A digital image-processing-based method for determining the crop coefficient of lettuce crops in the southeast of Spain

Abstract

In the arid and semi-arid regions of the southeast of Spain, the low availability of water for irrigation requires the development of new water-conserving irrigation techniques. This leads to the use of precision agriculture technologies that permit an improvement in performance or reductions in the consumption of water and fertilisers. In this context, the use of digital photography enables plant growth monitoring, which allows crop water requirements to be determined from variables that are directly related to evapotranspiration. One of these variables is the percentage of ground cover, which has also been correlated with plant height. This paper presents a new method based on computer vision for estimating the crop coefficient (Kc) of lettuce crops from the percentage of ground cover (PGC) extracted from digital photographs. In contrast to other methods reported in the literature, plant height (h) is estimated first; then, the term PGC/h is correlated with Kc. The method was successfully applied to and validated using a commercial crop of lettuce (Lactuca sativa L. cv. ‘Hierro’) located in the southeast of Spain.