Evaluation of different water absorption bands, indices and multivariate models for water-deficit stress monitoring in rice using visible-near infrared spectroscopy

Das, Bappa; Sahoo, Rabi Narayan; Pargal, Sourabh; Krishna, Gopal; Verma, Rakesh Kumar; Chinnusamy, Viswanathan; Sehgal, Vinay Kumar; Gupta, Vinod Kumar

doi:10.1016/j.saa.2020.119104

Cited by 35 publications

(24 citation statements)

References 57 publications

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“…In accordance with the literature [26,28,36,48,56,67], the wavelengths most correlated with SWP belong to the SWIR domain, in particular, to the minimum ("SWIR e" and "SWIR j") that corresponds to water absorption, or to the maximum ("SWIR c", "SWIR d", "SWIR g", "SWIR i") reflectance in this range. Those particular spectral signatures (1259 nm in "SWIR c", 1264 nm in "SWIR c", and 1334 nm in "SWIR d") indeed correspond to the vibrations of the O-H stretch in water molecules [28].…”

Section: Spectral Domain and VI Sensitivitysupporting

confidence: 87%

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Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

Laroche-Pinel

Albughdadi²,

Duthoit³

et al. 2021

Remote Sensing

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The main challenge encountered by Mediterranean winegrowers is water management. Indeed, with climate change, drought events are becoming more intense each year, dragging the yield down. Moreover, the quality of the vineyards is affected and the level of alcohol increases. Remote sensing data are a potential solution to measure water status in vineyards. However, important questions are still open such as which spectral, spatial, and temporal scales are adapted to achieve the latter. This study aims at using hyperspectral measurements to investigate the spectral scale adapted to measure their water status. The final objective is to find out whether it would be possible to monitor the vine water status with the spectral bands available in multispectral satellites such as Sentinel-2. Four Mediterranean vine plots with three grape varieties and different water status management systems are considered for the analysis. Results show the main significant domains related to vine water status (Short Wave Infrared, Near Infrared, and Red-Edge) and the best vegetation indices that combine these domains. These results give some promising perspectives to monitor vine water status.

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Section: Spectral Domain and VI Sensitivitysupporting

confidence: 87%

“…-In the case of NDSI, a feature data set is constructed using two-wavelength combinations ( [46][47][48]) in following the formula:…”

Section: Methodsmentioning

confidence: 99%

Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

Laroche-Pinel

Albughdadi²,

Duthoit³

et al. 2021

Remote Sensing

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show abstract

“…The SWIR domains are known to be related to water concentration in plants [16][17][18][19] as they correspond to the vibrations of the O-H stretch in water molecules [17]. The NIR domains also react to water status as they can be affected by leaf morphology and structure [20].…”

Section: Introductionmentioning

confidence: 99%

Towards Vine Water Status Monitoring on a Large Scale Using Sentinel-2 Images

Laroche-Pinel

Duthoit²,

Albughdadi³

et al. 2021

Remote Sensing

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Wine growing needs to adapt to confront climate change. In fact, the lack of water becomes more and more important in many regions. Whereas vineyards have been located in dry areas for decades, so they need special resilient varieties and/or a sufficient water supply at key development stages in case of severe drought. With climate change and the decrease of water availability, some vineyard regions face difficulties because of unsuitable variety, wrong vine management or due to the limited water access. Decision support tools are therefore required to optimize water use or to adapt agronomic practices. This study aimed at monitoring vine water status at a large scale with Sentinel-2 images. The goal was to provide a solution that would give spatialized and temporal information throughout the season on the water status of the vines. For this purpose, thirty six plots were monitored in total over three years (2018, 2019 and 2020). Vine water status was measured with stem water potential in field measurements from pea size to ripening stage. Simultaneously Sentinel-2 images were downloaded and processed to extract band reflectance values and compute vegetation indices. In our study, we tested five supervised regression machine learning algorithms to find possible relationships between stem water potential and data acquired from Sentinel-2 images (bands reflectance values and vegetation indices). Regression model using Red, NIR, Red-Edge and SWIR bands gave promising result to predict stem water potential (R2=0.40, RMSE=0.26).

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“…Plants showed a rapid decrease of the NIR signal after about drought stress and recover signal after re-watering. Das et al [ 37 ] identified water absorption bands using partial least squares regression (PLSR) model from NIR image. NIR can provide an effective means for real-times and non-invasive monitoring of leaf water content in crop plants.…”

Section: Htp Methodsmentioning

confidence: 99%

High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

Kim

Lee

Hong

et al. 2021

IJMS

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Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

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Evaluation of different water absorption bands, indices and multivariate models for water-deficit stress monitoring in rice using visible-near infrared spectroscopy

Cited by 35 publications

References 57 publications

Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

Towards Vine Water Status Monitoring on a Large Scale Using Sentinel-2 Images

High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

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