustainability. Author(s): CABRAL, J. E. de O.; COSTA, M. da P. B. Repository: BDPA Publication year: 2010
Detecting and classifying pests in crops using proximal images and machine learning: a review. Author(s): BARBEDO, J. G. A. Abstract: Pest management is among the most important activities in a farm. Monitoring all different species visually may not be effective, especially in large properties. Accordingly, considerable re... ... Repository: BDPA Publication year: 2020
Utilização de machine learning para classificação de plantas saudáveis e plantas submetidas ao estresse. Author(s): VIANA, J. V. S.; DANTAS, L. P.; PAULA, O. R. de; BARRETO, B. B.; MILORI, D. M. B. P. A integração de tecnologias na agricultura tem se tornado cada vez mais comum, trazendo consigo uma série de benefícios, desde o aumento da produtividade até contribuições para a sustentabilidade. Uma... ... Repository: BDPA Publication year: 2023
Identificação de marcadores SNPs para teor de amilose em arroz pela estratégia de Machine Learning. Author(s): SARTORI, D. E. L.; RODRIGUES, A. H. A.; CERRI, R.; BASSINELLO, P. Z.; NARCISO, M. G.; BRONDANI, C.; VIANELLO, R. P. O objetivo deste estudo foi identificar, por meio da estratégia Machine Learning, marcadores SNPs relacionados com TA para uso na seleção assistida por marcadores no programa de melhoramento genético... ... Repository: BDPA Publication year: 2018
Big earth observation data and machine learning for mapping crop-livestock integrated system in Brazil. Author(s): KUCHLER, P. C.; SIMÕES, M.; BEGUE, A.; FERRAZ, R. P. D. The adoption of crop-livestock (iCL) integrated systems has been pointed out as an important strategy for increasing production based on sustainable intensification of land use in Brazil. Mapping and... ... Repository: BDPA Publication year: 2021
Machine learning prediction of multiple anthelmintic resistance and gastrointestinal nematode control in sheep flocks. Author(s): NICIURA, S. C. M.; SANCHES, G. M. The high prevalence of Haemonchus contortus and its anthelmintic resistance have affected sheep production worldwide. Machine learning approaches are able to investigate the complex relationships amon... ... Repository: BDPA Publication year: 2024
Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms. Author(s): SOUSA, I. C. de; NASCIMENTO, M.; SILVA, G. N.; NASCIMENTO, A. C. C.; CRUZ, C. D.; SILVA, F. F. e; ALMEIDA, D. P. de; PESTANA, K. N.; AZEVEDO, C. F.; ZAMBOLIM, L.; CAIXETA, E. T. Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the p... ... Repository: BDPA Publication year: 2021
Decision Support in Attribute Selection with Machine Learning Approach. Author(s): ARBEX, W. A.; SILVA, F. F. e; SILVA, M. V. G. B.; BORGES, C. C. H.; OLIVEIRA, F. C. de; VARONA, L.; VERNEQUE, R. da S. Repository: BDPA Publication year: 2014

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