| Autor: |
Fernandez-Gallego JA; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio; Programa de Ingeniería Electrónica, Facultad de Ingeniería, Universidad de Ibagué., Buchaillot ML; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Gracia-Romero A; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Vatter T; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Diaz OV; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Aparicio Gutiérrez N; Instituto Tecnológico Agrario de Castilla y León (ITACyL)., Nieto-Taladriz MT; Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)., Kerfal S; Syngenta Spain., Serret MD; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Araus JL; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio., Kefauver SC; Plant Physiology Section, Faculty of Biology, University of Barcelona; Agrotecnio; sckefauver@ub.edu. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of visualized experiments : JoVE [J Vis Exp] 2019 Feb 02 (144). Date of Electronic Publication: 2019 Feb 02. |
| DOI: |
10.3791/58695 |
| Abstrakt: |
Ear density, or the number of ears per square meter (ears/m 2 ), is a central focus in many cereal crop breeding programs, such as wheat and barley, representing an important agronomic yield component for estimating grain yield. Therefore, a quick, efficient, and standardized technique for assessing ear density would aid in improving agricultural management, providing improvements in preharvest yield predictions, or could even be used as a tool for crop breeding when it has been defined as a trait of importance. Not only are the current techniques for manual ear density assessments laborious and time-consuming, but they are also without any official standardized protocol, whether by linear meter, area quadrant, or an extrapolation based on plant ear density and plant counts postharvest. An automatic ear counting algorithm is presented in detail for estimating ear density with only sunlight illumination in field conditions based on zenithal (nadir) natural color (red, green, and blue [RGB]) digital images, allowing for high-throughput standardized measurements. Different field trials of durum wheat and barley distributed geographically across Spain during the 2014/2015 and 2015/2016 crop seasons in irrigated and rainfed trials were used to provide representative results. The three-phase protocol includes crop growth stage and field condition planning, image capture guidelines, and a computer algorithm of three steps: (i) a Laplacian frequency filter to remove low- and high-frequency artifacts, (ii) a median filter to reduce high noise, and (iii) segmentation and counting using local maxima peaks for the final count. Minor adjustments to the algorithm code must be made corresponding to the camera resolution, focal length, and distance between the camera and the crop canopy. The results demonstrate a high success rate (higher than 90%) and R 2 values (of 0.62-0.75) between the algorithm counts and the manual image-based ear counts for both durum wheat and barley. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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