Photosynthetica 2024, 62(4):372-380 | DOI: 10.32615/ps.2024.040

Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content

J. LIU1, Y. WANG2, X.M. LIN3, Z.C. XUE2, F.R. ZENG4
1 College of Teacher Education, Hebei Minzu Normal University, 067000 Chengde, Hebei, China
2 School of Resources and Environmental Sciences, Innovative Research Center for Soil and Plant Nutrition in Mountain Areas of Northern Hebei, Hebei Minzu Normal University, 067000 Chengde, Hebei, China
3 Laboratory Management Center, Hebei Minzu Normal University, 067000 Chengde, Hebei, China
4 Chengde Bijiashan Ecological Agriculture Technology Development Co., Ltd., 067000 Chengde, Hebei, China

Application of hyperspectral reflectance technology to track changes in photosynthetic activity in Atractylodes chinensis (A. chinensis) remains underexplored. This study aimed to investigate the relationship between hyperspectral reflectance and photosynthetic activity in the leaves of A. chinensis in response to a decrease in soil water content. Results demonstrated that the reflectance in both the visible light and near-infrared bands increased in conjunction with reduced soil water content. The derived vegetable indices of photochemical reflection index (PRI) and the pigment-specific simple ratio of chlorophyll b (PSSRb) gradually decreased. In contrast, the normalized difference in water index (NWI) and water index (WI) increased. Moreover, significant correlations were observed between PRI, PSSRb, WI, and NWI and photosynthetic activity indices, namely photosynthetic rate and total performance index. Consequently, hyperspectral reflection represents a productive approach for evaluating the influence of water deficit on photosynthetic activity in A. chinensis leaves.

Additional key words: Atractylodes chinensis; hyperspectral reflectance; photosynthesis; vegetable indices; water stress.

Received: June 11, 2024; Revised: October 18, 2024; Accepted: November 12, 2024; Prepublished online: December 5, 2024; Published: December 19, 2024  Show citation

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LIU, J., WANG, Y., LIN, X.M., XUE, Z.C., & ZENG, F.R. (2024). Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content. Photosynthetica, 62(4), 372-380. doi: 10.32615/ps.2024.040
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    References

    1. Asgari A., Hooshmand A., Broumand-Nasab S., Zivdar S.: Potential application of spectral indices for olive water status assessment in (semi-)arid regions: A case study in Khuzestan Province, Iran. - Plant Direct 7: e494, 2023. Go to original source...
    2. Blackburn G.A.: Quantifying chlorophylls and caroteniods at leaf and canopy scales: An evaluation of some hyperspectral approaches. - Remote Sens. Environ. 66: 273-285, 1998. Go to original source...
    3. Borges C.V., Minatel I.O., Gomez-Gomez H.A., Lima G.P.P.: Medicinal plants: Influence of environmental factors on the content of secondary metabolites. - In: Ghorbanpour M., Varma A. (ed.): Medicinal Plants and Environmental Challenges. Pp. 259-277. Springer, Cham 2017. Go to original source...
    4. Buchaillot M.L., Soba D., Shu T. et al.: Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models. - Planta 255: 93, 2022. Go to original source...
    5. Burnett A.C., Serbin S.P., Davidson K.J. et al.: Detection of the metabolic response to drought stress using hyperspectral reflectance. - J. Exp. Bot. 72: 6474-6489, 2021. Go to original source...
    6. Ejaz I., Li W., Naseer M.A. et al.: Detection of combined frost and drought stress in wheat using hyperspectral and chlorophyll fluorescence imaging. - Environ. Technol. Innov. 30: 103051, 2023. Go to original source...
    7. Estrada F., Flexas J., Araus J.L. et al.: Exploring plant responses to abiotic stress by contrasting spectral signature changes. - Front. Plant Sci. 13: 1026323, 2023. Go to original source...
    8. Flynn K.C., Witt T.W., Baath G.S. et al.: Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth. - Smart Agric. Technol. 9: 100536, 2024. Go to original source...
    9. Gamon J.A., Peñuelas J., Field C.B.: A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. -Remote Sens. Environ. 41: 35-44, 1992. Go to original source...
    10. Guha A., Sengupta D., Reddy A.R.: Polyphasic chlorophyll a fluorescence kinetics and leaf protein analyses to track dynamics of photosynthetic performance in mulberry during progressive drought. - J. Photoch. Photobio. B 119: 71-83, 2013. Go to original source...
    11. Gupta A., Rico-Medina A., Caño-Delgado A.I.: The physiology of plant responses to drought. - Science 368: 266-269, 2020. Go to original source...
    12. Ilyas M., Nisar M., Khan N. et al.: Drought tolerance strategies in plants: A mechanistic approach. - J. Plant Growth Regul. 40: 926-944, 2021. Go to original source...
    13. Jia Q., Liu Z., Guo C. et al.: Relationship between photosynthetic CO2 assimilation and chlorophyll fluorescence for winter wheat under water stress. - Plants-Basel 12: 3365, 2023. Go to original source...
    14. Jia Y., Xiao W., Ye Y. et al.: Response of photosynthetic performance to drough duration and re-watering in maize. - Agronomy 10: 533, 2020. Go to original source...
    15. Kalisz A., Korna¶ A., Skoczowski A. et al.: Leaf chlorophyll fluorescence and reflectance of oakleaf lettuce exposed to metal and metal(oid) oxide nanoparticles. - BMC Plant Biol. 23: 329, 2023. Go to original source...
    16. Kanash E.V., Sinyavina N.G., Rusakov D.V. et al.: Morpho-physiological, chlorophyll fluorescence, and diffuse reflectance spectra characteristics of lettuce under the main macronutrient deficiency. - Horticulturae 9: 1185, 2023. Go to original source...
    17. Lei H., Yue J., Yin X. et al.: HS-SPME coupled with GC-MS for elucidating differences between the volatile components in wild and cultivated Atractylodes chinensis. - Phytochem. Analysis 34: 317-328, 2023. Go to original source...
    18. Lei J., Tu Y., Xu J., Yu J.: Mechanisms of the traditional Chinese herb Atractylodes lancea against COVID-19 based on network pharmacology and molecular docking. - Wuhan Univ. J. Nat. Sci. 27: 349-360, 2022. Go to original source...
    19. Li Y., Song H., Zhou L. et al.: Tracking chlorophyll fluorescence as an indicator of drought and rewatering across the entire leaf lifespan in a maize field. - Agr. Water Manage. 211: 190-201, 2019. Go to original source...
    20. Lima A.A., Santos I.S., Torres M.E.L. et al.: Drought and re-watering modify ethylene production and sensitivity, and are associated with coffee anthesis. - Environ. Exp. Bot. 181: 104289, 2021. Go to original source...
    21. Ma S., Sun C., Su W. et al.: Transcriptomic and physiological analysis of Atractylodes chinensis in response to drought stress reveals the putative genes related to sesquiterpenoid biosynthesis. - BMC Plant Biol. 24: 91, 2024. Go to original source...
    22. Ma Z., Liu G., Yang Z. et al.: Species differentiation and quality evaluation for Atractylodes medicinal plants by GC/MS coupled with chemometric analysis. - Chem. Biodivers. 20: e202300793, 2023. Go to original source...
    23. Munné-Bosch S., Villadangos S.: Cheap, cost-effective, and quick stress biomarkers for drought stress detection and monitoring in plants. - Trends Plant Sci. 28: 527-536, 2023. Go to original source...
    24. Nión M., Gándara J., Ross S. et al.: Photosynthesis adaptation to long- and short-term water restriction in commercial plantlets of Eucalyptus grandis and hybrids with Red Gums. - Trees 38: 537-547, 2024. Go to original source...
    25. Penuelas J., Pinol J., Ogaya R., Filella I.: Estimation of plant water concentration by the reflectance Water Index WI (R900/R970). - Int. J. Remote Sens 18: 2869-2875, 1997. Go to original source...
    26. Poudel S., Vennam R.R., Shrestha A. et al.: Resilience of soybean cultivars to drought stress during flowering and early-seed setting stages. - Sci. Rep.-UK 13: 1277, 2023. Go to original source...
    27. Rapacz M., Wójcik-Jagła M., Fiust A. et al.: Genome-wide associations of chlorophyll fluorescence OJIP transient parameters connected with soil drought response in barley. - Front. Plant Sci. 10: 78, 2019. Go to original source...
    28. Raypah M. E., Nasru M.I.M., Nazim M.H.H. et al.: Reflectance spectra for identifying stress in different parts of leaf: a case study on oil palm seedlings. - Int. J. Remote Sens. 45: 954-980, 2024. Go to original source...
    29. Rusakov D.V., Kanash E.V.: Spectral characteristics of leaves diffuse reflection in conditions of soil drought: a study of soft spring wheat cultivars of different drought resistance. - Plant Soil Environ. 68: 137-145, 2022. Go to original source...
    30. Singh R.: Spectral reflectance and fluorescence is a rapid, non-destructive tool for drought tolerance monitoring in Withania somnifera (L.) Dunal. - Protoplasma 260: 1421-1435, 2023. Go to original source...
    31. Song K.E., Hong S.S., Hwang H.R. et al.: Effect analysis of hydrogen peroxide using hyperspectral reflectance in sorghum [Sorghum bicolor (L.) Moench] under drought stress. - Plants-Basel 12: 2958, 2023. Go to original source...
    32. Tankari M., Wang C., Ma H. et al.: Drought priming improved water status, photosynthesis and water productivity of cowpea during post-anthesis drought stress. - Agr. Water Manage. 245: 106565, 2021. Go to original source...
    33. Tominaga J., Kawamitsu Y.: Combined leaf gas-exchange system for model assessment. - J. Exp. Bot. 75: 2982-2993, 2024. Go to original source...
    34. Tsimilli-Michael M.: Revisiting JIP-test: An educative review on concepts, assumptions, approximations, definitions and terminology. - Photosynthetica 58: 275-292, 2020. Go to original source...
    35. Wang Y., Xue Z., Yang Y. et al.: [Effects of climate change on the distribution pattern of the suitable growing region for Atractylodes chinensis (DC.) Koidz. in Yanshan area.] - Chin. J. Inform. Tradit. Chin. Med. 30: 1-7, 2023. [In Chinese]
    36. Xia Y.-G., Yang B.-Y., Wang Q.-H. et al.: Species classification and quality assessment of Cangzhu (Atractylodis Rhizoma) by high-performance liquid chromatography and chemometric methods. - J. Anal. Methods Chem. 2013: 497532, 2013. Go to original source...
    37. Xu J., Chen D., Liu C. et al.: Structural characterization and anti-tumor effects of an inulin-type fructan from Atractylodes chinensis. - Int. J. Biol. Macromol. 82: 765-771, 2016. Go to original source...
    38. Xue Z., Gao H., Zhao S.: Effects of cadmium on the photosynthetic activity in mature and young leaves of soybean plants. - Environ. Sci. Pollut. Res. 21: 4656-4664, 2014. Go to original source...
    39. Xue Z.C., Wang Y., Liu J.: Systematic salt tolerance-related physiological mechanisms of wild soybean and their role in the photosynthetic activity and Na+ distribution of grafted soybean plants. - Photosynthetica 60: 400-407, 2022. Go to original source...
    40. Zhang A., Liu M., Gu W. et al.: Effect of drought on photosynthesis, total antioxidant capacity, bioactive component accumulation, and the transcriptome of Atractylodes lancea. - BMC Plant Biol. 21: 293, 2021b. Go to original source...
    41. Zhang W., Bai Q., Cui G. et al.: Recent progress and ongoing challenges in Rhizoma atractylodis research: biogeography, biosynthesis, quality formation and control. - Med. Plant Biol. 2: 19, 2023. Go to original source...
    42. Zhang W., Zhao Z., Chang L. et al.: Atractylodis Rhizoma: A review of its traditional uses, phytochemistry, pharmacology, toxicology and quality control. - J. Ethnopharmacol. 266: 113415, 2021a. Go to original source...

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