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Journal Article 2019-05

Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar.

Autor: Moya, I. Loayza, H. Llanos, M. Quiróz, R. Ounis, A. Goulas, Y.

LEDFLEX is a micro-lidar dedicated to the measurement of vegetation fluorescence. The light source consists of 4 blue Light-Emitting Diodes (LED) to illuminate part of the canopy in order to average the spatial variability of small crops. The fluorescence emitted in response to a 5-μs width pulse...

Enlace original: https://cgspace.cgiar.org/handle/10568/102367

Investigación en Agricultura

CANOPY

CHLOROPHYLL

STRESS

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Moya, I. , Loayza, H. , Llanos, M. , Quiróz, R. , Ounis, A. , Goulas, Y. , [Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar.] , Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar.

Journal Article 2020-01

Development of an open-source thermal image processing software for improving irrigation management in potato crops (Solanum tuberosum L.).

Autor: Cucho-Padin, G. Rinza, J. Ninanya, J. Loayza, H. Quiróz, R. Ramírez, D.A.

Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processo...

Enlace original: https://cgspace.cgiar.org/handle/10568/106636

Investigación en Agricultura

IMAGE PROCESSING

CANOPY

CROP WATER USE

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Cucho-Padin, G. , Rinza, J. , Ninanya, J. , Loayza, H. , Quiróz, R. , Ramírez, D.A. , [Development of an open-source thermal image processing software for improving irrigation management in potato crops (Solanum tuberosum L.).] , Development of an open-source thermal image processing software for improving irrigation management in potato crops (Solanum tuberosum L.).

Journal Article 2017

Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?

Autor: Quiróz, R. Loayza, H. Barreda, Carolina Gavilán, C. Posadas, A. Ramírez, D.

Data acquisition for parameterization is one of the most important limitations for the use of potato crop growth models. Non destructive techniques such as remote sensing for gathering required data could circumvent this limitation. Our goal was to analyze the effects of incorporating ground-base...

Enlace original: https://cgspace.cgiar.org/handle/10568/78288

Investigación en Agricultura

CANOPY

REMOTE SENSING

CROPPING SYSTEMS

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Quiróz, R. , Loayza, H. , Barreda, Carolina , Gavilán, C. , Posadas, A. , Ramírez, D. , [Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?] , Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?

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Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar.

Development of an open-source thermal image processing software for improving irrigation management in potato crops (Solanum tuberosum L.).

Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?