Monitoring of water stress in peanut using multispectral indices derived from canopy hyperspectral

Tingting Chen, Leidi Wang, Haixia Qi, Xinyue Wang, Ruier Zeng, Bingyu Zhu, Yubin Lan, Lei Zhang

Abstract


Abstract: Drought stress was a severe environmental constraint to peanut growth all over the world, and became more and more serious with the global warming context.  So, timely and accurate monitoring of water status in peanut is important for farmer to irrigate promptly and acquire higher yield.  Our study was conducted to select the most appropriate multispectral indices for water stress monitoring of two peanut cultivars based on canopy spectral reflectance in visible-infrared (VIS) and near infrared (NIR) region.  The physiological parameters chlorophyll fluorescence (Fv/Fm), chlorophyll content (SPAD) and leaf relative water content (LRWC) decreased as the drought stress level increased and showed significant relationships between each other.  Decreases on the canopy spectral reflectance were observed in both cultivars, especially in NIR region (720-900 nm) as the leaf water loss was intensified.  Six indices (RDVI, TCARI, OSAVI, TCARI/OSAVI, MTVI, and EVI-2) showed higher polynomial relationship (R2>R20.05, n=93) with the physiology parameters (Fv/Fm, SPAD and LRWC, respectively) based on the pooled data, which included the two cultivars, three drought stress treatments and the replications.  After testing the above six sensitive indices under different drought stress, MTVI was the only multispectral indices, which showed significant curvilinear relationships with the three parameters under different drought stress conditions and might be a useful tool in the development of automatic systems.  Our results may provide a non-destructive, simple and real-time method for water status monitoring in peanut production that can assist farmers in timely irrigation.

Keywords: Arachis hypogaea L., drought, canopy reflectance, monitor

DOI: 10.33440/j.ijpaa.20200303.104

 

Citation: Chen T T, Wang L D, Qi H X, Wang X Y, Zeng R E, Zhu B Y, Lan Y B, Zhang L.  Monitoring of water stress in peanut using multispectral indices derived from canopy hyperspectral.  Int J Precis Agric Aviat, 2020; 3(3): 50–58.


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