IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v260y2022ics0378377421005242.html
   My bibliography  Save this article

The potential of stable carbon isotope ratios and leaf temperature as proxies for drought stress in banana under field conditions

Author

Listed:
  • Vantyghem, Mathilde
  • Merckx, Roel
  • Stevens, Bert
  • Hood-Nowotny, Rebecca
  • Swennen, Rony
  • Dercon, Gerd

Abstract

Drought stress is a major limiting factor for banana production and the incidence of drought spells is expected to increase with climate change. Climate smart practices and varieties are needed, but evaluation in the field is hampered by a lack of reliable physiological drought stress indicators. We investigated the potential of using stable carbon isotope ratios (δ13C) and leaf temperature and its derived DANS (Degrees above Non-Stressed Canopy) index as proxies for drought stress in banana. Leaf samples were taken for δ13C analysis and leaf temperature was monitored throughout the day in a field trial with different banana plant stages (mother and daughter plants) under two irrigation treatments (rainfed and irrigated) during the dry season in Arusha, Tanzania. We found that δ13C, leaf temperature and DANS were highly sensitive proxies for drought stress in banana. Soil volumetric water content had a significant effect on both δ13C values and DANS. There was a significant difference in δ13C (1.5 ± 0.1‰, p < 0.01) and afternoon leaf temperature (7 ± 1 °C, p < 0.01) between the rainfed and irrigated treatment. To deal with variability in δ13C within the leaf, we developed a banana tailored sampling method. This study also revealed the complexity of carbon isotope dynamics in the intertwined system of mother and daughter plants. Daughter plants had more negative δ13C values (−1.9 ± 0.1‰, p < 0.01) and lower temperatures (4 ± 1 °C) than mother plants. This indicates less stress, but interpretation of the δ13C ratio is complicated by the potential carbon flux from mother to daughter plant. Once we have a full understanding of these complexities within the plant, the δ13C and leaf temperature based methods we developed, can be directly implemented for both mother and daughter plants under various field conditions.

Suggested Citation

  • Vantyghem, Mathilde & Merckx, Roel & Stevens, Bert & Hood-Nowotny, Rebecca & Swennen, Rony & Dercon, Gerd, 2022. "The potential of stable carbon isotope ratios and leaf temperature as proxies for drought stress in banana under field conditions," Agricultural Water Management, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:agiwat:v:260:y:2022:i:c:s0378377421005242
    DOI: 10.1016/j.agwat.2021.107247
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421005242
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.107247?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alderfasi, Ali Abdullah & Nielsen, David C., 2001. "Use of crop water stress index for monitoring water status and scheduling irrigation in wheat," Agricultural Water Management, Elsevier, vol. 47(1), pages 69-75, February.
    2. Machovina, Brian & Feeley, Kenneth J., 2013. "Climate change driven shifts in the extent and location of areas suitable for export banana production," Ecological Economics, Elsevier, vol. 95(C), pages 83-95.
    3. Varun Varma & Daniel P. Bebber, 2019. "Climate change impacts on banana yields around the world," Nature Climate Change, Nature, vol. 9(10), pages 752-757, October.
    4. DeJonge, Kendall C. & Taghvaeian, Saleh & Trout, Thomas J. & Comas, Louise H., 2015. "Comparison of canopy temperature-based water stress indices for maize," Agricultural Water Management, Elsevier, vol. 156(C), pages 51-62.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    2. Mukherjee, Subham & Nandi, Ramprosad & Kundu, Arnab & Bandyopadhyay, Prasanta Kumar & Nalia, Arpita & Ghatak, Priyanka & Nath, Rajib, 2022. "Soil water stress and physiological responses of chickpea (Cicer arietinum L.) subject to tillage and irrigation management in lower Gangetic plain," Agricultural Water Management, Elsevier, vol. 263(C).
    3. Manners, Rhys & Vandamme, Elke & Adewopo, Julius & Thornton, Philip & Friedmann, Michael & Carpentier, Sebastien & Ezui, Kodjovi Senam & Thiele, Graham, 2021. "Suitability of root, tuber, and banana crops in Central Africa can be favoured under future climates," Agricultural Systems, Elsevier, vol. 193(C).
    4. Kullberg, Emily G. & DeJonge, Kendall C. & Chávez, José L., 2017. "Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients," Agricultural Water Management, Elsevier, vol. 179(C), pages 64-73.
    5. Singh, Kuntal & McClean, Colin J. & Büker, Patrick & Hartley, Sue E. & Hill, Jane K., 2017. "Mapping regional risks from climate change for rainfed rice cultivation in India," Agricultural Systems, Elsevier, vol. 156(C), pages 76-84.
    6. Khorsand, Afshin & Rezaverdinejad, Vahid & Asgarzadeh, Hossein & Majnooni-Heris, Abolfazl & Rahimi, Amir & Besharat, Sina, 2019. "Irrigation scheduling of maize based on plant and soil indices with surface drip irrigation subjected to different irrigation regimes," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    7. Han, Ming & Zhang, Huihui & DeJonge, Kendall C. & Comas, Louise H. & Gleason, Sean, 2018. "Comparison of three crop water stress index models with sap flow measurements in maize," Agricultural Water Management, Elsevier, vol. 203(C), pages 366-375.
    8. Zhang, Liyuan & Zhang, Huihui & Zhu, Qingzhen & Niu, Yaxiao, 2023. "Further investigating the performance of crop water stress index for maize from baseline fluctuation, effects of environmental factors, and variation of critical value," Agricultural Water Management, Elsevier, vol. 285(C).
    9. Erdem, Yesim & Arin, Levent & Erdem, Tolga & Polat, Serdar & Deveci, Murat & Okursoy, Hakan & Gültas, Hüseyin T., 2010. "Crop water stress index for assessing irrigation scheduling of drip irrigated broccoli (Brassica oleracea L. var. italica)," Agricultural Water Management, Elsevier, vol. 98(1), pages 148-156, December.
    10. Wanglin Ma & Sanghyun Hong & W. Robert Reed & Jianhua Duan & Phong Luu, 2023. "Yield effects of agricultural cooperative membership in developing countries: A meta‐analysis," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(3), pages 761-780, September.
    11. Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).
    12. Xun Su & Minpeng Chen, 2022. "Econometric Approaches That Consider Farmers’ Adaptation in Estimating the Impacts of Climate Change on Agriculture: A Review," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    13. Wang, Chunyu & Li, Sien & Wu, Mousong & Zhang, Wenxin & Guo, Zhenyu & Huang, Siyu & Yang, Danni, 2023. "Co-regulation of temperature and moisture in the irrigated agricultural ecosystem productivity," Agricultural Water Management, Elsevier, vol. 275(C).
    14. Al-Kayssi, A.W. & Shihab, R.M. & Mustafa, S.H., 2011. "Impact of soil water stress on Nigellone oil content of black cumin seeds grown in calcareous-gypsifereous soils," Agricultural Water Management, Elsevier, vol. 100(1), pages 46-57.
    15. Li, Cheng & Luo, Xiaoqi & Wang, Naijiang & Wu, Wenjie & Li, Yue & Quan, Hao & Zhang, Tibin & Ding, Dianyuan & Dong, Qin’ge & Feng, Hao, 2022. "Transparent plastic film combined with deficit irrigation improves hydrothermal status of the soil-crop system and spring maize growth in arid areas," Agricultural Water Management, Elsevier, vol. 265(C).
    16. Katimbo, Abia & Rudnick, Daran R. & Liang, Wei-zhen & DeJonge, Kendall C. & Lo, Tsz Him & Franz, Trenton E. & Ge, Yufeng & Qiao, Xin & Kabenge, Isa & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions," Agricultural Water Management, Elsevier, vol. 274(C).
    17. Lebourgeois, V. & Chopart, J.-L. & Bégué, A. & Le Mézo, L., 2010. "Towards using a thermal infrared index combined with water balance modelling to monitor sugarcane irrigation in a tropical environment," Agricultural Water Management, Elsevier, vol. 97(1), pages 75-82, January.
    18. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2021. "The mean value of gaussian distribution of excess green index: A new crop water stress indicator," Agricultural Water Management, Elsevier, vol. 251(C).
    19. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    20. Minglu Wang & Bruce A. McCarl, 2021. "Impacts of Climate Change on Livestock Location in the US: A Statistical Analysis," Land, MDPI, vol. 10(11), pages 1-20, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:260:y:2022:i:c:s0378377421005242. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.