Proceedings :: International Society of Precision Agriculture

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DE BRITO FILHO , A.L

Yatskul, A

Gyanwali, P

Gorthi, S

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Authors

Andrade da Silva, A

Moura Oliveira, T.C

Sales, E

de Souza Silva, R.H

Luns, S

Costa Souza, J

DE BRITO FILHO , A.L

Pereira da Silva, R.P

Perussi, E.M

Loganathan Girija, D

Gorthi, S

Bhalekar, D

Khot, L.R

Keller, M

Urbina Salazar, D

Yatskul, A

Pinet, F

Dujany, A

Ugarte, C

Carrillo Montoya, K

De Guzman, C

Burgos, N

Ramos, L

Gyanwali, P

Uzoetoh, U

McCarty, D

Reddy Kalluri, R

Mason, D

Topics

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Precision Horticulture and Specialty Crop Management

Type

Oral

Poster

Year

2026

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Filter results4 paper(s) found.
1. Can Management Zones Be Useful in Guiding Mechanized Peanut Harvesting? Mechanized peanut harvesting presents challenges due to the crop’s indeterminate growth habit, which results in non-uniform maturation across the field; the ideal harvest point is reached when the maturity index exceeds 0.7. Consequently, analyzing the spatial variability of maturation is essential for identifying homogeneous areas and guiding harvest at the optimal time. In this context, Management Zones (MZs), as a Precision Agriculture tool, enable the subdivision of fields into more... A. Andrade Da Silva, T.C. Moura Oliveira, E. Sales, S. Luns, E.M. Perussi, R.H. De Souza Silva, S. Luns, R.P. Silva, J. , A.L. De Brito Filho , R.P. Silva
2. Enhanced Deep Learning Framework Driven Grape Berry Temperature Estimation and 72-h Forecasting for Precision Heat Stress Management The increasing frequency of extreme summer heat events poses a significant threat to grape production in the Pacific Northwest (PNW), U.S., and globally. Elevated temperatures can induce sunburn, accelerate organic acid degradation, and cause anthocyanin loss, ultimately reducing berry quality. Berry surface temperature (BST), which can exceed ambient air temperature by up to 15 °C, is a primary indicator of heat stress severity. However, BST dynamics are governed by complex, nonlinear thermodynamic...
3. Integrating Tractor-tire-tool Adjustable Parameters and UAV‑derived Soil Indices to Predict Fuel Consumption and Crop Emergence in Spring Barley Sowing The optimization of energy use and agronomic performance in agricultural operations has become a central challenge in modern agriculture. To achieve this dual objective, farmers could adjust the machinery settings of a tractor-tire-tool system to ensure efficient resource utilization while maintaining optimal agronomic outcomes. This study was conducted as a part of the AgrEnOp project, which aims to predict fuel consumption (l/ha) and crop emergence (plant/m2) based on operator-adjustable... D. Urbina Salazar, A. Yatskul, F. Pinet, A. Dujany, C. Ugarte Download paper
4. 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 results4 paper(s) found.

1. Can Management Zones Be Useful in Guiding Mechanized Peanut Harvesting?

Mechanized peanut harvesting presents challenges due to the crop’s indeterminate growth habit, which results in non-uniform maturation across the field; the ideal harvest point is reached when the maturity index exceeds 0.7. Consequently, analyzing the spatial variability of maturation is essential for identifying homogeneous areas and guiding harvest at the optimal time. In this context, Management Zones (MZs), as a Precision Agriculture tool, enable the subdivision of fields into more... A. Andrade Da Silva, T.C. Moura Oliveira, E. Sales, S. Luns, E.M. Perussi, R.H. De Souza Silva, S. Luns, R.P. Silva, J. , A.L. De Brito Filho , R.P. Silva

2. Enhanced Deep Learning Framework Driven Grape Berry Temperature Estimation and 72-h Forecasting for Precision Heat Stress Management

The increasing frequency of extreme summer heat events poses a significant threat to grape production in the Pacific Northwest (PNW), U.S., and globally. Elevated temperatures can induce sunburn, accelerate organic acid degradation, and cause anthocyanin loss, ultimately reducing berry quality. Berry surface temperature (BST), which can exceed ambient air temperature by up to 15 °C, is a primary indicator of heat stress severity. However, BST dynamics are governed by complex, nonlinear thermodynamic...

3. Integrating Tractor-tire-tool Adjustable Parameters and UAV‑derived Soil Indices to Predict Fuel Consumption and Crop Emergence in Spring Barley Sowing

The optimization of energy use and agronomic performance in agricultural operations has become a central challenge in modern agriculture. To achieve this dual objective, farmers could adjust the machinery settings of a tractor-tire-tool system to ensure efficient resource utilization while maintaining optimal agronomic outcomes. This study was conducted as a part of the AgrEnOp project, which aims to predict fuel consumption (l/ha) and crop emergence (plant/m2) based on operator-adjustable... D. Urbina Salazar, A. Yatskul, F. Pinet, A. Dujany, C. Ugarte

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4. 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...