Andreas Hund

Plant phenotyping: from bean weighing to image analysis

Plant phenotyping refers to a quantitative description of the plant’s anatomical, ontogenetical, physiological and biochemical properties. Today, rapid developments are taking place in the field of non-destructive, image-analysis -based phenotyping that allow for a characterization of plant traits in high-throughput. During the last decade, ‘the field of image-based phenotyping has broadened its focus from the initial characterization of single-plant traits in controlled conditions towards ‘real-life’ applications of robust field techniques in plant plots and canopies. An important component of successful phenotyping approaches is the holistic characterization of plant performance that can be achieved with several methodologies, ranging from multispectral image analyses via thermographical analyses to growth measurements, also taking root phenotypes into account.

Growth of axile and lateral roots of maize: I development of a phenotying platform

The objective of this study was to develop a phenotyping platform for the non-destructive, digital measurement of early root growth of axile and lateral roots and to evaluate its suitability for identifying maize (Zea mays L.) genotypes with contrasting root development. The system was designed to capture images of the root system within minutes and to batch process them automatically. For system establishment, roots of the inbred line Ac7729/TZSRW were grown until nine days after germination on the surface of a blotting paper in pouches. An A4 scanner was used for image acquisition followed by digital image analysis. Image processing was optimized to enhance the separation between the roots and the background and to remove image noise. Based on the root length in diameter-class distribution (RLDD), small-diameter lateral roots and large-diameter axile roots were separated. Root systems were scanned daily to model the growth dynamics of these root types. While the axile roots exhibited an almost linear growth, total lateral root length increased exponentially. Given the determined exponential growth, it was demonstrated that two plants, germinated one day apart but with the same growth rates differed in root length by 100%. From the growth rates we were able to identify contrasting genotypes from 236 recombinant inbred lines (RILs) of the CML444 x SC-Malawi cross. Differences in the growth of lateral roots of two selected RILs were due to differences in the final length and linear density of the primary lateral roots, as proven by the manual reanalysis of the digital images. The high throughput makes the phenotyping platform attractive for routine genetic studies and other screening purposes.

A consensus map of QTLs controlling the root length of maize

Traits related to the root length of maize (Zea mays L.), reported by 15 QTL studies of nine mapping populations, were subjected to a QTL meta-analysis. Traits were grouped according to ontology, and we propose a system of abbreviations to unambiguously identify the different root types and branching orders. The nine maps were merged into a consensus map, and the number and positions of putative QTL clusters (MQTLs) were determined. A total of 161 QTLs was grouped into 24 MQTLs and 16 individual QTLs. Seven MQTLs harbored root traits, which had been reported to be collocated with QTLs for grain yield or other drought-responsive traits in the field. The most consistent collocations were observed for the number and weight of the seminal roots (five loci). Based on our analysis at least six loci are good candidates for further evaluation (bins 1.07, 2.04, 2.08, 3.06, 6.05 and 7.04). For example, the MQTL in bin 2.04 harbored ten different single QTLs; the MQTLs in bins 1.07 and 3.06 combined 11 and 7 QTLs, respectively, that were detected in more than three populations. The presented database is a first step for a comprehensive overview of the genetic architecture of root system architecture and its ecophysiological function.

QTLs for the elongation of axile and lateral roots of maize in response to low water potential.

Changes in root architecture and the maintenance of root growth in drying soil are key traits for the adaptation of maize (Zea mays L.) to drought environments. The goal of this study was to map quantitative trait loci (QTLs) for root growth and its response to dehydration in a population of 208 recombinant inbred lines from the International Maize and Wheat Improvement Center (CIMMYT). The parents, Ac7643 and Ac7729/TZSRW, are known to be drought-tolerant and drought-sensitive, respectively. Roots were grown in pouches under well-watered conditions or at low water potential induced by the osmolyte polyethylene glycol (PEG 8000). Axile root length (LAx) increased linearly, while lateral root length (LLat) increased exponentially over time. Thirteen QTLs were identified for six seedling traits: elongation rates of axile roots (ERAx), the rate constant of lateral root elongation (kLat), the final respective lengths (LAx and LLat), and the ratios kLat/ERAx and LLat/LAx. While QTLs for lateral root traits were constitutively expressed, most QTLs for axile root traits responded to water stress. For axile roots, common QTLs existed for ERAx and LAx. Quantitative trait loci for the elongation rates of axile roots responded more clearly to water stress compared to root length. Two major QTLs were detected: a QTL for general vigor in bin 2.02, affecting most of the traits, and a QTL for the constitutive increase in kLat and kLat/ERAx in bins 6.04–6.05. The latter co-located with a major QTL for the anthesis-silking interval (ASI) reported in published field experiments, suggesting an involvement of root morphology in drought tolerance. Rapid seedling tests are feasible for elucidating the genetic response of root growth to low water potential. Some loci may even have pleiotropic effects on yield-related traits under drought stress.

Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach.

BackgroundField-based high throughput phenotyping is a bottleneck for crop breeding research. We present a novel method for repeated remote phenotyping of maize genotypes using the Zeppelin NT aircraft as an experimental sensor platform. The system has the advantage of a low altitude and cruising speed compared to many drones or airplanes, thus enhancing image resolution while reducing blurring effects. Additionally there was no restriction in sensor weight. Using the platform, red, green and blue colour space (RGB), normalized difference vegetation index (NDVI) and thermal images were acquired throughout the growing season and compared with traits measured on the ground. Ground control points were used to co-register the images and to overlay them with a plot map.ResultsNDVI images were better suited than RGB images to segment plants from soil background leading to two separate traits: the canopy cover (CC) and its NDVI value (NDVIPlant). Remotely sensed CC correlated well with plant density, early vigour, leaf size, and radiation interception. NDVIPlant was less well related to ground truth data. However, it related well to the vigour rating, leaf area index (LAI) and leaf biomass around flowering and to very late senescence rating. Unexpectedly, NDVIPlant correlated negatively with chlorophyll meter measurements. This could be explained, at least partially, by methodical differences between the used devices and effects imposed by the population structure. Thermal images revealed information about the combination of radiation interception, early vigour, biomass, plant height and LAI. Based on repeatability values, we consider two row plots as best choice to balance between precision and available field space. However, for thermography, more than two rows improve the precision.ConclusionsWe made important steps towards automated processing of remotely sensed data, and demonstrated the value of several procedural steps, facilitating the application in plant genetics and breeding. Important developments are: the ability to monitor throughout the season, robust image segmentation and the identification of individual plots in images from different sensor types at different dates. Remaining bottlenecks are: sufficient ground resolution, particularly for thermal imaging, as well as a deeper understanding of the relatedness of remotely sensed data and basic crop characteristics.

QTLs for early vigor of tropical maize

A strong photosynthetic performance and rapid leaf development, are important indicators of vigorous early growth. The aim of this study was to (1) evaluate the tropical maize (Zea mays L.) inbred lines CML444 and SC-Malawi for their photosynthetic performance at different growth stages and (2) assess quantitative trait loci (QTL) of photosynthesis-related traits in their 236 recombinant inbred lines at the heterotrophic growth stage. CML444 had a higher leaf chlorophyll (SPAD) content than SC-Malawi. Ten QTLs were found for the quantum efficiency of photosystem II (ΦPSII; four), SPAD (three) and the specific leaf area (SLA; three). The relevance of seedling QTLs for ΦPSII, SPAD and SLA for yield formation is emphasized by seven collocations (bins 5.01, 7.03, 8.05) with QTLs for kernel number and grain yield under field conditions. QTLs for SPAD at the V2 and at the reproductive stage did not collocate, indicating differences in the genetic control of SPAD at different growth stages. Knowing which loci affect SLA, SPAD and ΦPSII simultaneously and which do not will help to optimize light harvest by the canopy.

The ETH field phenotyping platform FIP: A cable-suspended multi-sensor system

Crop phenotyping is a major bottleneck in current plant research. Field-based high-throughput phenotyping platforms are an important prerequisite to advance crop breeding. We developed a cable-suspended field phenotyping platform covering an area of ~1ha. The system operates from 2 to 5m above the canopy, enabling a high image resolution. It can carry payloads of up to 12kg and can be operated under adverse weather conditions. This ensures regular measurements throughout the growing period even during cold, windy and moist conditions. Multiple sensors capture the reflectance spectrum, temperature, height or architecture of the canopy. Monitoring from early development to maturity at high temporal resolution allows the determination of dynamic traits and their correlation to environmental conditions throughout the entire season. We demonstrate the capabilities of the system with respect to monitoring canopy cover, canopy height and traits related to thermal and multi-spectral imaging by selected examples from winter wheat, maize and soybean. The system is discussed in the context of other, recently established field phenotyping approaches; such as ground-operating or aerial vehicles, which impose traffic on the field or require a higher distance to the canopy.

Image based phenotyping during winter: a powerful tool to assess wheat genetic variation in growth response to temperature

Having a strong effect on plant growth, temperature adaption has become a major breeding aim. Due to a lack of efficient methods, we developed an image-based approach to characterise genotypes for their temperature behaviour in the field. Twenty-nine winter wheat (Triticum aestivum L.) genotypes were continuously monitored at 3-day intervals on a plot basis during early growth from November to March using a modified digital camera. Canopy cover (CC) was determined by segmentation of leaves in calibrated images. Relative growth rates (RGR) of CC were then calculated for each measurement interval and related to the respective temperature. Also, classical traits used in plant breeding were assessed. Measurements of CC at single dates were highly repeatable with respect to genotype. For the tested range of temperatures (0-7°C), a linear relation between RGR and temperature was observed. Genotypes differed for base temperature and increase in RGR with rising temperature, these two traits showing a strong positive correlation with each other but being independent of CC at a single date. Our simple approach is suitable to screen large populations for differences in growth response to environmental stimuli. Furthermore, the derived parameters reveal additional information that cannot be assessed by usual measurements of static size.

Early vertical distribution of roots and its association with drought tolerance in tropical maize

Background and aimsSelection for deep roots to improve drought tolerance of maize (Zea mays L.) requires presence of genetic variation and suitable screening methods.MethodsWe examined a diverse set of 33 tropical maize inbred lines that were grown in growth columns in the greenhouse up to the 2-, 4-, and 6-leaf stage and in the field in Mexico. To determine length of roots from different depths at high throughput, we tested an approach based on staining roots with methylene blue and measuring the amount of absorbed dye as proxy measure for root length.ResultsStaining provided no advantage over root weights that are much easier to measure and therefore preferable. We found significant genotypic variation for all traits at the 6-leaf stage. For development rates between the 2-leaf and the 6-leaf stage, genotypes only differed for rooting depth and the number of crown roots. Positive correlations of leaf area with root length and rooting depth indicated a common effect of plant vigor. However, leaf area in growth columns was negatively related to grain yield under drought (r = −0.50).ConclusionThe selection for deeper roots by an increase in plant vigor likely results in a poorer performance under drought conditions. The proportion of deep roots was independent of other traits but showed a low heritability and was not correlated to field performance. An improved screening protocol is proposed to increase throughput and heritability for this trait.

Genetic structure and history of Swiss maize ( Zea mays L. ssp. mays ) landraces

Between 1930 and 2003 with emphasis on the 1940s maize landraces (Zea mays L. ssp. mays) from all over Switzerland were collected for maintenance and further use in a new Swiss breeding program. The genetic relationship and diversity among these accessions stored in the Swiss gene bank is largely unknown. Our hypothesis was that due to the unique geographic, climatic, and cultural diversity in Switzerland a diverse population of maize landraces had developed over the past three centuries. The aims were to characterize the genetic diversity of the Swiss landraces and their genetic relationship with accessions from neighbouring regions as well as reviewing their history, collection, and maintenance. The characterization and grouping was based on analyses with ten microsatellite markers. Geographic, cultural, and climatic conditions explained a division in two distinct groups of accessions. One group consisted of landraces collected in the southern parts of Switzerland. This group was related to the Italian Orange Flints. The other group contained accessions from northern Switzerland which were related to Northern European Flints in particular German Flints. Historic evidence was found for a frequent exchange of landraces within the country resulting in a lack of region-specific or landrace-specific genetic groups. The relatively large separation between the accessions, indicated by high FST (0.42), might be explained partly by a bottleneck during the collection and maintenance phase as well as by geographical and cultural separation of north and south of the country. Due to the high genetic diversity, the accessions here are a potential resource for broadening the European flint pool.