Sandra M. Guzmán

Sandra M. Guzmán

University of Florida

H-index: 10

North America-United States

About Sandra M. Guzmán

Sandra M. Guzmán, With an exceptional h-index of 10 and a recent h-index of 8 (since 2020), a distinguished researcher at University of Florida, specializes in the field of Machine learning, irrigation, hydrology, water management, crop modeling.

His recent articles reflect a diverse array of research interests and contributions to the field:

Adaptive and predictive decision support system for irrigation scheduling: An approach integrating humans in the control loop

How to Identify If Your Time Series Inputs Are Adequate for AI Applications: Assessing Minimum Data Requirements in Environmental Analyses: AE594, 12/2023

2023–2024 Florida Citrus Production Guide: Irrigation Management of Citrus Trees: CPG ch. 14, CG093/CPG12, rev. 5/2023

Perspective: Phosphorus monitoring must be rooted in sustainability frameworks spanning material scale to human scale

Grapefruit Root and Rhizosphere Responses to Varying Planting Densities, Fertilizer Concentrations and Application Methods

Baseflow estimation based on a self-adaptive non-linear reservoir algorithm in a rainy watershed of eastern China

Effect of fabric mulch ground covers on lemon trees rhizosphere microbiome in Florida flatwood soils

Preguntas comunes cuando se usan sensores de humedad en el suelo para cítricos y otros árboles frutales: AE583/AE583, 2/2023

Sandra M. Guzmán Information

University

Position

Assistant Professor

Citations(all)

454

Citations(since 2020)

403

Cited By

175

hIndex(all)

10

hIndex(since 2020)

8

i10Index(all)

10

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Sandra M. Guzmán Skills & Research Interests

Machine learning

irrigation

hydrology

water management

crop modeling

Top articles of Sandra M. Guzmán

Adaptive and predictive decision support system for irrigation scheduling: An approach integrating humans in the control loop

Computers and Electronics in Agriculture

2024/2/1

How to Identify If Your Time Series Inputs Are Adequate for AI Applications: Assessing Minimum Data Requirements in Environmental Analyses: AE594, 12/2023

EDIS

2024/1/11

2023–2024 Florida Citrus Production Guide: Irrigation Management of Citrus Trees: CPG ch. 14, CG093/CPG12, rev. 5/2023

EDIS

2023/8/16

Perspective: Phosphorus monitoring must be rooted in sustainability frameworks spanning material scale to human scale

Water Research X

2023/5/1

Grapefruit Root and Rhizosphere Responses to Varying Planting Densities, Fertilizer Concentrations and Application Methods

Plants

2023/4/15

Baseflow estimation based on a self-adaptive non-linear reservoir algorithm in a rainy watershed of eastern China

Journal of Environmental Management

2023/4/15

Effect of fabric mulch ground covers on lemon trees rhizosphere microbiome in Florida flatwood soils

Frontiers in Soil Science

2023/2/22

Preguntas comunes cuando se usan sensores de humedad en el suelo para cítricos y otros árboles frutales: AE583/AE583, 2/2023

EDIS

2023/2/9

Evapotranspiration Rates of Three Sweet Corn Cultivars under Different Irrigation Levels

HortTechnology

2023/2/1

Enhancing Smart Irrigation With Centralized Data

EDIS

2023

Irrigation Scheduling for Young Pongamia (Millettia pinnata (L.) Panigrahi) Trees: AE590, 11/2023

EDIS

2023/12/5

Forming the future of agrohydrology

Earth's Future

2023/12

Mapping Root Zone Soil Moisture for Irrigation Management by Artificial Intelligence Using Data from Both Satellite Soil Moisture Products and In-Situ Observations

AGU Fall Meeting Abstracts

2022/12

Your Farm as a Water Storage System: Steps to Establish an Agreement with the Water Management Districts: AE577/AE577, 9/2022

EDIS

2022/9/16

2022–2023 Florida Citrus Production Guide: Irrigation Management of Citrus Trees: CPG ch. 15, CG093/CPG12, rev. 4/2022

EDIS

2022/8/16

Potential Impacts of Improper Irrigation System Design: AE73/AE027, rev. 8/2022

EDIS

2022/8/15

Identification of the Meteorological Variables Influencing Evapotranspiration Variability Over Florida

Environmental Modeling & Assessment

2022/8

Are we ahead on the game? Technologies and solutions to support citrus management decisions

EDIS

2022/7/11

Artificial Intelligence (AI) for Crop Yield Forecasting: AE571/AE571, 4/2022

Edis

2022/4/27

Citrus Section

Proc. Fla. State Hort. Soc

2022

See List of Professors in Sandra M. Guzmán University(University of Florida)

Co-Authors

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