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The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management./
Author:	Ihuoma, Samuel Onyekachi.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	193 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-05, Section: B.
Contained By:	Dissertations Abstracts International82-05B.
Subject:	Plant sciences. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28267081
ISBN:	9798691248504

The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management.
Ihuoma, Samuel Onyekachi.

The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 193 p.

Source: Dissertations Abstracts International, Volume: 82-05, Section: B.

Thesis (Ph.D.)--McGill University (Canada), 2020.

This item must not be sold to any third party vendors.

Early identification and prediction of plant abiotic stress are required to ensure sustainable agricultural management. Traditional plant and soil-based methods of estimating plant stress are destructive, labour intensive, and time-consuming. These methods often do not represent the heterogeneity of soil and crop parameters at large spatial scales. Spectral reflectance data provide near real-time and non-destructive estimates of plant stress, and account for spatial and temporal variability of crops and soil. This research focused on the use of spectral reflectance data to estimate plant water and nitrogen requirements to improve field management of high-value vegetable crops.The first study in this thesis investigated the potential of crop reflectance indices for detecting water stress, in order to improve the irrigation of greenhouse-grown vegetable crops. Two widely grown vegetable crops (tomato plants: Solanum Lycopersicum L. and bell pepper: Capsicum annuum L.) were chosen due to their canopy architecture and sensitivity to water stress. Spectral data and plant stress parameters (stomatal conductance, leaf temperature, relative water content, and crop yield) were concurrently acquired from plants subjected to different irrigation treatments (100, 80, 60, 40, and 20% of plant available water). Various reflectance indices were obtained from the spectral data. The relationships between crop reflectance indices and water stress indicators were statistically examined to evaluate the most useful indices for detecting water stress. The results indicate that the photochemical reflectance indices (PRI) centered at 553 nm (PRI553) was the most useful index for detecting water stress in bell pepper plants, while the PRI centered at 550 nm (PRI550) was suitable for tomato crops. These results contrast the findings of previous studies, which recommended the use of PRI570 for monitoring water stress in most field crops.Given that the spectral vegetation indices for monitoring plant water status are affected by microclimatic conditions, it was hypothesized that the findings of the greenhouse studies will not be applicable to open field conditions. The second study in this thesis assessed the use of reflectance indices for monitoring water and nitrogen stresses in field-grown tomato crops. Spectral reflectance data and plant stress indicators (leaf temperature, relative water content, crop yield, and leaf chlorophyll content) were measured from tomato plants subjected to three irrigation water treatments (100, 70, and 30% of field capacity) and three nitrogen treatments (100, 70, and 30% of crop nutrient requirement). The results showed that the PRI550 and water index (R900/R970) were the most sensitive indices for distinguishing crop water stress, while renormalized difference vegetation index and Transformed Chlorophyll Absorption in Reflectance Index had the best correlation with nitrogen stress indicators. Normalized PRI was the most sensitive index for detecting the combined effect of water and nitrogen stress.The last study in this thesis compared the suitability of multispectral images acquired from unmanned aerial vehicles, PlanetScope, and Sentinel-2 satellite platforms for estimating crop coefficient and evapotranspiration. Sentinel-2 data were used to predict crop evapotranspiration (ETc) and the results were compared with ETc estimated from the FAO 56 Penman-Monteith module of the AquaCrop model. ETc data were coupled with time domain reflectometry soil moisture measurements to estimate irrigation water requirements (IWR). The estimated seasonal IWR was less than the actual amount of water applied by the grower, indicating that the field was over irrigated by 17% and 20% in the 2017 and 2018 growing seasons, respectively. This thesis concludes that leaf spectral data are advantageous over conventional methods of crop stress assessment for improving irrigation water management.

ISBN: 9798691248504Subjects--Topical Terms:

3173832
Plant sciences.
Subjects--Index Terms:

Plant abiotic stress identification

The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management.
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100 1 $a Ihuoma, Samuel Onyekachi. $3 3559895
245 1 4 $a The Use of Spectral Reflectance Data to Assess Plant Stress and Improve Irrigation Water Management.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 193 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-05, Section: B.
500 $a Advisor: Madramootoo, Chandra A.
502 $a Thesis (Ph.D.)--McGill University (Canada), 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Early identification and prediction of plant abiotic stress are required to ensure sustainable agricultural management. Traditional plant and soil-based methods of estimating plant stress are destructive, labour intensive, and time-consuming. These methods often do not represent the heterogeneity of soil and crop parameters at large spatial scales. Spectral reflectance data provide near real-time and non-destructive estimates of plant stress, and account for spatial and temporal variability of crops and soil. This research focused on the use of spectral reflectance data to estimate plant water and nitrogen requirements to improve field management of high-value vegetable crops.The first study in this thesis investigated the potential of crop reflectance indices for detecting water stress, in order to improve the irrigation of greenhouse-grown vegetable crops. Two widely grown vegetable crops (tomato plants: Solanum Lycopersicum L. and bell pepper: Capsicum annuum L.) were chosen due to their canopy architecture and sensitivity to water stress. Spectral data and plant stress parameters (stomatal conductance, leaf temperature, relative water content, and crop yield) were concurrently acquired from plants subjected to different irrigation treatments (100, 80, 60, 40, and 20% of plant available water). Various reflectance indices were obtained from the spectral data. The relationships between crop reflectance indices and water stress indicators were statistically examined to evaluate the most useful indices for detecting water stress. The results indicate that the photochemical reflectance indices (PRI) centered at 553 nm (PRI553) was the most useful index for detecting water stress in bell pepper plants, while the PRI centered at 550 nm (PRI550) was suitable for tomato crops. These results contrast the findings of previous studies, which recommended the use of PRI570 for monitoring water stress in most field crops.Given that the spectral vegetation indices for monitoring plant water status are affected by microclimatic conditions, it was hypothesized that the findings of the greenhouse studies will not be applicable to open field conditions. The second study in this thesis assessed the use of reflectance indices for monitoring water and nitrogen stresses in field-grown tomato crops. Spectral reflectance data and plant stress indicators (leaf temperature, relative water content, crop yield, and leaf chlorophyll content) were measured from tomato plants subjected to three irrigation water treatments (100, 70, and 30% of field capacity) and three nitrogen treatments (100, 70, and 30% of crop nutrient requirement). The results showed that the PRI550 and water index (R900/R970) were the most sensitive indices for distinguishing crop water stress, while renormalized difference vegetation index and Transformed Chlorophyll Absorption in Reflectance Index had the best correlation with nitrogen stress indicators. Normalized PRI was the most sensitive index for detecting the combined effect of water and nitrogen stress.The last study in this thesis compared the suitability of multispectral images acquired from unmanned aerial vehicles, PlanetScope, and Sentinel-2 satellite platforms for estimating crop coefficient and evapotranspiration. Sentinel-2 data were used to predict crop evapotranspiration (ETc) and the results were compared with ETc estimated from the FAO 56 Penman-Monteith module of the AquaCrop model. ETc data were coupled with time domain reflectometry soil moisture measurements to estimate irrigation water requirements (IWR). The estimated seasonal IWR was less than the actual amount of water applied by the grower, indicating that the field was over irrigated by 17% and 20% in the 2017 and 2018 growing seasons, respectively. This thesis concludes that leaf spectral data are advantageous over conventional methods of crop stress assessment for improving irrigation water management.
520 $a L'identification precoce et la prevision du stress abiotique des cultures s'averent necessaires a une gestion agricole durable. Fondees sur l'etat des plantes et du sol, les methodes d'antan pour estimer le stress subi par une culture s'avererent destructrices et intenses en temps et travail, en plus de ne pas tenir compte de l'heterogeneite des cultures et du sol. Les donnees de reflectance spectrale fournissent des estimations non destructives et en temps quasi-reel du stress subi par les plantes, tout en tenant compte de la variabilite spatiotemporelle des cultures et du sol. Visant a ameliorer la gestion des besoins en eau et en azote des cultures maraicheres a l'echelle du champ, par l'emploi des donnees de reflectance spectrale, une premiere etude, axee sur l'amelioration de l'irrigation des cultures maraicheres en serre, s'attarda a l'etude du potentiel des indices de reflectance des cultures a detecter le stress hydrique. Deux cultures maraicheres (tomate - Solanum lycopersicum L. et poivron - Capsicum annuum L.) furent choisies pour l'architecture de leur canopee et leur sensibilite au stress hydrique. Le recueil simultane aupres de plantes soumises a differents regimes d'irrigation (100, 80, 60, 40 et 20% de l'eau disponible aux plantes), des donnees spectrales et parametres de stress (conductance stomatique, temperature des feuilles, teneur en eau relative, rendement des cultures), permit de calculer divers indices de reflectance et d'evaluer statistiquement leurs relations aux indicateurs de stress hydrique, afin d'identifier les indices les plus utiles a la detection du stress hydrique. En contraste aux resultats d'etudes precedentes recommandant l'utilisation du PRI570 pour surveiller le stress hydrique, dna sla presente etude les indices de reflectance photochimique (PRI) centres a 553 nm (PRI553) se revelerent les plus utiles a la detection du stress hydrique des poivrons, tandis qu'un PRI centre a 550 nm (PRI550) fut le plus utile pour les tomates.Les indices de vegetation spectrale utilises pour surveiller the stress hydrique des plantes etant affectes par les conditions microclimatiques, nous emimes l'hypothese que les resultats d'une culture en serre n'aurait pas leur application en plein champ. La deuxieme partie de l'etude evalua donc l'utilisation d'indices de reflectance pour surveiller les stress hydriques et azotes des tomates cultivees en plein champ. La reflectance spectrale et les indicateurs de stress des plantes (temperature des feuilles, teneur en eau relative, rendement et teneur en chlorophylle des feuilles) furent mesures pour des plants de tomates soumis a trois traitements d'irrigation (100, 70 et 30% de la capacite au champ) combines de maniere factorielle a trois niveaux de fertilisation azotee (100, 70 et 30% des besoins). L'indice PRI550 et l'indice d'eau (R900/R970) permirent la meilleure discrimination entre niveaux de stress hydrique, tandis que l'indice de vegetation par difference renormalisee et l'indice d'absorption de chlorophylle transformee en reflectance furent le plus fortement correles aux indicateurs de stress azote. Le PRI normalise s'avera l'indice le plus sensible a l'effet combine du stress hydrique et azote.La derniere etude presentee dans cette these compara l'aptitude des images multispectrales acquises a partir de vehicules aeriens sans pilote, de PlanetScope et de plateformes satellites Sentinel-2 pour estimer le facteur culture et l'evapotranspiration. Ces dernieres donnees ont permi a predire l'evapotranspiration des cultures (ETc) et de comparer ces resultats a l'ETc estime par la methode Penman-Monteith. Les donnees ETc furent couplees a des mesures d'humidite du sol acquises par reflectometrie temporelle afin d'estimer les besoins en eau d'irrigation (IWR). Pour ameliorer la gestion de l''irrigation, les donnees spectrales foliaires offrent une meilleure evaluation du stress des cultures que les methodes conventionnelles.
590 $a School code: 0781.
650 4 $a Plant sciences. $3 3173832
650 4 $a Bioengineering. $3 657580
653 $a Plant abiotic stress identification
653 $a Greenhouse-grown vegetable crops
653 $a Plant water status
653 $a Crop evapotranspiration
690 $a 0202
690 $a 0479
710 2 $a McGill University (Canada). $3 1018122
773 0 $t Dissertations Abstracts International $g 82-05B.
790 $a 0781
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28267081