FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386220384> ?p ?o ?g. }

• W4386220384 endingPage "4222" @default.
• W4386220384 startingPage "4222" @default.
• W4386220384 abstract "Non-photochemical quenching (NPQ) is an indicator of crop stress. Until now, only a limited number of studies have focused on how to estimate NPQ using remote sensing technology. The main challenge is the complicated regulatory mechanism of NPQ. NPQ can be divided into energy-dependent (qE) and non-energy-dependent (non-qE) quenching. The contribution of these two components varies with environmental factors, such as light intensity and stress level due to the different response mechanisms. This study aims to explore the feasibility of estimating NPQ using photosynthesis-related vegetation parameters available from remote sensing by considering the two components of NPQ. We concurrently measured passive vegetation reflectance spectra by spectrometer, as well as active fluorescence parameters by pulse-amplitude modulated (PAM) of rice (Oryza sativa) leaves. Subsequently, we explored the ability of the selected vegetation parameters (including the photochemical reflectance index (PRI), inverted red-edge chlorophyll index (IRECI), near-infrared reflectance of vegetation (NIRv), and fluorescence quantum yield (ΦF)) to estimate NPQ. Based on different combinations of these remote sensing parameters, empirical models were established to estimate NPQ using the linear regression method. Experimental analysis shows that the contribution of qE and non-qE components varied under different illumination conditions. Under high illumination, the NPQ was attributed primarily to the qE component, while under low illumination, it was equally attributed to the qE and non-qE components. Among all tested parameters, ΦF was sensitive to the qE component variation, while IRECI and NIRv were sensitive to the non-qE component variation. Under high illumination, integrating ΦF in the regression model captured NPQ variations well (R2 > 0.74). Under low illumination, ΦF, IRECI, and NIRv explained 24%, 62%, and 65% of the variation in NPQ, respectively, while coupling IRECI or NIRv with ΦF considerably improved the accuracy of NPQ estimation (R2 > 0.9). For all the samples under both low and high illumination, the combination of ΦF with at least one of the other parameters (including IRECI, NIRv and PAR) offers a more versatile and reliable approach to estimating NPQ than using any single parameter alone. The findings of this study contribute to the further development of remote sensing methods for NPQ estimation at the canopy scale in the future." @default.
• W4386220384 created "2023-08-29" @default.
• W4386220384 creator A5024144516 @default.
• W4386220384 creator A5033750172 @default.
• W4386220384 creator A5034692909 @default.
• W4386220384 creator A5050552097 @default.
• W4386220384 creator A5064739851 @default.
• W4386220384 creator A5064792356 @default.
• W4386220384 creator A5069998992 @default.
• W4386220384 date "2023-08-28" @default.
• W4386220384 modified "2023-09-30" @default.
• W4386220384 title "Combining Chlorophyll Fluorescence and Vegetation Reflectance Indices to Estimate Non-Photochemical Quenching (NPQ) of Rice at the Leaf Scale" @default.
• W4386220384 cites W1964462201 @default.
• W4386220384 cites W1975892234 @default.
• W4386220384 cites W1977096467 @default.
• W4386220384 cites W1981718931 @default.
• W4386220384 cites W1985870430 @default.
• W4386220384 cites W1992244454 @default.
• W4386220384 cites W2001739950 @default.
• W4386220384 cites W2005348740 @default.
• W4386220384 cites W2023519189 @default.
• W4386220384 cites W2030233869 @default.
• W4386220384 cites W2046857879 @default.
• W4386220384 cites W2057833130 @default.
• W4386220384 cites W2058312673 @default.
• W4386220384 cites W2059384562 @default.
• W4386220384 cites W2063623478 @default.
• W4386220384 cites W2069267285 @default.
• W4386220384 cites W2078143541 @default.
• W4386220384 cites W2089898136 @default.
• W4386220384 cites W2109542058 @default.
• W4386220384 cites W2115492173 @default.
• W4386220384 cites W2115663229 @default.
• W4386220384 cites W2115781687 @default.
• W4386220384 cites W2142283539 @default.
• W4386220384 cites W2145230623 @default.
• W4386220384 cites W2147766323 @default.
• W4386220384 cites W2160056290 @default.
• W4386220384 cites W2161324059 @default.
• W4386220384 cites W2163004831 @default.
• W4386220384 cites W2220179545 @default.
• W4386220384 cites W2282184259 @default.
• W4386220384 cites W2322888409 @default.
• W4386220384 cites W2412604357 @default.
• W4386220384 cites W2482145818 @default.
• W4386220384 cites W2571189887 @default.
• W4386220384 cites W2603028033 @default.
• W4386220384 cites W2740761456 @default.
• W4386220384 cites W2741490225 @default.
• W4386220384 cites W2768035654 @default.
• W4386220384 cites W2790197537 @default.
• W4386220384 cites W2930080528 @default.
• W4386220384 cites W2950734190 @default.
• W4386220384 cites W2956697767 @default.
• W4386220384 cites W2966594090 @default.
• W4386220384 cites W2975855924 @default.
• W4386220384 cites W2981360590 @default.
• W4386220384 cites W2988314595 @default.
• W4386220384 cites W3003379506 @default.
• W4386220384 cites W3004804411 @default.
• W4386220384 cites W3005444277 @default.
• W4386220384 cites W3018268432 @default.
• W4386220384 cites W3026932151 @default.
• W4386220384 cites W3110494317 @default.
• W4386220384 cites W3174889302 @default.
• W4386220384 cites W3196303752 @default.
• W4386220384 cites W3199773189 @default.
• W4386220384 cites W4206047302 @default.
• W4386220384 cites W4283215110 @default.
• W4386220384 cites W4292672185 @default.
• W4386220384 cites W574088521 @default.
• W4386220384 doi "https://doi.org/10.3390/rs15174222" @default.
• W4386220384 hasPublicationYear "2023" @default.
• W4386220384 type Work @default.
• W4386220384 citedByCount "0" @default.
• W4386220384 crossrefType "journal-article" @default.
• W4386220384 hasAuthorship W4386220384A5024144516 @default.
• W4386220384 hasAuthorship W4386220384A5033750172 @default.
• W4386220384 hasAuthorship W4386220384A5034692909 @default.
• W4386220384 hasAuthorship W4386220384A5050552097 @default.
• W4386220384 hasAuthorship W4386220384A5064739851 @default.
• W4386220384 hasAuthorship W4386220384A5064792356 @default.
• W4386220384 hasAuthorship W4386220384A5069998992 @default.
• W4386220384 hasBestOaLocation W43862203841 @default.
• W4386220384 hasConcept C115278976 @default.
• W4386220384 hasConcept C120665830 @default.
• W4386220384 hasConcept C121332964 @default.
• W4386220384 hasConcept C121745418 @default.
• W4386220384 hasConcept C127313418 @default.
• W4386220384 hasConcept C183688256 @default.
• W4386220384 hasConcept C185592680 @default.
• W4386220384 hasConcept C192562407 @default.
• W4386220384 hasConcept C24630173 @default.
• W4386220384 hasConcept C2777476368 @default.
• W4386220384 hasConcept C39432304 @default.
• W4386220384 hasConcept C55493867 @default.
• W4386220384 hasConcept C62649853 @default.
• W4386220384 hasConcept C91881484 @default.

• next