A novel 3D imaging system for strawberry phenotyping

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique

Two decades of digital photogrammetry: Revisiting Chandler’s 1999 paper on “Effective application of automated digital photogrammetry for geomorphological research” – a synthesis

This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this record.Digital photogrammetry has experienced rapid development regarding the technology involved and its ease of use over the past two decades. We revisit the work of Jim Chandler who in 1999 published a technical communication seeking to familiarise novice users of photogrammetric methods with important theoretical concepts and practical considerations. In doing so, we assess considerations such as camera calibration and the need for photo-control and check points, as they apply to modern software and workflows, in particular for Structure-from-Motion (SfM) photogrammetry. We also highlight the implications of lightweight drones being the new platform of choice for many photogrammetry-based studies in the geosciences. Finally, we present three examples based on our own work, showing the opportunities that SfM photogrammetry offers at different scales and systems: at the micro-scale for monitoring geomorphological change, and at the meso-scale for hydrological modelling and the reconstruction of vegetation canopies. Our examples showcase developments and applications of photogrammetry which go beyond what was considered feasible 20 years ago and indicate future directions that applications may take. Nevertheless, we demonstrate that, in-line with Chandler’s recommendations, the pre-calibration of consumer-grade cameras, instead of relying entirely on self-calibration by software, can yield palpable benefits in micro-scale applications and that measurements of sufficient control points are still central to generating reproducible, high-accuracy products. With the unprecedented ease of use and wide areas of application, scientists applying photogrammetric methods would do well to remember basic considerations and seek methods for the validation of generated products.European Union’s Horizon 2020 researchMarie Skłodowska-CurieUK Department for Environment, Food and Rural Affair

Potentiale von Laserscannern zur Phänotypisierung von Pflanzen für den Einsatz im Hochdurchsatz-Screening

Die Züchtung hochertragreicher Pflanzen ist von essentieller Wichtigkeit für die Ernährung der Weltbevölkerung. Diese Züchtung geht einher mit einer genauen Analyse der Interaktion zwischen pflanzlichem Genom und Umwelteinflüssen, die gemeinsam den Phänotyp der Pflanze bilden. Phänotypisierung beschreibt den Vorgang der Vermessung, um die Größe von Pflanzen, Wachstum, Leistungsfähigkeit, Architektur und Zusammensetzung mit einer bestimmten Genauigkeit in verschiedenen Skalen mit verschiedenen Sensoren, vom Organ bis hin zum Bestand zu bestimmen. Ein neuer Sensor in diesem Feld ist der Laserscanner. Durch Laserscanning lässt sich die dreidimensionale Geometrie der Pflanzenoberfläche vermessen. Das Ergebnis ist eine punktweise Beschreibung der 3D-Koordinaten auf der Oberfläche. Im Rahmen dieser Arbeit wurde die Genauigkeit der Lasermessungen mit konventionellen Methoden zur Vermessung von Pflanzen verglichen. In verschiedenen Experimenten wurde die Anwendbarkeit des Sensors für die Verfolgung von Wachstum auf Pflanzen und Organebene gezeigt. Die Messung von Wachstum bedarf wiederholter Messungen in kurzen zeitlichen Abständen. Diese Messungen mit hohem Durchsatz erzeugen sehr große Datenmengen. Dabei ist die manuelle Auswertung zeit- und kostenintensiv. Durch Entwicklung einer Auswertemethode auf Grundlage von punktweisen Oberflächenmerkmalen und Support Vector Machines konnte die Segmentierung und Parametrisierung der Organe automatisiert werden. Dabei wurden verschiedene Auflösungen der Punktwolke getestet um eine sensorunabhängige Anwendbarkeit des Algorithmus zu gewährleisten. Das benutzte Lasertriangulations-verfahren beruht auf der Emittierung einer Laserlinie und der Aufnahme der Reflektion durch eine Kamera. Dies ermöglicht die Ableitung dreidimensionaler Informationen. Die Genauigkeit dieser Messung hängt unter anderem von der Interaktion des Laserstrahls mit dem pflanzlichen Gewebe ab. In verschiedenen Experimenten wurde die Interaktion mit Chlorophyll, das Eindringverhalten in die Epidermis, der Einfluss des physiologischen Stadiums, sowie die Interaktion mit Pflanzenkrankheiten (Mehltau) erörtert und quantifiziert. Das im Rahmen dieser Arbeit benutzte Lasermesssystem setzt sehr hohe Investitionskosten voraus. Daher wurden zwei alternative Low-Cost 3D-Messsysteme evaluiert. Diese Evaluierung erfolgte durch die Vermessung hochpräziser Testobjekte, sowie durch die Messung und Ableitung von phänotypischen Parametern an Getreide- und Rübenpflanzen. Es wurde deutlich, dass sich das investitionsintensive Messsystem je nach fokussiertem Parameter durch ein Low-Cost Systems ersetzen lässt. Diese Arbeit und die begleitenden Publikationen führen das Laserscanning als hochgenaues Werkzeug zur Ableitung phänotypischer Parameter bei Pflanzen ein. Die Anwendbarkeit als Ersatz zu konventionellen Messmethoden wurde gezeigt. Weiterhin wurden Methoden zur automatisierten Ableitung phänotypisch wichtiger Parameter entwickelt und evaluiert. Die Interaktion zwischen Laserstrahl und pflanzlicher Oberfläche wurde untersucht und quantifiziert. Abschließend wurden Low-Cost Systeme als Ersatz für das benutzte investitionsintensive Industriemesssystem untersucht. Laserscanning stellt ein effizientes, genaues und evaluiertes Messsystem dar, welches die Anforderungen zur Phänotypisierung von Pflanzen erfüllt und zur Bearbeitung phänotypischer Aufgaben benutzt werden kann.Potential of laserscanners for plant phenotyping for use in high-throughput screening Breeding of plants with high yield is essential for feeding future world population. Thus, breeding comes together with a detailed analysis of the interaction between plant genotype and environmental influences, which creates the plant phenotype. Phenotyping describes the act of measuring the plant to derive a measurement for size, growth, fitness, architecture and composition according to a specific accuracy at different scales with different sensors from the organ to the plot. A new sensor, the laserscanner, has been introduced in the field of plant phenotyping. Using laserscanning the three dimensional geometry of the plant surface can be measured. The result is a pointwise description of the 3D-coordinate of the surface. One part of this work is the comparison of the accuracy of the laserscanner with conventional measuring techniques. Applicability has been shown for tracking of growth on plant and organ level. Measuring of growth requires repeated measurements at short time intervals. This high throughput measuring generates huge amounts of data. Manual analysis is time intensive and costly. By developing an analysis method using pointwise surface features and support vector machines the process of segmentation and parameterization of plant organs could be automated. Different scan resolutions have been tested to proof a sensor independent usability. The technique of laser triangulation uses an emitted laser line and the recording of its reflection by a camera. This enables the derivation of three dimensional information (laser triangulation). The accuracy of this measurement is affected by the interaction between laser ray and plant tissue. Different experiments show and quantify the interaction with chlorophyll, the penetration of the laser into the epidermis layer, the influence of the physiological state of the plant as well as the interaction with plant diseases (mildew). The used laserscanning system requires high invocation cost. Therefore alternative low-cost methods have been evaluated. This evaluation was performed by measuring highly accurate test specimen, as well as measuring and derivation of phenotypic parameters from cereal and sugar beet plants. It was shown that an expensive measuring system could be replaced, depending on the focused parameter, by a low-cost system. This work and accompanying publications introduce the laserscanner as a highly accurate tool for the derivation of phenotypic parameters from plants. The applicability as a replacement for conventional measuring systems has been shown. Furthermore, methods for the automated derivation of phenotypic parameters have been developed and evaluated. The interaction between laser ray and plant tissue has been evaluated and quantified. Finally low-cost sensors have been analyzed as an alternative for the expensive industrial measuring system. Thus, laserscanning depicts an efficient, accurate and evaluated measuring system that meets the requirements of plant phenotyping to solve phenotypic tasks

Structured Light-Based 3D Reconstruction System for Plants.

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance

Potentiale von Laserscannern zur Phänotypisierung von Pflanzen für den Einsatz im Hochdurchsatz-Screening

Die Züchtung hochertragreicher Pflanzen ist von essentieller Wichtigkeit für die Ernährung der Weltbevölkerung. Diese Züchtung geht einher mit einer genauen Analyse der Interaktion zwischen pflanzlichem Genom und Umwelteinflüssen, die gemeinsam den Phänotyp der Pflanze bilden. Phänotypisierung beschreibt den Vorgang der Vermessung, um die Größe von Pflanzen, Wachstum, Leistungsfähigkeit, Architektur und Zusammensetzung mit einer bestimmten Genauigkeit in verschiedenen Skalen mit verschiedenen Sensoren, vom Organ bis hin zum Bestand zu bestimmen. Ein neuer Sensor in diesem Feld ist der Laserscanner. Durch Laserscanning lässt sich die dreidimensionale Geometrie der Pflanzenoberfläche vermessen. Das Ergebnis ist eine punktweise Beschreibung der 3D-Koordinaten auf der Oberfläche. Im Rahmen dieser Arbeit wurde die Genauigkeit der Lasermessungen mit konventionellen Methoden zur Vermessung von Pflanzen verglichen. In verschiedenen Experimenten wurde die Anwendbarkeit des Sensors für die Verfolgung von Wachstum auf Pflanzen und Organebene gezeigt. Die Messung von Wachstum bedarf wiederholter Messungen in kurzen zeitlichen Abständen. Diese Messungen mit hohem Durchsatz erzeugen sehr große Datenmengen. Dabei ist die manuelle Auswertung zeit- und kostenintensiv. Durch Entwicklung einer Auswertemethode auf Grundlage von punktweisen Oberflächenmerkmalen und Support Vector Machines konnte die Segmentierung und Parametrisierung der Organe automatisiert werden. Dabei wurden verschiedene Auflösungen der Punktwolke getestet um eine sensorunabhängige Anwendbarkeit des Algorithmus zu gewährleisten. Das benutzte Lasertriangulations-verfahren beruht auf der Emittierung einer Laserlinie und der Aufnahme der Reflektion durch eine Kamera. Dies ermöglicht die Ableitung dreidimensionaler Informationen. Die Genauigkeit dieser Messung hängt unter anderem von der Interaktion des Laserstrahls mit dem pflanzlichen Gewebe ab. In verschiedenen Experimenten wurde die Interaktion mit Chlorophyll, das Eindringverhalten in die Epidermis, der Einfluss des physiologischen Stadiums, sowie die Interaktion mit Pflanzenkrankheiten (Mehltau) erörtert und quantifiziert. Das im Rahmen dieser Arbeit benutzte Lasermesssystem setzt sehr hohe Investitionskosten voraus. Daher wurden zwei alternative Low-Cost 3D-Messsysteme evaluiert. Diese Evaluierung erfolgte durch die Vermessung hochpräziser Testobjekte, sowie durch die Messung und Ableitung von phänotypischen Parametern an Getreide- und Rübenpflanzen. Es wurde deutlich, dass sich das investitionsintensive Messsystem je nach fokussiertem Parameter durch ein Low-Cost Systems ersetzen lässt. Diese Arbeit und die begleitenden Publikationen führen das Laserscanning als hochgenaues Werkzeug zur Ableitung phänotypischer Parameter bei Pflanzen ein. Die Anwendbarkeit als Ersatz zu konventionellen Messmethoden wurde gezeigt. Weiterhin wurden Methoden zur automatisierten Ableitung phänotypisch wichtiger Parameter entwickelt und evaluiert. Die Interaktion zwischen Laserstrahl und pflanzlicher Oberfläche wurde untersucht und quantifiziert. Abschließend wurden Low-Cost Systeme als Ersatz für das benutzte investitionsintensive Industriemesssystem untersucht. Laserscanning stellt ein effizientes, genaues und evaluiertes Messsystem dar, welches die Anforderungen zur Phänotypisierung von Pflanzen erfüllt und zur Bearbeitung phänotypischer Aufgaben benutzt werden kann.Potential of laserscanners for plant phenotyping for use in high-throughput screening Breeding of plants with high yield is essential for feeding future world population. Thus, breeding comes together with a detailed analysis of the interaction between plant genotype and environmental influences, which creates the plant phenotype. Phenotyping describes the act of measuring the plant to derive a measurement for size, growth, fitness, architecture and composition according to a specific accuracy at different scales with different sensors from the organ to the plot. A new sensor, the laserscanner, has been introduced in the field of plant phenotyping. Using laserscanning the three dimensional geometry of the plant surface can be measured. The result is a pointwise description of the 3D-coordinate of the surface. One part of this work is the comparison of the accuracy of the laserscanner with conventional measuring techniques. Applicability has been shown for tracking of growth on plant and organ level. Measuring of growth requires repeated measurements at short time intervals. This high throughput measuring generates huge amounts of data. Manual analysis is time intensive and costly. By developing an analysis method using pointwise surface features and support vector machines the process of segmentation and parameterization of plant organs could be automated. Different scan resolutions have been tested to proof a sensor independent usability. The technique of laser triangulation uses an emitted laser line and the recording of its reflection by a camera. This enables the derivation of three dimensional information (laser triangulation). The accuracy of this measurement is affected by the interaction between laser ray and plant tissue. Different experiments show and quantify the interaction with chlorophyll, the penetration of the laser into the epidermis layer, the influence of the physiological state of the plant as well as the interaction with plant diseases (mildew). The used laserscanning system requires high invocation cost. Therefore alternative low-cost methods have been evaluated. This evaluation was performed by measuring highly accurate test specimen, as well as measuring and derivation of phenotypic parameters from cereal and sugar beet plants. It was shown that an expensive measuring system could be replaced, depending on the focused parameter, by a low-cost system. This work and accompanying publications introduce the laserscanner as a highly accurate tool for the derivation of phenotypic parameters from plants. The applicability as a replacement for conventional measuring systems has been shown. Furthermore, methods for the automated derivation of phenotypic parameters have been developed and evaluated. The interaction between laser ray and plant tissue has been evaluated and quantified. Finally low-cost sensors have been analyzed as an alternative for the expensive industrial measuring system. Thus, laserscanning depicts an efficient, accurate and evaluated measuring system that meets the requirements of plant phenotyping to solve phenotypic tasks

3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts) were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level

Evaluation of borage extracts as potential biostimulant using a phenomic, agronomic, physiological and biochemical approach

Biostimulants are substances able to improve water and nutrient use efficiency and counteract stress factors by enhancing primary and secondary metabolism. Premise of the work was to exploit raw extracts from leaves (LE) or flowers (FE) of Borago officinalis L., to enhance yield and quality of Lactuca sativa ‘Longifolia,’ and to set up a protocol to assess their effects. To this aim, an integrated study on agronomic, physiological and biochemical aspects, including also a phenomic approach, has been adopted. Extracts were diluted to 1 or 10 mL L–1, sprayed onto lettuce plants at the middle of the growing cycle and 1 day before harvest. Control plants were treated with water. Non-destructive analyses were conducted to assess the effect of extracts on biomass with an innovative imaging technique, and on leaf photosynthetic efficiency (chlorophyll a fluorescence and leaf gas exchanges). At harvest, the levels of ethylene, photosynthetic pigments, nitrate, and primary (sucrose and total sugars) and secondary (total phenols and flavonoids) metabolites, including the activity and levels of phenylalanine ammonia lyase (PAL) were assessed. Moreover, a preliminary study of the effects during postharvest was performed. Borage extracts enhanced the primary metabolism by increasing leaf pigments and photosynthetic activity. Plant fresh weight increased upon treatments with 10 mL L–1 doses, as correctly estimated by multi-view angles images. Chlorophyll a fluorescence data showed that FEs were able to increase the number of active reaction centers per cross section; a similar trend was observed for the performance index. Ethylene was three-fold lower in FEs treatments. Nitrate and sugar levels did not change in response to the different treatments. Total flavonoids and phenols, as well as the total protein levels, the in vitro PAL specific activity, and the levels of PAL-like polypeptides were increased by all borage extracts, with particular regard to FEs. FEs also proved efficient in preventing degradation and inducing an increase in photosynthetic pigments during storage. In conclusion, borage extracts, with particular regard to the flower ones, appear to indeed exert biostimulant effects on lettuce; future work will be required to further investigate on their efficacy in different conditions and/or species

Accuracy Analysis of a Multi-View Stereo Approach for Phenotyping of Tomato Plants at the Organ Level

Accessing a plant’s 3D geometry has become of significant importance for phenotyping during the last few years. Close-up laser scanning is an established method to acquire 3D plant shapes in real time with high detail, but it is stationary and has high investment costs. 3D reconstruction from images using structure from motion (SfM) and multi-view stereo (MVS) is a flexible cost-effective method, but requires post-processing procedures. The aim of this study is to evaluate the potential measuring accuracy of an SfM- and MVS-based photogrammetric method for the task of organ-level plant phenotyping. For this, reference data are provided by a high-accuracy close-up laser scanner. Using both methods, point clouds of several tomato plants were reconstructed at six following days. The parameters leaf area, main stem height and convex hull of the complete plant were extracted from the 3D point clouds and compared to the reference data regarding accuracy and correlation. These parameters were chosen regarding the demands of current phenotyping scenarios. The study shows that the photogrammetric approach is highly suitable for the presented monitoring scenario, yielding high correlations to the reference measurements. This cost-effective 3D reconstruction method depicts an alternative to an expensive laser scanner in the studied scenarios with potential for automated procedures