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The mean value of gaussian distribution of excess green index: A new crop water stress indicator

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  • Zhang, Liyuan
  • Zhang, Huihui
  • Han, Wenting
  • Niu, Yaxiao
  • Chávez, José L.
  • Ma, Weitong

Abstract

The study proposed a new crop water stress indicator - the mean value of Gaussian distribution of excess green index for maize canopy (MGDEXG) within an RGB image. A series of RGB images were collected in a maize field under varying levels of deficit irrigation during 2013, 2015 and 2016 growth seasons in northern Colorado. To evaluate the sensitivity of MGDEXG to maize water status, canopy temperature, canopy-to-air temperature difference, crop water stress index (CWSI), leaf water potential, and sap flow were used as water status references. The results show that MGDEXG distinguished different levels of deficit irrigation treatments well and responded to the release and reimposition of deficit irrigation. The MGDEXG showed a significant correlation (p < 0.01) to different water stress references. Especially, the coefficient of determination (R2) with CWSI was 0.63 (n = 59) for 2013, 0.80 (n = 90) for 2015, and 0.80 (n = 50) for 2016. In addition, among the three Tc-based water stress indicators, the relationship between MGDEXG and CWSI was the most robust with the least annual changes of slope and intercept. The robust relationship between MGDEXG and CWSI could also show that MGDEXG was resistant to the micro-meteorological conditions within the field. Significant correlations (p < 0.01) were found between MGDEXG and leaf water potential with R2 of 0.85 and 0.87 for 2013 and 2015, and between MGDEXG and sap flow in 2015 (R2 = 0.62). MGDEXG relies only on the distribution of crop pixels within an RGB image and could be calculated easily, so it could be cheaper or easier to popularize than other crop water stress indicators in practice. Overall, our results show that MGDEXG could be successfully used as a maize water stress indicator. In the future, more field experiments are needed to further explore the changes of MGDEXG with different scale and spatial resolution of RGB images, and to evaluate MGDEXG for specific climate and crop varieties.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:251:y:2021:i:c:s0378377421001311
    DOI: 10.1016/j.agwat.2021.106866
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    References listed on IDEAS

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    1. 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.
    2. Li, L. & Nielsen, D.C. & Yu, Q. & Ma, L. & Ahuja, L.R., 2010. "Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1146-1155, August.
    3. 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.
    4. Emekli, Yasar & Bastug, Ruhi & Buyuktas, Dursun & Emekli, Nefise Yasemin, 2007. "Evaluation of a crop water stress index for irrigation scheduling of bermudagrass," Agricultural Water Management, Elsevier, vol. 90(3), pages 205-212, June.
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    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.
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    1. 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).
    2. 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).

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