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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #376957
Research Project: Improving the Sustainability of Irrigated Farming Systems in Semi-Arid Regions

Location: Water Management and Systems Research

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

Author
item ZHANG, LIYUAN - Northwest A&f University
item Zhang, Huihui
item HAN, WENTING - Northwest A&f University
item NIU, YAXIAO - Northwest A&f University
item CHÁVEZ, JOSÉ - Colorado State University
item MA, WEITONG - Northwest A&f University

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/5/2021
Publication Date: 3/25/2021
Citation: Zhang, L., Zhang, H., Han, W., Niu, Y., Chávez, J.L., Ma, W. 2021. The mean value of gaussian distribution of excess green index: A new crop water stress indicator. Agricultural Water Management. 251. Article e106866. https://doi.org/10.1016/j.agwat.2021.106866.
DOI: https://doi.org/10.1016/j.agwat.2021.106866

Interpretive Summary: To adopt more accurate irrigation scheduling approaches and improve water productivity, it is necessary to monitor crop water status timely and accurately. The study proposed a new crop water stress indicator (MGDEXG) which is derived from RGB images of crop canopy. 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. We used a few common crop water stress references, such as canopy temperature, canopy-to-air temperature difference, crop water stress index (CWSI), leaf water potential, and sap flow, to evaluate the performance of MGDEXG for monitoring maize water status. The results show that MGDEXG distinguished different levels of deficit irrigation treatments and responded well as the crop entered and exited deficit irrigation periods. All the water stress indicators had significant correlations with MGDEXG. The relationship between MGDEXG and CWSI was the most robust among the three Tc-based water stress indicators. The robust relationship between MGDEXG and CWSI could also show that MGDEXG was resistant to the micro-meteorological conditions within the field. Overall, the 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 indicators in practice.

Technical Abstract: To adopt more accurate irrigation scheduling approaches and improve water productivity, it is necessary to monitor crop water status timely and accurately. The study proposed a new crop water stress indicator - the mean value of Gaussian distribution of excess green index (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. All water stress references had significant (p<0.01) correlations with MGDEXG. 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, the relationship between MGDEXG and CWSI was the most robust among the three Tc-based water stress indicators. 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 CWSI 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.