Using satellite data to optimize wheat yield and quality under climate change

Shilo Shiff, Itamar M. Lensky, David J. Bonfil

Research output: Contribution to journalArticlepeer-review

14 Scopus citations
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Abstract

Climatic conditions during the grain-filling period are a major factor affecting wheat grain yield and quality. Wheat in many semi-arid and arid areas faces high-temperature stress during this period. Remote sensing can be used to monitor both crops and environmental temperature. The objective of this study was to develop a tool to optimize field management (cultivar and sowing time). Analysis of 155 cultivar experiments (from 10 growth seasons) representing different environmental conditions revealed the required degree-days for each Israeli spring wheat cultivar to reach heading (from emergence). We developed a Google Earth Engine (GEE) app to analyze time series of gap-filled 1 km MODIS land surface temperature (LSTcont). By changing the cultivar and/or emergence date in the GEE app, the farmer can “expose” each wheat field to different climatic conditions during the grain-filling period, thereafter enabling him to choose the best cultivar to be sown in the field with the right timing. This approach is expected to reduce the number of fields that suffer from heat stress during the grain-filling period. The app can be also used to assess the effects of different global warming scenarios and to plan adaptation strategies in other regions too.

Original languageEnglish
Article number2049
JournalRemote Sensing
Volume13
Issue number11
DOIs
StatePublished - 1 Jun 2021

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Funding

Funding: This research was funded by the Chief Scientist of the Israeli Ministry of Agriculture and Rural Development, grant number #20-10-0066, and the Israeli Ministry of Science, Technology and Space, grant number 3-14675.

FundersFunder number
Ministry of Science, Technology and Space3-14675
Ministry of Agriculture and Rural Development20-10-0066

    Keywords

    • Climate change
    • Google Earth Engine
    • LST
    • MODIS
    • Optimize
    • Wheat
    • Yield

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