Estimation of Corn Leaf Area Index and Ground Cover With Vegetation Indices as a Result of Irrigation Dose


  •  C. D. Papanikolaou    
  •  M. A. Sakellariou-Makrantonaki    

Abstract

New technologies have been implemented in the agricultural sector to improve crop production and resource management including irrigation water. A three-year long project was conducted to determine whether vegetation indices (VIs) could be used to estimate the leaf area index (LAI) as well as the soil cover fraction (fc) at different crop growth stages in order to use these parameters in a future study concerning irrigation through drones. A low cost unmanned aerial vehicle (drone) and a multispectral camera were used to calculate different VIs of corn (Zea mays). The irrigation scheduling based on the FAO Penman-Monteith equation and the drip irrigation method were used. Three treatments were organized in three replications and the irrigation doses were equal to 100%, 75%, and 50% of the daily evapotranspiration respectively. The Simple and Multiple Regression analysis were used and different equations were formed where the VIs were the predictor variables and the LAI and fc the predicted ones. According to the two-year period data (2018-2019), during 2018 the average maximum LAI in the full irrigation treatment (100%) was 4.1. In the medium irrigation treatment (75%) the LAI was 4.0. The LAI in the third treatment (50%) was 3.9. In 2019, the LAI was 3.7 (100% treatment). In the second treatment, the LAI was 3.3. The LAI in the third treatment was 3.0. According to the results different VIs and prediction equations could be used to estimate the LAI values with high accuracy with the in situ measurements as well as the soil cover fraction.



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