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

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.