Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Guimarães Moreira, S

Gyanwali, P

» Add more authors

Add filter to result:

Authors

Costa Barboza, T

Batista da Silva, W

Guimarães Moreira, S

Godinho Silva, S

Lacerda, L

Felipe dos Santos, A

Carrillo Montoya, K

De Guzman, C

Burgos, N

Ramos, L

Gyanwali, P

Uzoetoh, U

McCarty, D

Reddy Kalluri, R

Mason, D

Topics

Remote and Proximal Sensing of Soils and Crops

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Type

Poster

Oral

Year

2026

Home » Authors » Results

Authors

Filter results2 paper(s) found.
1. Assessment of Machine Learning Models for Leaf Chlorophyll Estimation Using Visible-Range Reflectance Chlorophyll content plays a central role in the photosynthetic process directly influencing plant growth, development and yield. However, plant pigment dynamics arise from complex metabolic interactions that are not adequately captured by conventional statistical approaches or traditional laboratory analyses, which are time-consuming and impractical for large-scale field applications. In this context, remote sensing offers a non-destructive alternative for assessing foliar pigments in agricultural... T. Costa Barboza, W. Batista Da Silva, S. Guimarães Moreira, S. Godinho Silva, L. Lacerda, A. Felipe Dos Santos Download paper
2. Temporal NDRE Dynamics from UAS Imagery to Characterize Rice Drought Response Characterizing drought resilience in rice remains challenging under increasing climate variability. Drought tolerance is a complex and dynamic trait that is difficult to quantify using traditional field phenotyping approaches, particularly when responses vary with time. High-throughput temporal phenotyping with unmanned aircraft systems (UAS) enables monitoring of canopy reflectance dynamics associated with water stress across the growing season. This study evaluated whether temporal...

Filter results2 paper(s) found.

1. Assessment of Machine Learning Models for Leaf Chlorophyll Estimation Using Visible-Range Reflectance

Chlorophyll content plays a central role in the photosynthetic process directly influencing plant growth, development and yield. However, plant pigment dynamics arise from complex metabolic interactions that are not adequately captured by conventional statistical approaches or traditional laboratory analyses, which are time-consuming and impractical for large-scale field applications. In this context, remote sensing offers a non-destructive alternative for assessing foliar pigments in agricultural... T. Costa Barboza, W. Batista Da Silva, S. Guimarães Moreira, S. Godinho Silva, L. Lacerda, A. Felipe Dos Santos

Download paper

2. Temporal NDRE Dynamics from UAS Imagery to Characterize Rice Drought Response

Characterizing drought resilience in rice remains challenging under increasing climate variability. Drought tolerance is a complex and dynamic trait that is difficult to quantify using traditional field phenotyping approaches, particularly when responses vary with time. High-throughput temporal phenotyping with unmanned aircraft systems (UAS) enables monitoring of canopy reflectance dynamics associated with water stress across the growing season. This study evaluated whether temporal...