Comparison of Trimble GreenSeeker and Crop Circle (Model ACS-210) Reflectance Meters for Assessment of Severity of Late Leaf Spot

Abstract

Four field experiments conducted in 2015 were used to examine the relationships among normalized difference vegetation index (NDVI) measurements from two canopy crop sensors and visual estimates of defoliation by late leaf spot ( Nothopassalora personata) of peanut ( Arachis hypogaea) the predominant foliar disease in this study. For each evaluation, reflectance was measured with each the two meters, and leaf spot severity was measured visually within as short a time as possible. Linear and quadratic regression models were used to characterize the relationships between percent defoliation from late leaf spot and NDVI measured with the GreenSeeker (NDVIGS) and Crop Circle (NDVICC) instruments and the relationships between NDVIGS and NDVICC. NDVIGS decreased with increasing percent defoliation according to linear or quadratic functions in three of the four trials, NDVICC decreased with increasing percent defoliation according to linear functions in three of four trials. In two of the four trials, NDVICC increased with increasing NDVIGS according to quadratic functions, but there was no significant regression for those variables in two trials. In three of the four trials, NDVICC linear regression had a better fit for predicting percent defoliation according to the coefficient of determination (R2). There was no indication for either instrument that the same NDVI reading corresponded with the same level of defoliation across trials. Results indicated that NDVI measurements from the two instruments are not interchangeable.

Field Phenotyping Monitoring Systems for High-Throughput: A Survey of Enabling Technologies, Equipment, and Research Challenges

“…Phenotyping parameters of crops can be attained based on the strong regularity between reflectivity in characteristic spectral bands and phenotype information of crops. The commonly used spectral sensors in this type include the handheld chlorophyll sensor SPAD-502 (Konica Minolta, Tokyo, Japan) [14], RapidSCAN CS-45 canopy monitor (Holland Scientific, Lincoln, NE, USA) [35], and the GreenSeeker spectrometer based on active light sources (Oklahoma State University and N-tech, Okmulgee, OK, USA) [21]. Spectral sensors show high sensitivity and low cost, while they set strict requirements for the light and generally need to measure phenotype information in specific time frames on sunny days [36].…”

“…Typical phenotyping sensors and phenotype monitoring systems as well as their research and development (R&D) institutions are displayed in Figure 3. The common physiological phenotyping sensors of crops include the single-leaf SPAD [14], Dualex [15], canopy-level ASDs (Analytical Spectral Devices) Field Spec Pro [16][17][18], CGMD-402 (Crop Growth Monitoring and Diagnosis 402) [19], and so on [20][21][22][23]. Phenotyping sensors of crop morphologies are mainly multiple types of image collectors.…”

High-Throughput Plant Phenotyping (HTPP) in Resource-Constrained Research Programs: A Working Example in Ghana

“…The extreme ends of HTPP are robotic phenotyping platforms (where single plants grow exclusively under artificial conditions) and satellite imagery [26]. Between these two extremes are various gadgets including handheld tools (e.g., SPAD meter, Green Seeker), mobile phenotyping platforms and unmanned aerial vehicles (e.g., light drones) [27][28][29][30][31]. The use of such technologies can improve the precision associated with data collection, leading to high heritability estimates and eventually increased genetic gains or response to selection.…”