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231225s2019 xx |||||o 00| ||eng c |
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|a 10.1016/j.plantsci.2018.10.022
|2 doi
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|a pubmed25n0987.xml
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|a (DE-627)NLM296240443
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|a (NLM)31003615
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|a (PII)S0168-9452(17)31020-8
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Hassan, Muhammad Adeel
|e verfasserin
|4 aut
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| 245 |
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|a A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform
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|c 2019
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 13.05.2019
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|a Date Revised 09.01.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Copyright © 2018 Elsevier B.V. All rights reserved.
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|a Wheat improvement programs require rapid assessment of large numbers of individual plots across multiple environments. Vegetation indices (VIs) that are mainly associated with yield and yield-related physiological traits, and rapid evaluation of canopy normalized difference vegetation index (NDVI) can assist in-season selection. Multi-spectral imagery using unmanned aerial vehicles (UAV) can readily assess the VIs traits at various crop growth stages. Thirty-two wheat cultivars and breeding lines grown in limited irrigation and full irrigation treatments were investigated to monitor NDVI across the growth cycle using a Sequoia sensor mounted on a UAV. Significant correlations ranging from R2 = 0.38 to 0.90 were observed between NDVI detected from UAV and Greenseeker (GS) during stem elongation (SE) to late grain gilling (LGF) across the treatments. UAV-NDVI also had high heritabilities at SE (h2 = 0.91), flowering (F)(h2 = 0.95), EGF (h2 = 0.79) and mid grain filling (MGF) (h2 = 0.71) under the full irrigation treatment, and at booting (B) (h2 = 0.89), EGF (h2 = 0.75) in the limited irrigation treatment. UAV-NDVI explained significant variation in grain yield (GY) at EGF (R2 = 0.86), MGF (R2 = 0.83) and LGF (R2 = 0.89) stages, and results were consistent with GS-NDVI. Higher correlations between UAV-NDVI and GY were observed under full irrigation at three different grain-filling stages (R2 = 0.40, 0.49 and 0.45) than the limited irrigation treatment (R2 = 0.08, 0.12 and 0.14) and GY was calculated to be 24.4% lower under limited irrigation conditions. Pearson correlations between UAV-NDVI and GY were also low ranging from r = 0.29 to 0.37 during grain-filling under limited irrigation but higher than GS-NDVI data. A similar pattern was observed for normalized difference red-edge (NDRE) and normalized green red difference index (NGRDI) when correlated with GY. Fresh biomass estimated at late flowering stage had significant correlations of r = 0.30 to 0.51 with UAV-NDVI at EGF. Some genotypes Nongda 211, Nongda 5181, Zhongmai 175 and Zhongmai 12 were identified as high yielding genotypes using NDVI during grain-filling. In conclusion, a multispectral sensor mounted on a UAV is a reliable high-throughput platform for NDVI measurement to predict biomass and GY and grain-filling stage seems the best period for selection
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|a Journal Article
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|a High throughput phenotyping
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|a Multi-spectral imaging
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|a Normalized difference vegetation index
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| 650 |
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|a Unmanned aerial vehicle
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| 700 |
1 |
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|a Yang, Mengjiao
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Rasheed, Awais
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Yang, Guijun
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Reynolds, Matthew
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Xia, Xianchun
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Xiao, Yonggui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a He, Zhonghu
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Plant science : an international journal of experimental plant biology
|d 1985
|g 282(2019) vom: 01. Mai, Seite 95-103
|w (DE-627)NLM098174193
|x 1873-2259
|7 nnns
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| 773 |
1 |
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|g volume:282
|g year:2019
|g day:01
|g month:05
|g pages:95-103
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| 856 |
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|u http://dx.doi.org/10.1016/j.plantsci.2018.10.022
|3 Volltext
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