Jeffrey W. White

ORCID: 0000-0002-2051-4645
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About
Contact & Profiles
Research Areas
  • Climate change impacts on agriculture
  • Crop Yield and Soil Fertility
  • Genetics and Plant Breeding
  • Plant pathogens and resistance mechanisms
  • Plant responses to elevated CO2
  • Plant Water Relations and Carbon Dynamics
  • Atmospheric and Environmental Gas Dynamics
  • Greenhouse Technology and Climate Control
  • Wheat and Barley Genetics and Pathology
  • Soybean genetics and cultivation
  • Soil Carbon and Nitrogen Dynamics
  • Remote Sensing in Agriculture
  • Methane Hydrates and Related Phenomena
  • Geology and Paleoclimatology Research
  • Agronomic Practices and Intercropping Systems
  • Cryospheric studies and observations
  • Legume Nitrogen Fixing Symbiosis
  • Genetic Mapping and Diversity in Plants and Animals
  • Isotope Analysis in Ecology
  • Atmospheric Ozone and Climate
  • Polar Research and Ecology
  • Research in Cotton Cultivation
  • Plant and animal studies
  • Rice Cultivation and Yield Improvement
  • Atmospheric chemistry and aerosols

University of Florida
1994-2024

Center for Cancer Research
2023

National Center for Complementary and Integrative Health
2023

U.S. Arid Land Agricultural Research Center
2012-2022

Agricultural Research Service
2010-2020

United States Department of Agriculture
1969-2017

Natural Resources Institute Finland
2017

University of Rhode Island
2016

Humboldt State University
2006-2014

Maricopa Medical Center
2010

Crop models of crop growth are increasingly used to quantify the impact global changes due climate or management. Therefore, accuracy simulation results is a major concern. Studies with ensembles can give valuable information about model and uncertainty, but such studies difficult organize have only recently begun. We report on largest ensemble study date, 27 wheat tested in four contrasting locations for their simulating multiple yield variables. The relative error averaged over was 24-38%...

10.1111/gcb.12768 article EN Global Change Biology 2014-10-20

Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In this light, we developed a novel system for phenotyping dynamic in the field. System performance was evaluated on 25 Pima cotton (Gossypium barbadense L.) cultivars grown 2011 at Maricopa, Arizona. Field-grown plants were irrigated well watered water-limited conditions, with measurements taken different times 3 days July August. The carried four sets of sensors measure...

10.1071/fp13126 article EN Functional Plant Biology 2013-09-05

Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop development at season-end, final yield. Their ability integrate effects genetics, environment management have led applications ranging from understanding gene function predicting potential impacts climate change. The history is reviewed briefly, their level mechanistic detail for assimilation respiration, leaf-to-canopy radiation-use efficiency discussed. improved...

10.1111/pce.12119 article EN Plant Cell & Environment 2013-04-18

SUMMARY Root growth of two drought tolerant and sensitive bean ( Phaseolus vulgaris L.) lines was compared at locations in Colombia differing primarily soil conditions. At Palmira, roots reached a depth 1.3 m, while only 0.8 m. These differences were associated with seed yield, crop growth, canopy temperature moisture extraction. Under acid conditions Quili-chao, yields supposedly genotypes similar to those the lines, root all four restricted less than Drought avoidance through greater...

10.1017/s0014479700016756 article EN Experimental Agriculture 1989-04-01

A rising global population and demand for protein-rich diets are increasing pressure to maximize agricultural productivity. Rising atmospheric [CO(2)] is altering temperature precipitation patterns, which challenges While provides a unique opportunity increase the productivity of C(3) crops, average yield stimulation observed date well below potential gains. Thus, there room improving However, only fraction available germplasm crops has been tested CO(2) responsiveness. Yield complex...

10.1111/j.1365-3040.2008.01841.x article EN Plant Cell & Environment 2008-06-03

Possible future increases in atmospheric temperature may threaten wheat ( Triticum aestivum L.) production and food security. The purpose of this research is to determine the response growth supplemental heating seasonal air from an unusually wide range planting dates. A field study was conducted at Maricopa, AZ, where planted September May over a 2‐yr period for total 12 Supplemental provided 6 dates using infrared heaters placed above crop which increased canopy by 1.3°C during day 2.7°C...

10.2134/agronj2011.0212 article EN Agronomy Journal 2012-01-01

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used measure Normalized Difference Vegetation Index (NDVI) in panel 248 elite durum wheat (Triticum turgidum L. ssp. Desf.) accessions at different growth stages water regimes. Our suggest increased ability...

10.3389/fpls.2018.00893 article EN cc-by Frontiers in Plant Science 2018-06-26

Decision support tools for agriculture often require meteorological data as inputs, but availability and quality are problematic. Difficulties arise with daily solar radiation (SRAD) because the instruments electronic integrators, accurate sensors expensive, calibration standards seldom available. NASA's Prediction of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov ) project estimates SRAD based on satellite observations atmospheric parameters obtained from assimilation models....

10.2134/agronj2011.0038 article EN Agronomy Journal 2011-07-01

Abstract The application of high-throughput plant phenotyping (HTPP) to continuously study populations under relevant growing conditions creates the possibility more efficiently dissect genetic basis dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets sensors simultaneously measure canopy temperature, reflectance, and height on cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. evaluation trials were conducted...

10.1534/g3.115.023515 article EN cc-by G3 Genes Genomes Genetics 2016-04-01
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