Johannes Pfeifer

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.

Beyond point clouds - 3D mapping and field parameter measurements using UAVs

Recent developments in Unmanned Aerial Vehicles (UAVs) have made them ideal tools for remotely monitoring agricultural fields. Complementary advancements in computer vision have enabled automated post-processing of images to generate dense 3D reconstructions in the form of point clouds. In this paper we present a monitoring pipeline that uses a readily available, low cost UAV and camera for quickly surveying a winter wheat field, generate a 3D point cloud from the collected imagery and present methods for automated crop height estimation from the extracted point cloud and compare our estimates with those using standardized techniques.

UAV-based crop and weed classification for smart farming

Unmanned aerial vehicles (UAVs) and other robots in smart farming applications offer the potential to monitor farm land on a per-plant basis, which in turn can reduce the amount of herbicides and pesticides that must be applied. A central information for the farmer as well as for autonomous agriculture robots is the knowledge about the type and distribution of the weeds in the field. In this regard, UAVs offer excellent survey capabilities at low cost. In this paper, we address the problem of detecting value crops such as sugar beets as well as typical weeds using a camera installed on a light-weight UAV. We propose a system that performs vegetation detection, plant-tailored feature extraction, and classification to obtain an estimate of the distribution of crops and weeds in the field. We implemented and evaluated our system using UAVs on two farms, one in Germany and one in Switzerland and demonstrate that our approach allows for analyzing the field and classifying individual plants.

Changes in the allocation of endogenous strigolactone improve plant biomass production on phosphate-poor soils

Summary Strigolactones (SLs) are carotenoid‐derived phytohormones shaping plant architecture and inducing the symbiosis with endomycorrhizal fungi. In Petunia hybrida, SL transport within the plant and towards the rhizosphere is driven by the ABCG‐class protein PDR1. PDR1 expression is regulated by phytohormones and by the soil phosphate abundance, and thus SL transport integrates plant development with nutrient conditions. We overexpressed PDR1 (PDR1 OE) to investigate whether increased endogenous SL transport is sufficient to improve plant nutrition and productivity. Phosphorus quantification and nondestructive X‐ray computed tomography were applied. Morphological and gene expression changes were quantified at cellular and whole tissue levels via time‐lapse microscopy and quantitative PCR. PDR1 OE significantly enhanced phosphate uptake and plant biomass production on phosphate‐poor soils. PDR1 OE plants showed increased lateral root formation, extended root hair elongation, faster mycorrhization and reduced leaf senescence. PDR1 overexpression allowed considerable SL biosynthesis by releasing SL biosynthetic genes from an SL‐dependent negative feedback. The increased endogenous SL transport/biosynthesis in PDR1 OE plants is a powerful tool to improve plant growth on phosphate‐poor soils. We propose PDR1 as an as yet unexplored trait to be investigated for crop production. The overexpression of PDR1 is a valuable strategy to investigate SL functions and transport routes.

RADIX: rhizoslide platform allowing high throughput digital image analysis of root system expansion

BackgroundPhenotyping of genotype-by-environment interactions in the root-zone is of major importance for crop improvement as the spatial distribution of a plant’s root system is crucial for a plant to access water and nutrient resources of the soil. However, so far it is unclear to what extent genetic variations in root system responses to spatially varying soil resources can be utilized for breeding applications. Among others, one limiting factor is the absence of phenotyping platforms allowing the analysis of such interactions.ResultsWe developed a system that is able to (a) monitor root and shoot growth synchronously, (b) investigate their dynamic responses and (c) analyse the effect of heterogeneous N distribution to parts of the root system in a split-nutrient setup with a throughput (200 individual maize plants at once) sufficient for mapping of quantitative trait loci or for screens of multiple environmental factors. In a test trial, 24 maize genotypes were grown under split nitrogen conditions and the response of shoot and root growth was investigated. An almost double elongation rate of crown and lateral roots was observed under high N for all genotypes. The intensity of genotype-specific responses varied strongly. For example, elongation of crown roots differed almost two times between the fastest and slowest growing genotype. A stronger selective root placement in the high-N compartment was related to an increased shoot development indicating that early vigour might be related to a more intense foraging behaviour.ConclusionTo our knowledge, RADIX is the only system currently existing which allows studying the differential response of crown roots to split-nutrient application to quantify foraging behaviour in genome mapping or selection experiments. In doing so, changes in root and shoot development and the connection to plant performance can be investigated.

Assessing potato tuber diel growth by means of X-ray computed tomography

The formation and development of belowground organs is difficult to study. X-ray computed tomography (CT) provides the possibility to analyse and interpret subtle volumetric changes of belowground organs such as tubers, storage roots and nodules. Here, we report on the establishment of a method based on a voxel dimension of 240 μm and precision (standard deviation) of 30 μL that allows interpreting growth differences among potato tubers happening within 3 h. Plants were not stressed by the application of X-ray radiation, which was shown both by morphological comparison with control plants and by analysis of lipid peroxidation as a measure of oxidative stress. Diel (24 h) tuber growth fluctuations of three potato genotypes were monitored in soil-filled pots of 10 L. In contrast to the results from previous reports, most tubers grew at similar rates during day and night. Tuber growth was not related to the developmental stage of plants and tubers. Pronounced differences were observed between average growth rates in different tubers within a plant. These results are discussed in the context of restrictions of past methods to study tuber growth and in the context of their potential for the characterization of the formation and development of other belowground plant organs.