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Nagy Z, Balogh J, Petrás D, Fóti S, MacArthur A, Pintér K. Detecting drought stress occurrence using synergies between Sun induced fluorescence and vegetation surface temperature spatial records. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:168053. [PMID: 37898200 DOI: 10.1016/j.scitotenv.2023.168053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/20/2023] [Accepted: 10/21/2023] [Indexed: 10/30/2023]
Abstract
Drought stress occurrence and recovery from drought can be detected using a single spatial set of simultaneous observations of SIF and canopy temperature records. Temporal and spatial responses to drought and heat stresses by plant stands of a drought-adapted diverse grassland ecosystem were studied using sun induced fluorescence (SIF,O2A and O2B bands) and further ecophysiological (canopy temperature (Tsurf), spatially modeled evapotranspiration, vegetation reflectance spectra) variables collected along spatial sampling grids while also utilizing eddy covariance measured carbon dioxide (net ecosystem exchange: NEE, gross primary production: GPP) and water flux (evapotranspiration: ET) data. The grids were of 0.5 and 5 ha spatial extents and contained 78 sampling points. Data were collected in four spatial sampling campaigns, two under drought (early summer) and another two during and after recovery (midsummer) at both spatial resolutions. Small values of spatial SIF_A averages (around 0.5 mW m-2 nm-1 sr-1) under strong early summer drought increased (to around 2 mW m-2 nm-1 sr-1) due recovery upon rain arrivals, showing high (R2: 0.8-0.88) positive temporal correlations to eddy covariance measured carbon (GPP, NEE) and water (ET) fluxes. Spatial averages of LAI, vegetation indices (NDVI, NIRv) and modeled ET followed similar temporal patterns. While SIF was depressed by drought, it showed higher values in high canopy temperature vegetation patches than in vegetation patches with lower Tsurf. The spatial pattern of higher SIF in higher Tsurf patches was persistent (2 weeks) under drought. The positive SIF_A-Tsurf spatial correlation turned into negative/not significant after recovery of the grassland from the drought, while hot summer weather persisted. It is proposed that, by using a single set of simultaneously measured spatial SIF and Tsurf data it is possible to infer whether the studied vegetation is under drought (and heat) stress while it could not be decided on the base of SIF data alone. Evaluation of the slope of the above relationship seems therefore beneficial before e.g. starting the (stress) classification procedure based on SIF.
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Affiliation(s)
- Zoltán Nagy
- Department of Plant Physiology and Plant Ecology, Agronomy Institute, Hungarian University for Life and Agriculture, 2100 Gödöllő, Páter 1., Hungary; HUN-REN-MATE Agroecology Research Group, 2100 Gödöllő, Páter 1., Hungary.
| | - János Balogh
- Department of Plant Physiology and Plant Ecology, Agronomy Institute, Hungarian University for Life and Agriculture, 2100 Gödöllő, Páter 1., Hungary
| | - Dóra Petrás
- Department of Plant Physiology and Plant Ecology, Agronomy Institute, Hungarian University for Life and Agriculture, 2100 Gödöllő, Páter 1., Hungary
| | - Szilvia Fóti
- Department of Plant Physiology and Plant Ecology, Agronomy Institute, Hungarian University for Life and Agriculture, 2100 Gödöllő, Páter 1., Hungary; HUN-REN-MATE Agroecology Research Group, 2100 Gödöllő, Páter 1., Hungary
| | | | - Krisztina Pintér
- HUN-REN-MATE Agroecology Research Group, 2100 Gödöllő, Páter 1., Hungary
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Chen R, Liu X, Chen J, Du S, Liu L. Solar-induced chlorophyll fluorescence imperfectly tracks the temperature response of photosynthesis in winter wheat. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:7596-7610. [PMID: 36173362 DOI: 10.1093/jxb/erac388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Solar-induced fluorescence (SIF) is a promising proxy for photosynthesis, but it is unclear whether it performs well in tracking the gross primary productivity (GPP) under different environmental conditions. In this study, we investigated the dynamics of the two parameters from October 2020 to June 2021 in field-grown winter wheat (Triticum aestivum) and found that the ability of SIF to track GPP was weakened at low temperatures. Accounting for the coupling of light and temperature at a seasonal scale, we found that SIF yield showed a lower temperature sensitivity and had a lower but broader optimal temperature range compared with light-use efficiency (LUE), although both SIF yield and LUE decreased in low-temperature conditions. The discrepancy between the temperature responses of SIF yield and GPP caused an increase in the ratio of SIF/GPP in winter, which indicated the variation in the relationship between them during this period. The results of our study highlight the impact of low temperature on the relationship between SIF and GPP and show the necessity of reconsidering the dynamics of energy distribution inside plants under changing environments.
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Affiliation(s)
- Ruonan Chen
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xinjie Liu
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Jidai Chen
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shanshan Du
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Liangyun Liu
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
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Guo C, Liu L, Sun H, Wang N, Zhang K, Zhang Y, Zhu J, Li A, Bai Z, Liu X, Dong H, Li C. Predicting F v /F m and evaluating cotton drought tolerance using hyperspectral and 1D-CNN. FRONTIERS IN PLANT SCIENCE 2022; 13:1007150. [PMID: 36330250 PMCID: PMC9623111 DOI: 10.3389/fpls.2022.1007150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 09/06/2022] [Indexed: 06/16/2023]
Abstract
The chlorophyll fluorescence parameter Fv/Fm is significant in abiotic plant stress. Current acquisition methods must deal with the dark adaptation of plants, which cannot achieve rapid, real-time, and high-throughput measurements. However, increased inputs on different genotypes based on hyperspectral model recognition verified its capabilities of handling large and variable samples. Fv/Fm is a drought tolerance index reflecting the best drought tolerant cotton genotype. Therefore, Fv/Fm hyperspectral prediction of different cotton varieties, and drought tolerance evaluation, are worth exploring. In this study, 80 cotton varieties were studied. The hyperspectral cotton data were obtained during the flowering, boll setting, and boll opening stages under normal and drought stress conditions. Next, One-dimensional convolutional neural networks (1D-CNN), Categorical Boosting (CatBoost), Light Gradient Boosting Machines (LightBGM), eXtreme Gradient Boosting (XGBoost), Decision Trees (DT), Random Forests (RF), Gradient elevation decision trees (GBDT), Adaptive Boosting (AdaBoost), Extra Trees (ET), and K-Nearest Neighbors (KNN) were modeled with F v /F m. The Savitzky-Golay + 1D-CNN model had the best robustness and accuracy (RMSE = 0.016, MAE = 0.009, MAPE = 0.011). In addition, the F v /F m prediction drought tolerance coefficient and the manually measured drought tolerance coefficient were similar. Therefore, cotton varieties with different drought tolerance degrees can be monitored using hyperspectral full band technology to establish a 1D-CNN model. This technique is non-destructive, fast and accurate in assessing the drought status of cotton, which promotes smart-scale agriculture.
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Affiliation(s)
- Congcong Guo
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Liantao Liu
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Hongchun Sun
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Nan Wang
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
- Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Ke Zhang
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Yongjiang Zhang
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Jijie Zhu
- Cotton Research Center, Shandong Key Lab for Cotton Culture and Physiology, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Anchang Li
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Zhiying Bai
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Xiaoqing Liu
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Hezhong Dong
- College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, Hebei, China
| | - Cundong Li
- State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding, China
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Abstract
Chlorophylls provide the basis for photosynthesis and thereby most life on Earth. Besides their involvement in primary charge separation in the reaction center, they serve as light-harvesting and light-sensing pigments, they also have additional functions, e.g., in inter-system electron transfer. Chlorophylls also have a wealth of applications in basic science, medicine, as colorants and, possibly, in optoelectronics. Considering that there has been more than 200 years of chlorophyll research, one would think that all has been said on these pigments. However, the opposite is true: ongoing research evidenced in this Special Issue brings together current work on chlorophylls and on their carotenoid counterparts. These introductory notes give a very brief and in part personal account of the history of chlorophyll research and applications, before concluding with a snapshot of this year's publications.
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Affiliation(s)
- Hugo Scheer
- Bereich Systematik, Biodiversität und Evolution der Pflanzen, Universität München, Menzinger Str. 67, 80638 München, Germany
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Kohzuma K, Sonoike K, Hikosaka K. Imaging, screening and remote sensing of photosynthetic activity and stress responses. JOURNAL OF PLANT RESEARCH 2021; 134:649-651. [PMID: 34152519 DOI: 10.1007/s10265-021-01324-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Affiliation(s)
- Kaori Kohzuma
- Graduate School of Life Sciences, Tohoku University, Sendai, Miyagi, 980-8578, Japan.
| | - Kintake Sonoike
- Faculty of Education and Integrated Arts and Sciences, Waseda University, Shinjuku-ku, Tokyo, 162-8480, Japan
| | - Kouki Hikosaka
- Graduate School of Life Sciences, Tohoku University, Sendai, Miyagi, 980-8578, Japan
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Nakashima N, Kato T, Morozumi T, Tsujimoto K, Akitsu TK, Nasahara KN, Murayama S, Muraoka H, Noda HM. Area-ratio Fraunhofer line depth (aFLD) method approach to estimate solar-induced chlorophyll fluorescence in low spectral resolution spectra in a cool-temperate deciduous broadleaf forest. JOURNAL OF PLANT RESEARCH 2021; 134:713-728. [PMID: 34159485 DOI: 10.1007/s10265-021-01322-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 06/09/2021] [Indexed: 06/13/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) emissions were estimated by the "area-ratio Fraunhofer line depth (aFLD) method", a new retrieval methodology in spectra from a low spectral resolution (SR) spectroradiometer (MS-700: full width half maximum (FWHM) of 10 nm and spectral sampling interval of 3.3 nm), assisted with a scaling to reference SIF detected from high SR spectrum. The sparse pixels of a spectrum of low SR misses detecting the minimum of the O2A absorption band around at 760 nm, which makes the SIF detection by conventional FLD methods lose accuracy considerably. To overcome this, the aFLD method uses the definite integral of spectra over a wide interval between 750 and 780 nm. The integration of the spectrum is insusceptible to the change in shape of the depression curve, leading to higher accuracy of the aFLD method. Daily SIF, calculated by the aFLD method using the spectra obtained with MS-700, was scaled to reference daily SIF calculated by the spectral fitting method using the spectra obtained from August to December 2019 with an ultrafine SR spectroradiometer (QE Pro, FWHM = 0.24 nm). As a result, SIF calculated from MS-700 spectra by aFLD method was strongly correlated with the reference SIF from QE Pro spectra (r2 = 0.81) and was successfully scaled. Then, the scaled 11-year SIF from MS-700 at a deciduous broadleaf forest showed the correlation with GPP at multiple time steps: daily, monthly, and yearly, consistently during 2008-2018. The comparison of aFLD-derived SIF with the global Orbiting Carbon Observatory-2 (OCO-2) SIF data set (GOSIF) showed high correlation on monthly values during 2008-2017 (r2 = 0.85). The combining approach of the aFLD method with a scaling to reference SIF successfully detected long-term canopy SIF emissions, which has great potential to provide essential information on ecosystem-level photosynthesis.
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Affiliation(s)
- Naohisa Nakashima
- Department of Agro-Eenvironmental Science, Obihiro University of Agriculture and Veterinary Medicine, 11 block, Nishi 2 sen, Inada-cho, Obihiro, Hokkaido, 080-8555, Japan.
- Research Faculty of Agriculture, Hokkaido University, Kita 9, Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-8589, Japan.
| | - Tomomichi Kato
- Research Faculty of Agriculture, Hokkaido University, Kita 9, Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-8589, Japan.
- Global Center for Food, Land, and Water Resources, Research Faculty of Agriculture, Hokkaido University, Sapporo, Hokkaido, 060-8589, Japan.
| | - Tomoki Morozumi
- Research Faculty of Agriculture, Hokkaido University, Kita 9, Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-8589, Japan
| | - Katsuto Tsujimoto
- Graduate School of Life Sciences, Tohoku University, Aoba, Sendai, Miyagi, 980-8578, Japan
| | - Tomoko Kawaguchi Akitsu
- Faculty of Life and Environmental Sciences, University of Tsukuba, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Kenlo Nishida Nasahara
- Faculty of Life and Environmental Sciences, University of Tsukuba, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Shohei Murayama
- Environmental Management Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, 305-8569, Japan
| | - Hiroyuki Muraoka
- River Basin Research Center, Gifu University, Yanagido, Gifu, 501-1193, Japan
| | - Hibiki M Noda
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki, 305-8506, Japan
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Cruz JA, Avenson TJ. Photosynthesis: a multiscopic view. JOURNAL OF PLANT RESEARCH 2021; 134:665-682. [PMID: 34170422 DOI: 10.1007/s10265-021-01321-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 06/11/2021] [Indexed: 06/13/2023]
Abstract
A recurring analogy for photosynthesis research is the fable of the blind men and the elephant. Photosynthesis has many complex working parts, which has driven the need to study each of them individually, with an inherent understanding that a more complete picture will require systematic integration of these views. However, unlike the blind men, who are limited to using their hands, researchers have developed over the past decades a repertoire of methods for studying these components, many of which capitalize on unique features intrinsic to each. More recent concerns about food security and clean, renewable energy have increased support for applied photosynthesis research, with the idea of either improving photosynthetic performance as a desired trait in select species or using photosynthetic measurements as a phenotyping tool in breeding efforts or for high precision crop management. In this review, we spotlight the migration of approaches for studying photosynthesis from the laboratory into field environments, highlight some recent advances and speculate on areas where further development would be fruitful, with an eye towards how applied photosynthesis research can have impacts at local and global scales.
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Affiliation(s)
- Jeffrey A Cruz
- Plant Research Laboratories, Michigan State University, 612 Wilson Road, MI, S-206, Lansing, USA.
- Department of Biochemistry and Molecular Biology, Michigan State University, Lansing, MI, USA.
| | - Thomas J Avenson
- Department of Plant Sciences, University of Cambridge, CB2 9EW, Cambridge, UK
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