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Araus, J.L.

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Araus
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J.L.
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Araus, J.L.
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AGROVOC: PHENOTYPES × Keyword: Phenotyping Platforms ×

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    Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
    (BioMed Central, 2015) Zaman-Allah, M.; Vergara Diaz, O.; Araus, J.L.; Tarekegne, A.T.; Magorokosho, C.; Zarco-Tejada, P.J.; Hornero, A.; Hernández-Alba, A.; Das, B.; Craufurd, P.; Olsen, M.; Prasanna, B.M.; Cairns, J.E.
    Background: Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement. Results: We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield. Conclusion: This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.
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