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Title:
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Combined use of low-cost remote sensing techniques and δ13C to assess bread wheat grain yield under different water and nitrogen conditions
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Author:
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Yousfi, Salima; Gracia-Romero, Adrian; Kellas, Nassim; Kaddour, Mohamed; Chadouli, Ahmed; Karrou, Mohamed; Araus Ortega, José Luis; Serret Molins, M. Dolors
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Notes:
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Vegetation indices and canopy temperature are the most usual remote sensing approaches
to assess cereal performance. Understanding the relationships of these parameters and yield may
help design more e cient strategies to monitor crop performance. We present an evaluation of
vegetation indices (derived from RGB images and multispectral data) and water status traits (through
the canopy temperature, stomatal conductance and carbon isotopic composition) measured during
the reproductive stage for genotype phenotyping in a study of four wheat genotypes growing under
di erent water and nitrogen regimes in north Algeria. Di erences among the cultivars were reported
through the vegetation indices, but not with the water status traits. Both approximations correlated
significantly with grain yield (GY), reporting stronger correlations under support irrigation and
N-fertilization than the rainfed or the no N-fertilization conditions. For N-fertilized trials (irrigated or
rainfed) water status parameters were the main factors predicting relative GY performance, while in
the absence of N-fertilization, the green canopy area (assessed through GGA) was the main factor
negatively correlated with GY. Regression models for GY estimation were generated using data from
three consecutive growing seasons. The results highlighted the usefulness of vegetation indices
derived from RGB images predicting GY.
This study was supported in part by the European project ACLIMAS (EuropeAid/131046/C/ACT/Multi) and the Spanish MINECO project grant No. AGL2016-76527-R). |
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Subject(s):
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-Wheat
-Canopy temperature depression
-Grain yield |
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Rights:
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cc-by (c) Yousfi et al., 2019
https://creativecommons.org/licenses/by/4.0/
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Document type:
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Article
Article - Published version |
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Published by:
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MDPI
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Share:
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