Research Paper Linking thermal imaging and soil remote sensing to enhance irrigation management of sugar beet L. Quebrajo a , M. Perez-Ruiz a,* , L. P  erez-Urrestarazu a , G. Martı´nez b , G. Egea a a Universidad de Sevilla,  Area de Ingenierı´a Agroforestal, Dpto. de Ingenierı´a Aeroespacial y Mec anica de Fluidos, Spain b Universidad de C ordoba, Dpto. de Agronomı´a, Spain article info Article history: Published online xxx Keywords: Remote sensing Unmanned aerial vehicle (UAV) Precision agriculture Aerial image Crop water stress index (CWSI) The use of reliable information and data that are rapidly and easily acquired is essential for farm water management and appropriate irrigation strategies. Over the past decade, new advances have been made in irrigation technology, such as platforms that continuously transmit data between irrigation controllers and field sensors, mobile apps, and equipment for variable rate irrigation. In this study, images captured with a thermal imaging camera mounted on an unmanned aerial vehicle (UAV) were used to evaluate the water status of sugar beet plants in a plot with large spatial variability in terms of soil properties. The results were compared with those of soil moisture measurements. No direct relationship was observed between the water status of the soil and that of the crops. However, the fresh root mass and sugar content tended to decrease when higher levels of water stress were detected in the crop using thermal imaging, with coefficients of determination of 0.28 and 0.94 for fresh root mass and sugar content, respectively. Differences were observed be- tween different soil types, and therefore different irrigation strategies are needed in highly heterogeneous plots. © 2017 IAgrE. Published by Elsevier Ltd. All rights reserved. 1. Introduction Farmers, cooperatives and agricultural consultants are facing radical changes regarding the methods employed to collect, analyse, and use information to add value to their production outputs. Over the past 20 years, we have observed increasing interest in farm- and block-level precision agriculture (Blackmore, Godwin, & Fountas, 2003; Zude-Sasse, Fountas, Gemtos, & Abu-Khalaf, 2016); however, the next 20 years will give rise to canopy-, branch-, and even fruit-level production practices that will demand a new farming mentality (Krishna, 2016, chap. 5). Field sensors will provide terabytes of quanti- tative and qualitative information about crops, such as nu- trients levels and plant and soil moisture status, and about orchards, such as the three-dimensional canopy shape, the mass and size of each fruit, as well as the number of fruits per plant. Amassing this information into a coherent database that can be rapidly and easily used to make informed de- cisions on what, when, where, and how to plant, irrigate, prune, thin, treat and harvest each crop will soon be one of the * Corresponding author. Ctra. Utrera, km 1, Sevilla, 41013, Spain. Fax: þ34 954 481389. E-mail address: manuelperez@us.es (M. Perez-Ruiz). Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/issn/15375110 biosystems engineering xxx (2017) 1 e11 http://dx.doi.org/10.1016/j.biosystemseng.2017.08.013 1537-5110/© 2017 IAgrE. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Quebrajo, L., et al., Linking thermal imaging and soil remote sensing to enhance irrigation man- agement of sugar beet, Biosystems Engineering (2017), http://dx.doi.org/10.1016/j.biosystemseng.2017.08.013