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Low-cost paper-based sensors modified with curcumin for the detection of ochratoxin a in beverages. Author(s): MATTOSO, L. H. C.; CORREA, D. S. Ochratoxin A (OTA) is a mycotoxin that can contaminate food and is produced by fungal species such as Aspergillus carbonarius, Penicillium verrucosum, Aspergillus ochraceus, and Aspergillus niger [1].... ... Repository: BDPA Publication year: 2024
Detection and decay rates of prey and prey symbionts in the gut of a predator through metagenomics. Author(s): PAULA, D. P.; LINARD, B.; ANDOW, D. A.; SUJII, E. R.; PIRES, C. S. S.; VOGLER, A. P. DNA methods are useful to identify ingested prey items from the gut of predators, but reliable detection is hampered by low amounts of degraded DNA. PCR-based methods can retrieve minute amounts of st... ... Repository: BDPA Publication year: 2015
InsectCV: a system for insect detection in the lab from trap images. Author(s): LAU, D. Advances in artificial intelligence, computer vision, and high-performance computing have enabled the creation of efficient solutions to monitor pests and identify plant diseases. In this context, we... ... Repository: BDPA Publication year: 2021
YOLO performance analysis for real-time detection of soybean pests. Author(s): BARBEDO, J. G. A. In this work, we evaluated the You Only Look Once (YOLO) architecture for real-time detection of soybean pests. Repository: BDPA Publication year: 2024
A methodology for detection and localization of fruits in apples orchards from aerial images. Author(s): SANTOS, T. T.; GEBLER, L. Abstract. Computer vision methods based on convolutional neural networks (CNNs) have presented promising results on image-based fruit detection at ground-level for different crops. However, the integr... ... Repository: BDPA Publication year: 2021
Integration of landsat TM and SPOT HRG Images for vegetation change detection in the Brazilian Amazon. Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of... ... Repository: BDPA Publication year: 2008
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
Simultaneous detection of Nosema spp., Ascosphaera apis and Paenibacillus larvae in honey bee products. Author(s): MARTINS, M. F. Abstract Honey bees are responsible for pollinating many native and cultivated plant species. These insects can be affected by many pathogens, including fungi and bacteria, both of which can form spor... ... Repository: BDPA Publication year: 2016
Cantilever nanobiosensor functionalized with tyrosinase for detection of estrone and (BETA)-estradiol in water. Author(s): CEZARO, A. M.; RIGO, A. A.; MARTINAZZO, J.; MUENCHEN, D. K.; MANZOLI, A.; CORREA, D. S.; STEFFENS, J.; STEFFENS, C. Repository: BDPA Publication year: 2019
From detection to protection: the role of optical sensors, robots,and arti?cial intelligence in modern plant disease management. Author(s): BARBEDO, J. G. A. In the past decade, there has been a recognized need for innovative methods to monitor and manage plant diseases, aiming to meet the precision demandsof modern agriculture. Over the last 15 years, sig... ... Repository: BDPA Publication year: 2024

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