Category: Conference paper

New Paper: Plant water stress detection based on aerial and terrestrial infrared thermography: a study case from vineyard and olive orchard

Authors: C. Poblete-Echeverrı́a1,a, D. Sepulveda-Reyes2, S. Ortega-Farias2, M. Zuñ iga1 and S. Fuentes3

1Escuela de Agronomı́a, Pontificia Universidad Católica de Valparaı́so, Quillota, Chile; 2Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Chile; 3The University of Melbourne, Melbourne School of Land and Environment, Victoria 3010, Australia.

Abstract: 

Irrigation scheduling is critical for vineyards and olive orchards, since it directly affects yield and fruit composition. Regulated deficit irrigation (RDI) strategies have been applied on both crops with positive results in the past. However, to successfully regulate stress levels, it is necessary to have accurate measurements of plant water status, which is usually achieved using a pressure chamber. In this regard, canopy temperature (Tc) has been shown to be an accurate indicator of plant water stress. Therefore, the objective of this study was to evaluate the accuracy of water stress detection based on aerial and terrestrial infrared thermography for a vineyard and an olive orchard. Lateral infrared thermal images were obtained using a handheld infrared camera and nadir-view infrared thermal images were obtained using an unmanned aerial vehicle (UAV). In addition, measurements of midday stem water potential (Ψstem) from olives trees (Olea europaea L. ‘Arbequina’) and grapevines (Vitis vinifera L. ‘Carménère’) were taken under different RDI strategies during the 2013- 2014 growing season. The image analysis was performed using a customized code written in Mathlab® defining thresholds to exclude non-plant elements. Results showed that the use of infrared thermal images aided in recognizing the differences in the water availability for irrigation treatments when the plants were under stress conditions.

Keywords: unmanned aerial vehicle (UAV), lateral infrared thermal images, nadir-view infrared thermal images

Irrigation scheduling is critical for vineyards and olive orchards, since it directly affects yield and fruit composition. Regulated deficit irrigation (RDI) strategies have been applied on both crops with positive results in the past. However, to successfully regulate stress levels, it is necessary to have accurate measurements of plant water status, which is usually achieved using a pressure chamber. In this regard, canopy temperature (Tc) has been shown to be an accurate indicator of plant water stress. Therefore, the objective of this study was to evaluate the accuracy of water stress detection based on aerial and terrestrial infrared thermography for a vineyard and an olive orchard. Lateral infrared thermal images were obtained using a handheld infrared camera and nadir-view infrared thermal images were obtained using an unmanned aerial vehicle (UAV). In addition, measurements of midday stem water potential (Ψstem) from olives trees (Olea europaea L. ‘Arbequina’) and grapevines (Vitis vinifera L. ‘Carménère’) were taken under different RDI strategies during the 2013- 2014 growing season. The image analysis was performed using a customized code written in Mathlab® defining thresholds to exclude non-plant elements. Results showed that the use of infrared thermal images aided in recognizing the differences in the water availability for irrigation treatments when the plants were under stress conditions.

Keywords: unmanned aerial vehicle (UAV), lateral infrared thermal images, nadir-view infrared thermal images

New Paper: Seasonal variation of night-time sap flow of a young olive orchard: the unconsidered process for evapotranspiration estimations

Authors: R. López-Olivari1, S. Fuentes2 and S. Ortega-Farı́as3

1Instituto de Investigaciones Agropecuarias, INIA Carillanca, km 10 camino Cajón-Vilcún s/n, Temuco, Chile; 2Department of Veterinary and Agricultural Sciences, The University of Melbourne, Victoria, 3010, Australia; 3CITRA-Facultad de Ciencias Agrarias, Universidad de Talca, Av. Lircay s/n, Talca, Chile.

Abstract: Night-time sap flow (Sn), with transpiration as an important proportion of it at moderate to high vapor pressure deficits (VPD), is an important unconsidered factor that contributes significantly to total evapotranspiration (ET) of horticultural and fruit tree crops. This nocturnal process will be likely increased in a climate change scenario, with increases in night-time temperatures at higher rates compared to diurnal temperatures. The aim of this study was to characterise night-time water consumption over a commercial drip-irrigated young olive orchard (Olea europaea L. ‘Arbequina’) located in Pencahue valley, Maule Region, Chile (35°23’LS; 71°44’LW; 96 m a.s.l.) and its dynamics within the 2010/11 season. Four olive trees were selected for sap flow measurements using the Compensated Heat Pulse Velocity technique (CHPV). The canopy conductance (Gc) was calculated by inverting a modified PenmanMonteith equation. The aerodynamic conductance (ga) was calculated using an algorithm of the two-layer model proposed by Shuttleworth and Wallace (1985). An eddy covariance system was installed in the orchard to measure real ET. Results showed that Sn varied between 1.79 and 3.09 L tree-1 night-1 depending mainly of the atmospheric demand. The diurnal sap flow (Sd) measured was from 7.1 to 18.2 L tree-1 day-1. Parabolic shape curves described the relationship between Sn and Gc. Furthermore, the Sn/Sd ratio changed between 16 and 25% depending on the weather conditions, which it is not currently considered in ET models. It is clear that there is a nocturnal flow of water from soil to plant and water movement within the plant, but it is not yet clear the partition between the transpiration process and hydraulic redistribution. However, the former could be more likely due to the highly significant correlations found between VPD and Sn. Keywords: transpiration, canopy and aerodynamic conductance, two-layer model, Olea europaea L., eddy covariance system.

Novel Applications of Image and Video Analysis in Agriculture Under Climate Change Using MATLAB

By: Sigfredo Fuentes

Presentation given at the Matlab tour 2013, Melbourne – Australia

To view proceedings CLICK HERE

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Climate change related phenomena like higher temperatures, increased carbon dioxide concentration in the atmosphere, and more frequent and intensive climatic anomalies, such as heat waves and floods, have placed great pressure on agricultural production around the world. In this scenario, agriculture research and production requires more intensive spatial and temporal monitoring of critical variables to assess the effects of climate change on plant physiology, growth, and fruit quality. Image analysis is becoming an important component in modern agriculture and horticulture. It allows the use of inexpensive devices to acquire meaningful information on crop growth, water status, and quality. In the past, these kinds of technology and analysis were too expensive and required specific know how, which was not readily available to growers. This presentation describes the tools used to solve this problem, such as automated analysis of RGB images and video of plant material, scanned images, and infrared thermal images of canopies to assess plant growth and canopy architectural parameters, leaves and fruit development and plant water status. Results from proposed analysis tools have shown similar outcomes in accuracy and robustness compared to more established techniques. The presenter has developed automated image and video analysis codes using the following MATLAB tools: Image Acquisition Toolbox™, Image Analysis Toolbox™, and Statistical Toolbox™.