Papers by Alexander Bucksch
Non-destructive underground fiber Bragg grating sensing system with ResNet prediction for root phenotyping
The quantitative evaluation of plant organs in a non-destructive and continuous fashion is the te... more The quantitative evaluation of plant organs in a non-destructive and continuous fashion is the technological bottleneck to meet the food, fuel, and fiber needs for the 10 billion people on earth by 2050 [1]. Quantifying crop root architecture paves promising ways to improve resource uptake in the face of the resource limitations in the degraded soils of future climates [2]. Current root measurement methods either have low resolution or involve uprooting the plant. In all cases, the measurement methods do not provide any prediction on how well the plant is growing. We propose the usage of three fiber Bragg gratings (FBG) embedded within soil to measure underground strain change due to pseudo-root growth and a Residual Neural Network (ResNet) to predict its characteristics in a non-destructive fashion. To generate large amounts of sensor data similar to that of a growing root, we developed an automated robot that inserts pseudo-roots of 1mm and 5mm in diameter to 15cm below the soil's surface over the span of 11 minutes. We used 2,582 and 240 samples in training of the diameter and depth models, while testing was performed using 646 and 60 samples. The models were able to achieve accuracy of 92% and 93% for diameter and depth prediction, respectively. Through transfer learning, our base models will be expanded so that real time prediction on actual plant roots diameter and depth can be achieved.
The soil microbiome modulates the sorghum root metabolome and cellular traits with a concomitant reduction of Striga infection
Cell reports, Mar 1, 2024
Highlights d The soil microbiome hinders Striga parasitism of sorghum roots d A Striga-suppressiv... more Highlights d The soil microbiome hinders Striga parasitism of sorghum roots d A Striga-suppressive microbiome tweaks root exudate, aerenchyma, and suberin content d Pseudomonas strain VK46 reduces haustorium formation by degrading syringic acid
The genomic basis of nitrogen utilization efficiency and trait plasticity to improve nutrient stress tolerance in cultivated sunflower
Journal of experimental botany, Jan 25, 2024
Maintaining crop productivity is challenging as population growth, climate change, and increasing... more Maintaining crop productivity is challenging as population growth, climate change, and increasing fertilizer costs necessitate expanding crop production to poorer lands whilst reducing inputs. Enhancing crops' nutrient use efficiency is thus an important goal, but requires a better understanding of related traits and their genetic basis. We investigated variation in low nutrient stress tolerance in a diverse panel of cultivated sunflower genotypes grown under high and low nutrient conditions, assessing relative growth rate (RGR) as performance. We assessed variation in traits related to nitrogen utilization efficiency (NUtE), mass allocation, and leaf elemental content. Across genotypes, nutrient limitation generally reduced RGR. Moreover, there was a negative correlation between vigor (RGR in control) and decline in RGR in response to stress. Given this trade-off, we focused on nutrient stress tolerance independent of vigor. This tolerance metric correlated with the change in NUtE, plasticity for a suite of morphological traits, and leaf element content. Genome-wide associations revealed regions associated with variation and plasticity in multiple traits, including two regions with seemingly additive effects on NUtE change. Our results demonstrate potential avenues for improving sunflower nutrient stress tolerance independent of vigor, and highlight specific traits and genomic regions that could play a role in enhancing tolerance.
A low-cost system to quantify root phenotypes resulting from root-root interactions
Root-root interactions significantly impact the formation of architectural root phenotypes, yet a... more Root-root interactions significantly impact the formation of architectural root phenotypes, yet are poorly understood. Phenotype formation is impacted by sensing of soil resources and exudates of neighboring plants (Nord et al., 2011; Wang et al., 2021), which motivates the need to accurately quantify this phenomenon into its underlying causes. Currently, we are developing a complete experimental system for root-root interactions. A mesh frame has been designed to support the growth of two mature plant root systems. The frame is inserted into a large mesocosm, filled with a sand/soil mixture, and two plants are grown. To harvest, the mesocosm is disassembled and the sand/soil is gently washed away. Root systems are left suspended in the mesh and using a Canon EOS Rebel T5, ~500 total photos are taken at 10 different angles ranging from below to above the roots, 360° around the frame. DIRT/3D is used to construct 3D models and extract data from individual root systems. We are in the ...
Non-destructive measurements of root traits and their soil-water environment using Fiber Bragg Grating-based fiber optic sensors
Plant roots exhibit distinct architectural organization and overall shape. Current concepts to qu... more Plant roots exhibit distinct architectural organization and overall shape. Current concepts to quantify architectural variation assume a homogeneous phenotype for a given genotype. However, this assumption neglects the observable variation in root architecture for two reasons: (i) sampling strategies are designed to capture architectural variation only for the most common phenotype, and (ii) traits are often measured locally within a root system and ignore the architectural organization. Here, we introduce a new concept: the phenotypic spectrum of crop roots to quantify architectural variation as the number of architecture types for one genotype in a specific environment. We use the shape descriptor DS-curve to characterize the whole root system architecture. Using DS curves as a core, we developed a computing pipeline that combines Kmeans++ clustering, outlier filtering and the Fréchet distance as a similarity metric to classify types of root architectures. Subsequently, we applied this pipeline to analyze a field dataset including three common bean (Phaseolus vulgaris) genotypes DOR364 (n=797), L88 57 (n=1772), and SEQ7 (n=768) under non-limiting and water-stressed conditions in 2015 and 2016. We found DOR364 showed five different root architecture types across environments, while L88 57 and SEQ7 showed four. The total variation within classified root architecture types of DOR364, L88 57, and SEQ reduced by 58.59%, 50.19% and 53.01%, compared to the variation of the complete data sets. DOR364 had stable fractions of root architecture types across environments. In contrast, L88 57 and SEQ7 showed more variation in their fractions. There was no significant biomass difference among root architecture types for all studied genotypes within each environment. As such, we hypothesize that the phenotypic spectrum might buffer the impact of environmental stresses as an acclimatization strategy by changing the composition of root architecture types at the population level.
Field phenotyping of root traits in barley
Journal of Plant Nutrition and Soil Science, Jun 27, 2019
Root architecture and anatomy are important determinants of nitrogen (N) and water acquisition, b... more Root architecture and anatomy are important determinants of nitrogen (N) and water acquisition, but they are also environmentally plastic to adapt to N and water availability. Therefore, understanding the relationship between root traits and environmental factors is essential for improving N and water acquisition. A field experiment was conducted in the semi-arid region of the Loess Plateau in northwestern China to quantify the architectural and anatomical root traits of maize (Zea mays L.) in response to plastic film mulching and N fertilization. We compared four treatments: non-mulching with and without N supply as well as plastic film mulching with and without N supply. Variation existed for all root architecture and anatomy traits within maize root crowns. Crown and brace root angles to the soil line decreased in response to film mulching and N fertilization. Crown roots under plastic film mulching showed a significantly decreased distance to branching, reduced lateral root length, and overall increased root diameter. Similarly, N application significantly decreased the distance to branching, yet induced more compact and denser crown roots, and increased the root diameter. Brace roots exhibited an increased distance to branching, greater lateral root length and density, as well as a larger root diameter in response to plastic film mulching and N fertilization. Additionally, the accumulated number of nodal roots increased greatly under plastic film mulching and N treatments. At the anatomical level, N application reduced the proportion of the root cortical aerenchyma area. In contrast, aerenchyma area, cortex cell size, and late metaxylem vessel diameter were increased as a result of plastic film mulching. These results demonstrate root architectural and anatomical traits respond to mulching practices and N fertilization.
The development of crops with deeper roots holds substantial promise to mitigate the consequences... more The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture to reduce fertilizer inputs and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major obstacle to achieving these improvements is the bottleneck in the highthroughput phenotyping of field-grown roots. We address this bottleneck with DIRT/3D, a newly developed imagebased 3D root phenotyping platform, which measures 16 architecture traits in mature maize root systems. DIRT/3D computed reliably all 16 traits on a test panel of 12 contrasting maize genotypes. The analysis of the maize panel validated traits such as distance between whorls, and the number, angle, and diameters of crown and brace roots. Overall, we observed a coefficient of determination of 𝑟 ! >0.84 and a high broad-sense heritability of 𝐻 "#$% ! .
bioRxiv (Cold Spring Harbor Laboratory), Aug 29, 2022
Maintaining crop productivity is a challenge as population growth, climate change, and increasing... more Maintaining crop productivity is a challenge as population growth, climate change, and increasing fertilizer costs necessitate expanding crop production to poorer lands whilst reducing inputs. Enhancing crops’ nutrient use efficiency is thus an important goal, but requires a better understanding of related traits and their genetic basis. We investigated variation in low nutrient stress tolerance in a diverse panel of cultivated sunflower genotypes grown under high and low nutrient conditions, assessing relative growth rate (RGR) as performance. We assessed variation in traits related to nitrogen utilization efficiency (NUtE), mass allocation, and leaf elemental content. Across genotypes, nutrient limitation reduced RGR. Moreover, higher vigor (higher control RGR) was associated with a greater absolute decrease under stress. Given this trade-off, we focused on nutrient stress tolerance independent from vigor. This tolerance metric correlated with the change in NUtE, plasticity for a ...
Morphological plant modeling
Root phenotyping of temperate cereals – a high throughput phenotyping pipeline for field experiments
IntroductionThe increased demand for plant based food products, raw materials, and resources for ... more IntroductionThe increased demand for plant based food products, raw materials, and resources for bioenergy from a growing world population and plant based bioeconomy with limited resources will subsequently lead to a higher demand of accelerated plant breeding of water- and nutrient-efficient plants. Phenotyping is the current bottleneck to accelerate plant breeding (Fiorani and Schurr, 2013), and new methods are needed to phenotype the root system in the field, which may lead to root systems with increased water and nutrient efficiency. ‘Shovelomics’ is a ‘low-tech’, high-throughput method (Trachsel et al., 2010) that allows the phenotyping of root crowns of single plants in large plant populations. This method was adapted to phenotype root systems of temperate cereals for architectural and anatomical root traits in the field.MethodsBased on the ‘shovelomics’ method, we developed a novel high-throughput phenotyping platform and pipeline for root crowns of field-grown, temperate cereals, including an imaging station ‘field photobox’ and a semi-automated imaging processing pipeline that links into the DIRT software (Bucksch et al., 2014) allowing fast phenotyping of root crowns. The methodology was used to measure variation of root traits within a genotype and specific groups in a field experiment. The groups were based on the origin of genotypes, including varieties from Norway, Germany, and Australia. A split-plot design with 10 repetitions was chosen to measure the existing variation within a field experiment including different levels of N-fertilization. Different root traits were extracted from the root images using the DIRT software and analyzed the software GenStat 17.1.Results and Discussion Comparing the bottom angle of the barley cultivar ‘Barke’ grown in different densities and N-fertilization, we found significant differences between the treatments (p>0.001) in a preliminary analysis of the data. Similar results were found for the top-angle of the root systems (p>0.001) for the same variety. Root angle is an important root trait that determines the rooting depth of the plant and subsequently nutrient and water acquisition of the root system (e.g. Ge et al., 2000).ConclusionA novel root phenotyping platform and pipeline has been established to measure the root crowns of temperate cereals in the field. This ‘low cost’ and high-throughput method is suited to measure root traits of temperate cereals in the field supporting pre-breeding and breeding efforts. Those developments are the first steps towards an automation of field root phenotyping in the future
This paper will give an insight into modern ways of buildings modelling considering the case of T... more This paper will give an insight into modern ways of buildings modelling considering the case of TU Delft's campus with the use of classic photogrammetry tools and terrestrial laser scanning data. In addition we will use airborne LIDAR (Light-Imaging Detection and Ranging) for generating of extrusion models. The used methods aim to obtain models which can be used in Geographical Information Systems supporting different level of details. The detail factor may vary from pure city models, which are only blocks containing no façade information, to more complex 3D models with façade information as a texture and/or geometry. In our paper we will make some comparisons using a building model and discuss upon its information type and the achieved accuracy. Further more we will show an application example for the extrusion models.
PlantIT: Containerized phenotyping in the cloud
Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version ... more Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]PlantIT: Containerized phenotyping in the cloudAuthorsWesleyBonelliiDSuxingLiuiDChrisCotterMeganFloryMariaLuckAlexanderBuckschiDSee all authors Wesley BonelliiDCorresponding Author• Submitting AuthorUniversity of GeorgiaiDhttps://orcid.org/0000-0002-2665-5078view email addressThe email was not providedcopy email addressSuxing LiuiDUniversity of GeorgiaiDhttps://orcid.org/0000-0001-7639-4470view email addressThe email was not providedcopy email addressChris CotterUniversity of Georgiaview email addressThe email was not providedcopy email addressMegan FloryUniversity of Georgiaview email addressThe email was not providedcopy email addressMaria LuckUniversity of Georgiaview email addressThe email was not providedcopy email addressAlexander BuckschiDUniversity of GeorgiaiDhttps://orcid.org/0000-0002-1071-5355view email addressThe email was not providedcopy email address
A Platform to Quantify Phenotypic Responses to Root-Root Interactions Among Kin and Non-kin Common Beans
Quantifying phenotypes of root-root interactions would allow a greater understanding of how plant... more Quantifying phenotypes of root-root interactions would allow a greater understanding of how plants react to belowground competition through plasticity of architectural traits. Past research has sho...
The study of complex biological systems necessitates computational modeling approaches that are c... more The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.
Groundwater Level Remote Monitoring Using Optical Power Measurement in Fiber Bragg Grating
Optical Fiber Communication Conference (OFC) 2022, 2022
Groundwater level provides critical insight to public resource allocation and climate variability... more Groundwater level provides critical insight to public resource allocation and climate variability. Remote monitoring of groundwater level is demonstrated, based on wavelength-shift induced optical power change in fiber Bragg grating caused by water pressure fluctuations.
Comparison of open-source image-based reconstruction pipelines for 3D maize root phenotyping
Understanding root traits is essential to improve water uptake, increase nitrogen capture and rai... more Understanding root traits is essential to improve water uptake, increase nitrogen capture and raise carbon sequestration from the atmosphere. However, high-throughput phenotyping to quantify root t...
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Papers by Alexander Bucksch