IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v285y2023ics0378377423002147.html
   My bibliography  Save this article

Further investigating the performance of crop water stress index for maize from baseline fluctuation, effects of environmental factors, and variation of critical value

Author

Listed:
  • Zhang, Liyuan
  • Zhang, Huihui
  • Zhu, Qingzhen
  • Niu, Yaxiao

Abstract

To further analyze the accuracy and applicability of empirical (CWSI_E) and theoretical (CWSI_T) crop water stress index calculation methods, study was conducted at the USDA-ARS Limited Irrigation Research Farm (LIRF), Colorado, USA during two maize growing seasons in 2013 and 2015. The growth stage and seasonal changes of non-water-stressed baseline (NWSB) and non-transpiration baseline (NTB), the effects of environmental factors, and the estimation performances of water stress, grain yield, and WUE were analyzed. Results show that significant correlations (p < 0.001) with vapor pressure deficit (VPD) were found for two baselines, however, the distributions with the changes of VPD and growth stage and seasonal changes of NWSB and NTB were different between two methods. Specifically, neither growth stage nor growing season significantly affects the baselines of CWSI_E, indicating that the baselines of the empirical method were more stable than those of the theoretical method. The lower baselines and smaller difference between NWSB and NTB were more likely to be observed in the theoretical method than the empirical method. The greater CWSI values were observed for the theoretical method because of the relatively smaller difference between NWSB and NTB. VPD with values greater than 1.5 kPa may a suitable environmental criterion to be used to indicate the applicability of the two CWSI methods for crop water stress estimation. Both methods could track maize water stress with R2 of 0.55 for CWSI_E and 0.49 for CWSI_T (n = 236) with sap flow measurements and could estimate grain yield with the highest R2 of 0.95 and WUE with the highest R2 of 0.87 (n = 24). However, greater values and a clear downtrend for three one-hour periods were observed for CWSI_T because of the relatively smaller difference between NWSB_T and NTB_T. This study contributes to the knowledge in the area of stable and accurate monitoring of crop water status based on CWSI.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:agiwat:v:285:y:2023:i:c:s0378377423002147
    DOI: 10.1016/j.agwat.2023.108349
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377423002147
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2023.108349?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. 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.
    2. Gontia, N.K. & Tiwari, K.N., 2008. "Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry," Agricultural Water Management, Elsevier, vol. 95(10), pages 1144-1152, October.
    3. Nielsen, D. C., 1994. "Non water-stressed baselines for sunflowers," Agricultural Water Management, Elsevier, vol. 26(4), pages 265-276, December.
    4. Tubaileh, Azzam. S. & Sammis, Theodore W. & Lugg, David G., 1986. "Utilization of thermal infrared thermometry for detection of water stress in spring barley," Agricultural Water Management, Elsevier, vol. 12(1-2), pages 75-85, October.
    5. 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.
    6. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    7. 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.
    8. 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.
    9. Venturin, Afonso Zucolotto & Guimarães, Claudinei Martins & Sousa, Elias Fernandes de & Machado Filho, José Altino & Rodrigues, Weverton Pereira & Serrazine, Ícaro de Araujo & Bressan-Smith, Ricardo &, 2020. "Using a crop water stress index based on a sap flow method to estimate water status in conilon coffee plants," Agricultural Water Management, Elsevier, vol. 241(C).
    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. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2022. "Effects of image spatial resolution and statistical scale on water stress estimation performance of MGDEXG: A new crop water stress indicator derived from RGB images," Agricultural Water Management, Elsevier, vol. 264(C).
    2. 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.
    3. 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).
    4. Candogan, Burak Nazmi & Sincik, Mehmet & Buyukcangaz, Hakan & Demirtas, Cigdem & Goksoy, Abdurrahim Tanju & Yazgan, Senih, 2013. "Yield, quality and crop water stress index relationships for deficit-irrigated soybean [Glycine max (L.) Merr.] in sub-humid climatic conditions," Agricultural Water Management, Elsevier, vol. 118(C), pages 113-121.
    5. Singh, Jasreman & Ge, Yufeng & Heeren, Derek M. & Walter-Shea, Elizabeth & Neale, Christopher M.U. & Irmak, Suat & Woldt, Wayne E. & Bai, Geng & Bhatti, Sandeep & Maguire, Mitchell S., 2021. "Inter-relationships between water depletion and temperature differential in row crop canopies in a sub-humid climate," Agricultural Water Management, Elsevier, vol. 256(C).
    6. 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.
    7. 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.
    8. 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).
    9. 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).
    10. 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).
    11. Anzhen Qin & Dongfeng Ning & Zhandong Liu & Sen Li & Ben Zhao & Aiwang Duan, 2021. "Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield," Agriculture, MDPI, vol. 11(10), pages 1-16, October.
    12. Han, Ming & Zhang, Huihui & DeJonge, Kendall C. & Comas, Louise H. & Trout, Thomas J., 2016. "Estimating maize water stress by standard deviation of canopy temperature in thermal imagery," Agricultural Water Management, Elsevier, vol. 177(C), pages 400-409.
    13. Luan, Yajun & Xu, Junzeng & Lv, Yuping & Liu, Xiaoyin & Wang, Haiyu & Liu, Shimeng, 2021. "Improving the performance in crop water deficit diagnosis with canopy temperature spatial distribution information measured by thermal imaging," Agricultural Water Management, Elsevier, vol. 246(C).
    14. Ekinzog, Elmer Kanjo & Schlerf, Martin & Kraft, Martin & Werner, Florian & Riedel, Angela & Rock, Gilles & Mallick, Kaniska, 2022. "Revisiting crop water stress index based on potato field experiments in Northern Germany," Agricultural Water Management, Elsevier, vol. 269(C).
    15. Komlan Koudahe & Aleksey Y. Sheshukov & Jonathan Aguilar & Koffi Djaman, 2021. "Irrigation-Water Management and Productivity of Cotton: A Review," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    16. Stepanovic, Strahinja & Rudnick, Daran & Kruger, Greg, 2021. "Impact of maize hybrid selection on water productivity under deficit irrigation in semiarid western Nebraska," Agricultural Water Management, Elsevier, vol. 244(C).
    17. Singh, Sukhbir & Angadi, Sangamesh V. & Grover, Kulbhushan K. & Hilaire, Rolston St. & Begna, Sultan, 2016. "Effect of growth stage based irrigation on soil water extraction and water use efficiency of spring safflower cultivars," Agricultural Water Management, Elsevier, vol. 177(C), pages 432-439.
    18. Andarzian, B. & Bannayan, M. & Steduto, P. & Mazraeh, H. & Barati, M.E. & Barati, M.A. & Rahnama, A., 2011. "Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran," Agricultural Water Management, Elsevier, vol. 100(1), pages 1-8.
    19. Koffi Djaman & Suat Irmak & Komlan Koudahe & Samuel Allen, 2021. "Irrigation Management in Potato ( Solanum tuberosum L.) Production: A Review," Sustainability, MDPI, vol. 13(3), pages 1-19, February.
    20. Saseendran, S.A. & Ahuja, Lajpat R. & Ma, Liwang & Trout, Thomas J. & McMaster, Gregory S. & Nielsen, David C. & Ham, Jay M. & Andales, Allan A. & Halvorson, Ardel D. & Chávez, José L. & Fang, Quanxia, 2015. "Developing and normalizing average corn crop water production functions across years and locations using a system model," Agricultural Water Management, Elsevier, vol. 157(C), pages 65-77.

    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:285:y:2023:i:c:s0378377423002147. 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.