Evaluation of “ground sensing” optical sensors for diagnosis of Plasmopara viticola on vines

Abstract

The present work considers the possible use of two commercial optical devices, the GreenSeeker RT100 and the Crop Circle, in detecting different levels of grapevine downy mildew symptoms. The analysis was conducted on vine leaves that had been picked from plants of cv. Cabernet Franc infected by Plasmopara viticola. Leaves were divided into eight homogeneous infection classes and then analyzed (on the leaves' adaxial surfaces) through the optical devices and a portable visible/near infrared (Vis/NIR) spectrophotometer used as tester. Data showed a linear relation between the percentage of symptomatic leaf area and the Normalized Difference Vegetation Index (NDVI) calculated through the optical sensors (R 2 = 0.708 for GreenSeeker; R 2 = 0.599 for Crop Circle; R 2 = 0.950 for the spectrophotometer). The regression obtained for GreenSeeker is more significant than the one obtained for Crop Circle. This fact suggests a greater capability of GreenSeeker than Crop Circle in detecting different disease levels and its possible use in diagnosis application in the vineyard. Finally, the NDVI measurements carried out through the two commercial sensors, showed lower values on abaxial surfaces than on adaxial surfaces, and a reduced range of values. Moreover, the identification of different infection classes was more difficult on the abaxial surface. This is due to both the different structure of the leaf tissue and the different symptoms of P. viticola on the abaxial and adaxial surfaces. The present work will allow, in the future, applying these optical devices to diagnosis directly in vineyards.Additional key words: Crop Circle; diagnosis of phytopathogenic fungi; GreenSeeker; NDVI; plant health status; proximal sensing. Resumen Evaluación de sensores ópticos para el diagnóstico de Plasmopara viticola en videsEl presente estudio describe la posibilidad de utilizar dos sensores ópticos comerciales, el GreenSeeker RT100 y el Crop Circle, para identificar diferentes niveles de síntomas de mildiu en vid. La experimentación ha sido realizada en hojas de vid cv. Cabernet Franc infectadas por Plasmopara viticola. Las hojas se dividieron en ocho clases homogéneas por nivel de infección y analizadas (en las caras superiores) con instrumentos ópticos y con un espectrofotómetro Vis/ NIR (visible/infrarrojo), utilizado como testigo. Los resultados muestran la presencia de una regresión lineal entre el porcentaje de superficie foliar con síntomas y el índice NVDI calculado por medio de los sensores ópticos (R 2 = 0,708 para GreenSeeker; R 2 = 0,599 para Crop Circle; R 2 = 0,950 para el espectrofotómetro). La regresión obtenida con el GreenSeeker es más significativa que la obtenida con el Crop Circle. Esto sugiere una mayor capacidad del GreenSeeker para detectar diferentes niveles de infección. Por último, las mediciones realizadas por medio de los dos sensores comerciales en el envés de las hojas mostraron valores de NVDI menores que los obtenidos en la cara superior, así como un menor rango de valores. Por lo tanto, la ide...

Exploratory study on vineyards soil mapping by visible/near-infrared spectroscopy of grapevine leaves

“…In 2012, two commercial optical devices (GreenSeeker RT100 and Crop Circle) were tested for detecting different levels of grapevine downy mildew symptoms in Cabernet Franc leaves. However, this method was not applied in-situ (Calcante et al, 2012). Off-line collected hyperspectral images of grapevine leaves in the range of 380-1028 nm were used to classify Tempranillo, Grenache and Cabernet Sauvignon varieties (Diago et al, 2013).…”

Development and Preliminary Tests of a Crop Monitoring Mobile Lab Based on a Combined use of Optical Sensors

“…Moreover, optical crop-sensing technology has been around for several years [20,21]. Optical cropsensing systems use light sensors to analyze in-season plant health.…”

Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications

“…Vision systems are the necessary premise to implement an adaptive-control system, whose actions are planned on the basis of the acquisitions by a vision system; in agriculture, for example, they are useful for implementing information systems to support the farmers through a continuous and global environmental, operational and crop monitoring (Calcante et al, 2012;Mazzetto et al, 2013aMazzetto et al, , 2010 but also for applying the principles of precision agriculture, and in particular the variable-rate application method (Oberti et al, 2013;Walklate and Cross, 2013). For example, electro valves of sprayers can be electronically driven to compensate the variations in canopy dimensions by ultrasonic sensors Llorens et al, 2010;Solanelles-Batlle et al, 2006) or by LiDAR sensors Walklate et al, 2002).…”